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In the intelligent reflecting surface (IRS)-enhanced wireless communication system, channel state information (CSI) is of paramount importance for achieving the passive beamforming gain of IRS, which, however, is a practically challenging task due to its massive number of passive elements without transmitting/receiving capabilities. In this letter, we propose a practical transmission protocol to execute channel estimation and reflection optimization successively for an IRS-enhanced orthogonal frequency division multiplexing (OFDM) system. Under the unit-modulus constraint, a novel reflection pattern at the IRS is designed to aid the channel estimation at the access point (AP) based on the received pilot signals from the user, for which the channel estimation error is derived in closed-form. With the estimated CSI, the reflection coefficients are then optimized by a low-complexity algorithm based on the resolved strongest signal path in the time domain. Simulation results corroborate the effectiveness of the proposed channel estimation and reflection optimization methods.

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... Using the sparsity of the RIS channel, Wan, et al. proposed a compressive sensing (CS) based algorithm to estimate the frequency-selective channel [12], but the CS-based broadband channel estimation did not appear robust in different simulation scenarios. In [13], Zheng et al. also considered the scenario of the wide-band and frequency-selective channels. Assuming high channel correlation between the adjacent elements of the RIS, they proposed to group the adjacent elements into some sub-surfaces to reduce the dimension of the channel estimation problem [13]. ...

... In [13], Zheng et al. also considered the scenario of the wide-band and frequency-selective channels. Assuming high channel correlation between the adjacent elements of the RIS, they proposed to group the adjacent elements into some sub-surfaces to reduce the dimension of the channel estimation problem [13]. But such elementsgrouping would cause performance degradation, because the reflection coefficients of all the elements in one group have to be set the same [13]. ...

... Assuming high channel correlation between the adjacent elements of the RIS, they proposed to group the adjacent elements into some sub-surfaces to reduce the dimension of the channel estimation problem [13]. But such elementsgrouping would cause performance degradation, because the reflection coefficients of all the elements in one group have to be set the same [13]. The channel estimation based on the RIS-element-grouping was extended to the multi-user scenario in [14] and the time-varying channel scenario [15]. ...

The reconfigurable intelligent surface (RIS) technology is a promising enabler for millimeter wave (mmWave) wireless communications, as it can potentially provide spectral efficiency comparable to the conventional massive multiple-input multiple-output (MIMO) but with significantly lower hardware complexity. In this paper, we focus on the estimation and projection of the uplink RIS-aided massive MIMO channel, which can be time-varying. We propose to let the user equipments (UE) transmit Zadoff-Chu (ZC) sequences and let the base station (BS) conduct maximum likelihood (ML) estimation of the uplink channel. The proposed scheme is computationally efficient: it uses ZC sequences to decouple the estimation of the frequency and time offsets; it uses the space-alternating generalized expectation-maximization (SAGE) method to reduce the high-dimensional problem due to the multipaths to multiple lower-dimensional ones per path. Owing to the estimation of the Doppler frequency offsets, the time-varying channel state can be projected, which can significantly lower the overhead of the pilots for channel estimation. The numerical simulations verify the effectiveness of the proposed scheme.

... As special multi-antenna transmission techniques, space shift keying (SSK) and spatial modulation (SM) are enhanced via RISs in [10] and [11], respectively. In [12] and [13], an RIS is used to enhance orthogonal frequency division multiplexing and cyclic-prefixed singlecarrier systems, respectively, for broadband communications. It is worth mentioning that in [5]- [12], the phase shifts of the RISs are configured to perform passive beamforming and the RISs do not transmit their own information. ...

... In [12] and [13], an RIS is used to enhance orthogonal frequency division multiplexing and cyclic-prefixed singlecarrier systems, respectively, for broadband communications. It is worth mentioning that in [5]- [12], the phase shifts of the RISs are configured to perform passive beamforming and the RISs do not transmit their own information. ...

... whereŝ m is the m-th element after the operation in (12). ...

Reconfigurable intelligent surface (RIS)-aided symbiotic active/passive transmission is a promising communication paradigm, which is able to improve the propagation environment while transmitting additional information. In this paper, a novel scheme, termed RIS-aided number modulation (RIS-NM), is proposed for symbiotic active/passive communications. In RIS-NM, the RIS elements are divided into in-phase (I-) and quadrature (Q-) subsets depending on their phase shift configurations, and the number of elements in the I-subset (or Q-subset, equivalently) is used to convey the RIS's private information. A low-complexity yet near-optimal detector is designed for RIS-NM by shrinking the search space of constellation points. We then investigate a special case of RIS-NM, termed RIS-aided number shift keying (RIS-NSK), in which the radio-frequency source transmits unmodulated carrier signals. Statistic channel state information (CSI)-based maximum-likelihood (ML) detection is developed for RIS-NSK. We analyze the bit error rate (BER) performance of RIS-NM/NSK over Rician fading channels. BER upper bounds are derived in closed-form for RIS-NM by assuming instantaneous CSI-based ML detection, while an approximate BER expression is obtained for RIS-NSK by assuming statistic CSI-based ML detection. Furthermore, we extend RIS-NM to multiple-input multiple-output scenarios. Our simulation results in terms of BER corroborate the performance analysis and the superiority of RIS-NM over the state-of-the-art RIS-aided symbiotic active/passive transmission scheme.

... So far, this problem seems mathematically intractable to solve to global optimality, thus the literature contains heuristic solutions based on successive convex approximation, semidefinite relaxation, and strongest tap maximization (STM) in the time domain [30]- [32]. In this article, we will focus on the STM solution from [31], [32] and compare it against an upper bound. ...

... The intuition behind STM is that the received signal power is spread out over the K subcarriers but rather concentrated in the time domain since M K [31]. Hence, selecting a configuration θ that is good for one strong channel tap is better than an arrangement that is good for one strong subcarrier. ...

... Since only M out of K subcarriers are used for pilots, the remaining ones can carry data. To handle mobility, one can develop protocols for progressive RIS reconfiguration where data is continuously transmitted and pilots are sent at regular intervals to re-estimate the channel and reconfigure the RIS [31], [32]. ...

... The authors of [16] optimized the channel capacity of RIS-assisted OFDM systems by jointly designing the transmit covariance matrix and the phase shifts of the RIS. In [17], the authors improved the performance of an OFDM system with a low-complexity method that matches the phase shifts of the RIS with the phase of the strongest channel path. Considering the practical RIS model with dual phase-and amplitudesquint effect, the authors of [18] studied the sum-rate maximization problem for a multiuser multi-antenna OFDM system with continuous and discrete phase shifts at the RIS. ...

... Even worse, the overhead of channel estimation is huge since a large number of reflecting elements are equipped at the RIS in order to compensate for the path losses of the BS-RIS channel and the RIS-UE channel [19]. Accordingly, the authors of [15] and [17] utilized a grouping method to reduce the training overhead for RIS-assisted OFDM systems, where the adjacent RIS reflecting elements were grouped to share a common reflection coefficient. However, the channel estimation schemes proposed in [15] and [17] cannot be efficiently applied to the scenario of multiple users since the UE-by-UE successive channel estimation leads to a large overhead that scales with the number of users. ...

... Accordingly, the authors of [15] and [17] utilized a grouping method to reduce the training overhead for RIS-assisted OFDM systems, where the adjacent RIS reflecting elements were grouped to share a common reflection coefficient. However, the channel estimation schemes proposed in [15] and [17] cannot be efficiently applied to the scenario of multiple users since the UE-by-UE successive channel estimation leads to a large overhead that scales with the number of users. In [20], the authors proposed two channel estimation schemes for the RISassisted multiuser orthogonal frequency division multiplexing access (OFDMA) system, where the maximum number of supported users was proved to be limited, and an increment of users was obtained at the expense of higher complexity and degraded performance. ...

Reconfigurable intelligent surfaces (RISs) can establish favorable wireless environments to combat the severe attenuation and blockages in millimeter-wave (mmWave) bands. However, to achieve the optimal enhancement of performance, the instantaneous channel state information (CSI) needs to be estimated at the cost of a large overhead that scales with the number of RIS elements and the number of users. In this paper, we design a quasi-static broad coverage at the RIS with the reduced overhead based on the statistical CSI. We propose a design framework to synthesize the power pattern reflected by the RIS that meets the customized requirements of broad coverage. For the communication of broadcast channels, we generalize the broad coverage of the single transmit stream to the scenario of multiple streams. Moreover, we employ the quasi-static broad coverage for a multiuser orthogonal frequency division multiplexing access (OFDMA) system, and derive the analytical expression of the downlink rate, which is proved to increase logarithmically with the power gain reflected by the RIS. By taking into account the overhead of channel estimation, the proposed quasi-static broad coverage even outperforms the design method that optimizes the RIS phases using the instantaneous CSI. Numerical simulations are conducted to verify these observations.

... Moreover, IRS dispenses with radio frequency (RF) chains and operates in full-duplex mode with passive reflection only, which thus features low hardware cost and power consumption, and is deemed a promising technology for the next-/sixth-generation (6G) wireless networks. As such, IRS has spurred intense research interest and been thoroughly investigated for various wireless systems, such as multiple-input multiple-output (MIMO) communications [14], [15], orthogonal frequency division multiplexing (OFDM) based systems [16], [17], non-orthogonal multiple access (NOMA) [18], [19], simultaneous wireless information and power transfer (SWIPT) [20], [21], mobile edge computing [23], [24], etc. ...

... To achieve effective control over the wireless propagation environment by IRSs, the acquisition of accurate channel state information (CSI) in IRS-aided wireless communication systems is crucial, which, however, is practically challenging to realize due to the lack of signal processing capabilities at IRS reflecting elements as well as their massive number in practice. Although the IRS→base station (BS)/user channels cannot be separately estimated by IRSs that are fully passive, the cascaded user→IRS→BS channels can be estimated at the BS based on the pilot symbols sent by the users with properly designed IRS reflection patterns over time [17]. However, the acquisition of such CSI in IRS-aided systems may require a prohibitively high training overhead that is in general proportional to the number of reflecting elements and thus can severely degrade the data communication throughput. ...

... where ν (i) 0 ∈ C M ×1 denotes the training reflection vector of IRS 1 , z (i) 0 ∼ N c (0, σ 2 I N B ) denotes the additive white Gaussian noise (AWGN) vector at the BS with σ 2 being the normalized noise 2 The direct link can be estimated at the BS using the conventional channel estimation scheme with the IRS turned OFF or via the estimation scheme in [17] with the IRS turned ON. ...

Intelligent reflecting surface (IRS) has emerged as a promising technique to control wireless propagation environment for enhancing the communication performance cost-effectively. However, the rapidly time-varying channel in high-mobility communication scenarios such as vehicular communication renders it challenging to obtain the instantaneous channel state information (CSI) efficiently for IRS with a large number of reflecting elements. In this paper, we propose a new roadside IRS-aided vehicular communication system to tackle this challenge. Specifically, by exploiting the symmetrical deployment of IRSs with inter-laced equal intervals on both sides of the road and the cooperation among nearby IRS controllers, we propose a new two-stage channel estimation scheme with off-line and online training, respectively, to obtain the static/time-varying CSI required by the proposed low-complexity passive beamforming scheme efficiently. The proposed IRS beamforming and online channel estimation designs leverage the existing uplink pilots in wireless networks and do not require any change of the existing transmission protocol. Moreover, they can be implemented by each of IRS controllers independently, without the need of any real-time feedback from the user's serving BS. Simulation results show that the proposed designs can efficiently achieve the high IRS passive beamforming gain and thus significantly enhance the achievable communication throughput for high-speed vehicular communications.

... A large amount of work on CSI estimation for passive RIS-based systems has been published recently. Initially, this work focused on estimating unstructured models, where the channels are simply described using complex gains [3][4][5][6][7][8][9][10][11][12][13][14]. Such models are simple and lead to straightforward algorithms, but the required training overhead is very large and may render such approaches impractical. ...

... where {H F d,n , H F n , G F n } represent the DFT at subcarrier n for the UE-BS, RIS-BS, and UE-RIS channel impulse responses, respectively. Thus, one can employ the same estimation methods discussed above on a per-subcarrier basis, although to exploit the channel correlation in frequency and reduce the training overhead, pilot data is normally transmitted only on a subset of the subcarriers, and interpolation is used to construct channel estimates for others [4]. An alternative approach proposed in [13] is to use shorter OFDM symbols during the training period. ...

... A simple approach to reduce the number of pilots and estimation complexity is to assign identical phases to RIS elements with highly correlated channels [4], [6]. High channel correlation occurs when adjacent RIS elements are closely spaced; retaining the flexibility of arbitrary phase shifts for such elements does not provide a significant increase in degrees of freedom for beamforming design, since the designed phases would likely be nearly identical. ...

... This can be achieved by adopting the ON/OFF training reflection pattern at the IRS with pilot symbols sent from the transmitter, as studied in [34], [55]. Later, the full-ON IRS training reflection pattern based on some special matrices (e.g., the discrete Fourier transform (DFT) matrix, Hadamard matrix, and circulant matrix generated by Zadoff-Chu sequence) was developed for the cascaded channel estimation in [35], [36], [56]. It was shown that the channel estimation accuracy can be significantly improved by exploiting the full IRS aperture gain with the full-ON IRS training reflection pattern. ...

... Furthermore, the training reflection pattern at the IRS was jointly designed with the pilot sequence at the transmitter in [36], [37], [57], aiming to achieve perfect orthogonality over the IRS-reflected signals for minimizing the channel estimation error. In addition, different algorithms based on some well-known signal processing methods such as least square (LS)/linear minimum mean-squared-error (LMMSE) [35]- [37], [56], [57], compressed sensing [58]- [67], and deep learning [68]- [72] were proposed to resolve both the direct and/or cascaded channels at the receiver. To sum up, the cascaded channel estimation for IRS hinges on how to jointly design the pilot sequence x 3) Comparison/Combination of Separate and Cascaded Channel Estimation: As summarized in Table IV, the separate and cascaded channel estimation approaches have their respective pros and cons. ...

... For the first time, the authors in [34] and [35] considered the IRS-aided single-user OFDM system and proposed the comb-type pilot schemes with the ON/OFF and full-ON training reflection designs for the IRS, respectively. Later, to reduce the large training delay arising from the long OFDM symbol duration, the authors in [36] proposed two efficient schemes to accelerate the broadband channel estimation by redesigning the OFDM pilot symbol structures and IRS training reflection patterns. ...

Intelligent reflecting surface (IRS) has emerged as a key enabling technology to realize smart and reconfigurable radio environment for wireless communications, by digitally controlling the signal reflection via a large number of passive reflecting elements in real time. Different from conventional wireless communication techniques that only adapt to but have no or limited control over dynamic wireless channels, IRS provides a new and cost-effective means to combat the wireless channel impairments in a proactive manner. However, despite its great potential, IRS faces new and unique challenges in its efficient integration into wireless communication systems, especially its channel estimation and passive beamforming design under various practical hardware constraints. In this paper, we provide a comprehensive survey on the up-to-date research in IRS-aided wireless communications, with an emphasis on the promising solutions to tackle practical design issues. Furthermore, we discuss new and emerging IRS architectures and applications as well as their practical design problems to motivate future research.

... Firstly, the signaling overhead due to estimation increases as the number of reflecting elements of an intelligent surface is large. 12 To achieve separate estimation for the channel at the cost of high overhead, the authors in Reference 13 studied an "on-off" technique for the channel estimation in passive intelligent reflecting surface-assisted systems. ...

... Putting U 2 ∕ α k = 0, leads toα k = Γ k . When the values of (F, ) are given, the new value of α k is upgraded to Γ k via solving (12) in each iteration. Then, by optimizing the values (F, ) in problem (16) with a given α k , the optimization problem becomes: ...

In wireless communication system with a high mobility scenario, there is a challenge to obtain fast data transmission service with proper stability. Also, it is difficult to obtain perfect channel state information in the high mobility case without large online computation. Intelligent surface has great potential to cost‐effectively enhance the system performance in next generation technology and beyond. In this paper, a railway communication system with the help of intelligent surface technology is proposed for high mobility scenario. We propose an applicable beamforming scheme with the help of mobile station location information for intelligent surface‐aided communication system under high mobility. In our proposed system, the beams from the intelligent surface are chosen based on the mobile stations locations, where the weights of the beams are optimized for maximum total service of base station. Also, we formulate the optimization problem and propose an alternating iterative technique as a solution. The weights and phase matrix of the beams are optimized to maximize the mobile service. An intelligent surface with beam selection scheme is also proposed. Results demonstrate the significant mobile service enhancement introduced by the intelligent surface in railway communication system and show the effectiveness of our proposed scheme. It can reduce the handover region and can save time for data transmission. In this paper, a railway communication system with the help of intelligent surface technology is proposed for high mobility scenario. Results demonstrate the significant mobile service enhancement introduced by the intelligent surface in railway communication system and show the effectiveness of our proposed scheme.

... • If a DLS does not exist: The SDN controller treats the PWE configuration as a large optimization problem [24]- [28]. The variables are the cells and their states over all metasurfaces present in the area. ...

... A continuous optimization loop is thus formed, with the Rx reception quality serving as the fitness function (e.g., received power), and all phase shifter states as optimization parameters. Note that, while many excellent works treat this optimization problem [24]- [28], the real-time operation under user mobility may be inherently impossible due to the large scale of the optimization. This flat optimization approach is normally fit in cases where there is just one metasurface and many slow-moving users are present, and a codebook solution would not make sense to the increased complexity of the solution. ...

... As a further benefit, the authors of [24] demonstrated that there is no need for upgrading the existing infrastructure when incorporating RISs in the existing systems. Given the above advantages, RISs have received special attention in various areas, including RISassisted physical layer security [25]- [27], RIS-aided wireless power transfer [28]- [32], and RIS-assisted OFDM [33], [34], etc. Furthermore, RIS-assisted AirComp systems have also been studied in [35]- [38]. ...

... By introducingē k = |v k | 2hH kh k and e k = |v k | 2hH kh k as the equivalent channel gain between WD k and the FC, we can respectively rewrite (34) and (35) as follows: ...

Over-the-air computation (AirComp) has received substantial attention, given its ability to aggregate massive amounts of data from distributed wireless devices (WDs). However, the computation accuracy at the fusion center (FC) may be severely affected by receiving data corrupted by the poor channel conditions. To mitigate this issue, we consider the employment of reconfigurable intelligent surfaces (RISs) in the AirComp system considered for improving the quality of received data, and hence improve the computation accuracy. However, most previous contributions on RIS-assisted AirComp systems only employ a single RIS in the resultant single-RIS-assisted (SRISassisted) AirComp systems. We develop this concept further for mitigating the deleterious channel effects by conceiving a double-RIS-assisted (DRIS-assisted) AirComp system, where one of the RISs is located near the WDs and the other in the vicinity of the FC. We theoretically prove that the DRIS-assisted AirComp system outperforms its SRIS-assisted counterpart in terms of the resultant computation mean-squared-error (MSE). Furthermore, we propose a pair of algorithms for jointly optimizing the transmit power at the WDs, the receive beamforming vector at the FC, and the passive beamforming matrices at the RISs for minimizing the computational MSE. Specifically, the transmit power is updated by exploiting the Lagrange duality method, while the receive beamforming vector is optimized by utilizing the first-order optimality condition. Furthermore, a pair of techniques are developed for optimizing the passive beamforming matrices at the RISs based on semidefinite relaxation (SDR) and penalty-duality-decomposition (PDD), respectively. Both the complexity and the convergence of the proposed algorithms are analyzed. Finally, simulation results are provided for quantifying the overall performance of the resultant DRIS-assisted AirComp system.

... Hence, the complexity of online optimization and the corresponding channel estimation overhead scale with the IRS codebook size and not explicitly with the number of reflecting elements. In [7], [8], the authors employed predefined phase-shift configurations based on the discrete Fourier transform (DFT) matrix for channel estimation in IRS-assisted systems. ...

... However, the shape of the generated beams cannot be explicitly controlled. Furthermore, the authors of [1], [2], [7], [8] focus on continuous IRS phase shifts, whereas in practice, discrete IRS phase shifts may be preferred to reduce the implementation cost [4]. ...

In this paper, we focus on large intelligent reflecting surfaces (IRSs) and propose a new codebook construction method to obtain a set of pre-designed phase-shift configurations for the IRS unit cells. Since the complexity of online optimization and the overhead for channel estimation for IRS-assisted communications scale with the size of the phase-shift codebook, the design of small codebooks is of high importance. We consider both continuous and discrete phase shift designs and formulate the codebook construction as optimization problems. To solve the optimization problems, we propose an optimal algorithm for the discrete phaseshift design and a low-complexity sub-optimal solution for the continuous design. Simulation results show that the proposed algorithms facilitate the construction of codebooks of different sizes and with different beamwidths. Moreover, the performance of the discrete phase-shift design with 2-bit quantization is shown to approach that of the continuous phase-shift design. Finally, our simulation results show that the proposed designs enable large transmit power savings compared to the existing linear and quadratic codebook designs.

... Note that h + , is an upper-bound since the amplitude gain of the LoS component is amplified by the number of passive elements of the panel ( ) in (19). ...

... After testing all entries of the codebook, the BS will choose that phase configuration corresponding to the highest measured received power (29). Hence, the gain of the reflective channel is significantly enhanced by the RIS (18)- (19). ...

The Reconfigurable Intelligent Surface (RIS) constitutes one of the prominent technologies for the next generation of wireless communications. It is envisioned to enhance the signal coverage in cases when the direct link of the communication is weak. Recently, beam training based on codebook selection is proposed to obtain the optimized phase configuration of the RIS, and then, the data is transmitted and received by using the classical coherent demodulation scheme (CDS). This training approach is able to avoid the large overhead required by the channel sounding process, and it also circumvents complex optimization problems. However, the beam training still requires the transmission of some reference signals to test the different phase configurations of the codebook, which reduces the spectral efficiency. The best codeword is chosen according to the received energy of the reference signals. In this paper, the data transmission and reception based on non-CDS (NCDS) is proposed during the beam training process in order to increase the efficiency of the system, and at the same time, enable the energy measurement for the determination of the best beam for the RIS. After choosing the best codebook, NCDS is still more suitable to transmit information for high mobility scenarios as compared to the classical CDS. Analytical expressions for the Signal-to-Interference and Noise Ratio (SINR) for the non-coherent RIS-empowered system are presented. Moreover, a detailed comparison between the NCDS and CDS in terms of efficiency and complexity is also given. The extensive computer simulation results verify the accuracy of the presented analysis and showcase that the proposed system outperforms the existing solutions.

... However, the pilot overhead of the LS-based estimation method is prohibitively high and scales with M , which can be quite large. To reduce the pilot overhead, [10] divided the elements of the RIS into P subgroups, and proposed a transmission protocol to successively execute channel estimation and phase shift optimization with a pilot overhead of P . By exploiting the common BS-RIS channel and the linear correlation among the RIS-user channels in multiuser multiple-input single-output (MU-MISO) systems, the authors in [11] further proposed a channel estimation strategy whose pilot overhead is inversely proportional to the number of the antennas at the BS: M + max(K − 1, K (K−1)M N ). ...

... repeat 9: d i = arg max d=1,2,...,D |R H (:,d) r i−1 |. 10: ...

... Several literatures are dedicated to develop efficient channel estimation algorithms and protocols. For instance, a novel reflection pattern at the IRS is designed in [133] for OFDM to aid the channel estimation at the access point based on the received pilot signals from the user. With the estimated CSI, the reflection coefficients are then optimized by a low-complexity algorithm based on the resolved strongest signal path in the time domain. ...

Intelligent reflecting surfaces aided communication have been emerging as strong candidates to support the 6G wireless
physical platforms. IRS has shown promising qualities in enhancing the spectral efficiency of wireless networks because
of its capability to alter the conduct of interacting electromagnetic waves through intelligent handling of the reflections
phase shifts. Also, NOMA proves itself to be superior among the other multiple access techniques as it supports a greater
number of users using non-orthogonal resource allocation. This paper brings a survey over the IRS-assisted NOMA networks.
The IRS and NOMA technologies, and their physical working principles are first introduced in the paper. The state-of-theart of the IRS-assisted NOMA communication networks is next presented followed by a discussion of related performance
parameters for analysis. Afterward, it discusses the resource allocation, and secrecy requirements in the IRS–NOMA networks.
Furthermore, it presents the relevant work related to the optimization of energy efficiency, power efficiency and coverage. A
comparison of IRS–NOMA network with MIMO–NOMA, and relay aided NOMA network is provided. Finally, a few exciting
open challenges for IRS-assisted NOMA networks are identified including optimization problem using ML, identifying
implementing scenarios of NOMA or OMA with IRS, PLS, and terahertz communication.

... In [4], a certain number of IRS elements are grouped together, where each group is called a sub-surface. Based on this grouping method, in [5], the cascaded channel is estimated in a orthogonal frequency division multiplexing (OFDM) system. b) CE for double-IRS assisted communication: : There may arise a scenario where the signal transmitted from the MU reaches the BS by reflection from two IRS's. ...

In this paper, two Intelligent reflecting surfaces (double IRS) assisted single-user single input single output (SISO) communication system is considered. The cascaded channels (mobile user (MU)$\rightarrow$IRS-1$\rightarrow$base station (BS), MU$\rightarrow$IRS-2$\rightarrow$BS and MU$\rightarrow$IRS-1$\rightarrow$IRS-2$\rightarrow$BS channels) are estimated under Bayesian setting. Here, the goal is to evaluate the performance of the estimator in case of MU$\rightarrow$IRS-1$\rightarrow$BS and MU$\rightarrow$IRS-2$\rightarrow$BS channel links using Bayesian Cramer-Rao lower bound (CRLB). Without the knowledge of closed form pdf of inner product of circularly symmetric complex Gaussian (CSCG) random vectors, we cannot obtain the fisher information. Hence, by numerical computation we obtain the Bayesian CRLB. In the simulation results, we show that we can approximate the pdf of the inner product of CSCG random vectors by a Rayleigh distribution by increasing the number of elements on the IRS, which is analogous to Central Limit Theorem (CLT). Also, the results convey that the mean squared error (MSE) almost matches with the Bayesian CRLB.

... Orthogonal frequency division multiplexing based single user wireless system is considered in [8], where RIS is used in ON/OFF reflection mode and the performance of the proposed system is evaluated in terms of achievable data rate. A grouping technique of RIS units is introduced in [9], where group of RIS units share the common coefficient of reflection to reduce the estimation complexity. In [10], RIS is combined with the receive quadrature spatial modulation technique, in which RIS is partitioned into two main parts to form the in-phase and quadature components of the signals. ...

Reconfigurable intelligent surface (RIS)-assisted power-domain non-orthogonal multiple access (PD-NOMA) system has emerged as a revolutionary technology to enhance the spectrum efficiency for future wireless networks. This work introduces two novel RIS systems, namely, RIS partition-assisted (RISP) PD-NOMA (RISP-PD-NOMA) and RISP-Quadrature NOMA (RISP-Q-NOMA), to improve the signal quality of all users by dedicating fixed RIS units to each user for phase cancellation. The closed-form expressions of average sum-rate, outage probability, and diversity order of both systems are evaluated under the Rician fading channel for perfect and imperfect successive interference cancellation (SIC). Further, the performance of both systems is compared with RIS-division PDNOMA (RISD-PD-NOMA) system where the RIS subsurface assigned to one user is not exposed to another user. It is noticed from the analysis that under perfect SIC, RISP-PD-NOMA outperforms RISP-Q-NOMA and RISD-PD-NOMA. However, under imperfect SIC, RISP-Q-NOMA demonstrates superior performance than other systems, due to lesser number of SIC operations that lead to less stringent constraints on the power allocation, reduce detection delay, and improve SIC stability. Furthermore, the analytical expression for bit error rate (BER) of RISP-PD-NOMA and RISP-Q-NOMA is derived, and then closed-form expression of average-BER is evaluated. Numerical results demonstrate that RISP-Q-NOMA is superior to RISPPD-NOMA and RISD-PD-NOMA.

... Note that, in this paper, we consider that the IRS elements are not frequency selective which has also been assumed such as in[11],[36]. Infact,[37] indicates that by proper choice of the IRS element-tuning circuit parameters, it is possible to achieve non-frequency selectivity of IRS elements even in wideband systems. ...

Intelligent reflecting surfaces (IRSs) are a promising technology for enhancing coverage and spectral efficiency, especially in the millimeter wave (mmWave) bands. Existing approaches to leverage the benefits of IRS involve a resource-intensive channel estimation step followed by a computationally expensive algorithm to optimize the reflection coefficients at the IRS. In this work, we present and analyze several alternative schemes, where the phase configuration of the IRS is randomized and multi-user diversity is exploited to opportunistically select the best user at each point in time for data transmission. We show that the throughput of an IRS assisted opportunistic system asymptotically converges to the optimal beamforming-based throughput under fair allocation of resources, as the number of users gets large. Further, for all the proposed schemes, we derive the scaling law of the throughput in terms of the number of users and IRS elements, as the number of users gets large. We also introduce schemes that enhance the rate of convergence of the opportunistic rate to the beamforming rate as the number of users is increased. Following this, we extend the setup to wideband channels via an orthogonal frequency division multiplexing (OFDM) system and discuss two opportunistic schemes in an IRS assisted setting that elucidate the superior performance that IRS aided systems can offer over conventional systems at very low implementation cost and complexity.

... A great number of researches on RIS have focused on the optimal beamforming scheme and channel estimation methods [5]- [7]. However, few systematic researches investigated on the impact of the RIS's deployment on system performance, such as the network capacity. ...

... When M t , M r → ∞, we can readily show that the array response vectors at the Tx and the Rx are asymptotically orthogonal, i.e., A H Mt A Mt → I and A H Mr A Mr → I. Therefore, (20) can be approximated as the truncated singular value decomposition (SVD) of H eff . ...

In next-generation wireless networks, reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output (MIMO) systems are foreseeable to support a large number of antennas at the transceiver as well as a large number of reflecting elements at the RIS. To fully unleash the potential of RIS, the phase shifts of RIS elements should be carefully designed, resulting in a high-dimensional non-convex optimization problem that is hard to solve with affordable computational complexity. In this paper, we address this scalability issue by partitioning RIS into sub-surfaces, so as to optimize the phase shifts in sub-surface levels to reduce complexity. Specifically, each sub-surface employs a linear phase variation structure to anomalously reflect the incident signal to a desired direction, and the sizes of sub-surfaces can be adaptively adjusted according to channel conditions. We formulate the achievable rate maximization problem by jointly optimizing the transmit covariance matrix and the RIS phase shifts. Then, we characterize the asymptotic behavior of the system with an infinitely large number of transceiver antennas and RIS elements. The asymptotic analysis provides useful insights on the understanding of the fundamental performance-complexity tradeoff in RIS partitioning design. We show that the achievable rate maximization problem has a rather simple form in the asymptotic regime, and we develop an efficient algorithm to find the optimal solution via one-dimensional (1D) search. Moreover, we discuss the insights and impacts of the asymptotically optimal solution on finite-size system design. By applying the asymptotic result to a finite-size system with necessary modifications, we show by numerical results that the proposed design achieves a favorable tradeoff between system performance and computational complexity.

... The existing RIS research mainly focuses on the new challenges that classical communication problems have faced since the introduction of RISs, such as channel estimation [9]- [13] and beamforming [14]- [16], and these studies focus on channel models in single-network scenarios [17]- [20]. According to our limited search, except in one review article [21], we did not find any literature on RIS network coexistence scenarios. ...

Reconfigurable intelligent surfaces (RISs) have attracted the attention of academia and industry circles because of their ability to control the electromagnetic characteristics of channel environments. However, it has been found that the introduction of an RIS may bring new and more serious network coexistence problems. It may even further deteriorate the network performance if these new network coexistence problems cannot be effectively solved. In this paper, an RIS network coexistence model is proposed and discussed in detail, and these problems are deeply analysed. Two novel RIS design mechanisms, including a novel multilayer RIS structure with an out-of-band filter and an RIS blocking mechanism, are further explored. Finally, numerical results and a discussion are given.

... The second approach estimates the relevant channels of the anchor point A1 and A2 first, namely the BS-RIS-A1 and A1-RIS-A2 channels, then estimates the A2-RIS-UE channel to restore the cascaded BS-RIS-UE channel. In [139], a transmission protocol for RIS CE and configuration optimization is proposed for RIS-empowered OFDM systems. However, the presented RIS reflection pattern is implemented by ON/OFF switching, which can be costly in practice, and the estimation accuracy suffers since only a portion of RIS elements are activated during the CE period. ...

The demanding objectives for the future sixth generation (6G) of wireless communication networks have spurred recent research efforts on novel materials and radio-frequency front-end architectures for wireless connectivity, as well as revolutionary communication and computing paradigms. Among the pioneering candidate technologies for 6G belong the reconfigurable intelligent surfaces (RISs), which are artificial planar structures with integrated electronic circuits that can be programmed to manipulate the incoming electromagnetic field in a wide variety of functionalities. Incorporating RISs in wireless networks has been recently advocated as a revolutionary means to transform any wireless signal propagation environment to a dynamically programmable one, intended for various networking objectives, such as coverage extension and capacity boosting, spatiotemporal focusing with benefits in energy efficiency and secrecy, and low electromagnetic field exposure. Motivated by the recent increasing interests in the field of RISs and the consequent pioneering concept of the RIS-enabled smart wireless environments, in this paper, we overview and taxonomize the latest advances in RIS hardware architectures as well as the most recent developments in the modeling of RIS unit elements and RIS-empowered wireless signal propagation. We also present a thorough overview of the channel estimation approaches for RIS-empowered communications systems, which constitute a prerequisite step for the optimized incorporation of RISs in future wireless networks. Finally, we discuss the relevance of the RIS technology in the latest wireless communication standards, and highlight the current and future standardization activities for the RIS technology and the consequent RIS-empowered wireless networking approaches.

... Nevertheless, due to CSI data collected from WiFi devices that have low resolution and high sensitivity, it is challenging to separate signals from a specific space. Beamforming technology with an intelligent reflecting surface (IRS) [116] and directional antennas [67] are considered methods to overcome this disadvantage and improve the performance. ...

WiFi sensing has recently received significant interest from academics, industry, healthcare professionals and other caregivers (including family members) as a potential mechanism to monitor our aging population at distance, without deploying devices on users bodies. In particular, these methods have gained significant interest to efficiently detect critical events such as falls, sleep disturbances, wandering behavior, respiratory disorders, and abnormal cardiac activity experienced by vulnerable people. The interest in such WiFi-based sensing systems stems from its practical deployments in indoor settings and compliance from monitored persons, unlike other sensors such as wearables, camera-based, and acoustic-based solutions. This paper reviews state-of-the-art research on collecting and analysing channel state information, extracted using ubiquitous WiFi signals, describing a range of healthcare applications and identifying a series of open research challenges, untapped areas, and related trends.This work aims to provide an overarching view in understanding the technology and discusses its uses-cases from a perspective that considers hardware, advanced signal processing, and data acquisition.

... Practical systems may operate over frequency-selective channels. In such cases, more complicated orthogonal frequency-division multiplexing (OFDM) based methods would be applied [77,78]. ...

... The IRS is equipped with a smart controller, which can dynamically adjust the phase shift of each reflecting element in terms of the instantaneous CSI acquired through periodic estimation. In particular, several channel estimation methods for IRS-aided systems have been proposed to obtain accurate CSI, such as [10]- [12], which is beyond the scope of this paper. To characterize the theoretical performance, we assume the CSI of all involved channels is perfectly known and follows quasi-static frequency-flat fading. ...

Intelligent reflecting surface (IRS) is a cost-efficient technique to improve power efficiency and spectral efficiency. However, IRS-aided multi-antenna transmission needs to jointly optimize the passive and active beamforming, imposing a high computational burden and high latency due to its iterative optimization process. Making use of hybrid analog-digital beamforming in high-frequency transmission systems, a novel technique, coined dual-beam IRS, is proposed in this paper. The key idea is to form a pair of beams towards the IRS and user, respectively. Then, the optimization of passive and active beamforming can be decoupled, resulting in a simplified system design. Simulation results corroborate that it achieves a good balance between the cell-edge and cell-center performance. Compared with the performance bound, the gap is moderate, but it remarkably outperforms other sub-optimal schemes.

... Due to its great benefit in improving communication performance, the IRS has been extensively used in various communication scenarios to realize diverse desired goals, such as SNR or capacity maximization [7,8], sum rate maximization [9], power minimization or energy efficiency maximization [3, 10], and symbol-error-rate minimization [11,12]. Also, the IRS has been proposed to be integrated with other promising technologies, such as orthogonal frequency division multiplexing (OFDM) [13,14], massive MIMO [15, 16], millimeter wave (mmWave) [17, 18], deep learning [19, 20], cognitive radio [21, 22], physical layer security [23, 24], unmanned aerial vehicle (UAV) [25, 26], and simultaneous wireless information and power transfer (SWIPT) [27], to improve the communication performance of the considered systems. ...

In this paper, we establish an integrated sensing and communication (ISAC) system based on a distributed semi-passive intelligent reflecting surface (IRS), which allows location sensing and data transmission to be carried out simultaneously, sharing the same frequency and time resources. The detailed working process of the proposed IRS-based ISAC system is designed, including the transmission protocol, location sensing and beamforming optimization. Specifically, each coherence block consists of two periods, the ISAC period with two time blocks and the pure communication (PC) period. During each time block of the ISAC period, data transmission and user positioning are carried out simultaneously. The estimated user location in the first time block will be used for beamforming design in the second time block. During the PC period, only data transmission is conducted, by invoking the user location estimated in the second time block of the ISAC period for beamforming design. {\color{black}Simulation results show that a millimeter-level positioning accuracy can be achieved by the proposed location sensing scheme, demonstrating the advantage of the proposed IRS-based ISAC framework. Besides, the proposed two beamforming schemes based on the estimated location information achieve similar performance to the benchmark schemes assuming perfect channel state information (CSI), which verifies the effectiveness of beamforming design using sensed location information.

... Moreover, [23] and [24] consider IRS-aided multi-user MISO communication systems and aim at energy efficiency maximization and weighted sum-rate maximization, respectively. Besides, IRS has been deployed in orthogonal frequency division multiplexing (OFD-M) wireless systems [25], [26], integrated with simultaneous wireless information and power transfer (SWIPT) technique [27], [28] and applied in edge caching [29] to remarkably improve the system performance. These existing research works demonstrate the benefits of IRS to wireless communications. ...

Mobile edge computing (MEC) is envisioned as a promising technique to support computation-intensive and timecritical applications in future Internet of Things (IoT) era. However, the uplink transmission performance will be highly impacted by the hostile wireless channel, the low bandwidth, and the low transmission power of IoT devices. Recently, intelligent reflecting surface (IRS) has drawn much attention because of its capability to control the wireless environments so as to enhance the spectrum and energy efficiencies of wireless communications. In this paper, we consider an IRS-aided multidevice MEC system where each IoT device follows the binary offloading policy, i.e., a task has to be computed as a whole either locally or remotely at the edge server. We aim to minimize the total energy consumption of devices by jointly optimizing the binary offloading modes, the CPU frequencies, the offloading powers, the offloading times and the IRS phase shifts for all devices. Two algorithms, which are greedy-based and penalty-based, are proposed to solve the challenging nonconvex and discontinuous problem. It is found that the penalty-based method has only linear complexity with respect to the number of devices, but it performs close to the greedy-based method with cubic complexity with respect to number of devices. Furthermore, binary offloading via IRS indeed saves more energy compared to the case without IRS.

... In the literature, RISs have been integrated with existing technologies such as orthogonal frequency division multiplexing (OFDM) and multiple-input multiple-output (MIMO) to enhance their performance. Solutions have been proposed for fast and efficient channel estimation, maximizing the average sum-rate over subcarriers and maximizing the downlink achievable rate for the user by jointly optimizing the transmit power allocation at the base station (BS) and the passive reflection coefficients at the RIS [11][12][13][14][15][16][17]. The RIS concept has also been investigated to work collectively with related approaches, such as relaying and backscatter communications. ...

Reconfigurable intelligent surface (RIS)‐empowered communications is on the rise and is a promising technology envisioned to aid in 6G and beyond wireless communication networks. RISs can manipulate impinging waves through their electromagnetic elements enabling some sort of control over the wireless channel. The potential of RIS technology is explored to perform a sort of virtual equalization over‐the‐air for frequency‐selective channels, whereas equalization is generally conducted at either the transmitter or receiver in conventional communication systems. Specifically, using an RIS, the frequency‐selective channel from the transmitter to the RIS is transformed to a frequency‐flat channel through elimination of inter‐symbol interference (ISI) components at the receiver. ISI is eliminated by adjusting the phases of impinging signals particularly to maximize the incoming signal of the strongest tap. First, a general end‐to‐end system model is provided and a continuous to discrete‐time signal model is presented. Subsequently, a probabilistic analysis for elimination of ISI terms is conducted and reinforced with computer simulations. Furthermore, a theoretical error probability analysis is performed along with computer simulations. It is analysed and demonstrated that conventional RIS phase alignment methods can successfully eliminate ISI, and the RIS‐aided communication channel can be converted from frequency‐selective to frequency‐flat.

... In 4G, 5G, and wireless local area network (WLAN) communication standards, orthogonal frequency division multiplexing (OFDM) has become one of the most dominant multicarrier techniques due to its merits in combating with the frequency selective Rayleigh fading channel [20][21][22][23]. Owing to the superior of bit error rate (BER) performance and flexible design introduced by the IM technique, IM-aided schemes have attracted considerable attention over the past few years. ...

Index modulation (IM) is a novel digital modulation technique, which inactivates some subcarriers in orthogonal frequency division multiplexing (OFDM) to exploit the indices of the subcarriers to transmit bits implicitly, and has potential to further improve the energy efficiency and error performance. For the multiple-input multiple-output- (MIMO-) aided IoT devices, a highly efficient and low-complexity IM-aided scheme is needed to reduce the computational complexity at the receiver sides. In this paper, we propose a novel highly efficient MIMO-OFDM with IM scheme by performing IM on each transmit antenna subgroup, which contains two transmit antennas, to achieve two transmit diversity order and significant reduction in computational complexity at the cost of a minor spectral efficiency. To reduce the demodulation complexity, a low-complexity sequential Monte Carlo (SMC) theory-based detector is proposed, which exploits the null space submatrix of the preprocessed channel response matrix by using QR decomposition, to calculate the most likely transmitted IM patterns before the detection of the modulated symbols. Computer simulation results and complexity analysis show that the proposed IM-aided scheme achieves better error performance with extremely low computational complexity under the same constellation and the proposed SMC detector has potential to achieve near optimal bit error rate performance with considerably low demodulation complexity.

... Moreover, to reduce the design complexity and hardware cost, the reflection amplitude of the IRS elements is assumed to be equal to one [11]. The reflectioncoefficient matrix of the IRS is denoted by Θ = diag(e jθ 1 , ..., e jθ N ), where j denotes the imaginary unit, and θ n ∈ [0, 2π) is the phase shift of the nth IRS element, n ∈ N = {1, · · · , N }. between BS and IRS is characterized by matrix G ∈ C M ×N , which can be estimated by the methods proposed in [33], [34]. This channel is slowly varying in practice since the BS and the IRS are deployed at fixed locations. ...

Besides improving communication performance, intelligent reflecting surfaces (IRSs) are also promising enablers for achieving larger sensing coverage and enhanced sensing quality. Nevertheless, in the absence of a direct path between the base station (BS) and the targets, multi-target sensing is generally very difficult, since IRSs are incapable of proactively transmitting sensing beams or analyzing target information. Moreover, the echoes of different targets reflected via the IRS-established virtual links share the same directionality at the BS. In this paper, we study a wireless system comprising a multi-antenna BS and an IRS for multi-target sensing, where the beamforming vector and the IRS phase shifts are jointly optimized to improve the sensing performance. To meet the different sensing requirements, such as a minimum received power and a minimum sensing frequency, we propose three novel IRS-assisted sensing schemes: Time division (TD) sensing, signature sequence (SS) sensing, and hybrid TD-SS sensing. First, for TD sensing, the sensing tasks are performed in sequence over time. Subsequently, a novel signature sequence (SS) sensing scheme is proposed to improve sensing efficiency by establishing a relationship between directions and SSs. To strike a flexible balance between the beam pattern gain and sensing efficiency, we also propose a general hybrid TD-SS sensing scheme with target grouping, where targets belonging to the same group are sensed simultaneously via SS sensing, while the targets in different groups are assigned to orthogonal time slots. By controlling the number of groups, the hybrid TD-SS sensing scheme can provide a more flexible balance between beam pattern gain and sensing frequency. Moreover, ...

... A large number of reflecting elements do not have the transmit/receive ability. So, [90] introduced a practical transmission scheme for the IRS supported OFDM network that performs effective channel estimation and reflecting optimization by deploying the strongest channel impulse response maximization (SCM) techniques where IRS elements are assumed to be ON status at all the time. Then the conventional SDR method was compared with the proposed SCM scheme, which showed less computing complexity. ...

... In [7], a single-user RIS-assisted system is proposed, for interference mitigating purposes, authors propose a channel estimation (CE) strategy, where each time slot, only a single RIS element is turned on and the remaining elements are switched off. In this method, only T time slots are required to perfectly estimate the channels while in [8] authors propose a scenario in which all RIS elements are switched-on in each time slot using discrete Fourier transform (DFT) matrix for RIS phase shift in the CE process. ...

In this paper, we investigate channel estimation performance on sum-rate for reconfigurable intelligent surface (RIS) assisted unmanned aerial vehicles (UAV)-based multiple-input single-output (MISO) systems with multi-users. We assume that a drone with a predetermined trajectory acts as a base station. The channel estimation is performed by PARAllel FACtor (PARAFAC) decomposition method. Sum-rate simulations are performed for the cases where the channel is perfectly known and unknown. From the simulation results, it has been observed that the number of pilot signals used for channel estimation is quite effective on the total transmission speed as it improves the channel estimation.

... The existing RIS research mainly focuses on the new challenges that classical communication problems have faced since the introduction of RISs, such as channel estimation [9]- [13] and beamforming [14]- [16], and these studies focus on channel models in single-network scenarios [17]- [20]. According to our limited search, except in one review article [21], we did not find any literature on RIS network coexistence scenarios. ...

Reconfigurable intelligent surfaces (RISs) have attracted the attention of academia and industry circles because of their ability to control the electromagnetic characteristics of channel environments. However, it has been found that the introduction of an RIS may bring new and more serious network coexistence problems. It may even further deteriorate the network performance if these new network coexistence problems cannot be effectively solved. In this paper, an RIS network coexistence model is proposed and discussed in detail, and these problems are deeply analysed. Two novel RIS design mechanisms, including a novel multilayer RIS structure with an out-of-band filter and an RIS blocking mechanism, are further explored. Finally, numerical results and a discussion are given.
Our contributions: Based on our previous studies [21], this paper makes two contributions: (1) to deeply analyse and model RIS network coexistence for the first time and (2) to further analyse and evaluate two novel RIS structures, including a novel multilayer RIS structure with an out-of-band filter and an RIS blocking mechanism.

... For example, for a system with K UTs, N RIS meta-atom elements, and M BS antennas, the cascaded channel consists of KNM coefficients. To alleviate this drawback, several methods have been proposed to reduce the pilots, which impose a model on the overall channel having less coefficients, via, e.g., grouping the RIS elements [16], exploiting the presence of a common channel [17], and imposing a sparsity prior [18]. The second drawback of passive RISs is that one can only estimate the cascaded channel, instead of the individual ones, which limits the plasticity for the transmission scheme design and restricts the network management flexibility [19]. ...

Reconfigurable Intelligent Surfaces (RISs) are envisioned to play a key role in future wireless communications, enabling programmable radio propagation environments. They are usually considered as almost passive planar structures that operate as adjustable reflectors, giving rise to a multitude of implementation challenges, including the inherent difficulty in estimating the underlying wireless channels. In this paper, we focus on the recently conceived concept of Hybrid Reconfigurable Intelligent Surfaces (HRISs), which do not solely reflect the impinging waveform in a controllable fashion, but are also capable of sensing and processing an adjustable portion of it. We first present implementation details for this metasurface architecture and propose a convenient mathematical model for characterizing its dual operation. As an indicative application of HRISs in wireless communications, we formulate the individual channel estimation problem for the uplink of a multi-user HRIS-empowered communication system. Considering first a noise-free setting, we theoretically quantify the advantage of HRISs in notably reducing the amount of pilots needed for channel estimation, as compared to the case of purely reflective RISs. We then present closed-form expressions for the MSE performance in estimating the individual channels at the HRISs and the base station for the noisy model. Based on these derivations, we propose an automatic differentiation-based first-order optimization approach to efficiently determine the HRIS phase and power splitting configurations for minimizing the weighted sum-MSE performance. Our numerical evaluations demonstrate that HRISs do not only enable the estimation of the individual channels in HRIS-empowered communication systems, but also improve the ability to recover the cascaded channel, as compared to existing methods using passive and reflective RISs.

... Compared with the traditional on/off scheme in [14], this RIS reflection pattern achieves better estimation performance since the large beamforming gain of the RIS can be fully exploited with all the elements switched on. Without loss of generality, it is assumed that the matrix Φ is chosen to satisfy ΦΦ H = N KI M , which indicates that Φ is a scaled unitary matrix [30]. ...

To reap the promised gain achieved by distributed reconfigurable intelligent surfaces (RISs)-enhanced communications in a wireless network, timing synchronization among these metasurfaces is an essential prerequisite in practice. This paper proposes a unified framework for the joint estimation of the unknown timing offsets and the RIS channel parameters, as well as the design of cooperative reflection and synchronization algorithm for the distributed multiple-RIS communication. Considering that RIS is usually a passive device with limited capability of signal processing, the individual timing offset and channel gains of each hop of the RIS links cannot be directly estimated. To make the estimation tractable, we propose to estimate the cascaded channels and timing offsets jointly by deriving a maximum likelihood estimator. Furthermore, we theoretically characterize the Cramer-Rao lower bound (CRLB) to evaluate the accuracy of this estimator. By using the proposed estimator and the derived CRLBs, an efficient resynchronization algorithm is devised jointly at the RISs and the destination to compensate the multiple timing offsets. Based on the majorization-minimization framework, the proposed algorithm admits semi-closed and closed form solutions for the RIS reflection matrices and the timing offset equalizer, respectively. Simulation results verify that our theoretical analysis well matches the numerical tests and validate the effectiveness of the proposed resynchronization algorithm.

... The results of this paper can be extended to the general case with inter-IRS signal reflection in future work. It should also be mentioned that there exist some prior works focusing on the joint channel estimation and IRS reflection optimization [26], [43], [44]. ...

Intelligent reflecting surface (IRS) has emerged as a promising technique to enhance wireless communication performance cost-effectively. The existing literature has mainly considered IRS being deployed near user terminals to improve their performance. However, this approach may incur a high cost if IRSs need to be densely deployed in the network to cater to random user locations. To avoid such high deployment cost, in this paper we consider a new IRS aided wireless network architecture, where IRSs are deployed in the vicinity of each base station (BS) to assist in its communications with distributed users regardless of their locations. Besides significantly enhancing IRSs’ signal coverage, this scheme helps reduce the IRS-associated channel estimation overhead as compared to conventional user-side IRSs, by exploiting the nearly static BS-IRS channels over short distance. For this scheme, we propose a new two-stage transmission protocol to achieve IRS channel estimation and reflection optimization for uplink data transmission efficiently. In addition, we propose effective methods for solving the user-IRS association problem based on longterm/statistical channel knowledge and the selected user-IRS-BS cascaded channel estimation problem. Finally, all IRSs’ passive reflections are jointly optimized with the BS’s multi-antenna receive combining to maximize the minimum achievable rate among all users for data transmission. Numerical results show that the proposed co-site-IRS empowered BS scheme can achieve significant performance gains over the conventional BS without co-site IRS and existing schemes for IRS channel estimation and reflection optimization, thus enabling an appealing low-cost and high-performance BS design for future wireless networks.

... On the other hand, if the inter-IRS channel is LoS, the equivalent SISO channel in (4) can be decomposed into two decoupled parts, v T 1 φ 1 and v T 2 φ 2 , each corresponding to one of the two IRSs. In this case, for the passive beamforming design of {φ 1 , φ 2 }, we only need to acquire the two signature channel vectors v 1 ∈ C M ×1 and v 2 ∈ C M ×1 , which can be estimated separately by fixing one IRS's reflection while tuning the training reflection of the other IRS over time (similar to the single-IRS channel estimation proposed in [50]), thus leading to a reduced minimum training overhead of 2M pilot symbols. ...

Intelligent reflecting surface (IRS) has emerged as a promising technique for wireless communication networks. By dynamically tuning the reflection amplitudes/phase shifts of a large number of passive elements, IRS enables flexible wireless channel control and configuration and thereby enhances the wireless signal transmission rate and reliability significantly. Despite the vast literature on designing and optimizing assorted IRS-aided wireless systems, prior works have mainly focused on enhancing wireless links with single signal reflection only by one or multiple IRSs, which may be insufficient to boost the wireless link capacity under some harsh propagation conditions (e.g., indoor environment with dense blockages/obstructions). This issue can be tackled by employing two or more IRSs to assist each wireless link and jointly exploiting their single as well as multiple signal reflections over them. However, the resultant double-/multi-IRS-aided wireless systems face more complex design issues as well as new practical challenges for implementation compared to the conventional single-IRS counterpart, in terms of IRS reflection optimization, channel acquisition, as well as IRS deployment and association/selection. As such, a new paradigm for designing multi-IRS cooperative passive beamforming and joint active/passive beam routing arises, which calls for innovative design approaches and optimization methods. In this article, we give a tutorial overview of multi-IRS-aided wireless networks, with an emphasis on addressing the new challenges due to multi-IRS signal reflection and routing. Moreover, we point out important directions worthy of research and investigation in the future.

... , K l ). From equation (2), we can see that it suffices to estimate {R l ,l,k } and {Q l ,l,k,j } for jointly designing the passive beamforming coefficients {θ l } in the multiple IRS cooperative system [11], [19]. In this paper, we assume all the cascaded channel matrices {R l ,l,k } and {Q l ,l,k,j } are accurately estimated at the BS [2], [13]. ...

... In [47], a least squares Khatri-Rao factorization algorithm was presented for RIS-assisted MIMO systems. A transmission protocol for CE and RIS phase profile optimization was proposed in [48] for RIS-enhanced Orthogonal Frequency-Division Multiplexing (OFDM) systems. A holographic version of an RIS was designed in [49] and its application to THz massive MIMO systems was investigated, along with a closed-loop CE scheme. ...

The emerging technology of Reconfigurable Intelligent Surfaces (RISs) is provisioned as an enabler of smart wireless environments, offering a highly scalable, low-cost, hardware-efficient, and almost energy-neutral solution for dynamic control of the propagation of electromagnetic signals over the wireless medium, ultimately providing increased environmental intelligence for diverse operation objectives. One of the major challenges with the envisioned dense deployment of RISs in such reconfigurable radio environments is the efficient configuration of multiple metasurfaces with limited, or even the absence of, computing hardware. In this paper, we consider multi-user and multi-RIS-empowered wireless systems, and present a thorough survey of the online machine learning approaches for the orchestration of their various tunable components. Focusing on the sum-rate maximization as a representative design objective, we present a comprehensive problem formulation based on Deep Reinforcement Learning (DRL). We detail the correspondences among the parameters of the wireless system and the DRL terminology, and devise generic algorithmic steps for the artificial neural network training and deployment, while discussing their implementation details. Further practical considerations for multi-RIS-empowered wireless communications in the sixth Generation (6G) era are presented along with some key open research challenges. Differently from the DRL-based status quo, we leverage the independence between the configuration of the system design parameters and the future states of the wireless environment, and present efficient multi-armed bandits approaches, whose resulting sum-rate performances are numerically shown to outperform random configurations, while being sufficiently close to the conventional Deep Q-Network (DQN) algorithm, but with lower implementation complexity.

... If the RIS operates as a reflector, then the working principle is relatively straightforward and the radio signals naturally come off the surface via the reflection coefficients of the surface atoms to reach the UEs after propagating onto the surface from the BS. The challenge is to acquire the CSI and optimize all the reflection coefficients at once to shape the reflected beams [106], [107]. By contrast, the RIS utilizing surface waves does require a transition from surface wave to space wave. ...

With massive deployment, multiple-input-multiple-output (MIMO) systems continue to take mobile communications to new heights, but the ever-increasing demands mean that there is a need to look beyond MIMO and pursue the next disruptive wireless technologies. Reconfigurable intelligent surface (RIS) is widely considered a key candidate technology block to provide the next generational leap. The first part of this article provides an updated overview of the conventional reflection-based RIS technology, which complements the existing literature to include active and semiactive RIS, and the synergies with cell-free massive MIMO (CF mMIMO). Then, we widen the scope to discuss the surface-wave-assisted RIS that represents a different design dimension in utilizing metasurface technologies. This goes beyond being a passive reflector and can use the surface as an intelligent propagation medium for superb radio propagation efficiency. The third part of this article turns the attention to the fluid antenna, a novel antenna technology that enables a diverse form of reconfigurability that can combine with RIS for ultrahigh capacity, power efficiency, and scalability. This article concludes with a discussion of the potential synergies that can be exploited between MIMO, RIS, and fluid antennas.

... Moreover, [23] and [24] consider IRS-aided multi-user MISO communication systems and aim at energy efficiency maximization and weighted sum-rate maximization, respectively. Besides, IRS has been deployed in orthogonal frequency division multiplexing (OFD-M) wireless systems [25], [26], integrated with simultaneous wireless information and power transfer (SWIPT) technique [27], [28] and applied in edge caching [29] to remarkably improve the system performance. These existing research works demonstrate the benefits of IRS to wireless communications. ...

Mobile edge computing (MEC) is envisioned as a promising technique to support computation-intensive and time-critical applications in future Internet of Things (IoT) era. However, the uplink transmission performance will be highly impacted by the hostile wireless channel, the low bandwidth, and the low transmission power of IoT devices. Recently, intelligent reflecting surface (IRS) has drawn much attention because of its capability to control the wireless environments so as to enhance the spectrum and energy efficiencies of wireless communications. In this paper, we consider an IRS-aided multidevice MEC system where each IoT device follows the binary offloading policy, i.e., a task has to be computed as a whole either locally or remotely at the edge server. We aim to minimize the total energy consumption of devices by jointly optimizing the binary offloading modes, the CPU frequencies, the offloading powers, the offloading times and the IRS phase shifts for all devices. Two algorithms, which are greedy-based and penalty-based, are proposed to solve the challenging nonconvex and discontinuous problem. It is found that the penalty-based method has only linear complexity with respect to the number of devices, but it performs close to the greedy-based method with cubic complexity with respect to number of devices. Furthermore, binary offloading via IRS indeed saves more energy compared to the case without IRS.

While 5G is tasked to transform our lives for the better over the next 10 years, next-generation mobile communications, a.k.a. 6G, will undoubtedly demand even higher energy and spectral efficiencies capable of providing myriads of new services and experience to users everywhere they go. Although our technologies do evolve from one generation to the next, the root of the ambition in mobile communications has always been to ensure reliable performance from an uncertain, fluctuating medium. The previous generations have already seen numerous technologies such as advanced coding and signal processing, resource allocation, and most famously, multiple-input multiple-output to redeem some stability from the wireless medium. Inevitably, 6G will be built upon further disruptive technologies that enable another cycle of revolution. In this article, we examine one emerging technology, referred to as fluid antenna system that represents any software-controllable fluidic, conductive, or dielectric structure that can alter its shape and position to reconfigure the gain, radiation pattern, operating frequency, and other characteristics. Fluid antenna takes inspiration from Bruce Lee's Jeet Kune Do to innovate mobile communication systems design. In Bruce Lee's philosophy, one can imitate water to adapt combat style, whereas fluid antenna exploits the dynamic nature of fluids or switchable pixels to achieve ultimate flexibility for diversity and multiplexing benefits that have been unseen before in mobile devices, and the implication can be transformative. This article discusses the potential of fluid antenna systems for 6G, and in particular, we introduce six research topics in fluid antenna systems that if solved successfully could revolutionize mobile communications network design and optimization. This article intends to stimulate discussion that will help shape the development of 6G technologies.

An intelligent reflecting surface (IRS), is a new era of wireless communication towards intelligent and reconfigurable wireless networks. IRS can enhance communication quality between the network terminals with a small cost, low complexity, and low energy consumption when the direct connection has been blocked. To obtain the IRS features, the acquisition of channel state information (CSI) is substantial but it’s challenging in practice, due to the massive number of IRS elements without any capabilities of signal processing. To deal with this challenge in this survey, we first introduce an overview of channel estimation for IRS, then we address the main recent techniques proposed to estimate channels in IRS with various strategies in different applications. Furthermore, we summarize these recent works and list the main points that affect the estimation of the channel in IRS-aided communication system, and finally outline some future researches in IRS channel estimation and the conclusion of this survey.

The existing sub-6 GHz band is insufficient to support the bandwidth requirement of emerging data-rate-hungry applications and Internet of Things devices, requiring ultrareliable low latency communication (URLLC), thus making the migration to millimeter-wave (mmWave) bands inevitable. A notable disadvantage of a mmWave band is the significant losses suffered at higher frequencies that may not be overcome by novel optimization algorithms at the transmitter and receiver and thus result in a performance degradation. To address this, Intelligent Reflecting Surface (IRS) is a new technology capable of transforming the wireless channel from a highly probabilistic to a highly deterministic channel and as a result, overcome the significant losses experienced in the mmWave band. This paper aims to survey the design and applications of an IRS, a 2-dimensional (2D) passive metasurface with the ability to control the wireless propagation channel and thus achieve better spectral efficiency (SE) and energy efficiency (EE) to aid the fifth and beyond generation to deliver the required data rate to support current and emerging technologies. It is imperative that the future wireless technology evolves toward an intelligent software paradigm, and the IRS is expected to be a key enabler in achieving this task. This work provides a detailed survey of the IRS technology, limitations in the current research, and the related research opportunities and possible solutions.

Intelligent reflecting surface (IRS) has been regarded as a promising and revolutionary technology for future wireless communication systems owing to its capability of tailoring signal propagation environment in an energy/spectrum/hardware-efficient manner. However, most existing studies on IRS optimizations are based on a simple and ideal reflection model that is impractical in hardware implementation, which thus leads to severe performance loss in realistic wideband/multi-band systems. To deal with this problem, in this paper we first propose a more practical and more tractable IRS reflection model that describes the difference of reflection responses for signals at different frequencies. Then, we investigate the joint transmit beamforming and IRS reflection beamforming design for an IRS-assisted multi-cell multi-band system. Both power minimization and sum-rate maximization problems are solved by exploiting popular second-order cone programming (SOCP), Riemannian manifold, minimization-majorization (MM), weighted minimum mean square error (WMMSE), and block coordinate descent (BCD) methods. Simulation results illustrate the significant performance improvement of our proposed joint transmit beamforming and reflection design algorithms based on the practical reflection model in terms of power saving and rate enhancement.

Channel estimation is a critical task in multiple-input multiple-output digital communications that has effects on end-to-end system performance. In this work, we introduce a novel approach for channel estimation using deep score-based generative models. These models are trained to estimate the gradient of the log-prior distribution, and can be used to iteratively refine estimates, given observed measurements of a signal. We introduce a framework for training score-based generative models for wireless channels, as well as performing channel estimation using posterior sampling at test time. We derive theoretical robustness guarantees of channel estimation with posterior sampling in single-input single-output scenarios, and show that the observations regarding estimation performance are verified experimentally in MIMO channels. Our results in simulated clustered delay line channels show competitive in-distribution performance without error floors in the high signal-to-noise ratio regime, and robust out-of-distribution performance, outperforming competing deep learning methods by up to 5 dB in end-to-end communication performance, while the complexity analysis reveals how model architecture can efficiently trade performance for estimation latency.

Satellite communication is expected to play a vital role in realizing Internet of Remote Things (IoRT) applications. This article considers an intelligent reflecting surface (IRS)-assisted downlink low Earth orbit (LEO) satellite communication network, where IRS provides additional reflective links to enhance the intended signal power. We aim to maximize the sum-rate of all the terrestrial users by jointly optimizing the satellite’s precoding matrix and IRS’s phase shifts. However, it is difficult to directly acquire the instantaneous channel state information (CSI) and optimal phase shifts of IRS due to the high mobility of LEO and the passive nature of reflective elements. Moreover, most conventional solution algorithms suffer from high computational complexity and are not applicable to these dynamic scenarios. A robust beamforming design based on graph attention networks (RBF-GAT) is proposed to establish a direct mapping from the received pilots and dynamic network topology to the satellite and IRS’s beamforming, which is trained offline using the unsupervised learning approach. The simulation results corroborate that the proposed RBF-GAT approach can achieve more than 95% of the performance provided by the upper bound with low complexity.

Future wireless networks are expected to constitute a distributed intelligent wireless communications, sensing, and computing platform, which will have the challenging requirement of interconnecting the physical and digital worlds in a seamless and sustainable manner. Currently, two main factors prevent wireless network operators from building such networks: (1) the lack of control of the wireless environment, whose impact on the radio waves cannot be customized, and (2) the current operation of wireless radios, which consume a lot of power because new signals are generated whenever data has to be transmitted. In this paper, we challenge the usual “more data needs more power and emission of radio waves” status quo, and motivate that future wireless networks necessitate a smart radio environment: a transformative wireless concept, where the environmental objects are coated with artificial thin films of electromagnetic and reconfigurable material (that are referred to as reconfigurable intelligent meta-surfaces), which are capable of sensing the environment and of applying customized transformations to the radio waves. Smart radio environments have the potential to provide future wireless networks with uninterrupted wireless connectivity, and with the capability of transmitting data without generating new signals but recycling existing radio waves. We will discuss, in particular, two major types of reconfigurable intelligent meta-surfaces applied to wireless networks. The first type of meta-surfaces will be embedded into, e.g., walls, and will be directly controlled by the wireless network operators via a software controller in order to shape the radio waves for, e.g., improving the network coverage. The second type of meta-surfaces will be embedded into objects, e.g., smart t-shirts with sensors for health monitoring, and will backscatter the radio waves generated by cellular base stations in order to report their sensed data to mobile phones. These functionalities will enable wireless network operators to offer new services without the emission of additional radio waves, but by recycling those already existing for other purposes. This paper overviews the current research efforts on smart radio environments, the enabling technologies to realize them in practice, the need of new communication-theoretic models for their analysis and design, and the long-term and open research issues to be solved towards their massive deployment. In a nutshell, this paper is focused on discussing how the availability of reconfigurable intelligent meta-surfaces will allow wireless network operators to redesign common and well-known network communication paradigms.

Intelligent reflecting surface (IRS) is a promising new technology for achieving both spectrum and energy efficient wireless communication systems in the future. However, existing works on IRS mainly consider frequency-flat channels and assume perfect knowledge of channel state information (CSI) at the transmitter. Motivated by the above, in this paper we study an IRS-enhanced orthogonal frequency division multiplexing (OFDM) system under frequency-selective channels and propose a practical transmission protocol with channel estimation. First, to reduce the overhead in channel training as well as exploit the channel spatial correlation, we propose a novel IRS elements grouping method, where each group consists of a set of adjacent IRS elements that share a common reflection coefficient. Based on this method, we propose a practical transmission protocol where only the combined channel of each group needs to be estimated, thus substantially reducing the training overhead. Next, with any given grouping and estimated CSI, we formulate the problem to maximize the achievable rate by jointly optimizing the transmit power allocation and the IRS passive array reflection coefficients. Although the formulated problem is non-convex and thus difficult to solve, we propose an efficient algorithm to obtain a high-quality suboptimal solution for it, by alternately optimizing the power allocation and the passive array coefficients in an iterative manner, along with a customized method for the initialization. Simulation results show that the proposed design significantly improves the OFDM link rate performance as compared to the case without using IRS. Moreover, it is shown that there exists an optimal size for IRS elements grouping which achieves the maximum achievable rate due to the practical trade-off between the training overhead and IRS passive beamforming flexibility.

IRS is a new and revolutionizing technology that is able to significantly improve the performance of wireless communication networks, by smartly reconfiguring the wireless propagation environment with the use of massive low-cost passive reflecting elements integrated on a planar surface. Specifically, different elements of an IRS can independently reflect the incident signal by controlling its amplitude and/or phase and thereby collaboratively achieve fine-grained 3D passive beamforming for directional signal enhancement or nulling. In this article, we first provide an overview of the IRS technology, including its main applications in wireless communication, competitive advantages over existing technologies, hardware architecture as well as the corresponding new signal model. We then address the key challenges in designing and implementing the new IRS-aided hybrid (with both active and passive components) wireless network, as compared to the traditional network comprising active components only. Finally, numerical results are provided to show the great performance enhancement with the use of IRS in typical wireless networks.

In this letter, we consider the problem of channel estimation for large intelligent metasurface (LIM) assisted massive multiple-input multiple-output (MIMO) systems. The main challenge of this problem is that the LIM integrated with a large number of low-cost metamaterial antennas can only passively reflect the incident signals by certain phase shifts, and does not have any signal processing capability. To deal with this, we introduce a general framework for the estimation of the transmitter-LIM and LIM-receiver cascaded channel, and propose a two-stage algorithm that includes a sparse matrix factorization stage and a matrix completion stage. Simulation results illustrate that the proposed method can achieve accurate channel estimation for LIM-assisted massive MIMO systems.

Intelligent reflecting surface (IRS) is a revolutionary and transformative technology for achieving spectrum and energy efficient wireless communication cost-effectively in the future. Specifically, an IRS consists of a large number of low-cost passive elements each being able to reflect the incident signal independently with an adjustable phase shift so as to collaboratively achieve three-dimensional (3D) passive beamforming without the need of any transmit radio-frequency (RF) chains. In this paper, we study an IRS-aided single-cell wireless system where one IRS is deployed to assist in the communications between a multi-antenna access point (AP) and multiple single-antenna users. We formulate and solve new problems to minimize the total transmit power at the AP by jointly optimizing the transmit beamforming by active antenna array at the AP and reflect beamforming by passive phase shifters at the IRS, subject to users’ individual signal-to-interference-plus-noise ratio (SINR) constraints. Moreover, we analyze the asymptotic performance of IRS’s passive beamforming with infinitely large number of reflecting elements and compare it to that of the traditional active beamforming/relaying. Simulation results demonstrate that an IRS-aided MIMO system can achieve the same rate performance as a benchmark massive MIMO system without using IRS, but with significantly reduced active antennas/RF chains. We also draw useful insights into optimally deploying IRS in future wireless systems.

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