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Virtual Polarization Detection: A Vector Signal Sensing Method for Cognitive Radios
Abstract
A Virtual Polarization Detection (VPD) method based on the vector signal processing, is presented in this paper for the effective spectrum sensing of cognitive radios. The purpose of such VPD method is to exploit the orthogonal polarization component of primary signals besides the conjugate, in terms of vector information elements of signals. The spectrum sensing scenario of a single secondary user and multiple primary users is discussed, where the vector signals arrived at the secondary user are received by a pair of orthogonally polarized antennae. For the test of two-class problem (the primary user present class versus absent class), the secondary user optimizes the receiving polarization state to get the maximum primary signal to noise ratio by processing the received orthogonal polarization components. Specifically, it takes place in the processor of the secondary user virtually instead of antennae devices adaptation. The VPD method does not require any prior knowledge of the signal polarization states. The performance of our VPD method is compared with that of energy detection which uses scalar amplitude information only to sense the primary users. Simulation results show that the VPD method improves the spectrum sensing performance significantly.
... The dual polarized spectrum sensing is firstly studied in [13]. A reconfigurable polarization detection (RPD) method is proposed in [14], in which the virtual polarization is mentioned. Virtual polarization is an adaptive technology, in which the receive antennas can be adaptively adjusted to match the transmit antennas. ...
... So the power of effective signal can be the maximum value. Nevertheless, the considerable correlation detection encountered the problem that the step size of the iteration should be a small value, which results in the high requirement of computation capacity [14]. The RPD method can be considered to be the energy based polarization detector, which select the optimal combine method for the pair of polarized antennas, and can obtain the optimal SNR. ...
Wireless communications is one of the most rapidly developing segments of the telecommunications industry. A large amount of intelligent terminal occupying the spectrum results in the reduction of radio spectrum resources. Cognitive radio is considered to be the most effective approach to solve this problem, which required rapid and exact spectrum sensing. This paper proposes a novel polarized antenna method based on likelihood ratio test and stochastic resonance. In the condition of adiabatic approximation, the stochastic resonance can increase signal to noise ratio, and adequately transfer the energy of noise to original signal. The proposed method applies the stochastic resonance to each polarized component. The experiments show that the proposed spectrum sensing method is suitable for generalized likelihood ratio test in additional white Gussion noise and lower signal to noise ratio, rather than polarized channel matrix and idealistic likelihood ratio test.
... Since PM changes the amplitude and the phase of the OFDM signal, the information carried by PM should be removed first at the receiver. After extracting the polarization parameters, the data transferred by the PM branch can be recovered using the polarization matching receive method [22]. Then the original amplitude and phase of the OFDM signals as 4 well as the data carried by the QAM branch can be recovered. ...
... Assume lowest modulation order for QAM and PM at first while R sum < R do if l ∈ {1, 2, · · ·, M } then Compute SER Q (m + 1) and SER Q (m) under the impact of PDL, PA nonlinearity and AWGN noise else {l ∈ {M, M + 1, · · ·, 2M }} Compute SER P (m + 1) and SER P (m) under the impact of PDL and AWGN noise Compute ∆η(m) for each subgroup using equation (22), and choose the maximal l th subgroup Update the modulation order of all the subcarriers in subgroup l to the next higher level ...
In this paper, an adaptive polarization-QAM modulation (APQAM) scheme is proposed to improve the power amplifier (PA) energy efficiency (EE) in OFDM systems. Since we found that polarization modulation (PM) has better EE performance than QAM in the nonlinear region of PA while QAM outperforms PM in the linear region, we can combine these two modulation schemes together and adjust their modulation orders adaptively to obtain higher EE performance. First, a truncated Taylor series model is used to represent PA nonlinearity, so the effects of both the in-band distortions and the out-of-band emissions on the OFDM signals can be analyzed. Second, two APQAM algorithms are investigated in both AWGN channel and depolarization channel with power dependent loss. Further, symbol error rate performance of the APQAM scheme is obtained in different channel conditions, and the influence of channel estimation error is analyzed to testify the robustness of the proposed APQAM scheme. Simulation results show that, if perfect channel state information is obtained, the EE of the proposed scheme is nearly fifty percent more than that of the traditional QAM scheme in OFDM systems.
... It can be easily seen that if γ(t) and φ(t) in (3) vary continuously, we can obtain arbitrary continuous polarizations. This is the basic principle to control the polarization P(t) through the amplitude and phase weighting operators [14]. More details can be found in [15]. ...
Facing the challenges of spectrum shortage and complex depolarization effects in wireless communication, a multilevel continuous polarization modulation (MCPoM) scheme is investigated to achieve high spectral efficiency and improve the symbol error rate performance in the practical depolarization channels. The principle of the MCPoM modulation is stated in details on the basis of the MCPoM system model. Then a noncoherent and a coherent MCPoM demodulation methods are proposed as the differential demodulation and the suboptimum sequence detection based demodulation, respectively. Furthermore, considering the depolarization effect of polarization-dependent loss in the practical wireless channels, MCPoM is evaluated with two influences of power attenuation and polarization difference distortion. After that, we propose a polarization pre-compensation algorithm for MCPoM to mitigate the influences of polarization-dependent loss. The performances of the proposed scheme are evaluated with symbol error rate and spectral efficiency. Simulations results demonstrate that higher spectral efficiency and enhanced symbol error rate of the proposed MCPoM scheme are guaranteed in the depolarization channels.
... Polarization spectrum hole sensing was proposed for cognitive radio to optimize the received polarization at the SU in order to protect the PU from interference caused by the SU and to reduce the interference from PU to SU [16]. Optimal Polarization Reception (OPR) was proposed for CR to improve the SINR [17]. A new blind spectrum sensing method based on the polarization characteristic of the received signal, which is completely represented by the orientation of a polarization vector, was proposed [18], and a closed-form expression for the probability of false alarm and probability of detection under Additive White Gaussian Noise (AWGN) and Rayleigh-fading channels was derived. ...
Schemes for spectrum holes sensing for cognitive radio based on the estimation of the Stokes parameters of monochromatic and quasimonochromatic polarized electromagnetic waves are developed. Statistical information that includes the variations of the polarization state in both cases (present and absent) of Primary User (PU) is accounted for. A detector based on the fluctuation of the Stokes parameters is analyzed, and
its performance is compared with that of energy detectors, which use only the scalar amplitude information to sense the PU signal. The cooperative spectrum sensing based on the polarization in which the reporting channels are noisy will be investigated. The cluster technique is proposed to reduce the bit error probability due to channel impairment. A closed-form expression for the polarization detection is derived using α-μ generalized fading model, which provides directly an expression for the special cases of Nakagami-m and Weibull models as well as their derivatives. These expressions are verified using simulation. The results show that the polarization spectrum sensing gives superior performance for a wide range of SNR over the conventional energy detection method.
Polarization is an important property of electromagnetic waves. It has shown the great application potential in optical fiber, radar, and satellite communications, where polarization has been exploited to be a promising means of enhancing channel capacity. The existing research has shown that, in theory, it has great potential to sixfold the channel capacity by using six co-located orthogonally polarized electric and magnetic dipoles. Wireless communications exploits the electromagnetic medium, which is also intrinsically polarization-sensitive. In the past decades, wireless communications have mainly exploited the dimensions of time, frequency, and space, and most wireless channels, technologies, and applications have been devised without explicit consideration of polarization. To keep up with the recent exponentially growing network capacity, as such, leveraging polarization for wireless communications is a logical next step. However, exploiting polarization in wireless communications involves many challenges that differentiate it from conventional polarization applications in terms of optical fiber, radar, and satellite communications due to complex depolarization effects, restriction on additional gain offered, and limited degrees of freedom in the polarization domain. These challenges have inspired recent advances, particularly related to polarization channels, polarization technologies (such as polarization-based modulation, polarization-based signal sensing, polarization-based orthogonal transmission, and polarization-based filtering), and their applications to emerging communication scenarios including energy-efficient communications, cognitive radio networks, and in-band full-duplex transmission. This paper thoroughly surveys these recent advances and presents the state-of-the-art research progress on each aspect. Furthermore, open research issues and challenges are discussed in order to provide perspectives for future research directions.
The continuously increasing demand of spectrum and current static spectrum allocation policies are rendering the available radio spectrum scarce. To address the problem of spectrum scarcity in the satellite paradigm, cognitive satellite communications has been considered as a promising technique. In addition to the existing spectrum sharing dimensions such as frequency, time, and space, polarization can be exploited as an additional degree of freedom in order to explore the spectral gaps in the underutilized licensed spectrum. In this context, this chapter firstly provides an overview of the existing works in polarization-based spectrum sharing. Secondly, it presents the theoretical analysis of energy detection technique for dual polarized Additive White Gaussian Noise and Rayleigh fading channels considering the spectral coexistence scenarios of dual and hybrid satellite systems. Thirdly, it provides the comparison of different combining techniques in terms of the sensing performance. Finally, it provides interesting future research directions in this domain.
Spectrum sensing exploiting polarization has been identified as an effective method for improving detection performance. However, the optimal polarization-based sensing algorithm with an upper bound performance has not yet been developed. The polarization likelihood ratio test (PLRT) is derived using the Neyman-Pearson (NP) theorem, resulting in an optimal detector with regard to the likelihood ratio. The best linear polarization processor or filter, the polarization matched filter (PMF), which processes the observed polarization data to provide the maximum signal-to-noise ratio (SNR) to the output of the filter, is also derived. Although the PLRT and PMF provide an ideal upper bound on the performance of all detection methods that exploit polarization when likelihood functions or statistic parameters of likelihood functions are known exactly, their performance for realistic blind sensing remains unknown. Using the generalized likelihood ratio test (GLRT) method, we formulate two practical polarizationbased detectors, GLRT based on received electric-field vector (GLRT-EV) and GLRT of the Stokes sub-vector (GLRTSSV), according to the statistical distribution of observed data expressed as a received electric-field vector and a Stokes vector, respectively. The two GLRT detectors can serve as a practical bound when all statistical parameters are unknown. Theoretical and numerical simulation results of the detection performance for the proposed detectors are presented. Additionally, these polarization-based detectors were thoroughly tested via a realistic wireless regional area network (WRAN). Our experimental results show that the GLRT-EV detector exhibits better performance than other polarization-based detectors both in sample and computational complexity, which is particularly critical in real-time applications.
In this work, a joint polarization adaption and beamforming technique is proposed for horizontal spectrum sharing for TD-LTE and FD-LTE users. The polarization and spatial information of multiple dual-polarized antennas on current LTE nodes is exploited to mitigate the mutual interference among the primary, TD-LTE and FD-LTE users. By this means, the opportunities in polarization and spatial domains are exploited, which means the licensed spectrum can be shared by TD-LTE and FD-LTE users with primary users simultaneously, thus the spectrum efficiency is improved. Simulation results show that the proposed technique can improve the spectrum efficiency in comparison traditional spectrum sharing approaches that utilize the spectrum opportunities in temporal domain, while acceptable interference is introduced to the primary user.
In cognitive radios, the biggest challenge is spectrum sensing. It usually makes use of the amplitude, frequency or space dimension of the received signal to differentiate signal from background noise. Polarization, also as an inherent characteristic of signals, provides an additional degree of freedom in signal space. Polarization-based spectrum sensing has been identified as an effective method for improving detection performance. In this paper, various polarization-based spectrum sensing methods including the optimal polarization likelihood ratio test using Neyman–Pearson theorem, virtual polarization detection utilizing maximum signal to noise ratio method and blind polarization detectors based on generalized likelihood ratio test method are reviewed. Then, a comprehensive comparison of various polarization-based sensing methods in terms of detection performance and computational complexity is detailed. Finally, challenges and possible future studies on polarization-based spectrum sensing are described. Copyright © 2015 John Wiley & Sons, Ltd.
In this paper, we consider the problem of spectrum sensing in cognitive radios by exploring Stokes sub-vector, which fully represents energy and polarization information of signal, captured by dual polarized antennas. We first find the fact that the correlation between Stokes variables (i.e., the elements of Stokes sub-vector) of the mixture of primary signal and noise are different from that of noise’s with high probability. Based on this, a new energy-polarization based detection is proposed. The false alarm probability and the detection threshold for the proposed detector are available in closed form. Our simulations show that the proposed method demonstrates a significant performance improvement with respect to existing polarization based methods due to the exploitation of both energy and polarization information and less affectedness by noise power uncertainty.
In this paper, we consider the problem of spectrum sensing in cognitive radios by exploiting Stokes subvector, which can completely describe energy and polarization information of the received vector signal captured by dual-polarized antennas. We first find that both component correlation between Stokes variables (i.e., the elements of Stokes subvector) and vector correlation between Stokes subvectors containing signal and noise are different from that of noise only with high probability. Therefore, two new blind detectors, namely, component-correlation-based energy-polarization detection (CCB-EPD) and vector-correlation-based energy-polarization detection (VCB-EPD), are proposed, respectively. The analysis results reveal that CCB-EPD and VCB-EPD are all constant false alarm rate detectors, and the VCB-EPD method achieves better performance than CCB-EPD when channel is low depolarized and vice versa. Simulations show that the proposed two methods exhibit better performances than other multiantenna-based detectors whether priori polarization information of primary user is known or not. We also show that the two proposed methods have performance improvement with respect to existing polarization-based detectors due to the exploitation of both energy and polarization information and the unaffectedness by noise uncertainty. The experimental results verify that the proposed two methods can satisfy the performance requirement specified by the IEEE 802.22 standard.
SUMMARYA new spectrum sensing algorithm-degree of polarization (DoP) sensing algorithm is proposed in this paper. By exploiting a pair of dual-polarized antenna at the receiver, DoP of the received vector signal is estimated and utilized to detect the presence of primary users based on the polarization characteristics of electromagnetic waves. The dual-polarized narrowband and broadband systems are both considered for DoP detection. In theoretical analysis, we derive the probability of detection, the probability of false and detection threshold of the proposed algorithm. It is shown that our algorithm overcomes the noise uncertainty problem. Considering the polarization-sensitive channel impairments, the impact of polarization mode dispersion on DoP detector is discussed. This method can be utilized for various signal detection applications without requiring the knowledge of signal, transmission channel, and noise power. In simulations based on wireless microphone signals, by applying polarization information signal carries, DoP achieves a better detection performance than arithmetic-to-geometric mean detector, the maximum-to-minimum ratio eigenvalue detector, and energy detector with noise uncertainty. The simulations based on digital video broadcasting-terrestrial signals are also presented, which may show the detection performance of the proposed method may be affected by polarization mode dispersion. Copyright © 2013 John Wiley & Sons, Ltd.
In this paper, we consider the problem of spectrum sensing in cognitive radios (CRs) by exploiting inherent polarization characteristics of signal. Since polarization vector can completely describe the radiation׳s polarization characteristics, we first derive the probability density function (PDF) of received polarization vector and its moments. Then we find the fact that both component and serial correlations of received polarization vector (i.e., the mixed polarization vector of primary signal and noise) are different from those of noise with high probability. This distinctive difference can be used to decide whether the primary signal exists or not. Therefore, component correlation sensing (CCS) algorithm and serial correlation sensing (SCS) algorithm are proposed respectively. Furthermore the closed-form expressions of probabilities of false alarm and detection are available for CCS and SCS algorithms. Simulations show that both CCS and SCS detectors achieve better performance with higher cross-polar discrimination (XPD) and polarization channel correlation coefficients. We also show that, if channel is highly depolarized, CCS performs better than SCS. Otherwise, the latter shows better performance. Compared with existing polarization based detectors, both CCS and SCS detectors perform better in the presence of noise power uncertainty.
To improve the Power Amplifier (PA) energy efficiency, a Polarization Modulation (PM) scheme that uses the Polarization State (PS) as the information bearing parameter is proposed. Since the PS determined by orthogonally dual-polarized antennas is unaffected by PA, PM can let PA operate in nonlinear region without suffering the distortion. Furthermore, to mitigate the wireless channel depolarization impairment to PM from the polarization dependent loss and the polarization mode dispersion, an Optimal Constellation Pre-compensation (OCP) algorithm is also presented. The simulation results show, with same symbol error rate, PM can reduce the energy consumption per bit by 25% at most compared with the traditional multi-phase shift keying.
Exploring new techniques for spectrum sensing (SS), which can detect the weak primary signals instantly, has been an important research challenge. In this paper, the problem of enhancing SS efficiency in cognitive SatComs has been considered. The analysis of different combining techniques has been carried out for SS using dual polarized antenna. Furthermore, polarization states of received signals are exploited and based on obtained polarization states, Optimum Polarization Based Combining (OPBC) technique has been used for carrying out SS in the satellite terminal. The sensing performance of OPBC technique has been compared to selection combining (SC), equal gain combining (EGC) and maximum ratio combining (MRC) techniques. The simulation results show that OPBC technique achieves a great improvement in sensing efficiency over other considered techniques at the expense of complexity in a dual polarized AWGN channel.
In this paper, we propose a new blind spectrum sensing method based on the polarization vector's orientation characteristics of the received signal. We first discuss a spectrum sensing model based on polarization characteristic and develop the directional statistics of a polarization vector which can be used to discriminate the signal and noise. Then, a new polarization sensing algorithm (GLRT-PV) is introduced based on the generalized likelihood ratio test (GLRT) paradigm. Applying the recent advances in directional statistics, we derive closed-form expressions of both the probability of false alarm and the probability of detection. Our simulation results show that the proposed GLRT-PV method exhibits better performance than other existing methods in the case of unknown primary transmitter polarization and/or in the presence of noise power uncertainty.
A new spectrum sensing algorithm-degree of polarization (DoP) sensing algorithm is proposed in this paper. By exploiting a pair of dual-polarized antenna at the receiver, DoP of the received vector signal is estimated and utilized to detect the presence of primary users (PU) based on the polarization characteristics of electromagnetic waves. This method requires no prior information of the PU signals and the channels from PUs to the secondary users (SU). Theoretical analysis of detection probability, false alarm probability and threshold of the proposed algorithm is presented in detail. The theoretical analysis also shows that our algorithm overcomes the noise uncertainty problem. Simulations based on wireless microphone signals considering different SU receiver scenarios are provided to certify the effectiveness of the proposed method. Compared with the energy detector (ED), the maximum-to-minimum ratio eigenvalue (MME) detector and the arithmetic-to-geometric mean (AGM) detector, by applying polarization information signal carries, DoP achieves a better detection performance than AGM, MME and ED with noise uncertainty.
In this paper, we propose a new blind spectrum sensing method based on the polarization characteristic of the received signal, which is completely represented by the orientation of a polarization vector. We first discuss a spectrum sensing model based on polarization vectors' orientation. Then we develop the directional statistics of polarization vectors that contain both the signal and noise or noise only. The distinctive difference between the two statistics can be used to decide whether the primary signal exists or not. Based on this, by using the well-known generalized likelihood ratio test (GLRT) paradigm, a new polarization sensing algorithm GLRT-polarization vector (GLRT-PV) is proposed. By applying directional statistics, we derive closed-form expressions for the probability of false alarm and the probability of detection under both dual-polarized additive white Gaussian noise (AWGN) and Rayleigh-fading channels. Our numerical simulation and experimental results show that the proposed method exhibits better performance than other existing methods in the case of unknown primary transmitter polarization and/or presence of noise power uncertainty.
To improve the power amplifier (PA) energy efficiency, a polarization–amplitude–phase modulation (PAPM) scheme in wireless communication is proposed. The proposed scheme introduces the signal’s polarization state (PS), amplitude, and phase as the information-bearing parameters. Thus, the data rate can be further enhanced on the basis of the traditional amplitude–phase modulation. Also, since the transmitted signal’s PS completely manipulated by orthogonally dual-polarized antennas is unaffected by PA, PAPM can let PA work in its nonlinear region to acquire high PA efficiency. To further optimize the PA energy efficiency based on PAPM, a constrained optimization problem regarding the output back-off value and the ratio between the data carried by the PS and the amplitude–phase is formulated, and the distribution of the optimum solutions is presented. The simulation results show that PAPM can improve the PA energy efficiency significantly.
Compared to classical spatially separated multiple antenna system, cross-polarized co-located antenna systems are an interesting way to reduce equipment size while reducing the inter-antenna correlation. In this paper the spectrum sensing of a Cognitive Radio (CR) system taking advantage of polarization diversity under Rayleigh fading is investigated and compared to an equivalent system using spatial diversity. This analysis is based on a theoretical formulation applied to a real-world scenario. For this purpose, an outdoor-to-indoor measurement campaign at a frequency of 3.5 GHz is realized, where an indoor secondary user senses the signals received from an outdoor primary base station. The signals received at each antenna are first combined and then applied to an energy detector. The theoretical expressions are simulated in the measurement context. The detection probability behavior as a function of distance between the Primary Transmitter (PTx) and the Secondary Terminal (STE) and the inter-antenna correlation effect on the sensing performance are studied.
Spectrum sensing is an essential enabling functionality for cognitive radio networks to detect spectrum holes and opportunistically use the under-utilized frequency bands without causing harmful interference to legacy networks. This paper introduces a novel wideband spectrum sensing technique, called multiband joint detection, which jointly detects the signal energy levels over multiple frequency bands rather than consider one band at a time. The proposed strategy is efficient in improving the dynamic spectrum utilization and reducing interference to the primary users. The spectrum sensing problem is formulated as a class of optimization problems in interference limited cognitive radio networks. By exploiting the hidden convexity in the seemingly non-convex problem formulations, optimal solutions for multiband joint detection are obtained under practical conditions. Simulation results show that the proposed spectrum sensing schemes can considerably improve the system performance. This paper establishes important principles for the design of wideband spectrum sensing algorithms in cognitive radio networks.
In cognitive wireless networks where secondary users (SUs) opportunistically access spectral white spaces of primary users (PUs), there exists an inherent tradeoff between sensing and transmission due to the competing goals of PU protection and SU access maximization. This paper studies means of sensing-transmission for SUs to better manage the competing goals by defining utility function to reward the SU for successful packet transmissions and to penalize it for colliding with PU. To maximize the SU utility, we present a threshold-based sensing-transmission structure that is optimal under a technical constraint. Both perfect sensing and imperfect sensing are considered, with or without SU acknowledgement of reception. This SU access scheme optimizes SU access efficiency while protecting PU performance. It sets a benchmark and provides insight for the design of sensing-transmission control in cognitive networks such as IEEE 802.22.
Wireless systems require spectrum to operate, but interference is likely if radios in physical proximity simultaneously operate on the same band. Therefore, spectrum is a potentially scarce resource; across the planet today, spectrum is regulated so that most bands are allocated exclusively to a single system licensed to use that band in any given location. However, such static spectrum allocation policies lead to significant underuse of spectrum [1]. This can be viewed as a kind of regulatory overhead that is paid to get reliable operation. With frequency-agile radios becoming commercially feasible within the next 5-10 years, Cognitive Radio is about making such radios smart enough to share spectrum and reduce the regulatory overhead. This is an impending wireless revolution that draws upon many signal-processing areas including robust detection, sensor networks, as well as the design of incentives and waveforms. This is a short column touching on the issues; further technical details/references can be found in [2]. THE OPPORTUNITY IN THE TELEVISION BANDS Right now, there is significant excitement surrounding the broadcast television bands. The Federal Communications Commission (FCC) has started considering dynamic approaches for spectrum sharing and the IEEE has launched the 802.22 standards process to use TV-band spectrum holes for enabling wide-area Internet service [3], [4]. This context is illustrated in Figure 1.
Indoor multiple-inputmultiple-output (MIMO) channel measurements undertaken with spatially separated dipoles are compared with crossed dipoles at 2.4 GHz. This essentially analyses how polarization can be exploited at the mobile using practical antennas where polarization diversity is an inherent feature within an angular diversity system. Results are encouragingly comparable between the two scenarios in terms of capacity and diversity order, which indicates that polarization could be exploited within an angular based MIMO antennas that are more compact than spatially separated antennas.
Spectrum sensing is an essential enabling functionality for cognitive radio networks to detect spectrum holes and opportunistically use the under-utilized frequency bands without causing harmful interference to legacy networks. This paper introduces a novel wideband spectrum sensing technique, called multiband joint detection, which jointly detects the signal energy levels over multiple frequency bands rather than consider one band at a time. The proposed strategy is efficient in improving the dynamic spectrum utilization and reducing interference to the primary users. The spectrum sensing problem is formulated as a class of optimization problems in interference limited cognitive radio networks. By exploiting the hidden convexity in the seemingly non-convex problem formulations, optimal solutions for multiband joint detection are obtained under practical conditions. Simulation results show that the proposed spectrum sensing schemes can considerably improve the system performance. This paper establishes important principles for the design of wideband spectrum sensing algorithms in cognitive radio networks.
Cooperative spectrum sensing for cognitive radio networks is recently being studied to simultaneously minimize uncertainty in primary user detection and solve hidden terminal problem. Sensing wideband spectrum is another challenging task for a single cognitive radio due to large sensing time required. In this paper, we introduce a technique to tackle both wideband and cooperative spectrum sensing tasks. We divide the wideband spectrum into several subbands. Then a group of cognitive radios is assigned for sensing of a particular narrow subband. A cognitive base station is used for collecting the results and making the final decision over the full spectrum. Our proposed algorithm minimizes time and amount of energy spent for wideband spectrum scanning by a cognitive radio, and effectively detects the primary users in the wideband spectrum thanks to cooperative shared spectrum sensing.
We consider a multi-channel opportunistic communication system where the states of these channels evolve as independent and statistically identical Markov chains (the Gilbert-Elliot channel model). A user chooses one channel to sense and access in each slot and collects a reward determined by the state of the chosen channel. The problem is to design a sensing policy for channel selection to maximize the average reward, which can be formulated as a multi-arm restless bandit process. In this paper, we study the structure, optimality, and performance of the myopic sensing policy. We show that the myopic sensing policy has a simple robust structure that reduces channel selection to a round-robin procedure and obviates the need for knowing the channel transition probabilities. The optimality of this simple policy is established for the two-channel case and conjectured for the general case based on numerical results. The performance of the myopic sensing policy is analyzed, which, based on the optimality of myopic sensing, characterizes the maximum throughput of a multi-channel opportunistic communication system and its scaling behavior with respect to the number of channels. These results apply to cognitive radio networks, opportunistic transmission in fading environments, and resource-constrained jamming and anti-jamming.
A spectrum sharing based cognitive radio (CR) communication system, which consists of a secondary user (SU) having multiple transmit antennas and a single receive antenna and a primary user (PU) having a single receive antenna, is considered. The channel state information (CSI) on the link of the SU is assumed to be perfectly known at the SU transmitter (SU-Tx). However, due to loose cooperation between the SU and the PU, only the channel mean and/or covariance (partial CSI) of the link between the SU-Tx and the PU is available at the SU-Tx. With the partial CSI and a prescribed transmit power constraint, our design objective is to determine the transmit signal covariance matrix that maximizes the rate of the SU while keeping the interference power to the PU below a threshold with high probability. This problem, termed the robust cognitive beamforming problem, can be naturally formulated as a semi-infinite programming (SIP) problem with infinitely many constraints. The SIP problem is transformed into a finite constrained optimization problem and yields to a simple analytical solution, which is developed from a geometric perspective. As an alternative, a much more complex approach based on an interior point algorithm is provided. Simulation examples are presented to validate the effectiveness of the proposed algorithms.
In this paper we present an experimental study that comprehensively evaluates the performance of three different detection methods proposed for sensing of primary user signals in cognitive radios. For pilot and energy detection, our measurement results confirmed the theoretical expectations on sensing time performance. However, a physical implementation of these detectors in the presence of real noise uncertainties, analog impairments and interference allowed us to establish practical bounds on the detectable signal levels. In the case of collaborative detection, our analysis of experimental data collected in indoor environments identified the design parameters that can significantly improve the sensing gain: adaptive threshold, spatial separation and multiple antennas.
Distinction of the type of modulated signals is very important in cognitive radio system. In this paper, a novel approach to signal classification is proposed for cognitive radio. Combining the spectral cyclostationary features, embed SVM into the framework of HMM to construct a hybrid HMM/SVM classifier for signal recognition. The simulation results show that the high performance and robustness of the proposed approach, even in low SNR of -5dB. Compared to the conventional methods including the classifiers based on HMM or ANN, the proposed approach has a rather higher recognition rate of signals.
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Cognitive radios are proposed for secondary users (SU) recovering spectrum holes unused by primary users (PU) in time and space domain. However, the polarization domain of spectrum, allowing simultaneous frequency usage at overlapped areas, is unexploited adequately. In this paper, a novel polarization spectrum holes sensing scheme is proposed for cognitive radios, which exploits transmit and receive polarizations taking into account the interference constraint of PU and the signal to interference noise ratio (SINR) demands of SU. The scheme enables novel spectral sharing opportunities between PU and SU, thereby improving the spectrum utilization efficiency of the wireless communication networks. The scheme is evaluated based on the principle of virtual polarization adaptation, and it has been concluded that the scheme is feasible.
A random periodic spectrum sensing scheme is proposed for cognitive radio networks. The sensing period is extended to a general form as a random variable. A generalized Markov analytical model for sensing period optimization is presented, and the optimal sensing period to maximum rewards generated by the channel is derived. Numerical examples show that sensing period does affect the maximum rewards of the channel, and the analytical model is justified by its analytical flexibility since it uses a general sensing period and hence the model can be easily adapted for the analysis of many different applications.
The ratio of the average target-signal power to the average unwanted-signal power at the input of a radar detection receiver can be significantly increased by applying the method of clutter/interference suppression described in the paper. The polarisation state of the emissions, the object-backscatter field, and the interference field are all taken into account in a technique referred to as `virtual adaptation¿ of the polarisation state of the transmit and receive antennas. This technique can be used to complement filtering techniques in the frequency and space domains. Attention is specifically drawn to the potential advantages of multinotch polarisation suppression filters of the `logic-product¿ type, which might have applications in cases where there are uncertainties regarding the polarisation state of unwanted signals that are to be suppressed.
A scheme based on optimal polarization receiving (OPR) is proposed for the cognitive radios to improve the signal to interference and noise ratio (SINR) of the cognitive user. This OPR-Based scheme will not produce extra interference to the licensed user. The simulation results show that without increasing the transmitting power of the cognitive user, the cognitive receiver with OPR-Based scheme can improve the SINR by over 30 dB at most compared with the traditional cognitive receiver.
Abstract—It is expected for multi-channel ad hoc networks to adopt cognitive radio (CR) technology since the CR technology can provide enough channels for high speed data transmission. These CR ad hoc networks should maintain accurate channel state information not only for protecting primary users (PUs) but also for obtaining enough channels. To cope with this, we propose a novel dissemination scheme for channel state information and an adjustment scheme of sensing priorities. According to the proposed dissemination scheme, a CR node can inform the PU presence or a request for a temporary quiet period on a channel for its sensing. When a CR node receives the PU presence on a channel, the CR node adjusts the sensing priority of a channel in order to confirm the availability of the channel by its own sensing. With these schemes, CR nodes cooperate together to accurately maintain the channel state information while each CR node grasps available channels in its own location. Using a simulation, we show that the proposed scheme provides more channels while guaranteeing the right of PUs. Since the proposed scheme uses only two bit channel map for informing the channel status and sends it on top of control packets, the performance gain can be achieved by low overhead.
In emerging cognitive radio (CR) networks with spectrum sharing, the first cognitive task preceding any dynamic spectrum access is the sensing and identification of spectral holes in wireless environments. This paper develops a distributed compressed spectrum sensing approach for (ultra-)wideband CR networks. Compressed sensing is performed at local CRs to scan the very wide spectrum at practical signal-acquisition complexity. Meanwhile, spectral estimates from multiple local CR detectors are fused to collect spatial diversity gain, which improves the sensing quality especially under fading channels. New distributed consensus algorithms are developed for collaborative sensing and fusion. Using only one-hop local communications, these distributed algorithms converge fast to the globally optimal solutions even for multi-hop CR networks, at low communication and computation load scalable to the network size.
We propose a closed-loop multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) transmission scheme appropriate for the IEEE 802.22 wireless regional area network (WRAN) channel environments. The proposed scheme utilizes the Grassmannian beamforming and an antenna selection algorithm to maintain bit-error-rate (BER) performance and to reduce feedback information. To further reduce the feedback information considering the channel property of the IEEE 802.22 WRAN, the proposed scheme employs an extension of the feedback period and subcarrier grouping. Simulation results in the IEEE 802.22 WRAN reference channel models indicate that the proposed MIMO-OFDM transmission scheme achieves superior BER performance and spectral efficiency than open-loop MIMO-OFDM system even considering the feedback overhead of the system.
In cognitive networks, cognitive (unlicensed) users need to continuously monitor spectrum to detect the presence of primary (licensed) users. In part I, we have illustrated the benefits of cooperation in cognitive radio by considering a simple two-user network and showing improvement in agility. In part II, we investigate multiple cognitive user networks. We first consider multiuser single carrier networks and develop sufficient conditions for agility gain when the cognitive population is arbitrarily large. We then propose a practical algorithm which allows cooperation between cognitive users in random networks. Finally, we provide an example to illustrate the concepts developed in this paper.
Cognitive radio is viewed as a novel approach for improving the utilization of a precious natural resource: the radio electromagnetic spectrum. The cognitive radio, built on a software-defined radio, is defined as an intelligent wireless communication system that is aware of its environment and uses the methodology of understanding-by-building to learn from the environment and adapt to statistical variations in the input stimuli, with two primary objectives in mind: · highly reliable communication whenever and wherever needed; · efficient utilization of the radio spectrum. Following the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks. 1) Radio-scene analysis. 2) Channel-state estimation and predictive modeling. 3) Transmit-power control and dynamic spectrum management. This work also discusses the emergent behavior of cognitive radio.
Base station polarization diversity reception in which signals are received by dual polarization (ex. ±45° polarization) is discussed. A theoretical analysis is presented on correlation coefficient ρ between diversity branches, and received signal level decrease L caused by polarization difference at the base and mobile station. The generalized expressions of ρ and L are then derived. Measurements were also carried out at 900 MHz in an urban area. Consequently, it was found that the ρ and L values are expressed by three factors, ρ is lower than 0.6 and L is smaller than 2.5 dB. It is concluded that this polarization diversity reception can be used as an effective diversity reception.
Algorithms are described which make use of polarimetric radar
information in the detection and discrimination of targets in a ground
clutter background. The optimal polarimetric detector (OPD) is derived.
This algorithm processes the complete polarization scattering matrix
(PSM) and provides the best possible detection performance from
polarimetric radar data. Also derived is the best linear polarimetric
detector, the polarimetric matched filter (PMF), and the structure of
this detector is related to simple polarimetric target types. New
polarimetric target and clutter models are described and used to predict
the performance of the OPD and the PME. The performance of these
algorithms is compared with that of simpler detectors that use only
amplitude information to detect targets. The ability to discriminate
between target types by exploring differences in polarimetric properties
is discussed