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Square-Law Selector and Square-Law Combiner for Cognitive Radio Systems: An Experimental Study
... The SLC is a straightforward diversity technique that exploits merging the energy of the received signals from every Rx antenna of the SU. It represents one of the diversity approaches with the lowest computing complexity [11]. It is expected that exploiting the diversity of the SLC technique during the ED process can improve the signal detection of PU in MIMO-OFDM systems affected by the NU. ...
... The previous research works show that a combination of OFDM and MIMO is a frequently used communication technique in CRNs [11][12][13]. As presented in [12][13][14][15][16], the ED in the MIMO-OFDM communication system employing SLC approaches is a promising candidate for improving SS. ...
... The authors of [11] discussed the difficulties encountered during the hardware implementation of an OFDM signal detection utilizing the ED SLC method and ED square law selection (SLS) approaches. Significant challenges such as modelling the PU signals, RF imperfections, SNR estimation, and the impact of fading channels were also analysed. ...
To ensure effective spectrum usage, cognitive radio networks (CRNs) are being investigated extensively. The important function of CRNs is spectrum sensing (SS). This is the process of sensing the unused frequency spectrum and deciding whether the signal transmission of a primary user (PU) exists. In this work, the results of a performance analysis related to detecting PU signals using the energy detection (ED) SS method realized by employing the square-law combining (SLC) technique are presented. The assessment of the effectiveness of the ED method is performed in relation to prominent communication technology based on Orthogonal Frequency Division Multiplexing (OFDM) and Multiple-Input Multiple-Output (MIMO) transmissions. Due to the impact of changes in the noise power of the PU signal, referred to as noise uncertainty (NU), the MIMO-OFDM transmission in a real communication environment cannot guarantee accurate sensing performed by employing ED based on the SLC method at the secondary user (SU). More precise SS can be achieved if dynamic detection threshold (DDT) changes are employed according to the channel conditions impacted by NU. Thus, this work investigated the effect of NU variations and DDT adjustments on the detection probability for various levels of false alarm probability. This interdependence is presented as receiver operating characteristic (ROC) curves. A mathematical model including different operational parameters was developed to define the fundamental parameters of the ED method based on the SLC approach. Using the developed mathematical model, an algorithm was created which simulates SLC ED processes using DDT in single-input single-output (SISO)- and MIMO-OFDM communication systems affected by NU. Based on the simulation results, comprehensive analyses of the impact of versatile DDT adaptations and NU variations on the shape of the ROC curves for the ED process performed with different numbers of transmitting and receiving antenna, modulation techniques, detection sample numbers, PU transmitting powers, and SNR values are presented.
... Table 1 presents the literature survey of related work. In the literature, the performance analysis of CR in MIMO-OFDM systems was performed in [18][19][20][21][22][23]. The authors in [22,23] show that the implementation of the MIMO-OFDM transmission contributes to the enhancement of SS efficiency performed using the ED method. ...
... Major Contribution [18] Improved SS at the SU side in a realistic environment by employing SLC and square-law selection (SLS) techniques. [19] Software radio implementation of MIMO-OFDM. ...
... The challenges related to the hardware implementation of ED employing Square-Law Selection (SLS) and SLC methods are presented in [18]. The authors showed that the proposed solutions can facilitate hardware reliability and antenna diversity in a realistic implementation scenario. ...
Due to the capability of the effective usage of the radio frequency spectrum, a concept known as cognitive radio has undergone a broad exploitation in real implementations. Spectrum sensing as a core function of the cognitive radio enables secondary users to monitor the frequency band of primary users and its exploitation in periods of availability. In this work, the efficiency of spectrum sensing performed with the energy detection method realized through the square-law combining of the received signals at secondary users has been analyzed. Performance evaluation of the energy detection method was done for the wireless system in which signal transmission is based on Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing. Although such transmission brings different advantages to wireless communication systems, the impact of noise variations known as noise uncertainty and the inability of selecting an optimal signal level threshold for deciding upon the presence of the primary user signal can compromise the sensing precision of the energy detection method. Since the energy detection may be enhanced by dynamic detection threshold adjustments, this manuscript analyses the influence of detection threshold adjustments and noise uncertainty on the performance of the energy detection spectrum sensing method in single-cell cognitive radio systems. For the evaluation of an energy detection method based on the square-law combining technique, the mathematical expressions of the main performance parameters used for the assessment of spectrum sensing efficiency have been derived. The developed expressions were further assessed by executing the algorithm that enabled the simulation of the energy detection method based on the square-law combining technique in Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing cognitive radio systems. The obtained simulation results provide insights into how different levels of detection threshold adjustments and noise uncertainty affect the probability of detection of primary user signals. It is shown that higher signal-to-noise-ratios, the transmitting powers of primary user, the number of primary user transmitting and the secondary user receiving antennas, the number of sampling points and the false alarm probabilities improve detection probability. The presented analyses establish the basis for understanding the energy detection operation through the possibility of exploiting the different combinations of operating parameters which can contribute to the improvement of spectrum sensing efficiency of the energy detection method.
... Considering the low complexity and versatility of the ED techniques, besides the SLC technique, the performance of SLS antenna diversity techniques at the SU was analyzed in [38]. That paper addressed the challenges involved in the hardware deployment of ED systems exploiting SL diversity techniques. ...
... That paper addressed the challenges involved in the hardware deployment of ED systems exploiting SL diversity techniques. ED in terms of hardware deployment was analyzed in [38] with a focus on challenges such as modeling the SNR estimation, radio-frequency imperfections, PU signal modeling, and realizing the effects of fading channels. Solutions based on simplifications have been proposed to ensure the hardware deployability of SL diversity techniques in realistic scenarios. ...
... In [49], we propose an algorithm for simulating the ED process based on SLC in MIMO-OFDM systems. According to the developed algorithm, analyses of impact of the The previous research showed that the implementation of MIMO transmissions has an impact on the ED process [9,27,[36][37][38][39][40][41][42][43]. Although a number of issues has been considered in related works, a comprehensive analysis dedicated to the ED performance based on SLC technique in MIMO-OFDM systems is still missing. ...
Cognitive radio (CR) technology has the potential to detect and share the unutilized spectrum by enabling dynamic spectrum access. To detect the primary users’ (PUs) activity, energy detection (ED) is widely exploited due to its applicability when it comes to sensing a large range of PU signals, low computation complexity, and implementation costs. As orthogonal frequency-division multiplexing (OFDM) transmission has been proven to have a high resistance to interference, the ED of OFDM signals has become an important local spectrum-sensing (SS) concept in cognitive radio networks (CRNs). In combination with multiple-input multiple-output (MIMO) transmissions, MIMO-OFDM-based transmissions have started to become a widely accepted air interface, which ensures a significant improvement in spectral efficiency. Taking into account the future massive implementation of MIMO-OFDM systems in the fifth and sixth generation of mobile networks, this work introduces a mathematical formulation of expressions that enable the analysis of ED performance based on the square-law combining (SLC) method in MIMO-OFDM systems. The analysis of the ED performance was done through simulations performed using the developed algorithms that enable the performance analysis of the ED process based on the SLC in the MIMO-OFDM systems having a different number of transmit (Tx) and receive (Rx) communication branches. The impact of the distinct factors including the PU Tx power, the false alarm probability, the number of Tx and Rx MIMO branches, the number of samples in the ED process, and the different modulation techniques on the ED performance in environments with different levels of signal-to-noise ratios are presented. A comprehensive analysis of the obtained results indicated how the appropriate selection of the analyzed factors can be used to enhance the ED performance of MIMO-OFDM-based CRNs.
... The hardware implementation of SL techniques for the ED process has been shown in [10]. Different research attempts dedicated to improving radio frequency (RF) imperfections, the effects of the fading channel and modeling the SNR and PU signal estimation for SL techniques in the ED process have been analyzed. ...
... Although previous research presented in [10,[20][21][22][23][24][25][26][27][28][29][30][31] considers the ED process in MIMO transmission systems, an algorithm that enables the simulation analysis of the ED performance in MIMO-OFDM systems based on the SLC method is still missing. According to our knowledge, this is the first paper that deals with an algorithm which enables such analyses through ROC curves developed for the different operating parameters of the analyzed MIMO-OFDM systems. ...
Cognitive radio technology enables spectrum sensing (SS), which allows the secondary user (SU) to access vacant frequency bands in the periods when the primary user (PU) is not active. Due to its minute implementation complexity, the SS approach based on energy detection (ED) of the PU signal has been analyzed in this paper. Analyses were performed for detecting PU signals by the SU in communication systems exploiting multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) transmission technology. To perform the analyses, a new algorithm for simulating the ED process based on a square-law combining (SLC) technique was developed. The main contribution of the proposed algorithm is enabling comprehensive simulation analyses of ED performance based on the SLC method for versatile combinations of operating parameter characteristics for different working environments of MIMO-OFDM systems. The influence of a false alarm on the detection probability of PU signals impacted by operating parameters such as the signal-to-noise ratios, the number of samples, the PU transmit powers, the modulation types and the number of the PU transmit and SU receive branches of the MIMO-OFDM systems have been analyzed in the paper. Simulation analyses are performed by running the proposed algorithm, which enables precise selection of and variation in the operating parameters, the level of noise uncertainty and the detection threshold in different simulation scenarios. The presented analysis of the obtained simulation results indicates how the considered operating parameters impact the ED efficiency of symmetric and asymmetric MIMO-OFDM systems.
... The results also demonstrated that increased OFDM symbol length factors into better detection probability. The effects of fading channels, modeling of SNR estimation, radio-frequency imperfections, and PU signal modeling were discussed in [35], while also analyzing the hardware deployment of ED systems employing SLC diversity techniques. The performance of the ED method has been analysed using receiver operating characteristic (ROC) curves for various fading channels [36][37][38][39]. ...
The UFMC waveform is a type of physical layer, used by Cognitive Radio systems, to achieve reliable communication by using adaptive spectrum access. It is designed to provide interference-free communication without erasing the signals of the existing licensed users. The UFMC waveform is advantageous in Cognitive Radio networks because it can be very easily configured for different operating scenarios, providing both reliable and efficient communication. MIMO-UFMC-based transmissions, when used in combination with multiple-input multiple-output (MIMO) transmissions, have become widely accepted air interfaces that significantly improve spectral efficiency. This work presents a hybrid technique (HEDSLCT) as mathematical formulation of expressions that enable the analysis of ED performance based on the square-law combining (SLC) method in MIMO-UFMC systems, considering the future massive implementation of these systems in the fourth and fifth generation of mobile networks. The developed algorithms were used to conduct simulations for analyzing the performance of an ED process based on the SLC in MIMO-UFMC systems with varied numbers of transmit (Tx) and receive (Rx) communication branches. The results of these simulations enabled an evaluation of the ED performance. This paper presents an analysis of the effects of various factors, such as PU Tx power, false alarm probability, number of Tx and Rx MIMO branches, number of samples in ED process, and modulation techniques, on ED performance according to different signal-to-noise ratios. The obtained results of a comprehensive analysis showed that an appropriate selection of the evaluated factors could be used to improve the energy detection performance of multiple-input multiple-output ultra-wideband frequency-division multiplexing-based cognitive radio networks.
The objective of this paper is to extend the idea of Cognitive Relay (CR).
CR, as a secondary user, follows an underlay paradigm to endorse secondary
usage of the spectrum to the indoor devices. To seek a spatial opportunity,
i.e., deciding its transmission over the primary user channels, CR models its
deployment scenario and the movements of the primary receivers and indoor
devices. Modeling is beneficial for theoretical analysis, however it is also
important to ensure the performance of CR in a real scenario. We consider
briefly, the challenges involved while deploying a hardware prototype of such a
system.
Cognitive radio as first coined by Mitola in 1999 illustrates a dynamic model that provides human intervention to the underlying radio hardware. Dynamic spectrum access (DSA) is one of the many applications of cognitive radio. The DSA umbrella considers the secondary usage of the spectrum. On these grounds, we meant to design a working prototype for Cognitive Relay (CR), a device that dynamically accesses the spectrum to support wireless services operating indoor.
Next generation networks are moving towards the convergence of mobile, fixed and broadcasting services in one standard platform, which requires the co-existence of satellite and terrestrial networks in the same spectrum. This framework has motivated the concept of cognitive Satellite Communication (SatComs). In this aspect, the problem of exploiting Spectrum Sensing (SS) techniques for a dual polarized fading channel is considered. In this paper, the performance of Energy Detection (ED) technique is evaluated in the context of a co-existence scenario of a satellite and a terrestrial link. Diversity combining techniques such as Equal Gain Combining (EGC) and Selection Combining (SC) are considered to enhance the SS efficiency. Furthermore, analytical expressions for probability of detection (Pd) and probability of false alarm (Pf) are presented for these techniques in the considered fading channel and the sensing performance is studied through analytical and simulation results. Moreover, the effect of Cross Polar Discrimination (XPD) on the sensing performance is presented and it is shown that SS efficiency improves for low XPD.
In a cognitive radio network, the secondary users are allowed to utilize the frequency bands of primary users when these bands are not currently being used. To support this spectrum reuse functionality, the secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance in cognitive radio networks. There are two parameters associated with spectrum sensing: probability of detection and probability of false alarm. The higher the probability of detection, the better the primary users are protected. However, from the secondary users' perspective, the lower the probability of false alarm, the more chances the channel can be reused when it is available, thus the higher the achievable throughput for the secondary network. In this paper, we study the problem of designing the sensing duration to maximize the achievable throughput for the secondary network under the constraint that the primary users are sufficiently protected. We formulate the sensing-throughput tradeoff problem mathematically, and use energy detection sensing scheme to prove that the formulated problem indeed has one optimal sensing time which yields the highest throughput for the secondary network. Cooperative sensing using multiple mini-slots or multiple secondary users are also studied using the methodology proposed in this paper. Computer simulations have shown that for a 6 MHz channel, when the frame duration is 100 ms, and the signal-to-noise ratio of primary user at the secondary receiver is -20 dB, the optimal sensing time achieving the highest throughput while maintaining 90% detection probability is 14.2 ms. This optimal sensing time decreases when distributed spectrum sensing is applied.
Cognitive radio (CR) has been considered as a potential candidate for addressing the spectrum scarcity problem of future wireless networks. Since its conception, several researchers, academic institutions, industries, and regulatory and standardization bodies have put their significant efforts toward the realization of CR technology. However, as this technology adapts its transmission based on the surrounding radio environment, several practical issues may need to be considered. In practice, several imperfections, such as noise uncertainty, channel/interference uncertainty, transceiver hardware imperfections, signal uncertainty, and synchronization issues, may severely deteriorate the performance of a CR system. To this end, the investigation of realistic solutions toward combating various practical imperfections is very important for the successful implementation of cognitive technology. In this direction, first, this survey paper provides an overview of the enabling techniques for CR communications. Subsequently, it discusses the main imperfections that may occur in the most widely used CR paradigms and then reviews the existing approaches toward addressing these imperfections. Finally, it provides some interesting open research issues.
Secondary access to the licensed spectrum is viable only if interference is
avoided at the primary system. In this regard, different paradigms have been
conceptualized in the existing literature. Of these, Interweave Systems (ISs)
that employ spectrum sensing have been widely investigated. Baseline models
investigated in the literature characterize the performance of IS in terms of a
sensing-throughput tradeoff, however, this characterization assumes the
knowledge of the involved channels at the secondary transmitter, which is
unavailable in practice. Motivated by this fact, we establish a novel approach
that incorporates channel estimation in the system model, and consequently
investigate the impact of imperfect channel estimation on the performance of
the IS. More particularly, the variation induced in the detection probability
affects the detector's performance at the secondary transmitter, which may
result in severe interference at the primary users. In this view, we propose to
employ average and outage constraints on the detection probability, in order to
capture the performance of the IS. Our analysis reveals that with an
appropriate choice of the estimation time determined by the proposed model, the
degradation in performance of the IS can be effectively controlled, and
subsequently the achievable secondary throughput can be significantly enhanced.
This paper presents another look at the problem of energy detection of unknown signals over different fading channels. We start with the no diversity case and present some alternative closed-form expressions for the probability of detection (Pd) to those recently reported in [V.I. Kostylev, May 2002]. We then investigate the system performance when different diversity schemes are employed. It is shown that there is not much improvement in the probability of detection when either the probability of false alarm (Pf) exceeds 0/1 or the average signal-to-noise ratio (SNR) exceeds 20 dB. In addition, receiver operating characteristic (ROC) curves comparing the performance of equal-gain combining (EGC), selection combining (SC), and switch and stay combining (SSC) are presented. As an example, EGC introduces a gain of two orders of magnitude from the probability of miss perspective compared to the no diversity case while both SC and SSC introduce a gain of about one order of magnitude.
This paper considers the detection of the presence/absence of signals in uncertain low SNR environments. Small modeling uncertainties are unavoidable in any practical system and so robustness to them is a fundamental performance metric. The impact of these modeling uncertainties can be quantified by the position of the "SNR wall" below which a detector will fail to be robust, no matter how long it can observe the channel. We propose simple mathematical models for the uncertainty in the noise and fading processes. These are used to show what aspects of the model lead to SNR walls for differing levels of knowledge of the signal to be detected. These results have implications for wireless spectrum regulators. The context is opportunistically sharing spectrum with primary users that must be detected in order to avoid causing harmful interference on a channel. Ideally, a secondary system would be able to detect primaries robustly without having to know much about their signaling strategies. We argue that the tension between primary and secondary users is captured by the technical question of computing the optimal tradeoff between the primary user's capacity and the secondary user's sensing robustness as quantified by the SNR wall. This is an open problem, but we compute this tradeoff for some simple detectors.
Cognitive radio: making software radios more personal
- J Mitola
- G Q Maguire