Cooperative Cognitive Radio Networks Research Articles

Enhanced physical layer security for cognitive radio systems through joint spectrum access and power allocation

Physical layer (PHY) security is an important issue in wireless communication systems. In this study, the authors investigate the interactions between the PHY security performance and the spectrum access technique in a cooperative cognitive radio (CR) network. In the classical spectrum access, if the measured energy on a given subchannel is less than a threshold, the subband is dedicated for CR transmission. Here, they consider a probabilistic spectrum access (PSA), which assigns to each primary subchannel a probability which is determined according to the measured energy on that subchannel. In addition, both spectrum access and CR power allocation are performed simultaneously. They formulate the general outage probability and some important PHY security performance metrics, such as average secrecy rate, secrecy outage probability, and probability of positive secrecy rate in terms of the spectrum access and optimal power allocation functions. The authors' numerical analysis indicates that the PSA method achieves a superior PHY security and outage performance compared to the classical threshold-based spectrum sensing and power allocation method.

Outage Analysis of Relay-Assisted NOMA in Cooperative Cognitive Radio Networks with SWIPT

In this paper, we investigate a relay-assisted cooperative spectrum sharing for the considered non-orthogonal multiple access (NOMA) scheme in cognitive radio networks, where the relay node assists the base station (BS) to transmit the superimposed composite signal to two receivers by utilizing an amplified-and-forward (AF) technique with simultaneous wireless information and power transfer (SWIPT). The exact expressions for outage probabilities of two receivers are derived in closed forms. Moreover, a joint optimization of power allocation and the proportion of information splitting for energy harvesting is proposed in terms of energy efficiency (EE) maximization under required data reliability. Simulation results validate the analytical results since the analytical results match well with simulation results and demonstrate the performance advantages of the proposed scheme over other schemes and direct transmission.

From Cognitive to Intelligent Secondary Cooperative Networks for the Future Internet: Design, Advances, and Challenges

Cognitive Radio (CR) technology was first introduced to solve the problem of radio spectrum under-utilization. A cognitive radio network consists of smart radio devices that have the ability to sense radio environment variables and take actions accordingly. To realize their full potential and to become fully cognitive, the CR nodes need to be equipped with learning and reasoning capabilities. Machine learning has been one of the enabling vehicles for intelligent CR networks. Inspired by the cognition cycle of a CR node, over the past years there has been an ever growing interest in using machine learning techniques to enhance the performance of CR networks. In this article, an overview of the various learning techniques currently used in the literature of CR networks is given. We focus on feature classification and clustering algorithms, and their application in cooperative CR networks. We outline the steps to establishing a learning-based cooperative secondary network, highlighting factors that impact detection performance. Additionally, current state-of-the-art learning-based applications in Cognitive Internet of Things (CIoT) are presented. Finally, the key challenges and future directions of intelligent cognitive networks are discussed.

Intelligent spectrum management based on reinforcement learning schemes in cooperative cognitive radio networks

Cognitive Radio (CR) and Cooperative Communication provide key technologies for efficient utilization of available unused spectrum bands (called resources) to achieve a spectral efficient system with high throughput. But to achieve its full potential, it is essential to empower the brain of CR that is Cognitive Engine (CE), using machine learning algorithms to control the operation and adapt parameters according to the dynamic environment. However, in practical scenarios, it is difficult to formulate network model beforehand due to complex network dynamics. To address this issue, the most favorable machine learning scheme, Reinforcement Learning (RL) based schemes are proposed to empower CE without forming an explicit network model. The proposed schemes, Comparison based Cooperative Q-Learning (CCopQL) and Comparison based Cooperative State-Action-Reward-(next) State-(next) Action (CCopSARSA) for resource allocation, allows each CR to learn cooperatively. The cooperation among CRs is in the form of comparing and then exchanging Q-values to obtain an optimal policy. Though these schemes involve information exchange among CRs as compared to independent Q-Leaning and SARSA but it provides improved system performance with high system throughput. Numerical results reveal the significant benefits from exploiting the cooperative feature with RL, both proposed schemes outperform other existing schemes in terms of system throughput and expedite the convergence than individual CR learning with CCopSARSA and CCopQL respectively.

Performance Analysis and Optimization of Bidirectional Overlay Cognitive Radio Networks With Hybrid-SWIPT

This paper considers a cooperative cognitive radio network with two primary users (PUs) and two secondary users (SUs) that enables two-way communications of primary and secondary systems in conjunction with non-linear energy harvesting based simultaneous wireless information and power transfer (SWIPT). With the considered network, SUs are able to realize their communications over the licensed spectrum while extending relay assistance to the PUs. The overall bidirectional end-to-end transmission takes place in four phases, which include both energy harvesting (EH) and information transfer. A non-linear energy harvester with a hybrid SWIPT scheme is adopted in which both power-splitting and time-switching EH techniques are used. The SUs aid in relay cooperation by performing an amplify-and-forward operation, whereas selection combining technique is adopted at the PUs to extract the intended signal from multiple received signals broadcasted by the SUs. Accurate outage probability expressions for the primary and secondary links are derived under the Nakagami-$m$ fading environment. Further, the system behavior is analyzed with respect to achievable system throughput and energy efficiency. Since the performance of the considered system is strongly affected by the spectrum sharing factor and hybrid SWIPT parameters, particle swarm optimization is implemented to optimize the system parameters so as to maximize the system throughput and energy efficiency. Simulation results are provided to corroborate the performance analysis and give useful insights into the system behavior concerning various system/channel parameters.

Secure Resource Allocation for Polarization-Based Non-Linear Energy Harvesting Over 5G Cooperative CRNs

We address secure resource allocation for energy harvesting (EH) based 5G cooperative cognitive radio networks (CRNs). To improve spectrum efficiency and the physical layer security, the size-limited secondary users (SUs) are equipped with orthogonally dual-polarized antennas (ODPAs). In particular, we propose, develop, and analyze an efficient resource allocation scheme under a realistic and non-linear EH model, which can capture the non-linear characteristics of the end-to-end wireless power transfer (WPT) for radio frequency based EH circuits. Our obtained numerical results validate that a substantial performance gain can be obtained by employing the non-linear EH model and equipping SUs with ODPAs.

Enhancing the Spectrum Sensing Performance of Cluster-Based Cooperative Cognitive Radio Networks via Sequential Multiple Reporting Channels

In cluster-based cooperative cognitive radio networks (CCRNs), spectrum sensing and decision making processes to determine whether the primary user (PU) signal is present or absent in the network are very important and vital issues to the utilisation of the idle spectrum. The reporting time delay is a very important matter to make quick and effective global decisions for the fusion center (FC) in a cluster-based CCRNs. In this paper, we propose the concept of multiple reporting channels (MRC) for cluster-based CCRNs to better utilize the reporting time slot by extending the sensing time of secondary users (SUs). A multiple reporting channels concept is proposed based on frequency division multiple access to enhance the spectrum sensing performance and reduce the reporting time delay of all cluster heads (CHs). In this approach, we assign an individual reporting channel to each cluster for reporting purposes. All the SUs in each cluster sequentially pass their sensing results to the corresponding cluster head (CH) via the assigned single reporting channel, which extends the sensing time duration of SUs. Each CH uses the dedicated reporting channel to forward the cluster decision to the FC that makes a final decision by using the “K-out-of-N” rule to identify the presence of the PU signal. This approach significantly enhances the sensing time for all SUs than the non-sequential as well as minimize the reporting time delay of all CHs than sequential single channel reporting approach. These two features of our proposed approach increase the decision accuracy of the FC more than the conventional approach. Simulation results prove that our proposed approach significantly enhances the sensing accuracy and mitigate the reporting time delay of CH compared to the conventional approach.

On Outage Analysis in SWIPT Enabled Bidirectional D2D Communications Using Spectrum Sharing in Cellular Networks

This paper explores a model on cooperative cognitive radio network (CCRN) to enable the in-band bidirectional device-to-device (D2D) communications by sharing the licensed spectrum of cellular system (CS) in a 5G heterogeneous networks (HetNets) framework. In this model, cellular nodes (CNs) are modelled as primary users (PUs) and devices involved in D2D communications are referred as secondary users (SUs). The D2D pair, as unlicensed users, access to the licensed spectrum originally assigned to the CN pair while assuring relaying action to assist two-way communications between the CNs. Further, the D2D pair exploits the information-bearing radio frequency (RF) signals transmitted by the CNs to energize their transceivers, using the principle of simultaneous wireless information and power transfer (SWIPT). Closed form outage expressions of both cellular and D2D communications are derived. Simulation results are used to validate our analytical results. Simulation results show that about ~ 68% and ~ 277% gains are achieved by the proposed system in terms of spectrum efficiency and energy efficiency, respectively as compared to another prominent study on spectrum sharing enabled two-way PU and two-way SU communications.

Throughput enhancement of cognitive M2M networks based on NOMA for 5G communication systems

SummaryOne of the promising technologies for 5G cellular networks is machine‐to‐machine (M2M) communications. We propose a cognitive radio network (CR) that includes a primary cellular system and a secondary cognitive system. The primary cellular system has a primary client (PC) and the secondary cognitive system has M2M clients which are called secondary clients (SCs). In a conventional system of CR network based on orthogonal frequency division multiple access (CR‐OFDMA), when the primary client (PC) is absent, only one SC can obtain the idle spectrum. But, the SC must leave the spectrum when detecting the existence of the PC. So, the spectrum usage of this system is very low. This paper proposes a cooperative CR network based on nonorthogonal multiple access (CCR‐NOMA) for spectrum sensing using energy detection (ED) to allow multiple SCs to share the same frequency at the same time, but are differentiated according to the power domain or code domain, to improve spectrum efficiency of 5G communications and the transmission performance of CR network at the absence and presence of the PC. To evaluate the channel sensing performance of the ED technique in CCR‐NOMA, we derived a closed‐form expression between the achievable throughput and sensing time for the CCR‐NOMA system. The same analysis for the case of CR‐OFDMA is reproduced for the sake of comparison. The analysis showed that the CR‐NOMA system for M2M communication outperforms the CR‐OFDMA system for M2M communication for the same noncooperative and cooperative spectrum sensing and physical layer parameters.

Throughput Maximization by Optimizing Secondary Users in a Cooperative Cognitive Radio Network using Hard Fusion Rules

Cognitive radio network is a promising technology for enabling secondary users to utilize the licensed spectrum of the primary user without causing interference. The data trans- mitted by the secondary users through primary channel without affecting the primary user is known as channel throughput. In cooperative spectrum sensing(CSS) as the number of secondary users increases the channel throughput increases which in turn reduces the spectrum efficiency due to more spectrum wastage. Therefore in this paper, channel throughput is maximized by optimizing secondary users proposed and throughput for variable secondary users for OR and AND fusion rules is investigated. The optimal secondary users is estimated mathematically and simulation results shows the variation of throughput for variable number of secondary users.

Optimization of secondary user capacity in a centralized cooperative cognitive radio network with primary user under priority

AbstractThe primary objective of cognitive radio is to maximize the spectrum utilization and the capacity of secondary users under standard parametric constraints. The radiometer, or energy detection, is one of the convenient methods of spectrum sensing under a cooperative communication framework. However, the selection of a suitable threshold is a major issue in order to optimize the secondary user capacity considering primary user on priority. In this article, we investigate a double threshold energy detection scheme and obtain an analytical model for optimum thresholding in diverse fading conditions under the constraint of the probability of detection. We use a meta‐heuristic optimization algorithm, namely, the particle swarm optimization with an aging leader and challengers, to observe the effect of varying threshold levels in fusion region, signal to noise ratio (SNR) levels of primary user, and calculate the normalized achievable capacity of secondary user for various fading channels. The results show that, with increasing value of threshold within the decision region, the probability of detection decreases while the normalized secondary user capacity is enhanced. Conversely, the probability of detection increases and the normalized secondary user capacity decreases with increasing values of the SNR level. We also observe the effect of receiver diversity with maximal ratio combining for Nakagami‐m fading channel coefficients. The result shows that the probability of detection and normalized capacity decrease with an increase of the number of receiver branches.

Quantized Soft-Decision-Based Compressive Reporting Design for Underlay/Overlay Cooperative Cognitive Radio Networks

Cooperative spectrum sensing (CSS) systems use underlay or overlay strategies to identify underused or unused bands to achieve higher spectrum utilization. In hybrid underlay and overlay systems, spectrum sensing results may be sparse and a general reporting strategy is required to take multiple spectrum usage status into account. In this paper, we propose a general quantized soft decision (QSD) based compressive sensing and reporting strategy for hybrid systems. Our objective is to provide a general framework to report more reliable sensing results to improve the sensing precision and reduce the collision probability with the low complexity. To this end, the soft sensing decisions are quantized to multiple levels, then they are compressed and encoded, while the characteristic information of secondary users (SUs) including the index of the SUs, the interference tolerance level etc, is transmitted over equivalent bit channels. Furthermore, considering that different users may have different quality of service requirements, we propose four methods to allow SUs to deliver local sensing results with different precisions. Simulations are performed over additive white Gaussian noise (AWGN) and Rayleigh fading channels. The results validate the theoretical analysis, and demonstrate that our scheme effectively improves the sensing decision precision and reduces the collision probability.

Session based cooperation in cognitive radio networks: network level approach

<p>The cognitive radio prototype performance is to alleviate the scarcity of spectral resources for wireless communication through intelligent sensing and quick resource allocation techniques. Secondary users (SU’s) actively obtain the spectrum access opportunity by supporting primary users (PU’s) in cognitive radio networks (CRNs). In present generation, spectrum access is endowed through cooperative communication based link-level frame-based cooperative (LLC) principle. In this SUs independently act as conveyors for PUs to achieve spectrum access opportunities. Unfortunately, this LLC approach cannot fully exploit spectrum access opportunities to enhance the throughput of CRNs and fails to motivate PUs to join the spectrum sharing processes. Therefore to overcome this con, network level cooperative (NLC) principle was used, where SUs are integrated mutually to collaborate with PUs session by session, instead of frame based cooperation for spectrum access opportunities. NLC approach has justified the challenges facing in LLC approach. In this paper we make a survey of some models that have been proposed to tackle the problem of LLC. We show the relevant aspects of each model, in order to characterize the parameters that we should take in account to achieve a spectrum access opportunity.</p>

Network Coding Techniques for Primary-Secondary User Cooperation in Cognitive Radio Networks

In this paper, we investigate transmission techniques for a fundamental cooperative cognitive radio network, i.e., a cognitive radio system where a Secondary user may act as relay for messages sent by the Primary user, hence offering performance improvement of Primary user transmissions, while at the same time obtaining more transmission opportunities for its own transmissions. Specifically, we examine the possibility of improving the overall system performance by employing network coding techniques. The objective is to achieve this while affecting Primary user transmissions only positively, namely: 1) avoid network coding operations at the Primary transmitter, hence avoiding increase of its storage requirements and keeping its complexity low, 2) keep the order of packets received by the Primary receiver the same as in the non cooperative case and 3) induce packet service times that are stochastically smaller than the packet service times induced in the non-cooperative case. A network coding algorithm is investigated in terms of achieved throughput region and it is shown to enlarge Secondary user throughput as compared to the case where the Secondary transmitter acts as a simple relay, while leaving the Primary user stability region unaffected. A notable feature of this algorithm is that it operates without knowledge of channel and packet arrival rate statistics. We further present a second network coding algorithm which increases the throughput region of the system under certain conditions on system parameters; however, the latter algorithm requires knowledge of channel and packet arrival rate statistics.

Secrecy performance of non-orthogonal multiple access cognitive untrusted relaying with friendly jamming

In this paper, we consider a cooperative cognitive radio non-orthogonal multiple access network, where a secondary transmitter (ST) assists transmission of a primary source-destination (PS-PD) pair, while simultaneously communicating with a secondary receiver. Specifically, ST acts as an untrusted relay for primary network, that overhears the primary confidential messages. To improve the secrecy of the network, we consider a secure transmission with friendly jamming, in which a friendly jammer transmits a jamming signal to confound the untrusted relay and accordingly to increase the secrecy performance of the primary network. We derive closed-form expressions for the secrecy outage probability, intercept probability, and average secrecy rate. Moreover, an optimal power allocation scheme between the PS and jammer is developed to maximize the instantaneous secrecy rate of the primary network, while ensuring an specific QoS for secondary network. Our findings reveal that proposed scheme can significantly enhance the secrecy of the system, especially when the quality of PS-ST link is inferior to that of the jammer-ST link. In particular, at high signal-to-noise ratio regime, optimal power allocation achieves the average secrecy rate of 0.72 bps/Hz, which is about 2.25 times than that of equal power allocation.

Characterization and Performance Improvement of Cooperative Wireless Networks With Nonlinear Power Amplifier at Relay

In this paper, the performance of the cooperative cognitive radio network with the amplify-and-forward protocol is studied when the relay uses a nonlinear power amplifier (NLPA). Furthermore, taking the pulse shaping filter for the data signal into account, the power of the adjacent channel interference (ACI) to the primary users (PUs) caused by the spectral regrowth of the relay output signal is analytically calculated. Moreover, two compensation techniques are proposed which are implemented at the destination receiver to deal with the in-band nonlinear interference. The first technique is based on the calculation of the distorted signal constellation to enhance the performance of the demodulator. The second technique is feedforward compensation at the receiver. The bit error rate (BER) expressions for both techniques are presented. The ACI resulting from the spectral regrowth due to the relay NLPA is investigated by the simulation and numerical studies, and then, the BER performance degradation at the destination node and the performance improvement resulting from the proposed compensation methods are evaluated. Since the ACI confines the transmit power due to the interference power constraint of the PU, the achievable BER of the secondary user (SU) is studied. The simulation results show that the feedforward compensation technique has better BER performance than the modified constellation based approach.

Energy-efficient resource allocation in wireless powered CCRNs with simultaneous wireless information and power transfer

In this paper, we study the optimal energy efficiency resource allocation for simultaneous wireless information and power transfer (SWIPT) in cooperative cognitive radio networks (CCRNs). The optimal design attempts to deploy each secondary receiver (SR) to harvest the energy and to use the signal received from the secondary transmitter (ST) to decode information. For the information transmission, a traditional multiple access scheme, namely, time division multiple access (TDMA) is addressed. For the TDMA-based information transmission, the users are scheduled in non-overlapping time slots to decode information. To tackle the design with the above scenarios, an optimization problem is formulated to maximize the energy efficiency of the secondary system constrained with the uncertainty of channel state information (CSI). To solve this non-convex problem, nonlinear fractional programming is utilized to transform the objective function into a subtractive form. The nonlinear fractional programming is also used to decompose the problem into two convex subproblems, and the probability constraints of signal to interference plus noise ratio (SINR) are converted into the deterministic ones using integral transformation. A joint optimal time and power allocation (JOTPA) iterative algorithm is proposed to determine the optimum of original non-convex problem. Simulation results have verified the effectiveness of the proposed resource allocation algorithm.

Feedback Bits Allocation for Guaranteed Bit Rate Services in Cooperative Cognitive Radio Networks.

As the number of users using multimedia sharing services increases, the need to ensure the minimum data rate of wireless users increases. Meanwhile, in the cooperative cognitive radio (CR) network, it is important to provide the quality-of-services for secondary users (SUs) while satisfying the inter-network interference constraint from secondary transmitters to primary users (PUs). Under the limited feedback resource constraint, this paper proposes a feedback bits allocation scheme for the guaranteed bit rate services of SUs while satisfying the inter-network interference constraint. This paper investigates how many feedback bits between the ST and PUs are required to guarantee the minimum data rate of SUs and then proposes a feedback bits allocation scheme that maximizes the average sum rate of SUs while reducing the outage probability of SUs.

Energy Harvesting for Cooperative Cognitive Radio Networks

In this paper, we analyze the performance of cooperative cognitive radio networks where the secondary nodes harvest energy from radio frequency signals. Our analysis takes into interference aspect: the secondary source and relays transmit only when they generate low interference to primary receiver ($$P_R$$). Besides, we analyze the signal to interference plus noise ratio at secondary relays and destination taking into consideration primary interference. To reach higher data rates, harvesting duration is optimized in this paper.

A decision confidence based multiuser MIMO cooperative spectrum sensing in CRNs

In this paper, we propose a novel spectrum sensing scheme for multiuser multiple-input–multiple-output cooperative cognitive radio networks and a decision confidence algorithm for the antenna selection in FC to reduce its computational burden. Here first, a log-likelihood-ratio test (LRT) based energy detection of primary user link is performed by each secondary user employing multiple receive antennas and with imperfect channel state information. Next, the local decision is sent to the fusion center (FC) via multiple transmit antennas to combat the hidden node problem. Finally, the global decision is made at FC, equipped with multiple receive antennas using maximal ratio combining algorithm considering correlated fading channel between FC and SUs. Closed form expressions are obtained for probability of detection (Pd) and probability of false alarm. The performance evaluations show that the Pd≥0.95 with Nt=2,Nrf=8,SNR=−5dB at Pfa=0.1 is achieved with the proposed scheme even in the presence of antenna interference between the MIMO channel. Further, the proposed scheme reduces the overall computational complexity and time complexity of MIMO cooperative sensing technique.