Cooperative Cognitive Networks Research Articles

Secrecy and Throughput Performance of Cooperative Cognitive Decode-and-Forward Relaying Vehicular Networks with Direct Links and Poisson Distributed Eavesdroppers

Cooperative communication and cognitive radio can effectively improve spectrum utilization, coverage range, and system throughput of vehicular networks, whereas they also incur several security issues and wiretapping attacks. Thus, security and threat detection are vitally important for such networks. This paper investigates the secrecy and throughput performance of an underlay cooperative cognitive vehicular network, where a pair of secondary vehicles communicate through a direct link and the assistance of a decode-and-forward (DF) secondary relay in the presence of Poisson-distributed colluding eavesdroppers and under an interference constraint set by the primary receiver. Considering mixed Rayleigh and double-Rayleigh fading channels, we design a realistic relaying transmission scheme and derive the closed-form expressions of secrecy and throughput performance, such as the secrecy outage probability (SOP), the connection outage probability (COP), the secrecy and connection outage probability (SCOP), and the overall secrecy throughput, for traditional and proposed schemes, respectively. An asymptotic analysis is further presented in the high signal-to-noise ratio (SNR) regime. Numerical results illustrate the impacts of network parameters on secrecy and throughput and reveal that the advantages of the proposed scheme are closely related to the channel gain of the relay link compared to the direct link.

Mutated Beamforming for Cognitive Radio 5G Relay Network

In fifth-generation (5G) relay networks, the network blockage situation upsurges owing to inadequate penetration capability of the radio waves or interruption due to tall buildings and obstacles. To improve the network coverage and spectrum efficiency, a cooperative cognitive relay network with mutated beamforming is proposed. This work introduces mutation and replacement-strategy-based beamforming to enhance the opportunistic throughput and spectral efficiency. The proposed model employs imperfect channel state information (CSI) with consideration of the CSI error due to interfering signal. The mutated beamforming technique is implemented for the cognitive radio environment postefficient spectrum sensing. The proposed mutated beamforming mitigates CSI error via performing beamforming with minimized sidelobes and placing nulls in the desired direction. The mutated beamforming in 5G relay network achieves a spectral efficiency of 30 b/s/Hz at SNR = 20 dB.

Connectivity Probability Analysis for Green Cooperative Cognitive Vehicular Networks

To meet the increasing demands of green communications for vehicular services, cognitive vehicular networks (CVNs) are expected to improve spectrum efficiency via cognitive radio (CR) technology. The connectivity of CVNs not only related to the communication between cognitive vehicles (CVs), but also detection of idle spectrum. Nevertheless, few existing works simultaneously consider the communication and cognitive probabilities on the road. In this paper, we use probability theory to deduce the connectivity probabilities of CVNs. The analysis scenario consists of two parts: single-hop scenario and multi-hop clustering scenario. Particularly, in multi-hop clustering scenario, we propose Inter-Cluster integration process and Intra-Cluster communication process respectively, and deduce the probability expressions for two cases. The relationships between connectivity and parameters of both channel circumstance and traffic factors are given via theoretical analysis. The simulation results show that connectivity in multi-hop clustering scenario is better than that in single-hop case and the effect of signal-to-noise ratio (SNR) on connectivity is prominent, which indicates that the cognitive probability deeply affects the connectivity probability in CVNs.

Optimal Cooperative Transmission for Overlay Cognitive Satellite Terrestrial Networks

In this letter, we investigate an overlay cognitive satellite terrestrial network, where the secondary terrestrial network cooperates with the primary satellite network for spectrum access in a time splitting manner. To maximize the spectrum efficiency of such a cooperative cognitive network, we propose an optimal cooperative transmission scheme by optimizing the time splitting factors. Specifically, we firstly analyze the feasible range of time splitting factors to guarantee both transmission requirements of the satellite and terrestrial networks. On this basis, we decompose the non-concave optimization problem into several categories and employ the Charnes-Cooper transformation to determine the optimal time splitting factors.

Energy Efficiency Analysis in Modified GoF Spectrum Sensing-Based AF Relay Cooperative Cognitive Sensor Network with Energy Harvesting

In this paper, we propose a joint sensing duration and transmission power allocation scheme to maximize the energy efficiency (EE) of the secondary user (SU) in a cooperative cognitive sensor network (CSN). At the initial time slot of the frame, the secondary transmitter (ST) performs energy harvesting (EH) and spectrum sensing simultaneously using power splitting (PS) protocol. The modified goodness of fit (GoF) spectrum sensing algorithm is employed to detect the licensed spectrum, which is not sensitive to an inaccurate noise power estimate. Based on the imperfect sensing results, the ST will act as an amplify-and-forward (AF) relay and assist in transmission of the primary user (PU) or transmit its own data. The SU’s EE maximization problem is constructed under the constraints of meeting energy causality, sensing reliability, and PU’s quality of service (QoS) requirement. Since the SU’s EE function is a nonconvex problem and difficult to solve, we transform the original problem into a tractable convex one with the aid of Dinkelbach’s method and convex optimization technique by applying a nonlinear fractional programming. The closed-form expression of the ST’s transmission power is also derived through Karush-Kuhn-Tucker (KKT) and gradient method. Simulation results show that our scheme is superior to the existing schemes.

Enhancement of Spectrum Sensing Performance via Cooperative Cognitive Radio ‎Networks at Low SNR

The inefficient use of spectrum is the key subject to overcome the upcoming spectrum crunch issue. This paper presents a study of performance of cooperative cognitive network via hard combining of decision fusion schemes. Simulation results presented different cooperative hard decision fusion schemes for cognitive network. The hard-decision fusion schemes provided different discriminations for detection levels. They also produced small values of Miss-Detection Probability at different values of Probability of False Alarm and adaptive threshold levels. The sensing performance was investigated under the influence of channel condition for proper operating conditions. An increase in the detection performance was achieved for cognitive users (secondary users) of the authorized unused dynamic spectrum holes (primary users) while operating in a very low signal-to-noise ratio with the proper condition of minimum total error rate.

MIMO Based Cooperative Communication and Joint Maximum Likelihood Detection for Cognitive Radio System

In this work, novel cooperative communication strategies like Decode and Forward based relay schemes, joint maximum likelihood signal detection in combinational Multiple Input Multiple Output (MIMO) cooperative relay cognitive networks are used. The joint cooperative signal detection using Maximum-Likelihood (ML) detector at each relays, and associated path links improves the quality of services at the destination node, which can be dynamically altered using different relay combinations and associated iterative computational complexity accumulated during ML detection. Here the relay performs ML decoding and transmit the detected symbols to the destination and also to the multiple antennas equipped for cooperative communication. The same ML detection at the destination combines the MIMO based diversity to narrow down the error probability among different orthogonal transmissions. The combination of iterative signal detection and relay assisted decoding scheme shows superior error rate performance when compared to non-iterative hard decoded signal detection. The simulations results proved the influence of MIMO assisted cooperative communication and the associated performance penalty gaps that come with imperfect channel state information at the destination node.

Intercept Probability Analysis of Cooperative Cognitive Networks Using Fountain Codes and Cooperative Jamming

This paper evaluates intercept probability (IP) of a cooperative cognitive radio network. Using Fountain codes, a secondary source continuously generates encoded packets, and sends them to secondary destination and relay nodes that attempt to receive a sufficient number of the encoded packets for recovering the source data. If the relay can sufficiently collect the packets before the destination, it replaces the source to transmit the encoded packets to the destination. Also in the secondary network, a passive eavesdropper attempts to illegally receive the packets sent by the source and relay nodes, and if it can accumulate enough encoded packets, the source data is intercepted. To enhance secrecy performance, in terms of IP, a cooperative jammer is used to transmit noises on the eavesdropper. We also propose a simple transmit power allocation method for the secondary transmitters such as source, relay and jammer so that outage performance of a primary network is not harmful. We derive an exact closed-form expression of IP over Rayleigh fading channel, and verify it by performing Monte-Carlo simulations.

Analysis of spectral efficiency for OFDM cooperative cognitive networks with non‐linear relay

This paper analyzes the downlink achievable spectral efficiency of an orthogonal frequency-division multiplexing (OFDM) cooperative cognitive network with a non-linear relay. The analysis is carried out subject to the power amplifier's (PA) non-linear effect on the relay node which operates in the amplify-and-forward (AF) mode. Specifically, an analytical expression for the power spectral density (PSD) of relay output in terms of its source power is derived. By using the obtained PSD, the power of relay's PA output is derived for each subcarrier and the 1 dB compression point is determined. Then, the adjacent channel power (ACP) of each subcarrier is analytically derived in terms of secondary user (SU) source input power. Next, the signal to interference and noise ratio (SINR) of each subcarrier at destination (SU receiver) is calculated by considering the non-linear effect of PA at the relay. Having the SINRs of all subcarriers, a constrained optimization problem on the source's input power is formulated in which the achievable spectral efficiency is the objective function and all ACPs being less than the interference temperature limit are its constraints. Finally, we perform some simulations and show that the numerical results are consistent with the analytical findings.

Approximations for the product, ratio, and sum ofα‐μrandom variables with application in the analysis of cognitive radio networks

SummaryNovel methods to approximate the probability density function of the product, ratio, and sum ofα‐μrandom variables are presented in this article. The approximations are simple to compute and produce results that range from fairly accurate to perfectly accurate, depending on the parameters of the involvedα‐μdistributions. In addition, as an application of the results, it is investigated the performance of a cooperative cognitive network in which the secondary source and the relays are energy‐constrained nodes and harvest their energy from the primary network.

Underlay spectrum‐sharing non‐orthogonal multiple access network with imperfect successive interference cancellation

This study investigates the performance of a cooperative non-orthogonal multiple access cognitive network with imperfect successive interference cancellation under Rayleigh fading conditions. Specifically, the authors consider an underlay cognitive network that consists of a primary transmitter–receiver pair and a secondary system where a source node communicates with two destinations nodes directly and indirectly through a relay node selected from a set of decode-and-forward relays. A partial relay selection scheme is used to determine the best relay. The authors present an analytical framework, with closed-form analytical expressions for the outage probabilities at the two destinations as well the primary destination. Moreover, to simplify the analysis and to provide further insights into the impact of key system parameters, asymptotic studies of the outage probabilities were carried out. To this end, the authors focus on two cases: (i) the maximum allowable transmit power of the secondary network grows sufficiently large and (ii) the interference power approaches infinity. Finally, Monte Carlo simulations are provided in an effort to assess the accuracy of the proposed mathematical framework.

In brief

PAGE 1103 Researchers from the Republic of Korea present a self-capacitance sensing technique for touch screen panels with alternating panel charge sharing, which effectively suppresses low-frequency noise and achieves better signal-to-noise ratio. SNR is improved by 7.65 dB compared to conventional panel charge sharing based techniques. PAGE 1148 A deep reinforcement learning-based approach for the delay-constrained buffer-aided relay selection in a cooperative cognitive network is proposed by Chinese researchers. The proposed algorithm can solve the complicated relay selection problem and achieves the optimal throughput when the buffer size and number of relays is large. Schematic of proposed analog front-end circuit. PAGE 1111 Brazilian researchers present an alternative analysis method to derive the voltage-current transmission matrix of transmission line sections. The method efficiently computes the relationship between the voltages and currents at the input and output of a circuit modelled through N identical cascaded two-port networks. The overall framework of the proposed Q-Learning algorithm. PAGE 1116 Researchers from Daejeon, Republic of Korea, present a new method for training convolutional neural networks that are designed to detect targets of interest in hyperspectral images. Using synthetic training data only, a Siamese CNN has been trained to learn robust features for the detection task. Experimental results on real hyperspectral images show the effectiveness of the proposed method. Circuit model composed of N identical cascaded two-ports. PAGE 1130 Indian researchers have designed and presented a photonic configurable logic block with a 1×1 Mach-Zehnder modulator as a universal photonic gate, capable of performing logical operations with the help of a field-programmable gate array as a configuration controller. The device exhibits neglibile transmission loss and a flexible switching control when compared to existing 2×2 MZI-basd photonic gates. A band image from the hyperspectral data cube (l) and ground truth for targets of interest (r). Cross-section details of the designed 1×1 Mach-Zehnder modulator.

Novel deep reinforcement learning‐based delay‐constrained buffer‐aided relay selection in cognitive cooperative networks

In this Letter, a deep reinforcement learning-based approach is proposed for the delay-constrained buffer-aided relay selection in a cooperative cognitive network. The proposed learning algorithm can efficiently solve the complicated relay selection problem, and achieves the optimal throughput when the buffer size and number of relays are large. In particular, the authors use the deep-Q-learning to design an agent to estimate a specific action for each state of the system, which is then utilised to provide an optimum trade-off between throughput and a given delay constraint. Simulation results are provided to demonstrate the advantages of the proposed scheme over conventional selection methods. More specifically, compared to the max-ratio selection criteria, where the relay with the highest signal-to-interference ratio is selected, the proposed scheme achieves a significant throughput gain with higher throughput-delay balance.

Secrecy Outage Probability of a NOMA Scheme and Impact Imperfect Channel State Information in Underlay Cooperative Cognitive Networks.

Security performance and the impact of imperfect channel state information (CSI) in underlay cooperative cognitive networks (UCCN) is investigated in this paper. In the proposed scheme, relay R uses non-orthogonal multiple access (NOMA) technology to transfer messages , from the source node S to User 1 (U1) and User 2 (U2), respectively. An eavesdropper (E) is also proposed to wiretap the messages of U1 and U2. The transmission’s security performance in the proposed system was analyzed and performed over Rayleigh fading channels. Through numerical analysis, the results showed that the proposed system’s secrecy performance became more efficient when the eavesdropper node E was farther away from the source node S and the intermediate cooperative relay R. The secrecy performance of U1 was also compared to the secrecy performance of U2. Finally, the simulation results matched the Monte Carlo simulations well.

Analysis of energy harvesting cognitive relay network with cooperative spectrum sensing

In this study, the authors investigate the performance of an energy harvesting cognitive cooperative multiple relays network with spectrum sensing, where secondary user accesses the licensed spectrum according to the spectrum sensing results. Particularly, if the spectrum hole is detected, the secondary nodes harvest energy from the ambient environment, otherwise, the secondary source and relays transmit with the energy collected from the primary signals. Taking the imperfect spectrum sensing results into account, exact closed-form expressions for the total outage probability and capacity of the secondary network are derived under the context of Rayleigh fading channels, where the proposed modified selective cooperative decode-and-forward relaying transmission schemes are adopted. Compared with the conventional cognitive relay network, the authors must undertake the correlations among the received signal-to-noise ratios or signal-to-interference-plus-noise ratios caused by both the presence of primary user's interference and energy harvesting for the system understudy. It is shown that spectrum sensing phase and data transmission phase are mutual influence and mutual restraint.

Improvement of Underlay Cooperative Cognitive Networks Bandwidth Efficiency under Interference and Power Constraints

The definition of the bandwidth efficiency (BE) of cognitive cooperative network (CCN) is the ratio between a number of the licensed slot(s) or sub-channel(s) used by the unlicensed users to transmit a single data packet from the unlicensed transmitter to unlicensed destination, and from unlicensed relay(s) to unlicensed destination. This paper analyzes and improves the BE in the underlay CCN with a new reactive relay selection under interference and power constraints. In other words, this paper studies how unlicensed cooperative users use the licensed network slot(s) or sub-channel(s) efficiently. To this end, a reactive relay selection method named as Relay Automatic Repeat Request (RARQ) is proposed and utilized with a CCN under interference and power constraints. It is shown that the BE of CCN is higher than that of cooperative transmission (CT) due to the interference and power constraint. Furthermore, the BE of CCN is affected by the distance of the interference links which are between the unlicensed transmitter to the licensed destination and unlicensed relay to the licensed destination. In addition, the BE for multiple relays selection over a CCN under interference and power constraints is also analyzed and studied, and it is shown that the BE of CCN decreases as the number of relays increases.

Framework for Discrete Rate Transmission in Buffer-Aided Underlay CRN With Direct Path

This paper investigates the performance of a buffered decode-and-forward (DF) relay-based three-node underlay cooperative cognitive relay network (CRN) with a direct path to the destination, assuming that the source and the relay use limited predefined discrete rates. Optimum rules are evolved for joint link and rate selection that maximize throughput while ensuring buffer stability. When two or all three links can provide the same maximum rate, then one of them is picked randomly based on a “coin-toss” with probability chosen to ensure buffer stability. System throughput expressions are derived, with the buffered and direct components evaluated separately. It is seen that the system throughput of the balanced buffer is independent of the coin-toss probabilities that assist in buffer balancing, and also, the buffer balancing condition can be evaluated from the expression of the system throughout itself. The analysis clearly confirms the importance of the buffer. Furthermore, it is observed that considering the direct path is important in underlay cognitive radio. Additionally, a scheme in which the direct link signal is combined with the relayed signal is also considered, and it is demonstrated that it offers improvement in performance when relay-to-destination link is weak.

Simultaneous wireless information and power transfer in energy‐augmented amplify and forward cooperative cognitive networks

Simultaneous wireless information and power transfer (SWIPT) and energy harvesting (EH) have been considered as the promising technique to enhance the lifetime of energy constrained relay nodes of the amplify and forward (AF)-based cognitive wireless network. The amalgamation of cognitive and cooperative communication has emerged as a powerful method for improving spectrum utilisation. In this study, an energy-augmented AF (EAF) protocol has been proposed to enhance the throughput and minimise the outage probability of cooperative cognitive relay networks. A power splitting based SWIPT relay secondary user in the EH module harvests the energy and uses the harvested energy to forward the amplified version of the signal to the destination. System model and analytical equations have been developed for the proposed EAF protocol. Simulation results demonstrate that the proposed EAF protocol outperforms the conventional schemes in terms of capacity, outage probability and throughput.

Secrecy Performance of Underlay Cooperative Cognitive Network Using Non-Orthogonal Multiple Access with Opportunistic Relay Selection

In this paper, an underlay cooperative cognitive network using a non-orthogonal multiple access (UCCN-NOMA) system is investigated, in which the intermediate multiple relays help to decode and forward two signals x 1 and x 2 from a source node to two users D1 and D2, respectively, under wiretapping of an eavesdropper (E). We study the best relay selection strategies by three types of relay selection criteria: the first and second best relay selection is based on the maximum channel gain of the links R i -D 1 , R i -D2, respectively; the third one is to ensure a minimum value of the channel gains from the R i -E link. We analyze and evaluate the secrecy performances of the transmissions x 1 and x 2 from the source node to the destination nodes D1, D2, respectively, in the proposed UCCN-NOMA system in terms of the secrecy outage probabilities (SOPs) over Rayleigh fading channels. Simulation and analysis results are presented as follows. The results of the (sum) secrecy outage probability show that proposed scheme can realize the maximal diversity gain. The security of the system is very good when eavesdropper node E is far from the source and cooperative relay. Finally, the theoretical analyses are verified by performing Monte Carlo simulations.

Stable Throughput of Cooperative Cognitive Networks With Energy Harvesting: Finite Relay Buffer and Finite Battery Capacity

This paper studies a generic model for cooperative cognitive radio networks where the secondary user is equipped with a finite relay queue as well as a finite battery queue. Our prime objective is to characterize the stable throughput region. Nevertheless, the complete characterization of the stable throughput region for such system is notoriously difficult, since the computation of the steady state distribution of the two-dimensional Markov chain model for both finite queues is prohibitively complex. We first propose an algorithm to characterize the stable throughput region numerically, and show its sheer computational complexity for large queue lengths. To lend tractability and explore the nature of design parameters optimization at the cognitive node, we next focus on two simpler systems, namely, finite battery queue with infinite relay queue and finite relay queue with infinite battery queue (referred henceforth as dominant system 1 and 2, respectively). For each proposed dominant system, we investigate the maximum service rate of the cognitive node subject to stability conditions. Despite the complexity of the formulated optimization problems, due to their non-convexity, we exploit the problems’ structure to transform them into linear programs. Thus, we are able to solve them efficiently using standard linear programming solvers. Our numerical results demonstrate that, in practical systems, finite battery and relay queues achieve the same level of benefits of a system with infinite queue sizes, when their sizes are sufficiently large. They also reveal that the achievable stable throughput region significantly expands when the arrival rate of the energy harvesting process increases.