Security-Reliability Analysis and Optimization for Cognitive Two-Way Relay Network with Energy Harvesting

This paper investigates the security and reliability of information transmission within an underlay wiretap energy harvesting cognitive two-way relay network.In the network,energy-constrained secondary network(SN)nodes harvest energy from radio frequency signals of a multi-antenna power beacon.Two SN sources exchange their messages via a SN decode-and-forward relay in the presence of a multiantenna eavesdropper by using a four-phase time division broadcast protocol,and the hardware impairments of SN nodes and eavesdropper are modeled.To alleviate eavesdropping attacks,the artificial noise is applied by SN nodes.The physical layer security performance of SN is analyzed and evaluated by the exact closed-form expressions of outage probability(OP),intercept probability(IP),and OP+IP over quasistatic Rayleigh fading channel.Additionally,due to the complexity of OP+IP expression,a self-adaptive chaotic quantum particle swarm optimization-based resource allocation algorithm is proposed to jointly optimize energy harvesting ratio and power allocation factor,which can achieve security-reliability tradeoff for SN.Extensive simulations demonstrate the correctness of theoretical analysis and the effectiveness of the proposed optimization algorithm.

Interference Alignment in Two-Way Relay Networks via Rank Constraints Rank Minimization

Interference alignment(IA) is one of the promising measures for the multi-user network to manage interference. The rank constraints rank minimization means that interference spans the lowest dimensional subspace and the useful signal spans all available spatial dimensions. In order to improve the performance of two-way relay network, we can use rank constrained rank minimization(RCRM) to solve the IA problem. This paper proposes left reweighted nuclear norm minimization-γalgorithm and selective coupling reweighted nuclear norm minimization algorithm to implement interference alignment in two-way relay networks. The left reweighted nuclear norm minimization-γ algorithm is based on reweighted nuclear norm minimization algorithm and has a novel γ choosing rule. The selective coupling reweighted nuclear norm minimization algorithm weighting methods choose according to singular value of interference matrixes. Simulation results show that the proposed algorithms considerably improve the sum rate performance and achieve the higher average achievable multiplexing gain in two-way relay interference networks.

A Novel Forwarding Method for Full-Duplex Two-Way Relay Networks

An estimate-and-forward(EF) scheme for single-input single-output(SISO) and multiple-input multiple-output(MIMO) full-duplex two-way relay networks is proposed and analyzed. The relay estimates the received signal from two terminal nodes by a minimum mean squared error(MMSE) estimation and forwards a scaled version of the MMSE estimate to the destination. The proposed EF outperforms conventional amplify-and-forward(AF) and decode-and-forward(DF) across all signal-to-noise ratio(SNR) region. Because its computational complexity is high for relays with a large number of antennas(large MIMO) and/or high order constellations, an approximate EF scheme, called list EF, are thus proposed to reduce the computational complexity. The proposed list EF computes a candidate list for the MMSE estimate by using a sphere decoder, and it approaches the performance of the exact EF relay at a negligible performance loss. The proposed forwarding approach also could be used to other relay networks, such as half-duplex, one-way or massive MIMO relay networks.

Joint power control and relay selection scheme for cognitive two-way relay networks

A joint power control and relay selection scheme is considered for a cooperative and cognitive radio system where a secondary network shares spectrum with the primary network. In the secondary network, two secondary users （SUs） communicate with each other via an assist relay. The main point is to provide the best system performance to SUs while maintaining the interference power at primary user （PU） under a certain level. Using convex optimization, a closed-form solution is obtained when optimizing the power allocation among the two nodes and relay. Based on this result, a joint power control and relay selection scheme with fewer variable dimensions is proposed to maximize the achievable rate of the secondary system. Simulation results demonstrate that the sum rate of the cognitive two-way relay network increases compared with a random relay selection and fixed power allocation.

The Average Achievable Rate of Multi-Antenna Two-Way Relay Networks with Interference Alignment

The large system analysis(LSA)has recently been shown to be a very useful tool for computing the average achievable rate.In this paper,we use LSA to derive the users’average achievable rate of multi-antenna two-way relay networks with interference alignment(IA),and we then derive the rate expressions under both equal power allocation and optimal power allocation.It is shown that the obtained closed-form rate expressions are functions of the average signal-to-noise ratio(SNR)for each data stream.Extensive simulation studies show that the average achievable rate expressions derived through LSA provide accurate estimates of the average achievable rate for two-way relay networks with interference alignment.

Joint Beamforming and Time Switching Designs for Energy-Constrained Cognitive Two-Way Relay Networks

In this paper, we investigate a joint beamforming and time switching(TS) design for an energy-constrained cognitive two-way relay(TWR) network. In the network, the energy-constrained secondary user(SU) relay employs TS protocol to harvest energy from the signals sent by the circuit-powered primary user(PU) transmitter, and then exploits the harvested energy to perform information forwarding. Our aim is to maximize the sum rate of SUs under the constraints of the data rate of PU, the energy harvesting and the transmit power of the SU relay. To determine the beamforming matrix and TS ratio, we decouple the original non-convex problem into two subproblems which can be solved by semidefinite relaxation and successive convex optimization methods. Furthermore, we derive closed form expressions of the optimal solutions for each subproblem, which facilitates the design of a suboptimal iterative algorithm to handle the original sum rate maximization problem. Simulation results are presented to illustrate the effectiveness and superior performance of the proposed joint design against other conventional schemes in the literature.

Performance evaluation of a two-way relay network with energy harvesting^and hardware noises

In this paper,we propose a Two-Way Cognitive Relay Network(TWCRN)where the secondary users operate on an underlay mode to access the licensed bands.In the proposed protocols,two secondary sources transmit their data to a relay in the first time slot,and then the relay would forward the received information to both sources in the remaining time.Moreover,the relay is self-powered by harvesting energy from ambient Radio Frequency(RF)signals,using the Time Switching(TS)and the Power Switching(PS)method.This paper concentrates on eval-uating the performance of the secondary networks under the impact of hardware impairments and co-channel interference from the primary networks.In particular,based on the secondary transmitters'constraint power,we derive the closed-form expressions of the outage probability and the throughput over Rayleigh fading channels in two cases:TS and PS.We also investigate the energy efficiency issue and the locally optimal position of the relay to maximize the system throughput,which provides much information to install the relay location.Finally,our derivations are verified by Monte Carlo simulation.

Secure Communications for Two-Way Relay Networks Via Relay Chatting

In this paper, we investigate a two-way relay network consisting of two sources, multiple cooperative relays and an eavesdropper. To enhance secure communications, a new relay chatting based on transmission scheme is proposed. Specifically, the proposed scheme selects a best relay that maximize the sum mutual information among the sources to forward the sources’ signals using an amplify-and-forward protocol, and the remaining relays transmit interference signals to confuse the eavesdropper via distributed beam forming. It can be found that the proposed scheme with relay chatting does not require the knowledge of the eavesdropper’s channel, and outperforms the joint relay and jammer selection scheme, which introduces the interference into the sources. Numerical results show that the secrecy outage probability of the proposed scheme converges to zero as the transmit power increases.

Joint Subcarrier and Power Allocation for DF-Based Multiuser Two-Way Relay Networks

Two-way decode-and-forward(DF) relay technique is an efficient method to improve system performance in 5G networks.However,traditional orthogonal frequency division multiplexing(OFDM) based two-way relay systems only consider a per-subcarrier relay strategy,which treats each subcarrier as a separate channel,which results in significant sum rate loss,especially in fading environments.In this paper,a joint coding scheme over multiple subcarriers is involved for multipair users in two-way relay systems to obtain multiuser diversity.A generalized subcarrier pairing strategy is proposed to permit each user-pair to occupy different subcarriers during the two transmission phases,i.e.,the multiple access and broadcast phases.Moreover,a low complexity joint resource allocation scheme is proposed to improve the spectrum efficiency with an additional multi-user diversity gain.Some numerical simulations are finally provided to verify the efficacy of our proposal.

Beamforming Design for IRS-and-UAV-Aided Two-Way Amplify-and-Forward Relay Networks in Maritime IoT

In this paper,an intelligent reflecting surface(IRS)-and-unmanned aerial vehicle(UAV)-assisted two-way amplify-and-forward(AF)relay network in maritime Internet of Things(IoT)is proposed,where ship1(S1)and ship2(S2)can be viewed as data collecting centers.To enhance the message exchange rate between S1 and S2,a problem of maximizing minimum rate is cast,where the variables,namely AF relay beamforming matrix and IRS phase shifts of two time slots,need to be optimized.To achieve a maximum rate,a low-complexity alternately iterative(AI)scheme based on zero forcing and successive convex approximation(LC-ZF-SCA)algorithm is presented.To obtain a significant rate enhancement,a high-performance AI method based on one step,semidefinite programming and penalty SCA(ONSSDP-PSCA)is proposed.Simulation results show that by the proposed LC-ZF-SCA and ONS-SDP-PSCA methods,the rate of the IRS-and-UAV-assisted AF relay network surpass those of with random phase and only AF relay networks.Moreover,ONS-SDP-PSCA perform better than LC-ZF-SCA in aspect of rate.

Joint relay selection and power allocation algorithm in two-way relay networks with proportional fair constraint

In this paper, we consider the joint relay selection and power allocation problem for two-way relay systems with multiple relay nodes. Traditionally, relay selection schemes are primarily focused on selecting one relay node to maximize the transmission sum rate or minimize the outage probability. If so, it is possible to cause certain relay nodes overloaded. In addition, the joint relay selection and power allocation problem is a mixed integer program problem and prohibitive in terms of complexity. Therefore, we propose a novel low complexity joint relay selection and power allocation algorithm with proportional fair scheduling to get the load-balancing among potential relays. Simulation results turn out that, compared with round-robin schemes and max sum rate schemes, the proposed algorithm can achieve the tradeoff between system transmission sum rate and load-balancing.

Automatic Classification of Superimposed Modulations for 5G MIMO Two-Way Cognitive Relay Networks

To promote reliable and secure communications in the cognitive radio network,the automatic modulation classification algorithms have been mainly proposed to estimate a single modulation.In this paper,we address the classification of superimposed modulations dedicated to 5G multipleinput multiple-output(MIMO)two-way cognitive relay network in realistic channels modeled with Nakagami-m distribution.Our purpose consists of classifying pairs of users modulations from superimposed signals.To achieve this goal,we apply the higher-order statistics in conjunction with the Multi-BoostAB classifier.We use several efficiency metrics including the true positive(TP)rate,false positive(FP)rate,precision,recall,F-Measure and receiver operating characteristic(ROC)area in order to evaluate the performance of the proposed algorithm in terms of correct superimposed modulations classification.Computer simulations prove that our proposal allows obtaining a good probability of classification for ten superimposed modulations at a low signal-to-noise ratio,including the worst case(i.e.,m=0.5),where the fading distribution follows a one-sided Gaussian distribution.We also carry out a comparative study between our proposal usingMultiBoostAB classifier with the decision tree(J48)classifier.Simulation results show that the performance of MultiBoostAB on the superimposed modulations classifications outperforms the one of J48 classifier.In addition,we study the impact of the symbols number,path loss exponent and relay position on the performance of the proposed automatic classification superimposed modulations in terms of probability of correct classification.

Performance of Physical-Layer Network Coding in Asymmetric Two-Way Relay Channels

In this paper, we study the performance of physical-layer network coding in asymmetric two-way relay channels using four different cases having different poor channels:phase asymmetry, downlink asymmetry, uplink asymmetry and node asymmetry. The decision and mapping rule for symmetric and asymmetric cases are studied. The performance in terms of bit error rate for each case will be studied and analysed by computer simulation. Analytical and simulation results show that uplink asymmetry is the worst case;intra-phase asymmetry and unreliable uplink channels will more severely affect the performance degradation, which is caused by channel asymmetry.

Residual energy based multi-relay selection and power allocation scheme in two-way relay network

In this paper, we have proposed a multi-relay selection and power allocation scheme for two-way relay network which aims to maximize the sum-rate of two-way relay system. First, to prolong network lifetime, a multi-relay selection strategy is proposed in which both channel state information （CSI） and remaining energy （RE） are considered. Next, a multi-relay power allocation algorithm based on convex optimization （MRPA-CO） is presented. To reduce the computational complexity, it can be divided into two steps： terminal nodes power allocation （TNPA） and relay nodes power allocation （RNPA）. Simulation results indicate that the proposed relay selection strategy can significantly prolong network lifetime compared to other relay selection strategies which consider CSI only, and the MRPA-CO algorithm has great advantage over equal power allocation （EPA） on sum-rate in two-way relay network.

Improving throughput in SWIPT-based wireless multirelay networks with relay selection and rateless codes

This paper studies a dual-hop Simultaneous Wireless Information and Power Transfer(SWIPT)-based multi-relay network with a direct link.To achieve high throughput in the network,a novel protocol is first developed,in which the network can switch between a direct transmission mode and a Single-Relay-Selection-based Cooperative Transmission(SRS-CT)mode that employs dynamic decode-and-forward relaying accomplished with Rateless Codes(RCs).Then,under this protocol,an optimization problem is formulated to jointly optimize the network operation mode and the resource allocation in the SRS-CT mode.The formulated problem is difficult to solve because not only does the noncausal Channel State Information(CSI)cause the problem to be stochastic,but also the energy state evolution at each relay is complicated by network operation mode decision and resource allocation.Assuming that noncausal CSI is available,the stochastic optimization issue is first to be addressed by solving an involved deterministic optimization problem via dynamic programming,where the complicated energy state evolution issue is addressed by a layered optimization method.Then,based on a finite-state Markov channel model and assuming that CSI statistical properties are known,the stochastic optimization problem is solved by extending the result derived for the noncausal CSI case to the causal CSI case.Finally,a myopic strategy is proposed to achieve a tradeoff between complexity and performance without the knowledge of CSI statistical properties.The simulation results verify that our proposed SRS-and-RC-based design can achieve a maximum of approximately 40%throughput gain over a simple SRS-and-RC-based baseline scheme in SWIPT-based multi-relay networks.

Secrecy-Enhancing Design for Two-Way Energy Harvesting Cooperative Networks with Full-Duplex Relay Jamming

To guarantee secure information transmission within two sources,a full-duplex(FD)relay jamming scheme for two-way energy harvesting(EH)cooperative networks is proposed,in which the relay can achieve simultaneous information reception and jamming transmission.The EH relay node scavenges energy from two source signals,and then,uses the harvested energy for information relaying and jamming transmission by the power splitting(PS)protocol.Considering multiple eavesdroppers,the nonconvex optimization for maximizing the smaller bidirectional secrecy rates is formulated by jointly optimizing the power allocation and PS factor.Furthermore,an iterative algorithm based on successive convex approximation and alternate search method is proposed to solve this non-convexity.Simulation results verify the proposed iterative algorithm and show that the proposed jamming scheme can achieve substantial performance gain than other conventional schemes.

Average Secrecy Capacity of the Reconfigurable Intelligent Surface-Assisted Integrated Satellite Unmanned Aerial Vehicle Relay Networks

Integrated satellite unmanned aerial vehicle relay networks(ISUAVRNs)have become a prominent topic in recent years.This paper investigates the average secrecy capacity(ASC)for reconfigurable intelligent surface(RIS)-enabled ISUAVRNs.Especially,an eve is considered to intercept the legitimate information from the considered secrecy system.Besides,we get detailed expressions for the ASC of the regarded secrecy system with the aid of the reconfigurable intelligent.Furthermore,to gain insightful results of the major parameters on the ASC in high signalto-noise ratio regime,the approximate investigations are further gotten,which give an efficient method to value the secrecy analysis.At last,some representative computer results are obtained to prove the theoretical findings.

Joint Linear Processing Design for Distributed Two-Way Amplify-and-Forward MIMO Relaying Networks

Linear transceiver designs are investigated for distributed two-way relaying networks,which aim at minimising the WeightedMean Square Error(WMSE) of data detections.The forwarding matrices at relays andequalization matrices at destinations are jointly optimised.To overcome the challenginglimitations introduced by individual powerconstraints,a Semi-Definite Relaxation(SDR)called element-wise relaxation is proposed,which can transform the original optimizationproblem into a standard convex optimizationproblem.In this research,two-way relaying isunderstood from a pure signal processing perspective which can potentially simplify thetheoretical analysis.Finally,simulation resultsare used for assessing the performance advantage of the proposed algorithm.

Distributed Relay Beamforming in Cognitive Two-Way Networks: SINR Balancing Approach

In this paper, we study the problem of distributed relay beamforming for a bidirectional cognitive relay network which consists of two secondary transceivers and K cognitive relay nodes and a primary network with a transmitter and receiver, using underlay model. For effective use of spectrum, we propose a Multiple Access Broadcasting (MABC) two-way relaying scheme for cognitive networks. The two transceivers transmit their data towards the relays and then relays retransmit the processed form of signal towards the receiver. Our aim is to design the beamforming coefficients to maximize quality of service (QoS) for the secondary network while satisfying tolerable interference constraint for the primary network. We show that this approach yields a closed-form solution. Our simulation results show that the maximum achievable SINR improved while the tolerable interference temperature becomes not strict for primary receiver.

Secrecy Outage Probability for Two-Way Integrated Satellite Unmanned Aerial Vehicle Relay Networks with Hardware Impairments

In this paper,we investigate the secrecy outage performance for the two-way integrated satellite unmanned aerial vehicle relay networks with hardware impairments.Particularly,the closed-form expression for the secrecy outage probability is obtained.Moreover,to get more information on the secrecy outage probability in a high signalto-noise regime,the asymptotic analysis along with the secrecy diversity order and secrecy coding gain for the secrecy outage probability are also further obtained,which presents a fast method to evaluate the impact of system parameters and hardware impairments on the considered network.Finally,Monte Carlo simulation results are provided to show the efficiency of the theoretical analysis.