Research On Communication Reliability Optimization Methods For Wireless Cooperartive Relaying

Currently,5G wireless communication networks are being deployed all over the world.The machine learning powered intelligent devices make significant progress in technological innovation.The roadmaps to 6G technology are presented by industry and academia.Based on these facts,the Internet of Things(Io T),industrial Io T,wireless sensor network(WSN)and Intelligent Transportation System(ITS)develop rapidly.All the above application scenarios need the support of communication techniques with the features of self-organization,high-dynamic,high-security and high-reliability.Cooperative relaying enables neighbor nodes to share their hardware,spectrum and power resources to obtain extra spatial diversity gains.Naturally,this technique is an effective approach to improve the performances of capacity,reliability and coverage of the above self-organized networks.However,the 5G and 6G networks work at high frequencies,and the propagation loss is high.The transmit power of the nodes are limited.Moreover,hardware damages or malicious attacks may cause relay misbehaviors.Thus,the communication reliability of cooperative relay networks is greatly challenged.In this dissertation,the approaches to improve the communications reliability in cooperative relay networks are investigated.The outage probability is used to evaluate the communication reliability.The widely used cooperative relaying protocols,amplify-and-forward(AF)and decode-and-forward(DF),are focused on.The relay misbehavior detection problem for DF networks,and the per-relay power constrained beamforming problem for AF networks are studied,respectively.Furthermore,the corresponding approaches to improve the communication reliability are presented.The main contributions of this dissertation are given as follows:Firstly,a detect-before-decode(Db D)method for relay misbehavior detection in a wireless DF cooperative network is proposed.Since this method makes no use of the decoding results,the detection errors caused by erroneously decoding are eliminated.A unified sufficient statistic for relay misbehavior detection,which is applicable to all link outage conditions,is constructed.Furthermore,the closed-form expression of the optimal threshold which minimizes the sourceto-destination outage probability is derived.Numerical simulations show that the proposed method has low false alarm rate,miss detection rate and computational complexity.The sourceto-destination outage probability is also reduced when the source transmit power is low.Secondly,we study the multi-relay misbehavior detection and identification problem in DF vehicular ad hoc networks(VANETs).We present a novel metric,hypothesis variance ratio(HVR),by which the closed-form expressions of the false-alarm rate,miss-detection rate,weighted detection error probability(WDEP)and the optimal threshold to minimize the WDEP are derived.Furthermore,the monotonicity of the above metrics with respect to the HVR is proved.Based on the above theories and the sparsity of relay misbehaviors,we develop a predetection scheme to reduce computation latencies.The maximum HVR based sufficient statistic is constructed for pre-detection.It is demonstrated that the proposed scheme can reduce the WDEP and computational complexity.Finally,we study the optimal cooperative beamforming problem in the AF multi-user and multi-relay networks,which face the challenges of rapid node number variations and per-node power limits.To achieve extra diversity gain,direct-link(source-to-destination)and distributed relay-link signals are jointly exploited.The optimal cooperative beamforming problem is formulated as the maximum relay transmit power minimization problem,subject to per-relay transmit power and the minimum destination signal-to-noise ratio(SNR)constraints.Since the problem is non-convex,we introduce a phase-regulation(PR)method to transform the non-convex problem into a tractable second-order cone programming(SOCP)problem.It is demonstrated that the proposed method can provide the robustness against node number variations in terms of worst-case convergence rates.Furthermore,the closed-form expressions of two necessary feasibility conditions are derived,by which the infeasible channels can be identified and excluded.Consequently,computational costs are reduced.The equivalence of the proposed Necessary Condition 1(NC1)and the signal-to-interference ratio(SIR)condition is proved theoretically and numerically.The proposed Necessary Condition 2(NC2)has a lower upper-bound than the SIR condition,thus reducing more computational costs.This method is applicable to both direct-link and non-direct-link scenarios.