Performance Of Relay Selection Research Articles

Optimal Relay Probing for UAV Millimeter Wave Communications with Beam Training Overhead

Blockage in millimeter wave (mmWave) channels can severely degrade the efficiency of air-to-ground (A2G) communications between unmanned aerial vehicles (UAVs) and base stations (BSs). Although relay-aided transmission has proved to be effective in mitigating the negative impact of blockage on mmWave communications, how to efficiently select the optimal relaying UAV for A2G communications remains an open problem. To enable optimal relay selection, the UAV under blockage should probe neighboring UAVs for the quality of their A2G links, which incurs non-negligible beam training overheads. Moreover, most existing studies ignore the impacts of UAV orientations as well as the finite sizes of beam codebooks on the performance of relay selection. In view of these challenges, we study the design of relay probing strategies for UAV mmWave A2G communications to maximize the expected achievable throughput between the UAV under blockage and the BS. Different from existing work, we jointly consider beam training overhead, the limited number of neighboring UAVs, the finite sizes of UAV codebooks, and the orientation of neighboring UAVs in our schematic design. Besides, we derive the closed-form expression for the distribution of achievable throughput when a specific neighboring UAV is adopted as the relay, in order to facilitate the development of the optimal relay probing strategy. Extensive simulation results demonstrate the accuracy of our analysis and the superiority of the obtained relay probing strategy.

Impact of Channel Estimation Error on the Performance of Relay Selection in Cognitive Radio Networks

Channel estimation error, which adversely affects the performance of any wireless communication system, is inevitably available in receivers. However, its impact on the bit error rate (BER) performance of relay selection in underlay cognitive networks has not been investigated analytically. This paper fills in this literature gap by firstly proposing an exact single-integral form BER formula for general network topology. Based on this proposal, we further analyze the diversity gain to have insights into asymptotic performance and system design. Secondly, we derive a closed-form approximate BER formula, which has been shown highly accurate, for a typical network topology where relays are closely positioned for reduced simulation time. Various results demonstrate that the channel estimation error significantly degrades the performance of the relay selection in underlay cognitive networks and completely destroys its diversity gain. In addition, increasing the number of involved relays drastically remedies its impact.

Weighted Bidirectional Relay Selection for Outdated Channel State Information

Most researches on relay selection (RS) in bidirectional relay network typically assume perfect channel state information (CSI). However, outdated CSI, which is caused by the the time-variation of channel, cannot be ignored in the practical system, and the performance of the conventional bidirectional RS scheme degrades greatly with outdated CSI. In this paper, to improve the performance of RS with outdated CSI, we propose a weighted bidirectional RS scheme, in which a deterministic weight factor decided by the correlation coefficient of outdated CSI, is introduced in the selection process. The outage probability bound of the weighted bidirectional RS is derived and verified, along with the asymptotic expression in high signal-to-noise ratio (SNR). Based on the analytical expressions, the optimal weight factor and the optimal power allocation scheme in minimizing the outage probability are obtained. Simulation results reveal that when the CSI is outdated, the diversity order reduces from full diversity to one. Furthermore, the weighted bidirectional RS scheme with the optimal weight factor yields a significant performance gain over the conventional bidirectional RS scheme, especially in high SNR.

Weighted Amplify-and-Forward Relay Selection with Outdated Channel State Information

Relay selection (RS) is a promising technique in the cooperative communications, which can achieve full diversity with the best relay when the channel state information (CSI) is perfect. However, the performance of conventional RS degrades greatly, once CSI is outdated. To compensate the performance loss caused by the outdated CSI, we propose the weighted RS scheme, in which a deterministic weight factor is introduced in the selection process. The performance bound of outage probability for the weighted RS is derived and verified, along with the asymptotic expression. Based on the analytical expression, the optimal weight factor in minimizing the outage probability is obtained. Simulation results reveal that when the CSI is outdated, the proposed RS with the optimal weight factor yields the significant performance gain over the conventional RS, especially in high signal-to-noise ratio.

Opportunistic Multiple Relay Selection With Outdated Channel State Information

The quality of channel state information (CSI) plays a significant role in the performance of relay selection (RS) schemes in cooperative communications. Particularly in a highly mobile environment when there exists delay between the selection and data transmission instants, the quality of CSI often degrades, given to what is known as outdated CSI phenomena. In this paper, we first outline several single RS schemes that achieve full diversity when using perfect CSI and prove that the diversity order of these schemes reduces to unity if outdated CSI exists. To deal with the performance deterioration due to the outdated CSI phenomena, we propose a new multiple RS scheme for both amplify-and-forward (AaF) and decode-and-forward (DaF) relay systems, namely, the plus normalized threshold opportunistic RS . In particular, we first opportunistically select best relays from all candidate relays with respect to end-to-end signal-to-noise ratios (SNRs) for AaF and relay-to-destination SNRs for DaF. Then, the ratios of the SNRs on the rest of the candidate relays to that of the th highest SNR are tested against a normalized threshold , and only those relays passing this test are selected in addition to the best relays. The performance of the scheme is theoretically analyzed in terms of outage probability, and its asymptotic diversity order is also examined. In addition, we outline a distributed selection protocol that makes no assumption of the global CSI at each relay. Numerical results confirm the analysis and show the advantage of the proposed scheme against existing counterparts in highly dynamic networks.