Semidistributed Relay Selection and Power Allocation for Outage Minimization in Cooperative Relaying Networks
Semidistributed Relay Selection and Power Allocation for Outage Minimization in Cooperative Relaying Networks
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DOI：
10.1109/tvt.2016.2547179
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发表时间：
2017
影响因子：
6.8
通讯作者：
Lingya Liu;Cunqing Hua;Cailian Chen;X. Guan
中科院分区：
文献类型：
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作者：
Lingya Liu;Cunqing Hua;Cailian Chen;X. Guan
在本文中，我们考虑放大转发（AF）中继网络中的中继选择和功率分配（RSPA）问题。假设只有平均信道增益信息可用，目标是最小化接收器处的中断概率。利用其特殊的结构，我们建议将 RSPA 问题分解为两个易于处理的子问题，并且可以以半分布式方式实现。对于中继选择（RS）子问题，设计了一种基于中继排序的方案，以集中方式根据特定度量从候选节点中增量选择中继子集，该度量由每个单独节点的平均信道增益主导。对于功率分配（PA）子问题，为每个中继提出了一种源驱动迭代算法，通过利用该子问题的凸性在本地决定其最佳发射功率。提供仿真结果来评估所提出方案在不同信道条件下的中断和信噪比（SNR）性能。结果表明，所提出的方案可以根据信噪比和信道条件动态选择中继并调整功率分配。它优于其他两个基准方案，性能接近穷举搜索的最优方案，但计算复杂度显着降低。
In this paper, we consider the relay selection and power allocation (RSPA) problem in amplify-and-forward (AF) relaying networks. The objective is to minimize the outage probability at the receiver, assuming that only the mean channel gain information is available. By taking advantage of its special structure, we propose to decompose the RSPA problem into two tractable subproblems, which can be implemented in a semidistributed manner. For the relay selection (RS) subproblem, a relay-ordering-based scheme is designed to incrementally select a subset of relays from the candidate nodes according to a specific metric in a centralized manner, which is dominated by the mean channel gain of each individual nodes. For the power allocation (PA) subproblem, a source-driven iterative algorithm is proposed for each relay to decide its optimal transmit power locally by exploiting the convexity of this subproblem. Simulation results are provided to evaluate the outage and signal-to-noise-ratio (SNR) performance of the proposed scheme under different channel conditions. It is shown that the proposed scheme can dynamically select relays and adjust power allocation according to the SNR and channel conditions. It outperforms the other two benchmark schemes, and the performance is close to the optimal scheme with exhaustive search, but the computational complexity is significantly reduced.