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相关环境下具有单中继选择的放大转发系统性能分析

Performance Analysis of Amplify-and-Forward Systems with Single Relay Selection in Correlated Environments.

作者信息

Van Nguyen Binh, Kim Kiseon

机构信息

Department of Nanobio Materials and Electronics, Gwangju Institute of Science and Technology, Gwangju 61005, Korea.

School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju 61005, Korea.

出版信息

Sensors (Basel). 2016 Sep 11;16(9):1472. doi: 10.3390/s16091472.

DOI:10.3390/s16091472
PMID:27626426
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5038750/
Abstract

In this paper, we consider amplify-and-forward (AnF) cooperative systems under correlated fading environments. We first present a brief overview of existing works on the effect of channel correlations on the system performance. We then focus on our main contribution which is analyzing the outage probability of a multi-AnF-relay system with the best relay selection (BRS) scheme under a condition that two channels of each relay, source-relay and relay-destination channels, are correlated. Using lower and upper bounds on the end-to-end received signal-to-noise ratio (SNR) at the destination, we derive corresponding upper and lower bounds on the system outage probability. We prove that the system can achieve a diversity order (DO) equal to the number of relays. In addition, and importantly, we show that the considered correlation form has a constructive effect on the system performance. In other words, the larger the correlation coefficient, the better system performance. Our analytic results are corroborated by extensive Monte-Carlo simulations.

摘要

在本文中,我们考虑相关衰落环境下的放大转发(AnF)协作系统。我们首先简要概述了关于信道相关性对系统性能影响的现有研究工作。然后,我们重点阐述主要贡献,即在每个中继的源 - 中继和中继 - 目的信道这两个信道相关的条件下,分析采用最佳中继选择(BRS)方案的多AnF中继系统的中断概率。利用目的端端到端接收信噪比(SNR)的上下界,我们推导出系统中断概率的相应上下界。我们证明该系统能够实现等于中继数量的分集阶数(DO)。此外,重要的是,我们表明所考虑的相关形式对系统性能具有建设性影响。换句话说,相关系数越大,系统性能越好。我们的分析结果得到了广泛的蒙特卡罗模拟的证实。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/93bd954408e4/sensors-16-01472-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/12afee14bd36/sensors-16-01472-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/8d9b7a513d76/sensors-16-01472-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/5dcee7fc430e/sensors-16-01472-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/210bfcd10a2b/sensors-16-01472-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/8c2d14c31eee/sensors-16-01472-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/73979f8e697e/sensors-16-01472-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/b027d6430ffe/sensors-16-01472-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/93bd954408e4/sensors-16-01472-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/12afee14bd36/sensors-16-01472-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/8d9b7a513d76/sensors-16-01472-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/5dcee7fc430e/sensors-16-01472-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/210bfcd10a2b/sensors-16-01472-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/8c2d14c31eee/sensors-16-01472-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/73979f8e697e/sensors-16-01472-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/b027d6430ffe/sensors-16-01472-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72b4/5038750/93bd954408e4/sensors-16-01472-g008.jpg

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