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基于减少反馈的中继辅助下行链路系统的多用户分集

On the multiuser diversity of relay-aided downlink systems using reduced feedback.

作者信息

Jang Yong-Up, Shin Won-Yong

机构信息

Agency for Defense Development, Daejeon 305-600, Republic of Korea.

Department of Computer Science and Engineering, Dankook University, Yongin 448-701, Republic of Korea.

出版信息

ScientificWorldJournal. 2014;2014:857540. doi: 10.1155/2014/857540. Epub 2014 Nov 10.

DOI:10.1155/2014/857540
PMID:25436232
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4241708/
Abstract

We introduce an efficient multiuser scheduling method using amplify-and-forward relaying in relay-aided downlink systems, consisting of one base station (BS), one relay station, and multiple mobile stations (MSs). In our scheme, the BS opportunistically selects both the transmission mode, that is, either one- or two-hop transmission, and the desired user (i.e., the desired MS). Closed-form expressions for the average achievable rates are derived for the two transmission modes with multiuser scheduling, and its asymptotic solutions are also analyzed in the limit of large number of MSs. Based on the analysis, we propose a feedback-efficient two-step multiuser scheduling algorithm: the transmission mode selection followed by the user selection that only needs a partial feedback for instantaneous signal-to-noise ratios (SNRs) to the BS. We also analyze the average SNR condition such that the multiuser diversity gain is fully exploited for two-hop transmission. The proposed two-step scheduling algorithm exhibits the quite comparable achievable rates to those of the optimal one using full feedback information, while its required feedback information is reduced by half of the optimal one.

摘要

我们介绍了一种在中继辅助下行链路系统中使用放大转发中继的高效多用户调度方法,该系统由一个基站(BS)、一个中继站和多个移动台(MS)组成。在我们的方案中,基站机会性地选择传输模式,即单跳或两跳传输,以及期望用户(即期望的移动台)。针对具有多用户调度的两种传输模式,推导了平均可达速率的闭式表达式,并在大量移动台的极限情况下分析了其渐近解。基于该分析,我们提出了一种反馈高效的两步多用户调度算法:先进行传输模式选择,然后进行用户选择,该算法仅需要向基站反馈部分瞬时信噪比(SNR)信息。我们还分析了平均SNR条件,以便在两跳传输中充分利用多用户分集增益。所提出的两步调度算法展示出与使用完整反馈信息的最优算法相当的可达速率,同时其所需的反馈信息减少为最优算法的一半。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/529b/4241708/6cf871955242/TSWJ2014-857540.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/529b/4241708/55688ff56617/TSWJ2014-857540.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/529b/4241708/7835ef25496b/TSWJ2014-857540.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/529b/4241708/6cf871955242/TSWJ2014-857540.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/529b/4241708/55688ff56617/TSWJ2014-857540.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/529b/4241708/7835ef25496b/TSWJ2014-857540.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/529b/4241708/6cf871955242/TSWJ2014-857540.003.jpg

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