SIEVE: Scalable user grouping for large MU-MIMO systems

Wei Liang Shen, Ching-Ju Lin, Ming Syan Chen, Kun Tan

研究成果: Conference contribution同行評審

36 引文 斯高帕斯(Scopus)


Multi-user multiple input and multiple output (MU-MIMO) is one predominate approach to improve the wireless capacity. However, since the aggregate capacity of MU-MIMO heavily depends on the channel correlations among the mobile users in a beamforming group, unwisely selecting beamforming groups may result in reduced overall capacity, instead of increasing it. How to select users into a beamforming group becomes the bottleneck of realizing the MU-MIMO gain. The fundamental challenge for user selection is the large searching space, and hence there exists a tradeoff between search complexity and achievable capacity. Previous works have proposed several low complexity heuristic algorithms, but they suffer a significant capacity loss. In this paper, we present a novel MU-MIMO MAC, called SIEVE. The core of SIEVE design is its scalable multi-user selection module that provides a knob to control the aggressiveness in searching the best beamforming group. SIEVE maintains a central database to track the channel and the coherence time for each mobile user, and largely avoids unnecessary computing with a progressive update strategy. Our evaluation, via both small-scale testbed experiments and large-scale trace-driven simulations, shows that SIEVE can achieve around 90% of the capacity compared to exhaustive search.

主出版物標題2015 IEEE Conference on Computer Communications, IEEE INFOCOM 2015
發行者Institute of Electrical and Electronics Engineers Inc.
出版狀態Published - 21 八月 2015
事件34th IEEE Annual Conference on Computer Communications and Networks, IEEE INFOCOM 2015 - Hong Kong, Hong Kong
持續時間: 26 四月 20151 五月 2015


名字Proceedings - IEEE INFOCOM


Conference34th IEEE Annual Conference on Computer Communications and Networks, IEEE INFOCOM 2015
國家Hong Kong
城市Hong Kong

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