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Signpost: Scalable MU-MIMO Signaling with Zero CSI Feedback

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Published:22 June 2015Publication History

ABSTRACT

Poor scalability is a long standing problem in multi-user MIMO (MU-MIMO) networks: in order to select concurrent uplink users with strong channel orthogonality and thus high total capacity, channel state information (CSI) feedback from users is required. However, when the user population is large, the overhead from CSI feedback can easily overwhelm the actual channel time spent on data transmission. Moreover, due to spontaneous uplink traffic, uplink user selection cannot rely on the access point's central assignment and needs a distributed realization instead, which makes the problem even more challenging.

In this paper, we propose a fully scalable and distributed uplink MU-MIMO protocol called Signpost. Firstly, Signpost is scalable, i.e., it achieves zero CSI overhead by exploiting a novel orthogonality evaluation mechanism that enables each user to speculate its orthogonality to other users, using its own CSI only. Secondly, Signpost realizes distributed user selection through a two-dimensional prioritized contention mechanism, which can single out the best users efficiently by utilizing both the time and frequency domain resources. The contention mechanism includes a unique collision recovery scheme, which enables Signpost to achieve a collision probability as low as one-tenth compared with traditional 802.11-like mechanism. Software-radio based implementation and testbed experimentation show that Signpost significantly outperforms state-of-the-art user selection methods under various traffic patterns and node mobility.

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      • Published in

        cover image ACM Conferences
        MobiHoc '15: Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing
        June 2015
        436 pages
        ISBN:9781450334891
        DOI:10.1145/2746285

        Copyright © 2015 ACM

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        Publication History

        • Published: 22 June 2015

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        MobiHoc '15 Paper Acceptance Rate37of250submissions,15%Overall Acceptance Rate296of1,843submissions,16%

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