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Computer Science > Information Theory

arXiv:2203.06273 (cs)
[Submitted on 11 Mar 2022 (v1), last revised 9 Sep 2022 (this version, v3)]

Title:Bit-Metric Decoding Rate in Multi-User MIMO Systems: Applications

Authors:K. Pavan Srinath, Jakob Hoydis
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Abstract:This is the second part of a two-part paper that focuses on link-adaptation (LA) and physical layer (PHY) abstraction for multi-user MIMO (MU-MIMO) systems with non-linear receivers. The first part proposes a new metric, called bit-metric decoding rate (BMDR) for a detector, as being the equivalent of post-equalization signal-to-interference-noise ratio (SINR) for non-linear receivers. Since this BMDR does not have a closed form expression, a machine-learning based approach to estimate it effectively is presented. In this part, the concepts developed in the first part are utilized to develop novel algorithms for LA, dynamic detector selection from a list of available detectors, and PHY abstraction in MU-MIMO systems with arbitrary receivers. Extensive simulation results that substantiate the efficacy of the proposed algorithms are presented.
Comments: This is the second part of a two-part paper. This part has 30 pages, 3 tables, and 11 figures. The first part is titled "Bit-Metric Decoding Rate in Multi-User MIMO Systems: Theory". This version has been significantly revised
Subjects: Information Theory (cs.IT); Machine Learning (cs.LG)
Cite as: arXiv:2203.06273 [cs.IT]
  (or arXiv:2203.06273v3 [cs.IT] for this version)
  https://doi.org/10.48550/arXiv.2203.06273

Submission history

From: Pavan Srinath [view email]
[v1] Fri, 11 Mar 2022 22:51:26 UTC (631 KB)
[v2] Tue, 15 Mar 2022 15:20:47 UTC (631 KB)
[v3] Fri, 9 Sep 2022 11:50:23 UTC (644 KB)
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