Effect of CSI quantization on the average rate in MU-MIMO WLANs

Sanjeeb Shrestha, Gengfa Fang, Eryk Dutkiewicz, Xiaojing Huang

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

2 Citations (Scopus)

Abstract

In Multi-User Multiple Input Multiple Output (MU-MIMO) Wireless Local Area Networks (WLANs), the optimal-solution such as Dirty Paper Coding (DPC) or the sub-optimal solution Zeroforcing Beamforming (ZFB) with perfect Channel State Information (CSI), is practically limited due to the complexity and the non-availability of perfect CSI at the Access Points (APs)/transmitters. In such a context, ZFB based on channel quantization available at the APs (ZFQ) is the obvious choice for the Multi-User transmission strategy. However, since the quantized CSI is used instead of the perfect CSI at the APs, the quantization error and its impact on the average rate for ZFQ have to be quantified in MU-MIMO WLAN settings. In this paper, we derive a closed-form expression for the upper bound of the channel quantization error and the average rate reduction due to the quantization error with respect to the perfect CSI at the APs. In MU-MIMO WLAN settings, our analytical and numerical studies show that, with an increasing number of antennas at the clients, both the quantization error bound and the average rate reduction increase for ZFQ, in comparison to the ZFB with the perfect CSI.

Original languageEnglish
Title of host publication2016 13th IEEE Annual Consumer Communications and Networking Conference, CCNC 2016
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages824-828
Number of pages5
ISBN (Electronic)9781467392921
DOIs
Publication statusPublished - 30 Mar 2016
Event13th IEEE Annual Consumer Communications and Networking Conference, CCNC 2016 - Las Vegas, United States
Duration: 6 Jan 201613 Jan 2016

Other

Other13th IEEE Annual Consumer Communications and Networking Conference, CCNC 2016
CountryUnited States
CityLas Vegas
Period6/01/1613/01/16

Keywords

  • Average Rate Reduction
  • Channel State Information
  • Quantization Error
  • Zeroforcing Beamforming

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