Compressed channel feedback for correlateci massive MIMO systems

Min Soo Sim, Chan Byoung Chae

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Massive multiple-input multiple-output (MIMO) is a promising approach for cellular communication due to its energy efficiency and high achievable data rate. These advantages, however, can be realized only when channel state information (CSI) is available at the transmitter. Since there are many antennas, CSI is too large to feed back without compression. As a sparsifying basis, prior work has applied compressive sensing (CS) techniques with the two-dimensional discrete cosine transform (2D-DCT) and the instantaneous Karhunen-Loeve transform (KLT). 2D-DCT fails, however, to reflect the spatial correlation and channel conditions. Instantaneous KLT requires perfect CSI, which means it is not feasible in practice. In this paper, we propose a new sparsifying basis that reflects the long-term characteristics of the channel and a new reconstruction algorithm for CS. We also suggest that dimensionality reduction is more proper to compress, and compare performance with the conventional method. Numerical results confirm that the proposed channel feedback mechanisms show better performance in point-to-point (single user) and point-to-multi-point (multiuser) scenarios.

Original languageEnglish
Title of host publication2014 IEEE Globecom Workshops, GC Wkshps 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages327-332
Number of pages6
ISBN (Electronic)9781479974702
DOIs
Publication statusPublished - 2014 Mar 18
Event2014 IEEE Globecom Workshops, GC Wkshps 2014 - Austin, United States
Duration: 2014 Dec 82014 Dec 12

Publication series

Name2014 IEEE Globecom Workshops, GC Wkshps 2014

Other

Other2014 IEEE Globecom Workshops, GC Wkshps 2014
CountryUnited States
CityAustin
Period14/12/814/12/12

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Communication

Fingerprint Dive into the research topics of 'Compressed channel feedback for correlateci massive MIMO systems'. Together they form a unique fingerprint.

  • Cite this

    Sim, M. S., & Chae, C. B. (2014). Compressed channel feedback for correlateci massive MIMO systems. In 2014 IEEE Globecom Workshops, GC Wkshps 2014 (pp. 327-332). [7063452] (2014 IEEE Globecom Workshops, GC Wkshps 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GLOCOMW.2014.7063452