Detection of Large-Scale Wireless Systems via Sparse Error Recovery

Jun Won Choi, Byonghyo Shim

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


In this paper, we propose a new detection algorithm for large-scale wireless systems, referred to as post sparse error detection (PSED) algorithm, that employs a sparse error recovery algorithm to refine the estimate of a symbol vector obtained by the conventional linear detector. The PSED algorithm operates in two steps: First, sparse transformation converting the original nonsparse system into the sparse system whose input is an error vector caused by the symbol slicing; and second, the estimation of the error vector using the sparse recovery algorithm. From the asymptotic mean square error analysis and empirical simulations performed on large-scale wireless systems, we show that the PSED algorithm brings significant performance gain over classical linear detectors while imposing relatively small computational overhead.

Original languageEnglish
Article number8025598
Pages (from-to)6038-6052
Number of pages15
JournalIEEE Transactions on Signal Processing
Issue number22
Publication statusPublished - 2017 Nov 15

Bibliographical note

Funding Information:
Manuscript received August 8, 2016; revised July 7, 2017; accepted August 22, 2017. Date of publication September 4, 2017; date of current version September 26, 2017. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Ami Wiesel. This work was supported in part by the research grant from Qualcomm Incorporated and in part by the Institute for Information & Communications Technology Promotion Grant funded by the Korea government (MSIP) (No. 2015-0-00294) and the Ministry of Education (NRF-2017R1D1A1A09000602). This paper was presented in part at the IEEE Global Telecommunications Conference, Austin, TX, USA, December 2014. (Corresponding author: Byonghyo Shim.) J. W. Choi is with the Department of Electrical Engineering, Hanyang University, Seoul 133-791, South Korea (e-mail:

Publisher Copyright:
© 2017 IEEE.


  • Sparse signal recovery
  • compressive sensing
  • error correction
  • large-scale systems
  • linear minimum mean square error
  • orthogonal matching pursuit
  • sparse transformation

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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