Detection of Large-Scale Wireless Systems via Sparse Error Recovery

Jun Won Choi, Byonghyo Shim

Research output: Contribution to journalArticlepeer-review

10 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


  • 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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