Detection of Large-Scale Wireless Systems via Sparse Error Recovery

Jun Won Choi, Byonghyo Shim

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

In this paper, we introduce 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: 1) sparse transformation converting the original non-sparse system into the sparse system whose input is an error vector caused by the symbol slicing and 2) estimation of the error vector using the sparse recovery algorithm. From the asymptotic mean square error (MSE) analysis and empirical simulations performed on large-scale systems, we show that the PSED algorithm brings significant performance gain over classical linear detectors while imposing relatively small computational overhead.

Original languageEnglish
JournalIEEE Transactions on Signal Processing
DOIs
Publication statusAccepted/In press - 2017 Sep 2
Externally publishedYes

Fingerprint

Error detection
Detectors
Mean square error
Error analysis
Large scale systems
Recovery

Keywords

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

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Detection of Large-Scale Wireless Systems via Sparse Error Recovery. / Choi, Jun Won; Shim, Byonghyo.

In: IEEE Transactions on Signal Processing, 02.09.2017.

Research output: Contribution to journalArticle

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