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Detection of Large-Scale Wireless Systems via Sparse Error Recovery

Authors
Choi, Jun WonShim, Byonghyo
Issue Date
Nov-2017
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Sparse signal recovery; compressive sensing; large-scale systems; orthogonal matching pursuit; sparse transformation; linear minimum mean square error; error correction
Citation
IEEE TRANSACTIONS ON SIGNAL PROCESSING, v.65, no.22, pp.6038 - 6052
Indexed
SCIE
SCOPUS
Journal Title
IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume
65
Number
22
Start Page
6038
End Page
6052
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/151367
DOI
10.1109/TSP.2017.2749214
ISSN
1053-587X
Abstract
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.
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COLLEGE OF ENGINEERING (MAJOR IN ELECTRICAL ENGINEERING)
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