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