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.
Original language | English |
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Article number | 8025598 |
Pages (from-to) | 6038-6052 |
Number of pages | 15 |
Journal | IEEE Transactions on Signal Processing |
Volume | 65 |
Issue number | 22 |
DOIs | |
Publication status | Published - 2017 Nov 15 |
Bibliographical note
Publisher Copyright:© 2017 IEEE.
Keywords
- 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