Sparsity-Aided Iterative Receiver for Large Scale Under-Determined MIMO Systems
In this paper, we propose a sparsity-aided iterative receiver for large scale under-determined multiple-input multiple-output (UD-MIMO) systems. The proposed scheme is motivated by the fact that most conventional receivers produce a sparse residual error vector, which is the difference between the actual transmitted symbol vector and the estimated one. The sparse feature of the residual error vector is utilized to locate the support set of the erroneously detected symbols by using the compressive sensing (CS) framework. We can then remove the effects of the correctly detected symbols and only update the soft information of the symbols with detection errors. Since the number of error symbols is usually much less than that of receive antennas, the sparsity-aided receiver equivalently convert the system into an over-determined MIMO system, and the soft information update of the error symbols can be performed with simple linear receivers. Simulation results demonstrate that our proposed sparsity-aided iterative receiver can achieve significant performance gains over conventional UD-MIMO receivers, at the cost of a small complexity overhead.
P. Zhao et al., "Sparsity-Aided Iterative Receiver for Large Scale Under-Determined MIMO Systems," Proceedings of the 18th IEEE International Workshop on Signal Processing Advances in Wireless Communications (2017, Sapporo, Japan), Institute of Electrical and Electronics Engineers (IEEE), Jul 2017.
The definitive version is available at https://doi.org/10.1109/SPAWC.2017.8227771
18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC (2017: Jul.3-6, Sapporo, Japan)
Electrical and Computer Engineering
National Natural Science Foundation (China)
Shenzhen Subject Arrangements
Shenzhen Peacock Plan
Shenzhen Fundamental Research Project
Keywords and Phrases
Channel estimation; Errors; MIMO systems; Receiving antennas; Signal receivers; Wireless telecommunication systems; Compressive sensing; Detection error; Iterative receivers; Linear receiver; Performance Gain; Receive antenna; Soft information; Under-determined; Signal processing
International Standard Book Number (ISBN)
International Standard Serial Number (ISSN)
Article - Conference proceedings
© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Jul 2017