Research Article
Performance Evaluation of Structured Compressed Sensing Based Signal Detection in Spatial Modulation 3D MIMO Systems
@INPROCEEDINGS{10.1007/978-3-319-73317-3_12, author={Wei Ren and Guan Gui and Fei Li}, title={Performance Evaluation of Structured Compressed Sensing Based Signal Detection in Spatial Modulation 3D MIMO Systems}, proceedings={Advanced Hybrid Information Processing. First International Conference, ADHIP 2017, Harbin, China, July 17--18, 2017, Proceedings}, proceedings_a={ADHIP}, year={2018}, month={2}, keywords={Structured compressed sensing Signal detection Structured subspace pursuit algorithm Spatial modulation}, doi={10.1007/978-3-319-73317-3_12} }- Wei Ren
Guan Gui
Fei Li
Year: 2018
Performance Evaluation of Structured Compressed Sensing Based Signal Detection in Spatial Modulation 3D MIMO Systems
ADHIP
Springer
DOI: 10.1007/978-3-319-73317-3_12
Abstract
Signal detection is one of the fundamental problems in three dimensional multiple-input multiple-output (3D MIMO) wireless communication systems. This paper addresses a signal detection problem in 3D MIMO system, in which spatial modulation (SM) transmission scheme is considered results of advantages of low complexity and high-energy efficiency. SM based signal transmission, typically results in the block-sparse structure in received signal. Hence, structured compressed sensing (SCS) based signal detection is proposed to exploit the inherent block sparsity information in the received signal for the uplink (UL). To extend the potential applications in different modulation based systems, this paper analyzes bit error rate (BER) of SCS-based method, in comparison with conventional methods such as minimum mean square error (MMSE) and zero padding (ZF). Simulation results are also provided to show the stable and reliable performance of the proposed SCS-based algorithm under most modulations.