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Fixed-Complexity Tree Search Schemes for Detecting Generalized Spatially Modulated Signals: Algorithms and Hardware Architectures.

Authors :
Liu, Tsung-Hsien
Wang, Shih-Lun
Lin, You-Jia
Hwang, Yin-Tsung
Chen, Chiao-En
Chu, Yuan-Sun
Source :
IEEE Transactions on Circuits & Systems. Part I: Regular Papers. Feb2021, Vol. 68 Issue 2, p904-917. 14p.
Publication Year :
2021

Abstract

In the generalized spatial modulation (GenSM) multiple input multiple output (MIMO) system, each block of data bits is mapped to a set of spatially multiplexed (SMX) symbols and an index of transmit antenna combination (TAC) of active antennas. The difficulty for the GenSM MIMO receiver is to detect the SMX symbols and TAC index simultaneously. Recently, we applied the conventional sphere decoding algorithm (SDA) successively to achieve the exact maximum likelihood detection (MLD) of GenSM MIMO signals. The SDA scheme suffers from variable computational complexity and leads to hardware detectors with variable throughput rate. Instead, fixed-complexity tree search algorithms, e.g., reduced fixed sphere decoding (rFSD), with nearly MLD performance are employed to facilitate hardware implementation. Here, we propose to apply the rFSD successively and design a hardware architecture for detecting GenSM MIMO signals under the scenario of 5 transmit antennas, 2 transmit radio frequency chains, 4 receive antennas, and 64-QAM SMX symbols. The VLSI implementation results under the TSMC 90nm CMOS technology reveal that our architecture requires 276.7K gates and provides detection throughput 1.613 Gbps, while operating at 322.6 MHz. Compared with other related architectures, our architecture provides higher detection throughput rate and is of better hardware efficiency. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15498328
Volume :
68
Issue :
2
Database :
Academic Search Index
Journal :
IEEE Transactions on Circuits & Systems. Part I: Regular Papers
Publication Type :
Periodical
Accession number :
148207874
Full Text :
https://doi.org/10.1109/TCSI.2020.3040375