Paper Info
Title
Low-Complexity ML Detection for Spatial Modulation MIMO with APSK Constellation
Abstract
Spatial modulation (SM) is a promising multipleinput- multiple-output (MIMO) transmission technology, which exploits the indices of the transmit antennas for encoding information into the spatial dimension and, thus, for increasing the transmission rate. Optimal demodulation is realized by using a maximum-likelihood (ML) detector, which jointly estimates the information bits encoded into the transmit antenna indices and into the transmitted symbol. If a large number of transmit antennas and/or a large modulation size are used, however, the computational complexity of ML demodulation may not be affordable for some applications. Against this background, we propose two novel near-ML but low-complexity detection schemes for SM-MIMO systems, which use M-ary amplitude-phase shift keying (APSK) digital modulation. The proposed algorithms exploit specific features of the M-ary APSK constellation diagram, in order to avoid searching among all constellation points. It is shown, in particular, that the complexity of the proposed detection schemes is independent of the constellation size and that it only depends on the number of rings that constitute the APSK constellation. Simulation results are also provided, which confirm that the proposed detection schemes provide bit error probability performance close to that of ML demodulation but with a lower demodulation complexity.
Year
DOI
Venue
2015
10.1109/TVT.2015.2430855
IEEE Trans. Vehicular Technology
Keywords
Field
DocType
M-ary amplitude and phase-shift keying (APSK) modulation, maximum-likelihood (ML) detection, multiple-input multiple-output (MIMO), spatial modulation (SM)
Quadrature modulation,Demodulation,Computer science,Amplitude and phase-shift keying,Keying,MIMO,Electronic engineering,Modulation,Constellation diagram,Computational complexity theory
Journal
Volume
Issue
ISSN
PP
99
0018-9545
Citations 
PageRank 
References 
5
0.41
23
Authors
5
Name
Order
Citations
PageRank
Cong Li170.79
Yuzhen Huang212620.46
Marco Di Renzo34721269.75
Jin-Long Wang4140294.86
Yunpeng Cheng5858.84