A low-complexity optimal sphere decoder for differential spatial modulation

Zhi Li, Xiang Cheng, Shuangshuang Han, Miaowen Wen, Liu Qing Yang, Bingli Jiao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

Motivated by the concept of spatial modulation (SM), a differential scheme has been recently proposed. This scheme, termed as differential (D-)SM, dispenses with channel estimation while maintains a similar bit error rate (BER) performance to SM. The conventional optimal DSM detector based on a maximum likelihood (ML) criterion, however, gives rise to prohibitive computational complexity when either the space-domain or signal-domain constellation size is large. In this paper, we propose a low-complexity yet optimal detection algorithm for DSM by utilizing sphere decoding (SD). The complexity analysis concerning Euclidian distance equation for DSM-SD is derived. Simulation results show that the proposed DSM-SD algorithm maintains an identical BER performance and achieves a significant reduction of computational complexity compared with the DSM-ML algorithm. The DSM- SD algorithm is especially efficient when the number of receive antennas is large. Moreover, compared with SD applied to SM, its application to DSM is verified to be more useful and attractive.

Original languageEnglish (US)
Title of host publication2015 IEEE Global Communications Conference, GLOBECOM 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479959525
DOIs
StatePublished - 2015
Externally publishedYes
Event58th IEEE Global Communications Conference, GLOBECOM 2015 - San Diego, United States
Duration: Dec 6 2015Dec 10 2015

Publication series

Name2015 IEEE Global Communications Conference, GLOBECOM 2015

Other

Other58th IEEE Global Communications Conference, GLOBECOM 2015
Country/TerritoryUnited States
CitySan Diego
Period12/6/1512/10/15

Bibliographical note

Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grants (61571020, 61172105, 61501461); by the National 973 Project under Grant 2013CB336700; by the National 863 Project under Grants 2014AA01A706 and SS2015AA011306; by the National Natural Science Foundation under Grant CNS-1343189; and by the Early Career Development Award of SKLMCCS (Y3S9021F34)

Publisher Copyright:
© 2015 IEEE.

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