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Enhanced Receive Spatial Modulation Based on Power Allocation
Univ Elect Sci & Technol China, Ctr Intelligent Networking & Commun, Chengdu 611731, Sichuan, Peoples R China.;Univ Elect Sci & Technol China, Natl Key Lab Sci & Technol Commun, Chengdu 611731, Sichuan, Peoples R China..
Univ Elect Sci & Technol China, Natl Key Lab Sci & Technol Commun, Chengdu 611731, Sichuan, Peoples R China..
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.ORCID iD: 0000-0002-5407-0835
Univ Elect Sci & Technol China, Natl Key Lab Sci & Technol Commun, Chengdu 611731, Sichuan, Peoples R China..
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2019 (English)In: IEEE Journal on Selected Topics in Signal Processing, ISSN 1932-4553, E-ISSN 1941-0484, Vol. 13, no 6, p. 1312-1325Article in journal (Refereed) Published
Abstract [en]

In this paper, we investigate the benefits of power allocation (PA) for multiple-input multiple-output (MIMO) receive spatial modulation (RSM) with both a total transmit power constraint (TTPC) and a per-antenna power constraint (PAPC). First, we derive optimal PA closed-form solutions that maximize the minimum distance d(min) between the received signal points for (N-t x 2)-element RSM with arbitrary phase-shift keying schemes (where N-t is the number of transmit antennas) subject to a TTPC. Based on the derived solutions and the error vector reduction (EVR) method, we propose a low-complexity iterative algorithm to identify PA parameters for high numbers of receive antennas (N-r >= 2). Specifically, the EVR-based PA (EVR-PA) algorithm resembles its traditional exhaustive-search-based counterpart, but only exploits the receive distances of a few dominant error vectors to iteratively optimize the PA matrix. Then, a more strict yet practical PAPC is considered for PA in RSM-MIMO systems, and a well-designed approximate convex optimization (ACO)-based iterative PA algorithm is proposed. Compared to EVR-PA, the ACO-based PA (ACO-PA) algorithm first formulates the PA problems with the PAPC in RSM into constrained quadratic program problems and then utilizes the powerful augmented Lagrangian multiplier to find their optimal solutions. Our simulation results show that the proposed EVR-PA- and ACO-PA-aided RSM schemes outperform the equal-power-allocated RSM- and PA-aided spatial multiplexing schemes.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019. Vol. 13, no 6, p. 1312-1325
Keywords [en]
Link adaptation, pre-coding aided spatial modulation (PSM), per-antenna power constraints, power allocation (PA), receive spatial modulation (RSM)
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-265487DOI: 10.1109/JSTSP.2019.2916608ISI: 000499332700009Scopus ID: 2-s2.0-85071056582OAI: oai:DiVA.org:kth-265487DiVA, id: diva2:1378558
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QC 20191213

Available from: 2019-12-13 Created: 2019-12-13 Last updated: 2019-12-13Bibliographically approved

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Xiao, Ming

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