The University of Southampton
University of Southampton Institutional Repository

Compressive-sensing-based multiuser detector for the large-scale SM-MIMO uplink

Compressive-sensing-based multiuser detector for the large-scale SM-MIMO uplink
Compressive-sensing-based multiuser detector for the large-scale SM-MIMO uplink
Conventional spatial modulation (SM) is typically considered for transmission in the downlink of smallscale MIMO systems, where a single one of a set of say 2p antenna elements (AEs) is activated for implicitly conveying p bits. By contrast, inspired by the compelling benefits of large-scale MIMO (LS-MIMO) systems, here we propose a LS-SM-MIMO scheme for the uplink (UL), where each user having multiple AEs but only a single radio frequency (RF) chain invokes SM for increasing the UL-throughput. At the same time, by relying on hundreds of AEs but a small number of RF chains, the base station (BS) can simultaneously serve multiple users whilst reducing the power consumption. Due to the large number of AEs of the UL-users and the comparably small number of RF chains at the BS, the UL multi-user signal detection becomes a challenging large-scale under-determined problem. To solve this problem, we propose a joint SM transmission scheme and a carefully designed structured compressive sensing (SCS)-based multi-user detector (MUD) to be used at the users and BS, respectively. Additionally, the cyclic-prefix single-carrier (CPSC) is used to combat the multipath channels, and a simple receive AE selection is used for the improved performance over correlated Rayleigh-fading MIMO channels. We demonstrate that the aggregate SM signal consisting of multiple UL-users’ SM signals of a CPSC block appears the distributed sparsity. Moreover, due to the joint SM transmission scheme, aggregate SM signals in the same transmission group exhibit the group sparsity. By exploiting these intrinsically sparse features, the proposed SCS-based MUD can reliably detect the resultant SM signals with low complexity. Simulation results demonstrate that the proposed SCS-based MUD achieves a better signal detection performance than its counterparts even with higher UL-throughtput.
large-ccale MIMO (LS-MIMO), compressive sensing, multi-user detector, spatial modulation (SM)
0018-9545
8725-8730
Gao, Zhen
e0ab17e4-5297-4334-8b64-87924feb7876
Dai, Linglong
a3b9a8e1-777f-4196-a388-969444c7239d
Wang, Zhaocheng
70339538-3970-4094-bcfc-1b5111dfd8b4
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Gao, Zhen
e0ab17e4-5297-4334-8b64-87924feb7876
Dai, Linglong
a3b9a8e1-777f-4196-a388-969444c7239d
Wang, Zhaocheng
70339538-3970-4094-bcfc-1b5111dfd8b4
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Gao, Zhen, Dai, Linglong, Wang, Zhaocheng, Chen, Sheng and Hanzo, Lajos (2016) Compressive-sensing-based multiuser detector for the large-scale SM-MIMO uplink. IEEE Transactions on Vehicular Technology, 65 (10), 8725-8730. (doi:10.1109/TVT.2015.2501460).

Record type: Article

Abstract

Conventional spatial modulation (SM) is typically considered for transmission in the downlink of smallscale MIMO systems, where a single one of a set of say 2p antenna elements (AEs) is activated for implicitly conveying p bits. By contrast, inspired by the compelling benefits of large-scale MIMO (LS-MIMO) systems, here we propose a LS-SM-MIMO scheme for the uplink (UL), where each user having multiple AEs but only a single radio frequency (RF) chain invokes SM for increasing the UL-throughput. At the same time, by relying on hundreds of AEs but a small number of RF chains, the base station (BS) can simultaneously serve multiple users whilst reducing the power consumption. Due to the large number of AEs of the UL-users and the comparably small number of RF chains at the BS, the UL multi-user signal detection becomes a challenging large-scale under-determined problem. To solve this problem, we propose a joint SM transmission scheme and a carefully designed structured compressive sensing (SCS)-based multi-user detector (MUD) to be used at the users and BS, respectively. Additionally, the cyclic-prefix single-carrier (CPSC) is used to combat the multipath channels, and a simple receive AE selection is used for the improved performance over correlated Rayleigh-fading MIMO channels. We demonstrate that the aggregate SM signal consisting of multiple UL-users’ SM signals of a CPSC block appears the distributed sparsity. Moreover, due to the joint SM transmission scheme, aggregate SM signals in the same transmission group exhibit the group sparsity. By exploiting these intrinsically sparse features, the proposed SCS-based MUD can reliably detect the resultant SM signals with low complexity. Simulation results demonstrate that the proposed SCS-based MUD achieves a better signal detection performance than its counterparts even with higher UL-throughtput.

Text
tvt-hanzo-2501460-proof.pdf - Accepted Manuscript
Download (1MB)
Text
TVT2016-Oct.pdf - Other
Restricted to Repository staff only
Request a copy

More information

Accepted/In Press date: 14 November 2015
e-pub ahead of print date: 18 November 2015
Published date: October 2016
Keywords: large-ccale MIMO (LS-MIMO), compressive sensing, multi-user detector, spatial modulation (SM)

Identifiers

Local EPrints ID: 384295
URI: http://eprints.soton.ac.uk/id/eprint/384295
ISSN: 0018-9545
PURE UUID: 7e7329fa-b52e-445a-bdd0-02986e5f1dba
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 21 Dec 2015 12:14
Last modified: 17 Dec 2019 02:03

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×