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Compressed sensing-aided space-time frequency index modulation

Compressed sensing-aided space-time frequency index modulation
Compressed sensing-aided space-time frequency index modulation
In space-time shift keying (STSK), the information is conveyed by both the spatial and time dimensions, which can be used to strike a trade-off between the diversity and multiplexing gains. On the other hand, orthogonal frequency division multiplexing (OFDM) relying on index modulation (IM) conveys information not only by the conventional signal constellations as in classical OFDM, but also by the indices of the subcarriers. In this paper, we combine the benefits of STSK and IM in order to strike a flexible trade-off between the throughput and bit-error performance by transmitting extra information bits in each subcarrier block, whilst increasing the diversity order. In order to further improve this trade-off, as well as to decrease the complexity of the detector, compressed sensing (CS) is combined with the proposed STSK-aided IM system. We first present the Maximum LikeLihood (ML) detection, which forms the best-case bound on the proposed system's performance. Then we propose a pair of reduced-complexity detection algorithms capable of approaching the ML detector's performance. Furthermore, in order to attain a near capacity-performance, we propose a soft-input-soft-output (SISO) decoder that is capable of exchanging soft-information with a channel decoder through iterative decoding.
0018-9545
1-14
Lu, Siyao
464cf7cc-b469-450a-93c2-489a31d1289c
Hemadeh, Ibrahim
6576ce7e-fe4c-4f4d-b5db-84935f38cd9c
El-Hajjar, Mohammed
3a829028-a427-4123-b885-2bab81a44b6f
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Lu, Siyao
464cf7cc-b469-450a-93c2-489a31d1289c
Hemadeh, Ibrahim
6576ce7e-fe4c-4f4d-b5db-84935f38cd9c
El-Hajjar, Mohammed
3a829028-a427-4123-b885-2bab81a44b6f
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Lu, Siyao, Hemadeh, Ibrahim, El-Hajjar, Mohammed and Hanzo, Lajos (2018) Compressed sensing-aided space-time frequency index modulation. IEEE Transactions on Vehicular Technology, 1-14. (doi:10.1109/TVT.2018.2818298).

Record type: Article

Abstract

In space-time shift keying (STSK), the information is conveyed by both the spatial and time dimensions, which can be used to strike a trade-off between the diversity and multiplexing gains. On the other hand, orthogonal frequency division multiplexing (OFDM) relying on index modulation (IM) conveys information not only by the conventional signal constellations as in classical OFDM, but also by the indices of the subcarriers. In this paper, we combine the benefits of STSK and IM in order to strike a flexible trade-off between the throughput and bit-error performance by transmitting extra information bits in each subcarrier block, whilst increasing the diversity order. In order to further improve this trade-off, as well as to decrease the complexity of the detector, compressed sensing (CS) is combined with the proposed STSK-aided IM system. We first present the Maximum LikeLihood (ML) detection, which forms the best-case bound on the proposed system's performance. Then we propose a pair of reduced-complexity detection algorithms capable of approaching the ML detector's performance. Furthermore, in order to attain a near capacity-performance, we propose a soft-input-soft-output (SISO) decoder that is capable of exchanging soft-information with a channel decoder through iterative decoding.

Text
CS-STSK-IM-Accepted - Accepted Manuscript
Available under License Creative Commons Attribution.
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More information

Accepted/In Press date: 20 March 2018
e-pub ahead of print date: 22 March 2018

Identifiers

Local EPrints ID: 418835
URI: https://eprints.soton.ac.uk/id/eprint/418835
ISSN: 0018-9545
PURE UUID: 73ad20ff-5554-4180-ac44-787b47e5ac7b
ORCID for Siyao Lu: ORCID iD orcid.org/0000-0002-5239-3964
ORCID for Mohammed El-Hajjar: ORCID iD orcid.org/0000-0002-7987-1401
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 23 Mar 2018 17:30
Last modified: 17 Sep 2019 01:10

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