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Compressive sensing based massive access for IoT relying on media modulation aided machine type communications

Compressive sensing based massive access for IoT relying on media modulation aided machine type communications
Compressive sensing based massive access for IoT relying on media modulation aided machine type communications
A fundamental challenge of the large-scale Internet-of-Things lies in how to support massive machine-type communications (mMTC). This letter proposes a media modulation based mMTC solution for increasing the throughput, where a massive multi-input multi-output based base station (BS) is used for enhancing the detection performance. For such a mMTC scenario, the reliable active device detection and data decoding pose a serious challenge. By leveraging the sparsity of the uplink access signals of mMTC received at the BS, a compressive sensing based massive access solution is proposed for tackling this challenge. Specifically, we propose a structured orthogonal matching pursuit algorithm for detecting the active devices, whereby the block-sparsity of the uplink access signals exhibited across the successive time slots and the structured sparsity of media-modulated symbols are exploited for enhancing the detection performance. Moreover, a successive interference cancellation based structured subspace pursuit algorithm is conceived for data demodulation of the active devices, whereby the structured sparsity of media modulation based symbols found in each time slot is exploited for improving the detection performance. Finally, our simulation results verify the superiority of the proposed scheme over state-of-the-art solutions.
Internet-of-Things, compressive sensing, massive access, massive machine type communications, massive multi-input multi-output, media modulation
0018-9545
10391-10396
Qiao, Li
f45484d1-2a7f-4974-a2bf-5f548650abc1
Zhang, Jun
6e318b53-b039-4f5f-8229-fd45312ca537
Gao, Zhen
e0ab17e4-5297-4334-8b64-87924feb7876
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Qiao, Li
f45484d1-2a7f-4974-a2bf-5f548650abc1
Zhang, Jun
6e318b53-b039-4f5f-8229-fd45312ca537
Gao, Zhen
e0ab17e4-5297-4334-8b64-87924feb7876
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Qiao, Li, Zhang, Jun, Gao, Zhen, Chen, Sheng and Hanzo, Lajos (2020) Compressive sensing based massive access for IoT relying on media modulation aided machine type communications. IEEE Transactions on Vehicular Technology, 69 (9), 10391-10396, [9130957]. (doi:10.1109/TVT.2020.3006318).

Record type: Article

Abstract

A fundamental challenge of the large-scale Internet-of-Things lies in how to support massive machine-type communications (mMTC). This letter proposes a media modulation based mMTC solution for increasing the throughput, where a massive multi-input multi-output based base station (BS) is used for enhancing the detection performance. For such a mMTC scenario, the reliable active device detection and data decoding pose a serious challenge. By leveraging the sparsity of the uplink access signals of mMTC received at the BS, a compressive sensing based massive access solution is proposed for tackling this challenge. Specifically, we propose a structured orthogonal matching pursuit algorithm for detecting the active devices, whereby the block-sparsity of the uplink access signals exhibited across the successive time slots and the structured sparsity of media-modulated symbols are exploited for enhancing the detection performance. Moreover, a successive interference cancellation based structured subspace pursuit algorithm is conceived for data demodulation of the active devices, whereby the structured sparsity of media modulation based symbols found in each time slot is exploited for improving the detection performance. Finally, our simulation results verify the superiority of the proposed scheme over state-of-the-art solutions.

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VT-2019-03492.R1-Final Version-with-my-ack - Accepted Manuscript
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TVT2020-Sep - Version of Record
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More information

Accepted/In Press date: 29 June 2020
e-pub ahead of print date: 1 July 2020
Published date: September 2020
Keywords: Internet-of-Things, compressive sensing, massive access, massive machine type communications, massive multi-input multi-output, media modulation

Identifiers

Local EPrints ID: 442128
URI: http://eprints.soton.ac.uk/id/eprint/442128
ISSN: 0018-9545
PURE UUID: 21e3c5ee-3e58-493f-9d61-a430ee276142
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 07 Jul 2020 16:49
Last modified: 03 Nov 2020 17:30

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