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Latency minimization for intelligent reflecting surface aided mobile edge computing

Latency minimization for intelligent reflecting surface aided mobile edge computing
Latency minimization for intelligent reflecting surface aided mobile edge computing

Computation off-loading in mobile edge computing (MEC) systems constitutes an efficient paradigm of supporting resource-intensive applications on mobile devices. However, the benefit of MEC cannot be fully exploited, when the communications link used for off-loading computational tasks is hostile. Fortunately, the propagation-induced impairments may be mitigated by intelligent reflecting surfaces (IRS), which are capable of enhancing both the spectral- and energy-efficiency. Specifically, an IRS comprises an IRS controller and a large number of passive reflecting elements, each of which may impose a phase shift on the incident signal, thus collaboratively improving the propagation environment. In this paper, the beneficial role of IRSs is investigated in MEC systems, where single-antenna devices may opt for off-loading a fraction of their computational tasks to the edge computing node via a multi-antenna access point with the aid of an IRS. Pertinent latency-minimization problems are formulated for both single-device and multi-device scenarios, subject to practical constraints imposed on both the edge computing capability and the IRS phase shift design. To solve this problem, the block coordinate descent (BCD) technique is invoked to decouple the original problem into two subproblems, and then the computing and communications settings are alternatively optimized using low-complexity iterative algorithms. It is demonstrated that our IRS-aided MEC system is capable of significantly outperforming the conventional MEC system operating without IRSs. Quantitatively, about 20 % computational latency reduction is achieved over the conventional MEC system in a single cell of a 300 m radius and 5 active devices, relying on a 5-antenna access point.

Intelligent reflecting surface, latency minimization, mobile edge computing
0733-8716
2666-2682
Bai, Tong
15e00a16-2ade-4fdb-a4d9-a490a526669a
Pan, Cunhua
9ee3d968-c5c2-42ba-8041-d54667205d5b
Deng, Yansha
0d528ce8-41ad-4d89-b2f9-0159c61fd0a1
Elkashlan, Maged
27c756ff-bfd3-4844-8769-ace5ad28c840
Nallanathan, Arumugam
d255cda5-a015-4bb9-9f17-88614a544396
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Bai, Tong
15e00a16-2ade-4fdb-a4d9-a490a526669a
Pan, Cunhua
9ee3d968-c5c2-42ba-8041-d54667205d5b
Deng, Yansha
0d528ce8-41ad-4d89-b2f9-0159c61fd0a1
Elkashlan, Maged
27c756ff-bfd3-4844-8769-ace5ad28c840
Nallanathan, Arumugam
d255cda5-a015-4bb9-9f17-88614a544396
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Bai, Tong, Pan, Cunhua, Deng, Yansha, Elkashlan, Maged, Nallanathan, Arumugam and Hanzo, Lajos (2020) Latency minimization for intelligent reflecting surface aided mobile edge computing. IEEE Journal on Selected Areas in Communications, 38 (11), 2666-2682, [9133107]. (doi:10.1109/JSAC.2020.3007035).

Record type: Article

Abstract

Computation off-loading in mobile edge computing (MEC) systems constitutes an efficient paradigm of supporting resource-intensive applications on mobile devices. However, the benefit of MEC cannot be fully exploited, when the communications link used for off-loading computational tasks is hostile. Fortunately, the propagation-induced impairments may be mitigated by intelligent reflecting surfaces (IRS), which are capable of enhancing both the spectral- and energy-efficiency. Specifically, an IRS comprises an IRS controller and a large number of passive reflecting elements, each of which may impose a phase shift on the incident signal, thus collaboratively improving the propagation environment. In this paper, the beneficial role of IRSs is investigated in MEC systems, where single-antenna devices may opt for off-loading a fraction of their computational tasks to the edge computing node via a multi-antenna access point with the aid of an IRS. Pertinent latency-minimization problems are formulated for both single-device and multi-device scenarios, subject to practical constraints imposed on both the edge computing capability and the IRS phase shift design. To solve this problem, the block coordinate descent (BCD) technique is invoked to decouple the original problem into two subproblems, and then the computing and communications settings are alternatively optimized using low-complexity iterative algorithms. It is demonstrated that our IRS-aided MEC system is capable of significantly outperforming the conventional MEC system operating without IRSs. Quantitatively, about 20 % computational latency reduction is achieved over the conventional MEC system in a single cell of a 300 m radius and 5 active devices, relying on a 5-antenna access point.

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IRS_MEC_0508_twocolumn - Accepted Manuscript
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Accepted/In Press date: 8 May 2020
e-pub ahead of print date: 3 July 2020
Published date: 1 November 2020
Additional Information: Funding Information: Manuscript received December 17, 2019; revised April 15, 2020; accepted May 8, 2020. Date of publication July 3, 2020; date of current version October 16, 2020. The work of Tong Bai and of Arumugam Nallanathan was supported by the Engineering and Physical Sciences Research Council under Project EP/R006466/1. The work of Lajos Hanzo was supported in part by the Engineering and Physical Sciences Research Council under Project EP/N004558/1, Project EP/P034284/1, and Project EP/P003990/1 (COALESCE), in part by the Royal Society’s Global Challenges Research Fund Grant, and in part by the European Research Council’s Advanced Fellow Grant QuantCom. (Corresponding authors: Cunhua Pan; Tong Bai.) Tong Bai, Cunhua Pan, Maged Elkashlan, and Arumugam Nallanathan are with the School of Electronic Engineering and Computer Science, Queen Mary University of London, London E1 4NS, U.K. (e-mail: t.bai@qmul.ac.uk; c.pan@qmul.ac.uk; maged.elkashlan@qmul.ac.uk; a.nallanathan@qmul.ac.uk). Funding Information: The work of Tong Bai and of Arumugam Nallanathan was supported by the Engineering and Physical Sciences Research Council under Project EP/R006466/1. The work of Lajos Hanzo was supported in part by the Engineering and Physical Sciences Research Council under Project EP/N004558/1, Project EP/P034284/1, and Project EP/P003990/1 (COALESCE), in part by the Royal Society?s Global Challenges Research Fund Grant, and in part by the European Research Council?s Advanced Fellow Grant QuantCom. Publisher Copyright: © 1983-2012 IEEE.
Keywords: Intelligent reflecting surface, latency minimization, mobile edge computing

Identifiers

Local EPrints ID: 440730
URI: http://eprints.soton.ac.uk/id/eprint/440730
ISSN: 0733-8716
PURE UUID: aff3d5eb-93a5-40b1-be59-0567dc4e06fd
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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Date deposited: 14 May 2020 16:32
Last modified: 13 Aug 2022 01:32

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Contributors

Author: Tong Bai
Author: Cunhua Pan
Author: Yansha Deng
Author: Maged Elkashlan
Author: Arumugam Nallanathan
Author: Lajos Hanzo ORCID iD

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