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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 multiantenna 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.
0733-8716
1-16
Bai, Tong
58cbdac7-1cea-4346-8fe2-70b4c9f2cc16
Pan, Cunhua
f7d52330-7fd8-42eb-8a5a-e094829a9fea
Deng, Yansha
66af8713-790e-4b21-a99a-1114ac762059
Elkashlan, Maged
27c756ff-bfd3-4844-8769-ace5ad28c840
Nallanathan, Arumugam
8accfa88-3b13-4cda-b080-0d247c6058e9
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Bai, Tong
58cbdac7-1cea-4346-8fe2-70b4c9f2cc16
Pan, Cunhua
f7d52330-7fd8-42eb-8a5a-e094829a9fea
Deng, Yansha
66af8713-790e-4b21-a99a-1114ac762059
Elkashlan, Maged
27c756ff-bfd3-4844-8769-ace5ad28c840
Nallanathan, Arumugam
8accfa88-3b13-4cda-b080-0d247c6058e9
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, 1-16. (In Press)

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 multiantenna 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

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

Catalogue record

Date deposited: 14 May 2020 16:32
Last modified: 13 Dec 2021 02:34

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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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