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. F...

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Vydané v:	IEEE journal on selected areas in communications Ročník 38; číslo 11; s. 2666 - 2682
Hlavní autori:	Bai, Tong, Pan, Cunhua, Deng, Yansha, Elkashlan, Maged, Nallanathan, Arumugam, Hanzo, Lajos
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.11.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Antennas Edge computing Electronic devices Intelligent reflecting surface Iterative algorithms Iterative methods latency minimization Minimization Mobile computing mobile edge computing Mobile handsets Optimization Phase shift Propagation Reconfigurable intelligent surfaces Resource management Task analysis Wireless communication
ISSN:	0733-8716, 1558-0008
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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.
AbstractList	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.
Author	Deng, Yansha Elkashlan, Maged Hanzo, Lajos Bai, Tong Pan, Cunhua Nallanathan, Arumugam
Author_xml	– sequence: 1 givenname: Tong orcidid: 0000-0002-2607-3561 surname: Bai fullname: Bai, Tong email: t.bai@qmul.ac.uk organization: School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K – sequence: 2 givenname: Cunhua orcidid: 0000-0001-5286-7958 surname: Pan fullname: Pan, Cunhua email: c.pan@qmul.ac.uk organization: School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K – sequence: 3 givenname: Yansha orcidid: 0000-0003-1001-7036 surname: Deng fullname: Deng, Yansha email: yansha.deng@kcl.ac.uk organization: Department of Engineering, King's College London, London, U.K – sequence: 4 givenname: Maged orcidid: 0000-0002-5168-0160 surname: Elkashlan fullname: Elkashlan, Maged email: maged.elkashlan@qmul.ac.uk organization: School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K – sequence: 5 givenname: Arumugam orcidid: 0000-0001-8337-5884 surname: Nallanathan fullname: Nallanathan, Arumugam email: a.nallanathan@qmul.ac.uk organization: School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K – sequence: 6 givenname: Lajos orcidid: 0000-0002-2636-5214 surname: Hanzo fullname: Hanzo, Lajos email: lh@ecs.soton.ac.uk organization: School of Electronics and Computer Science, University of Southampton, Southampton, U.K
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ContentType	Journal Article
Copyright	Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020
Copyright_xml	– notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020
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Snippet	Computation off-loading in mobile edge computing (MEC) systems constitutes an efficient paradigm of supporting resource-intensive applications on mobile...
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SubjectTerms	Antennas Edge computing Electronic devices Intelligent reflecting surface Iterative algorithms Iterative methods latency minimization Minimization Mobile computing mobile edge computing Mobile handsets Optimization Phase shift Propagation Reconfigurable intelligent surfaces Resource management Task analysis Wireless communication
Title	Latency Minimization for Intelligent Reflecting Surface Aided Mobile Edge Computing
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