Computation Efficiency Optimization for RIS-Assisted Millimeter-Wave Mobile Edge Computing Systems

Yu, Xiangbin, Yu, Kai, Huang, Xu, Dang, Xiaoyu, Wang, Kezhi and Cai, Jiali (2022) Computation Efficiency Optimization for RIS-Assisted Millimeter-Wave Mobile Edge Computing Systems. IEEE Transactions on Communications, 70 (8). pp. 5528-5542. ISSN 0090-6778

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In this paper, we present the computation-efficient resource allocation (RA) schemes for millimeter-wave mobile edge computing (mmWave-MEC) system with the aid of reconfigurable intelligent surface (RIS), which is used to assist the uplink communication from the users to the base station (BS). By means of the theoretical analysis, the achievable rate and computation efficiency (CE) are derived. Then, the optimization problem for the CE maximization under the constraints of the minimum rate, maximum power consumption and local CPU frequency is formulated, where the joint design of the hybrid beamforming at the BS and the passive beamforming at the RIS as well as the local resource allocation of each user is carried out. An effective iterative algorithm based on the penalized inexact block coordinate descent (BCD) method is proposed to obtain the computation-efficient RA scheme. Next, a low-complexity suboptimal RA scheme based on the BCD method is proposed, and corresponding algorithm is presented. Simulation results show that the proposed schemes are effective, and high CE can be attained. Moreover, the second scheme can achieve the CE performance close to the first scheme but with lower complexity. Besides, it is effective to deploy the RIS scheme in mmWave-MEC system, which can strike a balance between the CE and energy consumption when compared to the conventional relay schemes.

Item Type: Article
Additional Information: Funding information: 10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61971220)
Uncontrolled Keywords: Millimeter-wave communication, computation efficiency, hybrid beamforming, mobile edge computing, reconfigurable intelligent surface
Subjects: G400 Computer Science
H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Rachel Branson
Date Deposited: 26 Sep 2022 10:44
Last Modified: 26 Sep 2022 10:45

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