Latency Minimization for Movable Antennas-Enabled Relay-aided D2D Mobile Edge Computing Communication Systems

作     者：Xiu, Yue Zhao, Yang Yang, Ran Tang, Huimin Qu, Long Khabbaz, Maurice Assi, Chadi Wei, Ning 

作者机构：National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China Chengdu611731 China Nanyang Technological University 50 Nanyang Ave Singapore639798 Singapore Cho Chun Shik Graduate School of Mobility Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China CMPS Department American University of Beirut Lebanon Concordia University MontrealQCH3G 1M8 Canada 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2024年

核心收录：

主　　题：Computation offloading 

摘      要：Device-to-device (D2D)-assisted mobile edge computing (MEC) is one of the critical technologies of future sixth generation (6G) networks. The core of D2D-assisted MEC is to reduce system latency for network edge UEs by supporting cloud computing services, thereby achieving high-speed transmission. Due to the sensitivity of communication signals to obstacles, relaying is adopted to enhance the D2D-assisted MEC system’s performance and its coverage area. However, relay nodes and the base station (BS) are typically equipped with large-scale antenna arrays. This increases the cost of relay-assisted D2D MEC systems and limits their deployment. Movable antenna (MA) technology is used to work around this limitation without compromising performance. Specifically, the core of MA technology lies in optimizing the antenna positions to increase system capacity. Therefore, this paper proposes a novel resource allocation scheme for MA-enhanced relay-assisted D2D MEC systems. Specifically, the MA positions and beamforming of user equipments (UEs), relay, and BS as well as the allocation of resources and the computation task offloading rate at the MEC server, all are optimized herein with the objective of minimizing the maximum latency while satisfying computation and communication rate constraints. Since this is a multivariable non-convex problem, a parallel and distributed penalty dual decomposition (PDD) based algorithm is developed and combined with successive convex approximation (SCA) to solve this nonconvex problem. The results of extensive numerical analyses show that the proposed algorithm significantly improves the performance of the MA-enhanced relay-assisted D2D communication system compared to a counterpart where relays and the BS are equiped with traditional fixed-position antenna (FPA). Copyright © 2024, The Authors. All rights reserved.