Mobile Edge Computing Meets mmWave Communications: Joint Beamforming and Resource Allocation for System Delay Minimization

• Published in: IEEE transactions on wireless communications Vol. 19; no. 4; pp. 2382 - 2396
• Main Authors: Zhao, Cunzhuo, Cai, Yunlong, Liu, An, Zhao, Minjian, Hanzo, Lajos
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Array signal processing; Beamforming; Cloud computing; Computation offloading; Delay; Delays; distributed implementation; Edge computing; hybrid beamforming; Mathematical analysis; Matrix methods; Millimeter wave; Millimeter wave communication; Millimeter waves; Mobile computing; mobile edge computing; Optimization; Resource allocation; Resource management; Servers; Task analysis; Wireless networks
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2020.2964543

Mobile edge computing (MEC) has been identified as a key technique of next-generation wireless networks, which supports cloud computing along with other compelling service capabilities at the network's edge with the objective of reducing the system delay. As one of the prospective candidates for new spectrum in next-generation networks, millimeter wave (mmWave) communications has been gaining significant attention as a benefit of its high rate. Hence we conceive a joint hybrid beamforming and resource allocation algorithm for mmWave MEC. Explicitly, we jointly optimize the analog beamforming vectors at the users, the analog and digital beamforming matrices at the base station (BS), the computation task offloading ratios and resource allocation at the MEC server for minimizing the maximum system delay subject to the affordable communication and computing budget. We conceive a powerful algorithm for solving this challenging nonconvex optimization problem with coupled constraints based on the penalty dual decomposition (PDD) technique. The proposed algorithm can be implemented in a parallel and distributed fashion. Our numerical results demonstrate the superiority of the proposed algorithm by quantifying the benefits of intrinsically amalgamating MEC with mmWave communications.