Resource Allocation for Multi-access Edge Computing with Coordinated Multi-Point Reception

Abstract

Multi-access edge computing (MEC) has emerged as a promising platform to provide user equipment (UEs) with timely computational services through the deployed edge servers. Typically, the size of an uplink task data (e.g., images or videos) required for processing is more pronounced than that of a downlink task result, and hence MEC offloading (MECO) plays a decisive role in the efficiency of MEC systems. In the light of an unprecedented growth of UEs in next-generation mobile networks, the reception of uplink signals at base stations (BSs) can be corrupted due to potential inter-user interference. To address this issue, coordinated multi-point (CoMP) reception which enables BSs to cooperatively receive uplink signals has evolved as an effective approach to enhance the received signal qualities. In this paper, we investigate a resource allocation problem for MECO with CoMP reception and formulate it as a mixed-integer non-linear program (MINLP). To solve this problem, we leverage the concept of interference graphs to characterize uplink inter-user interference, based on which we propose a resource allocation algorithm that consists of three phases: 1) computing resource allocation, 2) subcarrier allocation and cell clustering, and 3) subcarrier reuse and cell re-clustering. The simulation results show that our proposed solution can effectively enhance the delay performance of MECO through CoMP reception as compared with existing solution approaches under various system settings.