Joint Latency Minimization and Power Allocation for MEC-Enabled MU-MISO Networks

This study investigates the Quality of Experience (QoE) for the user equipment (UE) at the network edge in a multi-user multiple-input single-output (MU-MISO) system. In this paper, a novel edge computing model which involves both offloading and local execution time is first introduced. Then we formulate a QoE fairness problem, aiming to minimize the system computational latency. To tackle this optimization challenge, we propose an approach based on convex approximation that accounts for constraints related to offloading ratios and power allocation. Finally, we present numerical findings that validate our theoretical framework and showcase the effectiveness of the proposed algorithm.