Joint Allocations of Radio and Computational Resource for User Energy Consumption Minimization Under Latency Constraints in Multi-Cell MEC Systems

This paper investigates the joint allocation of radio resources (i.e., base stations (BSs), sub-channels, and uplink transmission powers) and computational resources for a multi-cell mobile edge computing (MEC) system, aimed at minimizing the sum energy consumption of all mobile terminals under strict delay and signal-to-interference-plus-noise ratio (SINR) constraints. The problem is challenging to solve due to the highly coupled mixed-integer variables and the complicated expressions of the constraints. To tackle the difficulty, we decompose the problem into two sub-problems: the power and computational resource allocation sub-problem and the user-BS-subchannel association sub-problem. For the first sub-problem, we derive the optimal computational resource as a function of the optimal transmission power. Then the power optimization problem is distributed to each cell, and the local-optimal power solution within each cell is derived in closed-form expressions. For the second sub-problem, we design an optimal modified-cutting-plane (MCP) algorithm with exponential time-complexity. A polynomial-time near-optimal pivoting-and-subgradient (PS) algorithm is further proposed to reduce the complexity. Simulation results demonstrate that the PS algorithm achieves comparable performance to the optimal MCP algorithm, while they both outperform the benchmark schemes in most cases.