Improving Energy Efficiency of Ultra-Reliable Low-Latency and Delay Tolerant Services in Mobile Edge Computing Systems

In the 5th generation communication systems, ultra-reliable low-latency communications (URLLC) will co-exist with delay tolerant services. Meanwhile, improving energy efficiency (EE) of mobile devices is an urgent task for prolonging battery lifetime. In this work, we study how to improve EE of mobile users with URLLC and delay tolerant services in a mobile edge computing (MEC) system. The normalized energy consumption, defined as the ratio of average power to the average data rate, is minimized by optimizing bandwidth allocation and offloading probabilities subject to the QoS requirements of both kinds of services. For URLLC services, the decoding error probability in the uplink transmission and the processing delay violation probability in the MEC server are considered. For delay tolerant services, the queues in both communication and computing systems should be stable. Although the problem is non-convex, we propose an algorithm to find the global optimal solution with low-complexity. Simulation results show that the optimal solution can achieve remarkable EE gain compared with baselines.