Energy Efficient Communication and Computation Resource Slicing for eMBB and URLLC Coexistence in 5G and Beyond

Abstract

Multi-access edge computing (MEC) enables mobile users to offload their computation tasks to the server located at the edge of the cellular network. Thereby, MEC prolongs the battery lifespan of mobile devices and significantly enhances their computation capacities. However, a significant challenge is to offload the computation tasks to the MEC server in an energy-efficient manner. Meanwhile, in the fifth-generation (5G) networks, mobile users with different service requirements classified as enhanced mobile broadband (eMBB) and ultra-reliable low-latency communications (URLLC) users will coexist in the current cellular network. Therefore, it is important to appropriately multiplex these users in the cellular network. In this work, we address the issues of these two promising technologies together. Firstly, we formulate an energy-efficient task offloading, and scheduling of eMBB and URLLC users as a mixed-integer non-linear problem. Then, we decompose the problem into multiple sub-problems in order to transform into convex form and alternately solve them until converging to the desired solutions by using the block coordinate descent (BCD) algorithm. Finally, we demonstrate numerical results to prove the superior effectiveness in the performance of our proposed algorithm over classical existing schemes.

Keywords

• Multi-access edge computing (MEC)
• resource slicing
• eMBB-URLLC coexistence
• block coordinate descent (BCD)