5G New Radio Resource Allocation Optimization for Heterogeneous Services

Abstract

5G new radio (NR) introduced flexible numerology to provide the necessary flexibility for multiplexing the communication of heterogeneous services on a shared channel. One of the fundamental challenges of 5G NR is to develop resource allocation schemes to efficiently exploit such flexibility to optimize resource allocation of ultra-reliable low-latency communications (URLLC) in coexistence with enhanced mobile broadband (eMBB) while ensuring their colliding performance requirements. This problem of 5G NR resource allocation to URLLC services coexisted with eMMB services is an NP -hard problem. We present a new formulation of this problem by considering the interplay of eMBB and URLLC services’ constraints and targets. The objective of the formulated problem is to probabilistically meet quality of service (QoS) requirements of both eMBB and URLLC services when the optimal global solution is infeasible. To this end, we express the problem as an integer linear programming problem and consider two formulations with hard and soft URLLC throughput constraints. The overall problem is then treated as a specific instance of bin packing optimization, whose objective is to minimize the placements of URLLC services. We apply a greedy resource allocation algorithm to provide a near-optimal solution in polynomial-time to this problem. Finally, we numerically evaluate the optimal solutions of the two different formulations. Performance results demonstrate and confirm that the proposed 5G NR resource allocation solutions can provide efficient resource utilization while satisfying the performance requirements of the eMBB and URLLC services.