Power Minimization of Downlink Spectrum Slicing for eMBB and URLLC Users
This addresses power efficiency in 5G networks for operators and users, but it is incremental as it builds on existing spectrum slicing and NOMA/OMA methods.
The paper tackles the problem of minimizing power consumption for downlink spectrum slicing in 5G networks serving eMBB and URLLC users, showing that NOMA generally leads to lower power than OMA except in specific high-gain URLLC cases where the gap is negligible.
5G technology allows heterogeneous services to share the wireless spectrum within the same radio access network. In this context, spectrum slicing of the shared radio resources is a critical task to guarantee the performance of each service. We analyze a downlink communication serving two types of traffic: enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC). Due to the nature of low-latency traffic, the base station knows the channel state information (CSI) of the eMBB users while having statistical CSI for the URLLC users. We study the power minimization problem employing orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) schemes. Based on this analysis, we propose a lookup table-based approach and a block coordinated descent (BCD) algorithm. We show that the BCD is optimal for the URLLC power allocation. The numerical results show that NOMA leads to lower power consumption than OMA, except when the average channel gain of the URLLC user is very high. For the latter case, the optimal approach depends on the channel condition of the eMBB user. Even when OMA attains the best performance, the gap with NOMA is negligible, showing the capability of NOMA to reduce power consumption in practically every condition.