NOMA Power Minimization of Downlink Spectrum Slicing for eMBB and URLLC Users
This addresses power efficiency in 5G networks for heterogeneous services, but it is incremental as it applies existing methods to a specific scenario.
The paper tackles power minimization in 5G downlink spectrum slicing for eMBB and URLLC users by comparing NOMA and OMA strategies, showing that NOMA reduces power consumption across all tested simulation parameters.
Spectrum slicing of the shared radio resources is a critical task in 5G networks with heterogeneous services, through which each service gets performance guarantees. In this paper, we consider a setup in which a Base Station (BS) should serve two types of traffic in the downlink, enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC), respectively. Two resource allocation strategies are compared: non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA). A framework for power minimization is presented, in which the BS knows the channel state information (CSI) of the eMBB users only. Nevertheless, due to the resource sharing, it is shown that this knowledge can be used also to the benefit of the URLLC users. The numerical results show that NOMA leads to a lower power consumption compared to OMA for every simulation parameter under test.