Power Minimization of Downlink Spectrum Slicing for eMBB and URLLC Users
Fabio Saggese, Marco Moretti, Petar Popovski

TL;DR
This paper investigates power minimization in 5G downlink spectrum slicing for eMBB and URLLC services, comparing OMA and NOMA schemes, and proposes algorithms demonstrating NOMA's generally superior power efficiency.
Contribution
It introduces a lookup table and a BCD algorithm for power allocation, showing NOMA's effectiveness over OMA in spectrum slicing for heterogeneous 5G services.
Findings
NOMA generally reduces power consumption compared to OMA.
The BCD algorithm is optimal for URLLC power allocation.
Power savings with NOMA are negligible when URLLC channel gain is very high.
Abstract
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…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Advanced MIMO Systems Optimization · Sparse and Compressive Sensing Techniques
