  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.
