  Network slicing allows 5G network operators to provide service to multiple
tenants with diverging service requirements. This paper considers network
slicing aware optimal resource allocation in terms of throughput and energy
efficiency. We define a heterogeneous Quality of Service (QoS) framework for a
sliced radio access network network with per-slice zero-forcing beamforming and
jointly optimize power and bandwidth allocation across slices and users. The
Pareto boundary of this multi-objective optimization problem is obtained by two
different algorithms based on the utility profile and scalarization approaches
combined with generalized fractional programming. Numerical results show the
merits of jointly allocating bandwidth and transmission power and how
throughput and global energy efficiency are influenced by slice specific QoS
requirements.
