Throughput and Energy-Efficient Network Slicing

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 with per-slice zeroforcing 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.