Along with spectral efficiency (SE), energy efficiency (EE) is a key performance metric for the design of 5G and beyond 5G (B5G) wireless networks. At the same time, infrastructure sharing among multiple operators has also emerged as a new trend in wireless communication networks. This paper presents an optimization framework for EE and SE maximization in a network, where radio resources are shared among multiple operators. We define a heterogeneous service level agreement (SLA) framework for a shared network, in which the constraints of different operators are handled by two different multi-objective optimization approaches namely the utility profile and scalarization methods. Pareto-optimal solutions are obtained by merging these approaches with the theory of generalized fractional programming. The approach applies to both noise-limited and interference-limited systems, with single-carrier or multi-carrier transmission. Extensive numerical results illustrate the effect of the operator specific SLA requirements on the global spectral and EE. Three network scenarios are considered in the numerical results, each one corresponding to a different SLA, with different operator-specific EE and SE constraints.
Energy-Spectral Efficiency Tradeoffs in 5G Multi-Operator Networks with Heterogeneous Constraints
Zappone A.
2017-01-01
Abstract
Along with spectral efficiency (SE), energy efficiency (EE) is a key performance metric for the design of 5G and beyond 5G (B5G) wireless networks. At the same time, infrastructure sharing among multiple operators has also emerged as a new trend in wireless communication networks. This paper presents an optimization framework for EE and SE maximization in a network, where radio resources are shared among multiple operators. We define a heterogeneous service level agreement (SLA) framework for a shared network, in which the constraints of different operators are handled by two different multi-objective optimization approaches namely the utility profile and scalarization methods. Pareto-optimal solutions are obtained by merging these approaches with the theory of generalized fractional programming. The approach applies to both noise-limited and interference-limited systems, with single-carrier or multi-carrier transmission. Extensive numerical results illustrate the effect of the operator specific SLA requirements on the global spectral and EE. Three network scenarios are considered in the numerical results, each one corresponding to a different SLA, with different operator-specific EE and SE constraints.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
