Multi-Objective Energy-Efficient Resource Allocation for Multi-RAT Heterogeneous Networks

Abstract

Heterogeneous network (HetNet) integrated with multiple radio access technologies (RATs) is a promising technique for satisfying the exponentially increasing traffic demand of future cellular systems. In this paper, we investigate energy-efficient resource allocation in a multi-RAT HetNet, aimed at maximizing the energy efficiency (EE) for each individual user while guaranteeing the quality-of-service (QoS) requirement. Since the EE cannot be simultaneously maximized for every user, a multiple-objective optimization problem (MOOP) is formulated. To find its Pareto optimal solution, we first introduce the concept of Utopia EE, defined as the maximum achievable EE, for each user. Then, using the weighted Tchebycheff method, a single-objective optimization problem (SOOP) is formulated, which can achieve Pareto optimal solution of the original MOOP. The SOOP is a generalized fractional programming problem that aims to minimize the maximum of several quasiconvex fractional functions. We further transform the problem into an equivalent but better tractable one, and develop an iterative algorithm to effectively solve it. Numerical results demonstrate that the proposed algorithm yields fast convergence, high system EE, and flexible EE tradeoff.