Energy efficient resource matching algorithm for multi-homing services in dynamic wireless environment

Abstract

This paper investigates the matching problem between radio resources and multi-homing services in a dynamic heterogeneous wireless environment. A mobile terminal with a multi-homing service simultaneously transmits data to multiple radio access networks using multiple air interfaces. This paper proposes an energy-efficient resource matching algorithm to statistically guarantee the service rate requirements of each user with the lowest power consumption. First, according to the concept of resource matching and the dynamic characteristics of wireless channels, this paper defines two matching probability metrics and subsequently selects the most appropriate metric to build a resource matching model to realize the maximum energy efficiency of each user while meeting the statistical guarantee constraints. In particular, the Rayleigh fading channel model is introduced in this paper to accurately reflect the dynamics of the wireless channel, and a complete expression of the matching probability metric is deduced. Second, according to the optimal solution characteristics of the optimization model, the original problem is decomposed into the inner power minimization problem and the outer matching probability maximization problem, and the convex optimization and the equality constrained optimization are separately used to solve the problem. Hence, the two-layer distributed solution algorithm is proposed. In particular, this paper conducts rigorous mathematical analyses on the convergence, optimality and complexity of the algorithm and constructs an improved resource matching model by relaxing the statistical guarantee parameters in the case of no solution to the model. Finally, the simulation results show that this algorithm has better performance than the three existing resource matching algorithms, can achieve lower user power consumption, and can realize the goal of the best match between the network resources and service requirements in a dynamic environment.