Multi-objective MTC device controller resource optimization in M2M communication

Abstract

Machine to machine (M2M) communication has received increasing attention in recent years. It exhibits features such as large number of devices and low data rates. In order to accommodate massive, energy efficient M2M traffic and to reduce the access delay and signalling overhead, the recommendation is to introduce a clustered network structure. In this effort, we consider machines (or devices) in a macro cell divided into clusters. The machines belonging to a cluster communicate to the cluster head/controller, which then aggregates the traffic and relays to the eNB. Unlike related work that focuses on formation of clusters and their energy consumption, in this paper we investigate the multi-objective optimization problem of throughput maximization and power control of cluster heads in interference-limited M2M communication. Our objective is to maximize the number of admitted MTC device controllers with least interference caused to conventional (human) devices such that their quality of service (QoS) is not affected by the M2M communications. To maximize the number of machines that can communicate while meeting the interference constraints of human devices and machines themselves, we formulate a mixed-integer non-linear programming (MINLP) problem. OPTI toolbox is used to optimize the power, capacity and maximum number of admitted machines collectively.