Self-optimising intelligent distributed antenna system for geographic load balancing

Increase in number of mobile users, generates unbalanced load traffic in wireless network. In this study, a load-balancing solution is investigated in order to optimise quality of service. An intelligent distributed antenna system (IDAS) fed by a base transceiver station (BTS) has the ability to distribute the cellular capacity over a given geographic area depending on the time-varying traffic. A virtual cell network is an IDAS with capacity routing capability. To enable load balancing among distributed antenna modules, the authors dynamically allocate the remote antenna modules to the BTS sectors. A self-organised network of virtual cells is formulated as an optimisation problem, which attempts to balance traffic load and minimises the hand-offs as two important cost factors in the network. Two evolutionary algorithms are proposed for optimisation: genetic algorithm and estimation distribution algorithm. Computational results of different traffic scenarios after performing the algorithms, demonstrate that the two algorithms attain excellent key performance indicators for small-scale networks.