Cost efficient 5G heterogeneous base station deployment using meta-heuristics

Abstract

Over the last two decades, the telecommunication industry has witnessed sustained growth in the number of mobile user devices driven by the introduction of data services, the take-off of the internet and smart user equipment. This growth, which is forecasted to continue, has continued to push the data transfer capacity requirement on mobile networks and has motivated research into the design of 5th generation (5G) mobile networks. A key concern in the design of 5G is the infrastructure and power consumption cost of the base station network which is expected to be significantly more advanced and dense than that of existing conventional mobile networks. This thesis presents an optimisation framework for the cost efficient design of 5G base station networks, based on the application of meta-heuristic algorithms. The presented optimisation framework is centred on the ability to exploit three key technologies of 5G, a heterogonous base station network with small-cells, multi-antenna spatial multiplexing MIMO and cell range extension. The framework includes mathematical integer programming models for supporting the decisions about the optimal base station topology in a 5G mobile network and provides a clear core for the application of meta-heuristics for optimising 5G base station deployment. The core optimisation framework includes the definition of solution encoding/decoding and fitness mechanisms. To increase power consumption awareness of base station network design, an independent base station deployment strategy has been presented and evaluated. Simulation results show that the strategy can improve base station network design power consumption by as much as 34%. The work in this thesis has been extensively evaluated using a simulated 5G mobile network system model. Evaluations of algorithms have been performed through empirical measurements. The main contribution of this thesis is the definition of a clear framework for application fitness based heuristic search in the design of 5G mobile networks.