Optimized LTE cell planning for multiple user density subareas using meta-heuristic algorithms
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Communication Theory Lab
Permanent link to this recordhttp://hdl.handle.net/10754/564989
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AbstractBase station deployment in cellular networks is one of the most fundamental problems in network design. This paper proposes a novel method for the cell planning problem for the fourth generation 4G-LTE cellular networks using meta heuristic algorithms. In this approach, we aim to satisfy both coverage and cell capacity constraints simultaneously by formulating a practical optimization problem. We start by performing a typical coverage and capacity dimensioning to identify the initial required number of base stations. Afterwards, we implement a Particle Swarm Optimization algorithm or a recently-proposed Grey Wolf Optimizer to find the optimal base station locations that satisfy both problem constraints in the area of interest which can be divided into several subareas with different user densities. Subsequently, an iterative approach is executed to eliminate eventual redundant base stations. We have also performed Monte Carlo simulations to study the performance of the proposed scheme and computed the average number of users in outage. Results show that our proposed approach respects in all cases the desired network quality of services even for large-scale dimension problems.
Conference/Event name80th IEEE Vehicular Technology Conference, VTC 2014-Fall