Abstract
Radio networks of universal mobile telecommunication system (UMTS) need accurate planning and optimisation, and many factors not seen in second generation (2G) networks must be considered. However, planning and optimisation of UMTS radio networks are often carried out with static simulations, for efficiency and to save time. To obtain a good trade-off between accuracy and computational load, link-level performance factors need to be taken into account. The authors propose a mathematical model for UMTS radio network planning taking into consideration fast power control, soft handover and pilot signal power in both uplink and downlink. Optimisation strategies are investigated based on three meta-heuristics: genetic algorithm, simulated annealing (SA) and evolutionary-SA. The base station location problem is modelled as a simplified p-median problem, and parameter tuning of these meta-heuristics are presented. Extensive experimental results are used to compare the performance of different algorithms in terms of statistical measurements.
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