Solution to the problem of optimum base station positioning with coverage, capacity and cost criteria. The optimization problem is tackled using both combinatorial and genetic algorithms.
Multi-objective genetic algorithms are employed.
- heterogeneous networks
- large geographical areas
- high capacity demands
- antenna pattern reconfiguration
- green planning
Example: Test planning scenario targeting an area of 2.5Km x 2.5Km with throughput requirement approximately 18.5Mbps/Km2.
The optimization algorithm provides an optimum network architecture along with suitable base-station antenna patterns. The capacity requirement is always met but the user can choose the criterion to be optimized, i.e. cost or power.
|Minimum Cost||Minimum Power|