A joint local-global technique for wireless mobile network planning and optimization

With the exponential growth in the number of mobile subscribers and applications, optimal allocation of limited resources such as bandwidth, power, code, time slot, etc., become necessary. To achieve this, the Telecom Operators need to improve the usage of their existing deployment as well as to plan for appropriate capacity. This can be realized through optimal Radio Frequency (RF) planning, deployment of Base Stations (BSs) and determination of appropriate network parameters. Since optimal RF planning and optimization is an NP-hard complex problem, we propose a simple and robust joint optimization technique using Clustering and Cooperative Game Theory approaches. Ours is a practical, easy to use, less complex real-time solution. This can not only improve the network coverage with desired Quality of Experience, but also can reduce the CAPEX and OPEX of the telecom operators. We demonstrate the usability of our solution through two different use cases and suggest that it can be used for planning new networks and optimizing existing networks.