Base Station and Relay Station Broadband Network Planning Using Immune Quantum Evolutionary Algorithm
In this paper, we present simultaneous planning technique for Base Stations (BSs) and Relay Stations (RSs) for a broadband wireless network while taking data flow also known as link flow into consideration. Infrastructure cost (BS cost, RS cost and their operational costs) of a wireless network proves to be a key factor for network service providers while planning a network. The objective of this study is to help determine the set of BSs and RSs that can serve all the subscribed users and fulfill their demands at the lowest cost to the utility firm. This problem setup can be used for laying new networks as well as enhancing the already existing ones. The combinatorial optimization problem at hand is NP-hard in nature. We formulate this problem as a non-linear discrete optimization problem and compare two recent Evolutionary Algorithms (EAs) in providing approximate solution to this problem. The Quantum Inspired Evolutionary Algorithm (QEA) is a probabilistic algorithm based on quantum computing with the concept of qubits and superposition of states. The Immune theory based Immune Quantum Evolutionary Algorithm (IQEA) adopts immune operator to raise the fitness and prevent deterioration during the evolutionary process. Simulation results show better performance of IQEA as compared to QEA.