Genetic algorithm optimization of wireless communication networks

The proliferation of wireless communication networks, particularly low cost configurations, has brought with it a natural interest in network optimization. Specifically, the low cost emphasis in many modern wireless networks often places severe constraints on the acceptable level of transceiver processing circuitry complexity. Available transmitter power is also often at a premium in these modern networks. The solution to the design problem therefore usually requires significant optimization coupled with network simulation. The paper considers the synthesis of a 2-D network of N transceiver nodes with a known spatial distribution using a genetic algorithm optimization method. Each of the nodes consists of a relatively simple a transceiver (antennas, a receiver and a transmitter) in which only limited adjustments of antenna pattern and transmission power level are available. The goal of the optimization is to maximize nodal signal to noise ratios (SNR) while minimizing the transmitter power levels.