Channel Allocation in Wireless Communication using Genetic Algorithm

The demand for mobile communication has been steadily increasing in recent years. With the limited frequency spectrum, the problem of channel assignment becomes increasingly important, i.e., how do we assign the calls to the available channels so that the interference is minimized while the demand is met? This problem is known to belong to a class of very difficult combinatorial optimization problems. In this Dissertation, we apply the genetic algorithms to channel assignment problems. Interference-free solutions cannot be found for some of these problems; however, the approach is able to minimize the interference significantly. With the limited frequency spectrum, the channel assignment problem (CAP) i.e., to assign the calls to the available channels so that the interference is minimized while the demand is met, has become increasingly important. The Channel Assignment Problem is an NP-complete problem to assign a minimum number of channels under certain constraints to requested calls in a cellular radio system. Examples of the many approaches to solve this problem include using neural-networks, simulated annealing, graph coloring, genetic algorithms, and heuristic searches. The dynamic channel assignment (DCA) in mobile communications systems using genetic algorithm (GA) is investigated in this research. Two new strategies using GA are proposed. in the first one, the channels previously assigned are kept locked during the call holding time (GAL). In the second one, the calls can be switched to different channels during the connection time (GAS). This paper reviews the available schemes for channel allocation.