Improving capacity in cellular mobile networks through hybrid channel allocation

Abstract

Mobile computing has found increased applications and gained importance in last few years. In modern cellular radio systems, the number of subscribers is likely to grow rapidly. Increasing the capacity of these systems, i.e., the number of users per unit area that can be managed at some predefined level of service quality, is of vital importance. In such environments, the limited frequency spectrum allocated for cellular communication is divided into a finite number of wireless channels. An efficient channel allocation strategy should take advantage of the principle of frequency reuse to increase the availability of wireless channels to support calls and improve the capacity of the network. Lot of research has been done to allocate wireless channels for communication sessions, to provide optimum bandwidth for cellular communication that is limited and small, but further research needs to be done to find more efficient algorithm. The purpose of this research is to design and implement efficient methods and algorithms in channel allocation. To achieve this, a new strategy in channel allocation schemes is proposed. An agent approach has been used to make dynamic decision and do the computation in the remote destination, in order to reduce the network traffic and efficiency of resource allocation. Vertical layered agent architecture (INTERRAP) has been chosen that fits our requirements of concurrency, robustness, intelligence, and distribution. The architecture is having three vertical control layers i.e. behavior-based or reactive layer, local planning layer, cooperative planning layer, and each layer is defined to perform a specific task. The Reactive layer allocates channels to the new as well as to the handoff calls. A new channel allocation algorithm has been designed for this layer. Channel re-allocation based on signal-to-noise ratio computations is done by the Local planning layer. The Co-operative planning layer performs the load balancing of the entire network.