Constraint satisfaction approach to improve capacity for indoor mobile network

The investments in indoor mobile networks are highly related to the spectrum availability and its associated approval options. The goal of this paper is to figure the physical network setup criteria for both wide and local area network deployment conditions. To produce the efficient output from the network, it is required to define network under defined constraints. These all constraint depends on type of network, its topology and the type of communication performed in that network. Constraint programming is the study of system which is based on constraints. The solution of a constraint satisfaction problem is a set of variable value assignments, which capture all members of the set of constraints in the CSP. In this paper the appliance of constraint satisfaction programming is used in predicting the signal processing in indoor topological environment. The distinct set of parameters such as distance (d), density, energy is used to define the constraints. The Branch and bound algorithm is used to optimize the constraint satisfaction problem. In this work, channel capacity will be figured out and then reduction of BER is predicted. The presented work will be performed on Ray-Leigh indoor propagation model.