An Iterative Power Regulation Technique in Emergency Cognitive Radio Network Based on Firefly Algorithm

Abstract

Background: Manmade disasters like explosion, toxic wastes, chemical spills etc. have become an imperative concern for our society. Manmade disasters are not everyday phenomenon. Thus, the allocation of separate resources is not realistic. The idea is to use existing cellular infrastructure to implement single hop cognitive radio sensor network for protecting human being from manmade disasters. Objective: The main objectives of this paper are as follows: (a) design of an efficient iterative power regulation algorithm based on the Firefly Algorithm for the proposed network, (b) computation of sensor nodes’ optimal power for different position of the cellular user from the base station assuming that cellular user compromises power for its own sensor node, (c) computation of the maximum number of sensor nodes coupled with single cellular user for different distances from the base station in worst channel condition, and (d) comparative performance analysis with state-of-the-art algorithms. Method: In the presence of explosive and toxic gases, cognitive radio in sensor node establishes a connection with the nearest base station to send pre-disaster alert signal utilizing cellular user’s resources. The power is distributed among sensor nodes maintaining the fundamental requirements of cellular users. Here, an iterative power regulation mechanism is employed for distributing the power between sensor node and cellular user to achieve reliable utility of the network. The fitness function is designed under the constraints of interference and the designed algorithm is implemented in MATLAB platform towards the search of optimal power of sensor nodes by maximizing the fitness function. Results: Comparative performance analysis demonstrates the effectiveness of the proposed algorithm in terms of speed of convergence, the position of mobile phone user from the base station, number of coupled sensor nodes with single cellular user, and Jain’s fairness factor. Conclusion: The proposed network controls the occurrence of manmade disasters and achieves reliable transmission of emergency information prior to disaster without disrupting cellular phone users. Simulation results validate that the proposed IPRFA algorithm outperforms with respect to state-ofthe- art methods in terms of sharing power and Jain’s fairness factor.