Maximum connectivity-based channel allocation algorithm in cognitive wireless networks for medical applications

Abstract

With the advent of multimedia and pattern recognition based medical technology, intelligence medical applications in smart hospital, smart clinic, and smart medical for Individual, such as disease diagnosis, rehabilitation, health monitoring, and so on, have received extensive attentions. However, the communication infrastructure of supporting these applications is facing a larger challenge. This paper studies the channel allocation problem in cognitive wireless networks for these medical applications. Channel allocations are of importance for cognitive wireless networks. How to assign the appropriate channels to each cognitive user is fairly challenging. In this paper we study this problem by combining collaborations of network nodes. We take the maximum network connectivity as an optimal objective to build our collaborative channel allocation model. Our approach takes in account the channel idle status and the transmission radiuses of cognitive users. We allocate firstly the idle channel to bottleneck node and assign the suited channels to all other cognitive users as possible. In such a way, we present three channel allocation strategies with the maximum network connectivity via the omni-directional and direction antennas. We also propose the corresponding algorithm to perform the channel allocation for all cognitive users in cognitive wireless networks. Simulation results show that our approach is promising.