Performance analysis of random access policies in cognitive radio network

Abstract

Spectral resource demand has greatly increased in the last two decades due to newly emerging wireless services and products and accordingly all usable spectrum resources have been already allocated. However, recent actual measurements have shown that most of the allocated spectrum resources are underutilized. This discrepancy between allocation and usage leads to the introduction of cognitive radio (CR) networks. The CR concept represents a significant paradigm change in wireless spectrum utilization and regulation, i.e., from exclusive use of spectrum by licensed users (,called primary users) to dynamic spectrum access for unlicensed users (,called secondary users). The high potential of CR has attracted considerable efforts for more efficient spectrum management policies and techniques.

In this dissertation, we consider random channel access policies in a CR networks under various environments. Secondary users in a CR network stochastically determine whether to access a channel at each slot by using the access probability and then active secondary users select the channel among primary channels consulting the information on the network. Main results of this dissertation can be categorized into two subjects. The first one is developing the analytical models for the performances of users in a CR network. We analyze the queueing performance and throughput of an arbitrary SU under a various scenarios. And we obtain the optimal APs that maximizing the performance of an SU and provide an insight on how to optimally design in a CR network when SUs adopt random channel access policy.

In Chapter 2, we consider a time slotted cognitive radio network under Rayleigh fading where multiple secondary users (SUs) contend for spectrum usage over available primary users’ channels. We analyze the performance of a channel access policy where each SU stochastically determines whether to access a wireless channel or not based on a given access probability. In the analysis, we...