Adaptive Quorum-Based Channel-Hopping Distributed Coordination Scheme for Cognitive Radio Networks

TL;DR

This paper introduces an adaptive, grid-based quorum channel-hopping algorithm for cognitive radio networks that dynamically adjusts to network conditions, significantly improving rendezvous success and reducing time and energy costs.

Contribution

It presents a novel adaptive quorum-based channel-hopping scheme that dynamically adjusts quorum selection based on traffic loads to enhance rendezvous efficiency in CRNs.

Findings

Reduces average time to rendezvous (TTR)

Increases probability of rendezvous (RDV)

Decreases energy consumption per successful RDV

Abstract

One of the most important challenges in deploying cognitive radio networks (CRNs) is to find a common control channel (CCC) to all secondary users (SUs) that enables efficient CR communications. This challenge is attributed to the dynamic time-varying change of network topology, location and spectrum availability conditions. Rendezvous, which is the process of establishing control communications, is an essential requirement to enable efficient communication between any two pair of CR nodes. The most popular CR rendezvous protocols are based on quorum systems (QSs). Quorum systems are systematic approaches, which have several attractive properties that can be utilized to establish communication without the need of a CCC and so overcome the rendezvous (RDV) problem. In this thesis, we propose new channel-hopping-based distributed rendezvous algorithm based on grid-based-quorum techniques. The proposed algorithm increases the probability of RDV within a single cycle by allowing CR nodes to meet more often according to intersection property of quorum systems. Our proposed algorithm is called Adaptive_Quorum-Based Channel-Hopping Distributed Coordination Scheme for Cognitive Radio Networks. The main idea of our algorithm is to dynamically adjusting the selected QS by CR users according to the varying traffic loads in the CRN. The proposed algorithm decreases the average time to rendezvous (TTR) and increase the probability of RDV. We evaluate the performance of our algorithm through Matlab simulations. The performance of proposed algorithm is compared with two different design scheme. The results show that our algorithm can reduce TTR, increase the RDV, and decrease the energy consumption per successful RDV.