Distributed Spectrum-Aware Clustering in Cognitive Radio Sensor Networks

TL;DR

This paper introduces a distributed clustering scheme for cognitive radio sensor networks that optimizes energy efficiency and minimizes interference with primary users through spectrum-aware, scalable, and stable clustering methods.

Contribution

The paper proposes a novel distributed spectrum-aware clustering algorithm (DSAC) that enhances energy efficiency and interference management in CRSN with low complexity and quick convergence.

Findings

DSAC effectively reduces communication power consumption.

The scheme demonstrates high scalability and stability.

Simulation results validate the performance improvements.

Abstract

A novel Distributed Spectrum-Aware Clustering (DSAC) scheme is proposed in the context of Cognitive Radio Sensor Networks (CRSN). DSAC aims at forming energy efficient clusters in a self-organized fashion while restricting interference to Primary User (PU) systems. The spectrum-aware clustered structure is presented where the communications consist of intra-cluster aggregation and inter-cluster relaying. In order to save communication power, the optimal number of clusters is derived and the idea of groupwise constrained clustering is introduced to minimize intra-cluster distance under spectrum-aware constraint. In terms of practical implementation, DSAC demonstrates preferable scalability and stability because of its low complexity and quick convergence under dynamic PU activity. Finally, simulation results are given to validate the proposed scheme.