Joint Cooperative Spectrum Sensing and MAC Protocol Design for Multi-channel Cognitive Radio Networks

TL;DR

This paper introduces a semi-distributed cooperative spectrum sensing and MAC protocol for multi-channel cognitive radio networks, optimizing throughput through sensing set selection and protocol parameter tuning.

Contribution

It presents a novel integrated framework combining cooperative sensing and MAC protocol design with algorithms for sensing set optimization to maximize throughput.

Findings

Optimized sensing and access parameters significantly improve throughput.

Greedy algorithms effectively approximate exhaustive search results.

The framework extends to account for reporting errors in sensing.

Abstract

In this paper, we propose a semi-distributed cooperative spectrum sen sing (SDCSS) and channel access framework for multi-channel cognitive radio networks (CRNs). In particular, we c onsider a SDCSS scheme where secondary users (SUs) perform sensing and exchange sensing outcomes with ea ch other to locate spectrum holes. In addition, we devise the p -persistent CSMA-based cognitive MAC protocol integrating the SDCSS to enable efficient spectrum sharing among SUs. We then perform throughput analysis and develop an algorithm to determine the spectrum sensing and access parameters to maximize the throughput for a given allocation of channel sensing sets. Moreover, we consider the spectrum sensing set optimization problem for SUs to maxim ize the overall system throughput. We present both exhaustive search and low-complexity greedy algorithms to determine the sensing sets for SUs and analyze their complexity. We also show how our design and analysis can be extended to consider reporting errors. Finally, extensive numerical results are presented to demonstrate the sig nificant performance gain of our optimized design framework with respect to non-optimized designs as well as the imp acts of different protocol parameters on the throughput performance.