Spectrum Sensing Strategy to Enhance the QoS in White-Fi Networks

TL;DR

This paper proposes an adaptive spectrum sensing strategy for White-Fi networks that improves QoS by dynamically adjusting sensing parameters based on application requirements, demonstrated through simulation results.

Contribution

It introduces a novel adaptive sensing strategy tailored to IEEE 802.11e, enhancing QoS in White-Fi networks by optimizing spectrum sensing processes.

Findings

Adaptive sensing improves QoS metrics significantly.

Simulation shows better spectrum utilization with the proposed method.

Enhanced QoS for applications in White-Fi networks.

Abstract

The rapidly growing number of wireless devices running applications that require high bandwidths, has resulted in increasing demands for the unlicensed frequency spectrum. Given the scarcity of allocated unlicensed frequencies, meeting such demands can become a serious concern. Cognitive Radio (CR)technology opens the door for the opportunistic use of the licensed spectrum to partially address the issues relevant to the limited availability of unlicensed frequencies. Combining CR and Wi-Fi to form the socalled White-Fi networks, has been proposed for achieving higher spectrum utilization. This article discusses the spectrum sensing in White-Fi networks and the impacts that it has on the QoS of typical applications. It also reports the analysis of such impacts through various simulation studies. Our results demonstrate the advantages of an adaptive sensing strategy that is capable of changing the related parameters based on QoS requirements. We also propose such a sensing strategy that can adapt to the IEEE 802.11e requirements. The goal of the proposed strategy is the enhancement of the overall QoS of the applications while maintaining efficient sensing of the spectrum. Simulation results of the scenarios that implement the proposed mechanisms demonstrate noticeable QoS improvements compared to cases where common sensing methods are utilized in IEEE802.11 networks.