EFFICIENT DISTRIBUTED RENDEZVOUS SCHEMES AND SPECTRUM MANAGEMENT FOR COGNITIVE RADIO NETWORKS
1 online resource (154 pages) : PDF
University of North Carolina at Charlotte
Cognitive radio emerges as a technology to realize the dynamic spectrum access bydynamically configuring its transmission parameters. In a cognitive radio network(CRN), there are two types of users: primary users (PUs) and secondary users (SUs).PUs are the licensed users or the traditional wireless users who can access a specificlicensed spectrum band. SUs are the unlicensed users equipped with cognitive radiosthat can opportunistically use currently unoccupied channels to transmit, but haveto vacate channels for the returning PUs, and then switch to other available channelsfor continuous transmissions. When two SUs want to establish a link, they have tomeet on the same channel that must be available for both of them simultaneously.This process is called rendezvous.Past research works on rendezvous only focused on designing the channel hoppingsequence for the rendezvous process while ignoring some practical problems likerendezvous in wide-band CRNs, rendezvous without a predetermined sender and receiver,rendezvous considering directional antennas, and how to maximize the numberof common available channels. In this dissertation, we propose five schemes to realizeefficient rendezvous and spectrum management considering these practical problemsunder different scenarios. We first propose a rendezvous and communicationframework for wide-band CRNs. Furthermore, we propose two efficient rendezvousschemes without predetermined sender and receiver. Moreover, we propose a rendezvousscheme specifically for SUs equipped with directional antennas. Last, wepropose a power control protocol to maximize the number of common available channels.All of the proposed schemes can realize both efficient rendezvous and spectrummanagement with practical assumptions under different scenarios.
COGNITIVE RADIORENDEZVOUSWIRELESS NETWORKING
Xie, JiangHan, TaoWang, YuHong, Keejae
Thesis (Ph.D.)--University of North Carolina at Charlotte, 2017.
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