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Maximizing rendezvous diversity in rendezvous protocols for decentralized cognitive radio networks
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Maximizing rendezvous diversity in rendezvous protocols for decentralized cognitive radio networks

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  • 1. Maximizing Rendezvous Diversity in Rendezvous Protocols for Decentralized Cognitive Radio Networks Abstract In decentralized cognitive radio (CR) networks, establishing a link between a pair of communicating nodes requires that the radios "rendezvous” in a common channel-such a channel is called a rendezvous channel-to exchange control information. When unlicensed (secondary) users opportunistically share spectrum with licensed (primary or incumbent) users, a given rendezvous channel may become unavailable due to the appearance of licensed user signals. Ideally, every node pair should be able to rendezvous in every available channel (i.e., maximize the rendezvous diversity) so that the possibility of rendezvous failures is minimized. Channel hopping (CH) protocols have been proposed previously for establishing pair wise rendezvous. Some of them enable pair wise rendezvous over all channels but require global clock synchronization, which may be very difficult to achieve in decentralized networks. Maximizing thepairwise rendezvous diversity in decentralized CR networks is a very challenging problem. In this paper, we present a systematic approach for designing CH protocols that maximize the rendezvous diversity of any node pair in decentralized CR networks. The resulting protocols are resistant to rendezvous failures caused by the appearance of primary user (PU) signals and do not require clock synchronization. The proposed approach, called asynchronous channel hopping (ACH), has two noteworthy features: 1) any pair of CH nodes are able to rendezvous on every channel so that the rendezvous process is robust to disruptions caused by the appearance of PU signals; and 2) an upper bounded time-to-rendezvous (TTR) is guaranteed between the two nodes even if their clocks are asynchronous. We propose two optimal ACH designs that maximize the rendezvous diversity between any pair of nodes and show their rendezvous performance via analytical and simulation results.