Rendezvous in Heterogeneous Cognitive Radio Networks
Rendezvous is a fundamental and important process in operating a distributed system, which can be applied in many distributed applications running on the system. In this chapter, we introduce the rendezvous process in a special type of cognitive radio net
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Rendezvous in Heterogeneous Cognitive Radio Networks
Abstract Rendezvous is a fundamental and important process in operating a distributed system, which can be applied in many distributed applications running on the system. In this chapter, we introduce the rendezvous process in a special type of cognitive radio network: Heterogeneous Cognitive Radio Network (HCRN) where different users have different capabilities to sense the licensed spectrum. Many elegant rendezvous algorithms have been proposed by constructing sequences based on the channels’ labels [1, 3, 7, 8, 10] or their identifiers (IDs) [2, 4, 5], and rendezvous can be guaranteed in a short time based on the special hopping sequences constructed. However, they all assume the users have the capability to sense and access all the licensed channels, which is unrealistic when the number of channels (N ) is very large and some wireless devices may only operate on a small fraction of the channels. Therefore, HCRN is proposed, in which the users may have different spectrum-sensing capabilities. We introduce the system model and formulate the problem in Sect. 17.1. Rendezvous algorithms for the fully available spectrum are presented in Sect. 17.2, and rendezvous algorithms for the partially available spectrum are introduced in Sect. 17.3. Finally, we summarize the chapter in Sect. 17.4.
© Springer Nature Singapore Pte Ltd. 2017 Z. Gu et al., Rendezvous in Distributed Systems, DOI 10.1007/978-981-10-3680-4_17
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17 Rendezvous in Heterogeneous Cognitive Radio Networks
17.1 Preliminaries We first introduce the system model of heterogeneous cognitive radio network (HCRN) and its difference with traditional cognitive radio network. Then, we define the rendezvous problem in the context of HCRN and show the challenges of designing efficient rendezvous algorithms for this kind of CRN.
17.1.1 System Model The licensed spectrum is assumed to be divided into N non-overlapping channels: U = {1, 2, . . . , N }
(17.1)
Each user (here we mean secondary users) is equipped with a cognitive radio to sense the licensed spectrum. We say a channel is available for the user if it is not occupied by any nearby primary users (PUs) who own these licensed channels. Actually, the users may have different spectrum sensing capabilities and suppose user i can sense a set of continuous channels: Ci = {cx , cx+1 , . . . , cx+ki −1 } ⊆ U
(17.2)
which is assumed in [11, 12], where cx is the starting channel and ki = |Ci |, 1 ≤ x ≤ N − ki + 1. The channels in set Ci are either occupied by nearby PUs or available for the (secondary) user i. We denote: (17.3) Vi ⊆ Ci as the set of all available channels after the spectrum sensing stage. Time is also assumed to be divided into slots of equal length 2t, where t is sufficient for establishing a communication link if the users access the same channel at the same time slot. According to the IEEE 802.22 [9], t is often set to be 10 ms. The intuitive idea of setting each time slot to be 2t is to ensure that an overlap of t exists for link
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