Fully distributed algorithms for blind rendezvous in cognitive radio networks

Gu, Zhaoquan; Hua, Qiang-Sheng; Dai, Weiguo

doi:10.1145/2632951.2632981

Cited by 37 publications

(36 citation statements)

References 19 publications

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“…A-HCH yields a relatively shorter ETTR than HH while guaranteeing the maximum number of rendezvous channels. CBH [27] is another representative heterogeneous algorithm with only local channel information. CBH converts SUs' IDs into distinct bit strings, which are then utilized to guide rendezvous.…”

Section: A Pairwise Single-radio Rendezvous Algorithmsmentioning

confidence: 99%

“…However, both A-HCH and CBH rely on SUs' IDs to construct CH sequences, Table I compares several representative single-radio rendezvous algorithms in terms of MTTR. Here, N is the number of global channels; P is the smallest prime number not smaller than N ; N A and N B are the numbers of local available channels of SU A and SU B , respectively; G is the number of common available channels; l is the length of the choice sequence in A-HCH; ψ is the degree of the symmetrization class in A-HCH; P A and P B are the smallest prime numbers not smaller than N A and N B , respectively; p is equal to max{P A , P B }; l p is a constant determined by SUs' IDs (see [27] for details); and * denotes that the conclusion is only valid for some values of N (see [19] and [21] for details).…”

Section: A Pairwise Single-radio Rendezvous Algorithmsmentioning

confidence: 99%

“…We compare the proposed SSS algorithm with two representative GC algorithms termed SSB [20] and HS [23] as well as two representative LC algorithms termed A-HCH [26] and CBH [27]. Note that SSB and HS are originally designed for the asymmetric model, and we extend them to the heterogeneous model.…”

Section: A Pairwise Single-radio Scenariomentioning

confidence: 99%

“…In this scenario, we compare the proposed collaborative SSS algorithm with two representative multiuser algorithms termed DCH [23] and CBH [27]. Fig.…”

Section: Multiuser Single-radio Scenariomentioning

confidence: 99%

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Fully Distributed Channel-Hopping Algorithms for Rendezvous Setup in Cognitive Multiradio Networks

Yang

Liang

Zheng

et al. 2016

IEEE Trans. Veh. Technol.

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Abstract-Channel rendezvous is a vital step to form a cognitive radio network (CRN). It is intractable to guarantee rendezvous for secondary users (SUs) within a short finite time in asynchronous, heterogeneous, and anonymous CRNs. However, most previous heterogeneous algorithms rely on explicit SUs' identifiers (IDs) to guide rendezvous, which is not fully distributed. In this paper, we exploit the mathematical construction of sunflower sets to develop a single-radio sunflower set (SSS)-based pairwise rendezvous algorithm. We propose an approximation algorithm to construct disjoint sunflower sets. Then, the SSS leverages the variant permutations of elements in sunflower sets to adjust the order of accessing channels instead of SUs' IDs, which is more favorable for anonymous SUs in distributed environments. We also propose a multiradio-sunflower-set-based pairwise rendezvous algorithm to bring additional rendezvous diversity and accelerate the rendezvous process. Moreover, for the case with more than two SUs, we propose a multiuser collaborative scheme in which SUs cooperatively exchange and update their channel-hopping sequences until rendezvous. We derive the theoretical upper and lower bounds of rendezvous latency of the proposed algorithms. Extensive simulation comparisons with the state-of-the-art blind-rendezvous algorithms are conducted, incorporating the metrics of maximum and expected time-to-rendezvous. The simulation results show that our algorithms can achieve rendezvous faster than previous works.

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Section: A Pairwise Single-radio Rendezvous Algorithmsmentioning

confidence: 99%

Section: A Pairwise Single-radio Rendezvous Algorithmsmentioning

confidence: 99%

Section: A Pairwise Single-radio Scenariomentioning

confidence: 99%

“…In this scenario, we compare the proposed collaborative SSS algorithm with two representative multiuser algorithms termed DCH [23] and CBH [27]. Fig.…”

Section: Multiuser Single-radio Scenariomentioning

confidence: 99%

See 2 more Smart Citations

Fully Distributed Channel-Hopping Algorithms for Rendezvous Setup in Cognitive Multiradio Networks

Yang

Liang

Zheng

et al. 2016

IEEE Trans. Veh. Technol.

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“…In the literature, most of the existing rendezvous algorithms [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] implicitly assume that each user is equipped with one radio (i.e., one wireless transceiver). That is, each user hops on one channel in one time slot.…”

Section: Introductionmentioning

confidence: 99%

Adjustable Rendezvous in Multi-Radio Cognitive Radio Networks

Liu

Leung

et al. 2014

2015 IEEE Global Communications Conference (GLOBECOM)

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Rendezvous is a fundamental operation for cognitive users to establish communication links so as to realize data communications and network management. Most of existing rendezvous algorithms implicitly assume that each cognitive user is equipped with one radio, i.e., one wireless transceiver. As the cost of wireless transceivers is dropping, it becomes economically feasible to utilize multiple radios to significantly improve the rendezvous performance. In this paper, we propose an Adjustable Multi-Radio Rendezvous (AMRR) algorithm which exploits multiple radios for fast rendezvous based on available channels only. Suppose that a cognitive user is equipped with m radios. Our basic idea is to partition the radios into two groups: k stay radios and (m − k) hopping radios. The user stays on specific channels in the stay radios while hops on its available channels parallelly in the hopping radios. We prove that the maximum time-to-rendezvous (MTTR) of AMRR is upper-bounded by, where |C1| and |C2| are the numbers of available channels of two users and m 1 and m2 are the numbers of radios of the two users. This bound meets the lower bound of MTTR of any deterministic rendezvous algorithm when two users are equipped with the same number of radios (i.e., m1 = m2). AMRR is adjustable in giving its best performance on either MTTR or E(TTR) by adjusting value of k. Simulation results show that AMRR performs better than the state-of-the-art.Index Terms-cognitive radio, multiple radios, blind rendezvous, channel hopping.

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Robust clustering for ad hoc cognitive radio network

Fang

Gross

2018

Trans Emerging Tel Tech

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Cluster structure in cognitive radio (CR) networks facilitates cooperative spectrum sensing, routing, and other functionalities. Unlicensed channels, which are temporally available for a group of CR users in one area, consolidate the group into a cluster. More available unlicensed channels in a cluster make the cluster more likely to uphold against the licensed users' influence, making clusters more robust. This paper analyzes the problem of how to form robust clusters in a CR network such that CR systems benefit from collaboration within clusters despite intense primary user activity. We give a formal description of the robust clustering problem, prove it to be NP‐hard, and propose both centralized and distributed solutions. The congestion game model is adopted to analyze the process of cluster formation, which not only contributes to the design of the distributed clustering scheme but also provides a guarantee on the convergence to a Nash equilibrium and the convergence speed. The proposed distributed clustering scheme outperforms state‐of‐the‐art in terms of cluster robustness, convergence speed, and overhead. Extensive simulations are presented supporting the theoretical claims.

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Fully distributed algorithms for blind rendezvous in cognitive radio networks

Cited by 37 publications

References 19 publications

Fully Distributed Channel-Hopping Algorithms for Rendezvous Setup in Cognitive Multiradio Networks

Fully Distributed Channel-Hopping Algorithms for Rendezvous Setup in Cognitive Multiradio Networks

Adjustable Rendezvous in Multi-Radio Cognitive Radio Networks

Robust clustering for ad hoc cognitive radio network

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