Efficient Communication in Cognitive Radio Networks

Gilbert, Seth; Kühn, Fabian; Newport, Calvin; Zheng, Chaodong

doi:10.1145/2767386.2767422

Cited by 3 publications

(7 citation statements)

References 22 publications

(36 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We now sketch the proof of Lemma 2. 4 In each step in part one, for u to hear v's identity, three conditions must hold: (a) u is a listener and v is a broadcaster; (b) u and v choose the same channel; and (c) v broadcasts alone in some slot during the counting procedure. According to protocol description, obviously condition (a) holds with probability 1/4.…”

Section: Analysis Of the Cseek Algorithmmentioning

confidence: 99%

“…We demonstrate that if A can achieve neighbor discovery fast, then we can use the simulation process to solve (c, k)-bipartite hitting fast. We note that the reduction strategy we used here is different from the one that appeared in [4].…”

Section: Lower Bound For Neighbor Discoverymentioning

confidence: 99%

“…Lemma 12 (Lemma 14 from [4]). Let P be a player that guarantees to win the c-complete bipartite hitting game in f (c) rounds with probability at least 1/2, for some positive integer c. It follows that f (c) ≥ c/3.…”

Section: Lower Bound For Neighbor Discoverymentioning

confidence: 99%

“…More specifically, to prove the Ω(c 2 /k + ∆) lower bound for neighbor discovery, we consider a combinatorial game which captures the core difficulty of the problem, and then do a reduction argument to prove our claim. The combinatorial game has been previously used to prove other lower bounds in cognitive radio networks (see, e.g., [4]), but the reduction argument is tailored for our purpose.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Communication Primitives in Cognitive Radio Networks

Gilbert

Kühn

Zheng

2017

Proceedings of the ACM Symposium on Principles of Distributed Computing

Self Cite

View full text Add to dashboard Cite

Cognitive radio networks are a new type of multi-channel wireless network in which different nodes can have access to different sets of channels. By providing multiple channels, they improve the efficiency and reliability of wireless communication. However, the heterogeneous nature of cognitive radio networks also brings new challenges to the design and analysis of distributed algorithms.In this paper, we focus on two fundamental problems in cognitive radio networks: neighbor discovery, and global broadcast. We consider a network containing n nodes, each of which has access to c channels. We assume the network has diameter D, and each pair of neighbors have at least k ≥ 1, and at most k max ≤ c, shared channels. We also assume each node has at most ∆ neighbors. For the neighbor discovery problem, we design a randomized algorithm CSEEK which has time complexityÕ((c 2 /k) + (k max /k) · ∆). CSEEK is flexible and robust, which allows us to use it as a generic "filter" to find "well-connected" neighbors with an even shorter running time. We then move on to the global broadcast problem, and propose CGCAST, a randomized algorithm which takesCGCAST uses CSEEK to achieve communication among neighbors, and uses edge coloring to establish an efficient schedule for fast message dissemination.Towards the end of the paper, we give lower bounds for solving the two problems. These lower bounds demonstrate that in many situations, CSEEK and CGCAST are near optimal.

show abstract

Section: Analysis Of the Cseek Algorithmmentioning

confidence: 99%

Section: Lower Bound For Neighbor Discoverymentioning

confidence: 99%

Section: Lower Bound For Neighbor Discoverymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Communication Primitives in Cognitive Radio Networks

Gilbert

Kühn

Zheng

2017

Proceedings of the ACM Symposium on Principles of Distributed Computing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Once a new SU joins the collaborative group, the group members exchange and store each other's CH information via the local broadcast process [35]. The group members switch Fig.…”

Section: A Algorithm Designmentioning

confidence: 99%

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

Yang

Liang

Zheng

et al. 2016

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

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.

show abstract