Fast Multichannel Topology Discovery in Cognitive Radio Networks

2025-04-23

AI Summary

This paper introduces the novel problem of “multi-channel topology discovery” for secondary users (SUs) in cognitive radio networks, aiming to efficiently identify interconnection topologies across multiple channels. To address the inefficiency of conventional rendezvous algorithms—which ignore underlying network topology—we propose a hybrid approach: (i) a pseudo-random scanning scheme with forward substitution to reduce channel probing correlation, and (ii) a distributed “sticky synchronization” strategy based on dynamic thresholds to coordinate hopping sequences among SUs. We analytically model expected topology discovery time (ETTD) and validate the design via extensive simulations. Results demonstrate that our method significantly reduces ETTD across varying network scales and primary user (PU) activity levels, outperforming traditional sequential scanning by a substantial margin.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Search and Optimization: Mixed Discrete/Continuous Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Web Mining and Content Analysis: Topic discovery and tracking
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs
• Security and Privacy: Large-scale security measurements

Abstract

In Cognitive Radio Networks (CRNs), secondary users (SUs) must efficiently discover each other across multiple communication channels while avoiding interference from primary users (PUs). Traditional multichannel rendezvous algorithms primarily focus on enabling pairs of SUs to find common channels without explicitly considering the underlying network topology. In this paper, we extend the rendezvous framework to explicitly incorporate network topology, introducing the emph{multichannel topology discovery problem}. We propose a novel emph{pseudo-random sweep algorithm with forward replacement}, designed to minimize correlation between consecutive unsuccessful rendezvous attempts, thereby significantly reducing the expected time-to-discovery (ETTD). Additionally, we introduce a emph{threshold-based stick-together strategy} that dynamically synchronizes user hopping sequences based on partially known information, further enhancing discovery efficiency. Extensive simulation results validate our theoretical analysis, demonstrating that the proposed algorithms substantially outperform conventional (sequential) sweep methods.

Problem

• Efficient multichannel discovery among secondary users in CRNs
• Incorporating network topology into rendezvous algorithms explicitly
• Reducing expected time-to-discovery with pseudo-random sweep algorithm

Innovation

• Pseudo-random sweep algorithm with forward replacement
• Threshold-based stick-together strategy
• Explicit incorporation of network topology