A Stable Path Routing Protocol for Cognitive Radio Ad hoc Networks based on the Maximum Number of Common Primary User Channels

We propose a novel local spectrum knowledge-based distributed stable path routing protocol for cognitive radio ad hoc networks (CRAHNs) where the unlicensed secondary users (SUs) make use of the licensed channels of the Primary Users (PUs) when the latter are not actively using the channels. We model a time-variant CRAHN of SUs with links between any two SUs if they have at least one common PU channel available for use in their neighborhood and the weight of an edge is the number of such common PU channels available for use. Referred to as the Maximum Common Primary User channel-based Routing (MCPUR) protocol, the proposed protocol prefers to choose an SU-SU source-destination ( s-d ) path with the largest value for the sum of the number of common PU channels available for use across each of its constituent edges. Our hypothesis is that such an s-d route is likely to exist for a longer time (and incur fewer broadcast route discoveries) as the end nodes of the constituent SU-SU edges are more likely to have at least one common available PU channel that can be used to complete the transmission and reception of data packets. Simulation results confirm our hypothesis to be true: the number of path transitions incurred with MCPUR could be at most 62% lower than that of the path transitions incurred with a minimum hop-based shortest path routing (SPR) protocol. The tradeoff is a low-moderate increase in the hop count per path (as large as 17%)

[1]  Chien-Chung Shen,et al.  A novel layered graph model for topology formation and routing in dynamic spectrum access networks , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[2]  Mikio Hasegawa,et al.  Minimum weight routing based on a common link control radio for cognitive wireless ad hoc networks , 2007, IWCMC.

[3]  Ian F. Akyildiz,et al.  Optimal spectrum sensing framework for cognitive radio networks , 2008, IEEE Transactions on Wireless Communications.

[4]  Wenqing Cheng,et al.  Spectrum Aware On-Demand Routing in Cognitive Radio Networks , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[5]  Ian F. Akyildiz,et al.  CRAHNs: Cognitive radio ad hoc networks , 2009, Ad Hoc Networks.

[6]  Brian M. Sadler,et al.  A Survey of Dynamic Spectrum Access , 2007, IEEE Signal Processing Magazine.

[7]  Xuesong Zhang,et al.  Cross-layer Routing Design in Cognitive Radio Networks by Colored Multigraph Model , 2009, Wirel. Pers. Commun..

[8]  Ian F. Akyildiz,et al.  NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey , 2006, Comput. Networks.

[9]  Yiwei Thomas Hou,et al.  A Distributed Optimization Algorithm for Multi-Hop Cognitive Radio Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[10]  Wei Zhang,et al.  A geometric approach to improve spectrum efficiency for cognitive relay networks , 2010, IEEE Transactions on Wireless Communications.

[11]  Wei Yuan,et al.  Local Coordination Based Routing and Spectrum Assignment in Multi-hop Cognitive Radio Networks , 2008, Mob. Networks Appl..

[12]  Brandon F. Lo A survey of common control channel design in cognitive radio networks , 2011, Phys. Commun..

[13]  Xin-She Yang,et al.  Introduction to Algorithms , 2021, Nature-Inspired Optimization Algorithms.

[14]  Wei Liu,et al.  Joint On-Demand Routing and Spectrum Assignment in Cognitive Radio Networks , 2007, 2007 IEEE International Conference on Communications.

[15]  Xiao Ma,et al.  Spectrum Aware Routing for Multi-Hop Cognitive Radio Networks with a Single Transceiver , 2008, 2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008).