Cooperative Spectrum-Aware Opportunistic Routing in Cognitive Radio Ad Hoc Networks

1. Cooperative Spectrum-Aware Opportunistic Routing in Cognitive Radio Ad Hoc Networks , Cuimei Cui* †, Hong Man† , Yiming Wang* *School of Electronics and Information Engineering, Soochow University † Dept. of Electrical and Computer Engineering, Stevens Institute of Technology nicolec2008@126.com, Hong.man@stevens.edu, ymwang@suda.edu.cn • The probability that a channel at Ui stays in busy state during the sensing period ts adopting DCSS scheme, • Path Selection • The successful routing probability between Ui and Uj in the channel m, • Select the optimal channel as routing path, • The successful routing opportunity of the path • Motivations & Contributions • Motivations • Cognitive radio (CR) technology has been recognized as an viable solution to counteract both spectrum inefficiency and spectrum scarcity problems. • To fully unleash the potentials of CR Ad Hoc networks (CRAHNs), new challenges must be addressed at the network layer by tightly coupling with physical layer spectrum sensing and MAC layer spectrum sharing, taking into account the unique properties of the cognitive environment. • How to extend opportunistic routing adopting cooperative spectrum sensing technology is still an open research issue. • Contributions • Propose a Dual-stage Collaborative Spectrum Sensing (DCSS) routing protocol to discover the established routing opportunity. • Metrics of cooperative spectrum-aware opportunistic routing were defined and derived • Evaluate the performance of the proposed routing protocol in CRAHNs. Performance Evaluation II. Opportunistic Cognitive Routing Protocol • Simulations are presented to evaluate the performance of cooperative spectrum-aware opportunistic routing in terms of accuracy and optimality. • Fig.1 & Fig.2 illustrate the routing breakage probability of DCSS is more closer to the practical result than these of SCSS and NCS when selecting optimal relay. • Fig.2 & Fig.3 show that the longer the average time of a PU is in ON state, the higher is the breakage probability of end-to-end routing, the less is the opportunity of routing. • Fig.4 presents that the successful end-to-end opportunity routing probability using the DCSS increases as the number of usable channels increases, and decreases as the number of routing hops. • Network Model • Model the CRAHN with a direct temporal graph: • Vertex denotes an CR routing node or an CR sensing relay, and an edge denotes the routing link from CR node Ui to Uj at t time . • If PU is not active, the route with the minimum hop count and the longest single-hop distance Us-Ui-Uj-Ud will be established. • Otherwise, the route with a higher hop count, as shown in dashed line, will be selected. • Channel Sensing • The occupancy rate of PU at m-th channel, • The transition probability after a duration of for Ui in busy(ON) state, Fig.1 Fig.2 Fig.3 Fig.4 Conclusions The mean time of PU in ON /OFF state is / • From accuracy and optimality of view, DCSS scheme is more accuracy to find routing access opportunity than other spectrum sensing approaches. • Simulation results suggest the benefit of using DCSS in CRAHNs is considerable. • In the future work, we will investigate how to adapt metric to optimize the routing performance in dynamic CRAHNs.