Routing And Resource Allocation In Multi-hop Cognitive Radio Networks

Cognitive radio is proposed as a promising technology to alleviate the problem of spectrum scarcity. Compared to the traditional wireless multi-hop networks, a multi-hop cognitive radio network is new network architecture with its inherent features and design challenges. In multi-hop cognitive networks, there are several problems:instability transmission of an end-to-end secondary flow, transmission collisions between primary users and secondary users, frequent route failure due to dynamic network environment. Towards these issues, routing and resource allocation algorithm for multi-hop cognitive networks are studied in this thesis.Stability based joint routing channel assignment problem in multi-hop cognitive network are studied. Specifically, our objective is to find a route selection and channel assignment scheme that can achieve the maximal expected switching interval of the secondary flow while the end-to-end date rate requirement is satisfied. Simulation results demonstrate that the proposed scheme enables a secondary flow to maintain a longer end-to-end effective transmission time on average and thus enhances its stability.Routing and resource allocation schemes under transmission collision constraint between the primary and secondary users in multi-hop cognitive network are studied. Our objective is to seek for routing path and conducting transmission unit allocation for a secondary flow, maximizing the average end-to-end throughput of the flow while the expected number of timeslots that experience collision is limited. A routing path selection algorithm which expands the paths hop by hop and a low complexity algorithm for resource allocation are proposed respectively. Simulation results verify the effeteness of the algorithms, and show the heuristic algorithm can achieve similar performance compared with the optimal solution.An opportunistic forwarding based routing protocol for cognitive radio networks is designed. In the protocol, the multi-channel multi-interface model of cognitive node is employed, location information aided opportunistic forwarding is considered, and the backoff operations of nodes are employed to coordinate the forwarding. The performance of the proposed protocol is evaluated in a NS2based cognitive network simulation platform developed by us. Simulation results show the proposed protocol can reduce the delay and has good scalability.