Optimization flow control—I: basic algorithm and convergence
IEEE/ACM Transactions on Networking (TON)
Fair end-to-end window-based congestion control
IEEE/ACM Transactions on Networking (TON)
Impact of interference on multi-hop wireless network performance
Proceedings of the 9th annual international conference on Mobile computing and networking
A duality model of TCP and queue management algorithms
IEEE/ACM Transactions on Networking (TON)
Capacity of multi-channel wireless networks: impact of number of channels and interfaces
Proceedings of the 11th annual international conference on Mobile computing and networking
Proceedings of the 11th annual international conference on Mobile computing and networking
Characterizing the capacity region in multi-radio multi-channel wireless mesh networks
Proceedings of the 11th annual international conference on Mobile computing and networking
Proceedings of the 12th annual international conference on Mobile computing and networking
Realistic propagation simulation of urban mesh networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Allocating dynamic time-spectrum blocks in cognitive radio networks
Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing
Computer Networks: The International Journal of Computer and Telecommunications Networking
Proceedings of the 4th Annual International Conference on Wireless Internet
| Hi-index | 0.00 |
Cognitive radio can dynamically adapt to the available spectrum in the wireless network. Scheduling and spectrum allocation are tasks affecting the performance of cognitive radio wireless network. In [1], an iterative approach was proposed to efficiently compute the optimal scheduling for wireless mesh networks with single channel and single radio. The optimal scheduling problem is decomposed to a sequence of small optimization problems and maximum weighted independent set (MWIS) problems, and both of them can be computed quickly even for large networks. For example, the optimal scheduling can be computed for the mesh network with more than 2,000 links in less than one hour. Here, the iterative algorithm is extended to the cognitive radio wireless network with multi-channel and multi-radio. Allowing the schedule problem over multi-channel multi-radio results in higher dimension optimization problem. However, the proposed algorithm can obtain the optimal spectrum allocation and the schedule quickly for moderate size of networks. Numerical experiments show that the optimal throughput is achieved when the number of channels is one or two more than the number of interfaces.