ISWCS'09 Proceedings of the 6th international conference on Symposium on Wireless Communication Systems
Performance of suboptimal cooperative opportunity scheduling strategy on cell-MIMO system
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Utility-based scheduling with non-deterministic fading channels in wireless multi-hop networks
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Centralized and distributed power allocation in multi-user wireless relay networks
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
IEEE Transactions on Wireless Communications
Cross-layer design for multihop wireless relaying networks
IEEE Transactions on Wireless Communications
Mobile Networks and Applications
Utility-based scheduling in wireless multi-hop networks over non-deterministic fading channels
Computer Networks: The International Journal of Computer and Telecommunications Networking
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We propose cross-layer optimization frameworks for multihop wireless networks using cooperative diversity. These frameworks provide solutions to fundamental relaying problems of determining who should be relays for whom and how to perform resource allocation for these relaying schemes jointly with routing and congestion control such that the system performance is optimized. We present a fully distributed algorithm where the joint routing, relay selection, and power allocation problem to minimize network power consumption is solved by using convex optimization. Via dual decomposition, the master optimization problem is decomposed into a routing subproblem in the network layer and a joint relay selection and power allocation subproblem in the physical layer, which can be solved efficiently in a distributed manner. We then extend the framework to incorporate congestion control and develop a framework for optimizing the sum rate utility and power tradeoff for wireless networks using cooperative diversity. The numerical results show the convergence of the proposed algorithms and significant improvement in terms of power consumption and source rates due to cooperative diversity.