Data networks
Parallel and distributed computation: numerical methods
Parallel and distributed computation: numerical methods
Discrete algorithmic mathematics
Discrete algorithmic mathematics
Convex Optimization
Joint Scheduling, Power Control, and Routing Algorithm for Ad-Hoc Wireless Networks
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences - Volume 09
Introduction to Space-Time Wireless Communications
Introduction to Space-Time Wireless Communications
IEEE Journal on Selected Areas in Communications
Throughput-range tradeoff of wireless mesh backhaul networks
IEEE Journal on Selected Areas in Communications
A framework for uplink power control in cellular radio systems
IEEE Journal on Selected Areas in Communications
Hi-index | 0.00 |
Efficiently transmitting data in wireless networks requires joint optimization of routing, scheduling, and power control. As opposed to the universal dual decomposition we present a method that solves this optimization problem by fully exploiting our knowledge of active constraints. Themethod still maintains main requirements such as optimality, distributed implementation, multiple path routing and per-hop error performance. To reduce the complexity of the whole problem, we separate scheduling from routing and power control, including it instead in the constraint set of the joint optimization problem. Apart fromthe mathematical framework we introduce a routing and power control decomposition algorithm that uses the active constraint method, and we give further details on its distributed application. For verification, we apply the distributed RPCD algorithm to examples of wireless mesh backhaul networks with fixed nodes. Impressive convergence results indicate that the distributed RPCD algorithm calculates the optimum solution in one decomposition step only.