Convex Optimization
Maximizing Queueing Network Utility Subject to Stability: Greedy Primal-Dual Algorithm
Queueing Systems: Theory and Applications
Fundamentals of wireless communication
Fundamentals of wireless communication
Resource Allocation and Cross Layer Control in Wireless Networks (Foundations and Trends in Networking, V. 1, No. 1)
IEEE/ACM Transactions on Networking (TON)
Fairness and optimal stochastic control for heterogeneous networks
IEEE/ACM Transactions on Networking (TON)
Joint scheduling and power control for wireless ad hoc networks
IEEE Transactions on Wireless Communications
Dynamic power allocation and routing for time-varying wireless networks
IEEE Journal on Selected Areas in Communications
A tutorial on cross-layer optimization in wireless networks
IEEE Journal on Selected Areas in Communications
Joint congestion control, routing, and MAC for stability and fairness in wireless networks
IEEE Journal on Selected Areas in Communications
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We consider the cross-layer utility maximization problem for wireless networks. It is well known that the optimal network control policy can be decomposed in three separate subproblems: 1) flow control at the network layer, 2) routing and scheduling at the network layer, and 3) resource allocation (RA) at the medium access control and physical layers. The main contribution of this paper is a power and rate control algorithm for the RA subproblem. In the case of single-hop networks, the proposed algorithm provides a locally optimal solution for the RA subproblem. Even though the global optimality of the solution cannot be guaranteed due to the nonconvexity of the problem, the numerical results show that the algorithm can provide significant gains at the network layer in terms of end-to-end rates and network congestion as compared to the optimal time division multiple access (TDMA) based RA. For solving the RA subproblem in the case of multi-hop networks, the proposed algorithm must be used in conjunction with an exhaustive search for the optimal set of transmitter nodes. However, the numerical results show that even with a random selection of the set of transmitter nodes, the proposed algorithm can provide significant improvement at the network layer in terms of end-to-end rates and network congestion as compared the optimal TDMA based RA.