Maximizing Queueing Network Utility Subject to Stability: Greedy Primal-Dual Algorithm
Queueing Systems: Theory and Applications
Resource allocation and cross-layer control in wireless networks
Foundations and Trends® in Networking
Stochastic Learning and Optimization: A Sensitivity-Based Approach (International Series on Discrete Event Dynamic Systems)
Dynamic Programming and Optimal Control, Vol. II
Dynamic Programming and Optimal Control, Vol. II
Order optimal delay for opportunistic scheduling in multi-user wireless uplinks and downlinks
IEEE/ACM Transactions on Networking (TON)
Cross-Layer Design for OFDMA Wireless Systems With Heterogeneous Delay Requirements
IEEE Transactions on Wireless Communications
Quality-of-Service Driven Power and Rate Adaptation over Wireless Links
IEEE Transactions on Wireless Communications
Providing quality of service over a shared wireless link
IEEE Communications Magazine
Multiuser OFDM with adaptive subcarrier, bit, and power allocation
IEEE Journal on Selected Areas in Communications
A tutorial on decomposition methods for network utility maximization
IEEE Journal on Selected Areas in Communications
Energy efficient quality of service traffic scheduler for MIMO downlink SVD channels
IEEE Transactions on Wireless Communications
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In this paper, we consider delay-optimal power and subcarrier allocation design for OFDMA systems with NF subcarriers, K mobiles and one base station. There are K queues at the base station for the downlink traffic to the K mobiles with heterogeneous packet arrivals and delay requirements. We shall model the problem as a K-dimensional infinite horizon average reward Markov Decision Problem (MDP) where the control actions are assumed to be a function of the instantaneous Channel State Information (CSI) as well as the joint Queue State Information (QSI). We propose an online stochastic value iteration solution using stochastic approximation. The proposed power control algorithm, which is a function of both the CSI and the QSI, takes the form of multi-level water-filling. We prove that under two mild conditions in Theorem 1, the proposed solution converges to the optimal solution almost surely (with probability 1) and the proposed framework offers a possible solution to the general stochastic NUM problem. By exploiting the birth-death structure of the queue dynamics, we obtain a reduced complexity decomposed solution with linear O(KNF) complexity and O(K) memory requirement.