The GBAR source model for VBR videoconferences
IEEE/ACM Transactions on Networking (TON)
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Convex Optimization
Wireless mesh networks: a survey
Computer Networks and ISDN Systems
Distributed Fair Scheduling in a Wireless LAN
IEEE Transactions on Mobile Computing
Distributed medium access control for wireless mesh networks: Research Articles
Wireless Communications & Mobile Computing - Medium Access Control Protocols for Wireless Ad Hoc Networks
QShine '06 Proceedings of the 3rd international conference on Quality of service in heterogeneous wired/wireless networks
Dynamic bandwidth allocation with fair scheduling for WCDMA systems
IEEE Wireless Communications
Multiuser adaptive subcarrier-and-bit allocation with adaptive cell selection for OFDM systems
IEEE Transactions on Wireless Communications
Cross-layer optimization for OFDM wireless networks-part I: theoretical framework
IEEE Transactions on Wireless Communications
Effective packet scheduling with fairness adaptation in ultra-wideband wireless networks
IEEE Transactions on Wireless Communications
The capacity of wireless networks
IEEE Transactions on Information Theory
Multiuser OFDM with adaptive subcarrier, bit, and power allocation
IEEE Journal on Selected Areas in Communications
Utilization-based dynamic scheduling algorithm for wireless mesh networks
EURASIP Journal on Wireless Communications and Networking
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Due to the requisite of multi-channel communications for high-speed data transmissions, power allocation for opportunistically exploiting fading wireless channels, and packet scheduling for quality-of-service provisioning, joint power-frequency-time resource allocation is indispensable. In this paper, we propose a low-complexity intra-cluster resource allocation algorithm, taking power allocation, subcarrier allocation, and packet scheduling into consideration. Numerical results demonstrate that our algorithm is close to optimal, and that our optimality-driven resource allocation algorithm outperforms a greedy algorithm, achieving higher resource utilization and better performance compromise among throughput, packet dropping rate, and packet delay.