Optimal resource allocation in the OFDMA downlink with imperfect channel knowledge
IEEE Transactions on Communications
Optimal resource allocation in uplink SC-FDMA systems
IEEE Transactions on Wireless Communications
International Journal of Mobile Network Design and Innovation
Dual optimal resource allocation for heterogeneous transmission in OFDMA systems
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Downlink mobile OFDMA resource allocation with minimum user rate requests
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Maintaining utility fairness using weighting factors in wireless networks
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Weighted-SNR-based fair scheduling for uplink OFDMA
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Constrained ergodic rates maximization for mobile WiMAX with statistical channel information
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Downlink OFDMA resource allocation under partial channel state information
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Slow adaptive OFDMA systems through chance constrained programming
IEEE Transactions on Signal Processing
Distributive stochastic learning for delay-optimal OFDMA power and subband allocation
IEEE Transactions on Signal Processing
Design of fair weights for heterogeneous traffic scheduling in multichannel wireless networks
IEEE Transactions on Communications
Using traffic asymmetry to enhance TCP performance
Computer Networks: The International Journal of Computer and Telecommunications Networking
Ergodic Sum Rate Maximization for Underlay Spectrum Sharing with Heterogeneous Traffic
Wireless Personal Communications: An International Journal
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OFDMA resource allocation assigns subcarriers and power, and possibly data rates, to each user. Previous research efforts to optimize OFDMA resource allocation with respect to communication performance have focused on formulations considering only instantaneous per-symbol rate maximization, and on solutions using suboptimal heuristic algorithms. This paper intends to fill gaps in the literature through two key contributions. First, we formulate continuous and discrete ergodic weighted sum rate maximization in OFDMA assuming the availability of perfect channel state information (CSI). Our formulations exploit time, frequency, and multi-user diversity, while enforcing various notions of fairness through weighting factors for each user. Second, we derive algorithms based on a dual optimization framework that solve the OFDMA ergodic rate maximization problem with O(MK) complexity per OFDMA symbol for M users and K subcarriers, while achieving data rates shown to be at least 99.9999% of the optimal rate in simulations based on realistic parameters. Hence, this paper attempts to demonstrate that OFDMA resource allocation problems are not computationally prohibitive to solve optimally, even when considering ergodic rates.