A cutting plane algorithm for convex programming that uses analytic centers
Mathematical Programming: Series A and B
Interior point algorithms: theory and analysis
Interior point algorithms: theory and analysis
Complexity Analysis of an Interior Cutting Plane Method for Convex Feasibility Problems
SIAM Journal on Optimization
Convex Approximations of Chance Constrained Programs
SIAM Journal on Optimization
Slow adaptive M-QAM under third-party received signal constraints in shadowing environments
Research Letters in Communications - Regular issue
Slow adaptive OFDMA via stochastic programming
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Robust power allocation algorithms for wireless relay networks
IEEE Transactions on Communications
Multiuser adaptive subcarrier-and-bit allocation with adaptive cell selection for OFDM systems
IEEE Transactions on Wireless Communications
Power-efficient wireless OFDMA using limited-rate feedback
IEEE Transactions on Wireless Communications
Optimal Downlink OFDMA Resource Allocation with Linear Complexity to Maximize Ergodic Rates
IEEE Transactions on Wireless Communications
Multiuser OFDM with adaptive subcarrier, bit, and power allocation
IEEE Journal on Selected Areas in Communications
Performance analysis of dynamic OFDMA systems with inband signaling
IEEE Journal on Selected Areas in Communications
Robust power allocation for energy-efficient location-aware networks
IEEE/ACM Transactions on Networking (TON)
Hi-index | 35.68 |
Adaptive orthogonal frequency division multiple access (OFDMA) has recently been recognized as a promising technique for providing high spectral efficiency in future broadband wireless systems. The research over the last decade on adaptive OFDMA systems has focused on adapting the allocation of radio resources, such as subcarriers and power, to the instantaneous channel conditions of all users. However, such "fast" adaptation requires high computational complexity and excessive signaling overhead. This hinders the deployment of adaptive OFDMA systems worldwide. This paper proposes a slow adaptive OFDMA scheme, in which the subcarrier allocation is updated on a much slower timescale than that of the fluctuation of instantaneous channel conditions. Meanwhile, the data rate requirements of individual users are accommodated on the fast timescale with high probability, thereby meeting the requirements except occasional outage. Such an objective has a natural chance constrained programming formulation, which is known to be intractable. To circumvent this difficulty, we formulate safe tractable constraints for the problem based on recent advances in chance constrained programming. We then develop a polynomial-time algorithm for computing an optimal solution to the reformulated problem. Our results show that the proposed slow adaptation scheme drastically reduces both computational cost and control signaling overhead when compared with the conventional fast adaptive OFDMA. Our work can be viewed as an initial attempt to apply the chance constrained programming methodology to wireless system designs. Given that most wireless systems can tolerate an occasional dip in the quality of service, we hope that the proposed methodology will find further applications in wireless communications.