Adaptive multiuser opportunistic fair transmission scheduling in power-controlled CDMA systems

• Published in: 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing Vol. 4; p. iv
• Main Authors: Chuziang Li, Xiadong Wang
• Format: Conference Proceeding
• Language: English
• Published: Piscataway, N.J IEEE 2004
• Subjects: Applied sciences; Approximation algorithms; Exact sciences and technology; Multiaccess communication; Power control; Resource management; Scheduling; Signal to noise ratio; Stochastic processes; Stochastic systems; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Teletraffic; Throughput; Transmission and modulation (techniques and equipments); Wireless networks; Performance evaluation; Wireless telecommunication; Resource allocation; Information rate; Equity; Stochastic approximation; Time variation; Traffic control; Convergence rate; Optimal planning; Multiple access; Time variable channel; Target tracking; Flow rate regulation; Teletraffic; Scheduling; Algorithm; Information transmission; Selection problem; Simulation; Power control; Optimal control; Traffic management; Code division multiple access; Resource management
• ISBN: 9780780384842; 0780384849
• ISSN: 1520-6149
• DOI: 10.1109/ICASSP.2004.1326886

We consider the problem of multiuser opportunistic fair transmission scheduling (OFS) in power-controlled CDMA systems. OFS is an important technique in wireless networks to achieve fair and efficient resource allocation. Power control is an effective resource management technique in CDMA systems. Given a certain user subset and the channel states, the optimal power control scheme can be calculated. The multiuser OFS problem then refers to the optimal user subset selection at each interval to maximize instantaneous system throughput subject to some fairness constraint. We propose discrete stochastic approximation algorithms to adaptively select user subsets with the maximal system throughput. We also consider the time-varying channel scenarios where the algorithm can track the time-varying optimal user subset. We present simulation results to show the performance of the proposed algorithms in terms of the throughput optimization, the fast convergence, the excellent time-varying tracking capability, and the fairness.