Control of mobile communication systems with time-varying channels via stability methods

Consider the forward link of a mobile communications system with a single transmitter and connecting to K destinations via randomly varying channels. Data arrives in some random way and is queued according to the K destinations until transmitted. Time is divided into small scheduling intervals. Current systems can estimate the channel (e.g, via pilot signals) and use this information for scheduling. The issues are the allocation of transmitter power and/or time and bandwidth to the various queues in a queue and channel-state dependent way to assure stability and good operation. The decisions are made at the beginning of the scheduling intervals. Stochastic stability methods are used both to assure that the system is stable and to get appropriate allocations, under very weak conditions. The choice of Lyapunov function allows a choice of the effective performance criteria. The resulting controls are readily implementable and allow a range of tradeoffs between current rates and queue lengths. The various extensions allow a large variety of schemes of current interest to be covered. All essential factors are incorporated into a "mean rate" function, so that the results cover many different systems. Because of the non-Markovian nature of the problem, we use the perturbed Stochastic Lyapunov function method, which is well adapted to such problems. The method is simple and effective.

[1]  Harold J. Kushner,et al.  Approximation and Weak Convergence Methods for Random Processes , 1984 .

[2]  W. Grassman Approximation and Weak Convergence Methods for Random Processes with Applications to Stochastic Systems Theory (Harold J. Kushner) , 1986 .

[3]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[4]  Leandros Tassiulas,et al.  Dynamic server allocation to parallel queues with randomly varying connectivity , 1993, IEEE Trans. Inf. Theory.

[5]  J. Quadrat Numerical methods for stochastic control problems in continuous time , 1994 .

[6]  A. Robert Calderbank,et al.  Space-Time Codes for High Data Rate Wireless Communications : Performance criterion and Code Construction , 1998, IEEE Trans. Inf. Theory.

[7]  Philip A. Whiting,et al.  Cdma data qos scheduling on the forward link with variable channel conditions , 2000 .

[8]  H. Kushner Numerical Methods for Stochastic Control Problems in Continuous Time , 2000 .

[9]  N. Seshadri,et al.  Increasing data rate over wireless channels , 2000, IEEE Signal Process. Mag..

[10]  Alexander L. Stolyar,et al.  Scheduling for multiple flows sharing a time-varying channel: the exponential rule , 2000 .

[11]  A. Robert Calderbank,et al.  Space-time coding and signal processing for high data rate wireless communications , 2001, Wirel. Commun. Mob. Comput..

[12]  Moe Z. Win,et al.  Optimum modulation and multicode formats in CDMA systems with multiuser receivers , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[13]  Roy D. Yates,et al.  Iterative construction of optimum signature sequence sets in synchronous CDMA systems , 2001, IEEE Trans. Inf. Theory.

[14]  Harold J. Kushner,et al.  Control of mobile communications with time-varying channels in heavy traffic , 2002, IEEE Trans. Autom. Control..

[15]  Harold J. Kushner,et al.  Stability and control of mobile communication systems with time-varying channels , 2002, 2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333).

[16]  Nicholas Bambos,et al.  Queueing Networks of Random Link Topology: Stationary Dynamics of Maximal Throughput Schedules , 2005, Queueing Syst. Theory Appl..