Stable scheduling policies for fading wireless channels

We study the problem of stable scheduling for a class of wireless networks. The goal is to stabilize the queues holding information to be transmitted over a fading channel. Few assumptions are made on the arrival process statistics other than the assumption that their mean values lie within the capacity region and that they satisfy a version of the law of large numbers. We prove that, for any mean arrival rate that lies in the capacity region, the queues will be stable under our policy. Moreover, we show that it is easy to incorporate imperfect queue length information and other approximations that can simplify the implementation of our policy.

[1]  Leandros Tassiulas,et al.  Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks , 1992 .

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

[3]  Dimitri P. Bertsekas,et al.  Nonlinear Programming , 1997 .

[4]  Sean P. Meyn,et al.  Stability of queueing networks and scheduling policies , 1995, IEEE Trans. Autom. Control..

[5]  D. Mitra,et al.  Multiple Time Scale Regulation and Worst Case Processes for ATM Network Control , 1995, Proceedings of 1995 34th IEEE Conference on Decision and Control.

[6]  Leandros Tassiulas,et al.  Scheduling and performance limits of networks with constantly changing topology , 1997, IEEE Trans. Inf. Theory.

[7]  Leandros Tassiulas Scheduling and performance limits of networks with constantly changing topology , 1997 .

[8]  Leandros Tassiulas,et al.  Linear complexity algorithms for maximum throughput in radio networks and input queued switches , 1998, Proceedings. IEEE INFOCOM '98, the Conference on Computer Communications. Seventeenth Annual Joint Conference of the IEEE Computer and Communications Societies. Gateway to the 21st Century (Cat. No.98.

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

[10]  Ness B. Shroff,et al.  Opportunistic transmission scheduling with resource-sharing constraints in wireless networks , 2001, IEEE J. Sel. Areas Commun..

[11]  Andrea J. Goldsmith,et al.  Capacity and optimal resource allocation for fading broadcast channels - Part I: Ergodic capacity , 2001, IEEE Trans. Inf. Theory.

[12]  Rajeev Agrawal,et al.  Scheduling in multimedia wireless networks , 2001 .

[13]  David Tse,et al.  Opportunistic beamforming using dumb antennas , 2002, IEEE Trans. Inf. Theory.

[14]  Paolo Giaccone,et al.  Towards simple, high-performance schedulers for high-aggregate bandwidth switches , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[15]  N. Bambos,et al.  PROJECTIVE PROCESSING SCHEDULES IN QUEUEING STRUCTURES ; Applications to Packet Scheduling in Communication Network Switches , 2002 .

[16]  Atilla Eryilmaz,et al.  Stable scheduling policies for fading wireless channels , 2003, IEEE International Symposium on Information Theory, 2003. Proceedings..

[17]  Rajeev Agrawal,et al.  Scheduling in multimedia CDMA wireless networks , 2003, IEEE Trans. Veh. Technol..

[18]  Nicholas Bambos,et al.  Queueing Dynamics and Maximal Throughput Scheduling in Switched Processing Systems , 2003, Queueing Syst. Theory Appl..

[19]  Philip A. Whiting,et al.  SCHEDULING IN A QUEUING SYSTEM WITH ASYNCHRONOUSLY VARYING SERVICE RATES , 2004, Probability in the Engineering and Informational Sciences.

[20]  S. Shakkottai,et al.  Pathwise optimality of the exponential scheduling rule for wireless channels , 2004, Advances in Applied Probability.