Distributed Opportunistic Scheduling With Two-Level Probing

Distributed opportunistic scheduling (DOS) is studied for wireless ad hoc networks in which many links contend for a channel using random access before data transmission. Simply put, DOS involves a process of joint channel probing and distributed scheduling for ad hoc (peer-to-peer) communications. Since, in practice, link conditions are estimated with noisy observations, the transmission rate must be backed off from the estimated rate in order to avoid transmission outages. Then, a natural question to ask is whether or not it is worthwhile for the link with successful contention to perform further channel probing to mitigate estimation errors, at the cost of additional probing. Thus motivated, this work investigates DOS with two-level channel probing by optimizing the tradeoff between the throughput gain from more accurate rate estimation and the resulting additional delay. By capitalizing on optimal stopping theory with incomplete information, it is shown that the optimal scheduling policy is threshold-based and is characterized by either one or two thresholds, depending on network settings. Necessary and sufficient conditions for both cases are rigorously established. In particular, this analysis reveals that performing second-level channel probing is optimal when the first-level estimated channel condition falls in between the two thresholds. Numerical results are provided to illustrate the effectiveness of the proposed DOS with two-level channel probing. This study is also extended to the case with limited feedback, in which the feedback from the receiver to its transmitter takes the form of (0,1,e).

[1]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[2]  H. Vincent Poor,et al.  Optimal selection of channel sensing order in cognitive radio , 2009, IEEE Transactions on Wireless Communications.

[3]  Junshan Zhang,et al.  Distributed opportunistic scheduling for ad-hoc communications: an optimal stopping approach , 2007, MobiHoc '07.

[4]  Ness B. Shroff,et al.  A framework for opportunistic scheduling in wireless networks , 2003, Comput. Networks.

[5]  Xuemin Shen,et al.  PHY-aware distributed scheduling for ad hoc communications with physical interference model , 2009, IEEE Transactions on Wireless Communications.

[6]  David Assaf,et al.  A statistical version of prophet inequalities , 1998 .

[7]  Dimitri P. Bertsekas,et al.  Data Networks , 1986 .

[8]  Junshan Zhang,et al.  Distributed Opportunistic Scheduling for Ad Hoc Networks With Random Access: An Optimal Stopping Approach , 2009, IEEE Transactions on Information Theory.

[9]  Zhenzhen Ye,et al.  Optimal Stochastic Policies for Distributed Data Aggregation in Wireless Sensor Networks , 2009, IEEE/ACM Transactions on Networking.

[10]  Randall Berry,et al.  Exploiting multiuser diversity for medium access control in wireless networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[11]  Sem C. Borst User-level performance of channel-aware scheduling algorithms in wireless data networks , 2005, IEEE/ACM Transactions on Networking.

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

[13]  Albert N. Shiryaev,et al.  Optimal Stopping Rules , 2011, International Encyclopedia of Statistical Science.

[14]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[15]  Babak Hassibi,et al.  The Effect of Channel Estimation Error on the Throughput of Broadcast Channels , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[16]  H. Vincent Poor,et al.  Distributed opportunistic scheduling for ad hoc communications with imperfect channel information , 2008, IEEE Transactions on Wireless Communications.

[17]  Yi Yang,et al.  Exploiting medium access diversity in rate adaptive wireless LANs , 2004, MobiCom '04.

[18]  David Siegmund,et al.  Great expectations: The theory of optimal stopping , 1971 .

[19]  Alʹbert Nikolaevich Shiri︠a︡ev,et al.  Optimal stopping rules , 1977 .

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

[21]  S. Kay Fundamentals of statistical signal processing: estimation theory , 1993 .

[22]  Bo Wang,et al.  Achievable Rates and Scaling Laws of Power-Constrained Wireless Sensory Relay Networks , 2006, IEEE Transactions on Information Theory.

[23]  G. Simons Great Expectations: Theory of Optimal Stopping , 1973 .

[24]  Wolfgang Stadje,et al.  An optimal stopping problem with two levels of incomplete information , 1997, Math. Methods Oper. Res..

[25]  Edward W. Knightly,et al.  Opportunistic media access for multirate ad hoc networks , 2002, MobiCom '02.

[26]  A. Cox Optimal Stopping and Applications , 2009 .