The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.04 - April (2010 vol.9)
pp: 527-539
Chih-ping Li , University of Southern California, Los Angeles
Michael J. Neely , University of Southern California, Los Angeles
ABSTRACT
We consider a wireless base station serving L users through L time-varying channels. It is well known that opportunistic scheduling algorithms with full channel state information (CSI) can stabilize the system with any data rates within the capacity region. However, such opportunistic scheduling algorithms may not be energy efficient when the cost of channel acquisition is high and traffic rates are low. In particular, under the low traffic rate regime, it may be sufficient and more energy efficient to transmit data with no CSI, i.e., to transmit data blindly, since no power for channel acquisition is consumed. In general, we show strategies that probe channels in every slot or never probe channels in any slot are not necessarily optimal, and we must consider mixed strategies. We derive a unified scheduling algorithm that dynamically chooses to transmit data with full or no CSI based on queue backlog and channel statistics. Our methodology is general and can be naturally extended to include timing overhead due to channel acquisition, and to treat systems that allow any subset of channels to be measured. Through Lyapunov analysis, we show that the unified algorithm is throughput-optimal and stabilizes the downlink with optimal power consumption, balancing well between channel-aware and channel-blind transmission modes.
INDEX TERMS
Stochastic control, queuing analysis, optimization, partial channel state information.
CITATION
Chih-ping Li, Michael J. Neely, "Energy-Optimal Scheduling with Dynamic Channel Acquisition in Wireless Downlinks", IEEE Transactions on Mobile Computing, vol.9, no. 4, pp. 527-539, April 2010, doi:10.1109/TMC.2009.140
REFERENCES
[1] C.-P. Li and M.J. Neely, "Energy-Optimal Scheduling with Dynamic Channel Acquisition in Wireless Downlinks," Proc. IEEE Conf. Decision and Control (CDC), pp. 1140-1147, Dec. 2007.
[2] M.J. Neely, "Energy Optimal Control for Time Varying Wireless Networks," IEEE Trans. Information Theory, vol. 52, no. 7, pp. 2915-2934, July 2006.
[3] P. Giaccone, B. Prabhakar, and D. Shah, "Energy Constrained Wireless Switching," Proc. Allerton Conf. Comm., Control, and Computing, Oct. 2003.
[4] E.M. Yeh and A.S. Cohen, "Throughput Optimal Power and Rate Control for Queued Multiaccess and Broadcast Communications," Proc. IEEE Int'l Symp. Information Theory (ISIT), p. 112, June 2004.
[5] M.J. Neely, E. Modiano, and C.E. Rohrs, "Power Allocation and Routing in Multibeam Satellites with Time-Varying Channels," IEEE/ACM Trans. Networking, vol. 11, no. 1, pp. 138-152, Feb. 2003.
[6] J.-W. Lee, R.R. Mazumdar, and N.B. Shroff, "Opportunistic Power Scheduling for Dynamic Multi-Server Wireless Systems," IEEE Trans. Wireless Comm., vol. 5, no. 6, pp. 1506-1515, June 2006.
[7] Z. Ji, Y. Yang, J. Zhou, M. Takai, and R. Bagrodia, "Exploiting Medium Access Diversity in Rate Adaptive Wireless Lans," Proc. ACM MobiCom, pp. 345-359, Sept. 2004.
[8] A. Sabharwal, A. Khoshnevis, and E. Knightly, "Opportunistic Spectral Usage: Bounds and a Multi-Band CSMA-CA Protocol," IEEE/ACM Trans. Networking, vol. 15, no. 3, pp. 533-545, June 2007.
[9] K. Kar, X. Luo, and S. Sarkar, "Throughput-Optimal Scheduling in Multichannel Access Point Networks under Infrequent Channel Measurements," IEEE Trans. Wireless Comm., vol. 7, no. 7, pp. 2619-2629, July 2008.
[10] A. Gopalan, C. Caramanis, and S. Shakkottai, "On Wireless Scheduling with Partial Channel-State Information," Proc. Allerton Conf. Comm., Control, and Computing, Sept. 2007.
[11] D. Gesbert and M.-S. Alouini, "How Much Feedback Is Multi-User Diversity Really Worth?" Proc. IEEE Int'l Conf. Comm. (ICC), pp. 234-238, June 2004.
[12] S. Patil and G. de Veciana, "Reducing Feedback for Opportunistic Scheduling in Wireless Systems," IEEE Trans. Wireless Comm., vol. 6, no. 12, pp. 4227-4232, Dec. 2007.
[13] T. Tang and R.W. Heath,Jr., "Opportunistic Feedback for Downlink Multiuser Diversity," IEEE Comm. Letters, vol. 9, no. 10, pp. 948-950, Oct. 2005.
[14] S. Guha, K. Munagala, and S. Sarkar, "Performance Guarantees through Partial Information Based Control in Multichannel Wireless Networks," technical report, Univ. of Pennsylvania, Sept. 2006.
[15] S. Guha, K. Munagala, and S. Sarkar, "Approximation Schemes for Information Acquisition and Exploration in Multichannel Wireless Networks," Proc. Allerton Conf. Comm., Control, and Computing, Sept. 2006.
[16] N.B. Chang and M. Liu, "Optimal Channel Probing and Transmission Scheduling in a Multichannel System," Proc. Information Theory and Application Workshop (ITA), Feb. 2007.
[17] L. Tassiulas and A. Ephremides, "Dynamic Server Allocation to Parallel Queues with Random Varying Connectivity," IEEE Trans. Information Theory, vol. 39, no. 2, pp. 466-478, Mar. 1993.
[18] L. Georgiadis, M.J. Neely, and L. Tassiulas, "Resource Allocation and Cross-Layer Control in Wireless Networks," Foundations and Trends in Networking, vol. 1, no. 1, 2006.
[19] M.J. Neely and R. Urgaonkar, "Opportunism, Backpressure, and Stochastic Optimization with the Wireless Broadcast Advantage," Proc. Asilomar Conf. Signals, Systems, and Computers, Oct. 2008.
[20] W. Rudin, Principles of Mathematical Analysis, third ed. McGraw-Hill, 1976.
5 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool