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Scheduling algorithms for multi-carrier wireless data systems
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International Conference on Mobile Computing and Networking archive
Proceedings of the 13th annual ACM international conference on Mobile computing and networking table of contents
Montréal, Québec, Canada
SESSION: Medium access control table of contents
Pages: 3 - 14  
Year of Publication: 2007
ISBN:978-1-59593-681-3
Authors
Matthew Andrews  Bell Labs
Lisa Zhang  Bell Labs
Sponsors
ACM: Association for Computing Machinery
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 31,   Downloads (12 Months): 324,   Citation Count: 3
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ABSTRACT

We consider the problem of scheduling wireless data in systems such as 802.16 (WIMAX). Each scheduling decision involves constructing a frame of one or more time slots. Within each time slot multiple carriers must be assigned to users. The important aspect of our problem is that a scheduler knows the channel rates across all users and all carriers whenever a scheduling decision is made. Hence there is no need to treat each carrier in complete isolation. This gives a potential for enhancing performance by allocating multiple carriers simultaneously.

We analyze this problem in a situation where finite queues are fed by a data arrival process. We generalize the well-known MaxWeight algorithm for the single-carrier setting to accommodate a number of natural optimization problems in the multi-carrier setting. We state the hardness of these problems and present simple algorithmic solutions with provable performance bounds. We also validate our algorithms via numerical examples.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
R. Agrawal and V. Subramanian. Optimality of certain channel aware scheduling policies. In Proceedings of the 40th Annual Allerton Conference on Communication, Control, and Computing, Monticello, Illinois, October 2002.
 
2
M. Andrews. Instability of the proportional fair scheduling algorithm for HDR. IEEE Transactions on Wireless Communications, 3(5), 2004.
 
3
M. Andrews, K. Kumaran, K. Ramanan, A. Stolyar, R. Vijayakumar, and P. Whiting. CDMA data QoS scheduling on the forward link with variable channel conditions. Bell Labs Technical Memorandum, April 2000.
 
4
M. Andrews, K. Kumaran, K. Ramanan, A. Stolyar, R. Vijayakumar, and P. Whiting. Providing quality of service over a shared wireless link. IEEE Communications Magazine, February 2001.
 
5
M. Andrews, L. Qian, and A. Stolyar. Optimal utility based multi-user throughput allocation subject to throughput constraints. In Proceedings of IEEE INFOCOM '05, 2005.
 
6
M. Andrews and A. Slivkins. Oscillations with TCP-like flow control in networks of queues. In Proceedings of IEEE INFOCOM '06, 2006.
 
7
 
8
P. Bender, P. Black, M. Grob, R. Padovani, and N. Sindhushayana A. Viterbi. CDMA/HDR: A bandwidth efficient high speed data service for nomadic users. IEEE Communications Magazine, July 2000.
 
9
 
10
A. Eryilmaz and R. Srikant. Fair resource allocation in wireless networks using queue-length based scheduling and congestion control. In Proceedings of IEEE INFOCOM '05, Miami, FL, March 2005.
 
11
M. Fisher, G. Nemhauser, and L. Wolsey. An analysis of approximations for maximizing submodular set functions-II. Mathematical Programming Study, 1978.
12
 
13
 
14
 
15
A. Jalali, R. Padovani, and R. Pankaj. Data throughput of CDMA-HDR a high efficiency-high data rate personal communication wireless system. In Proceedings of the IEEE Semiannual Vehicular Technology Conference, VTC2000-Spring, Tokyo, Japan, May 2000.
 
16
 
17
H. Kushner and P. Whiting. Asymptotic properties of proportional-fair sharing algorithms. In 40th Annual Allerton Conference on Communication, Control, and Computing, 2002.
 
18
X. Liu, E. Chong, and N. B. Shroff. Opportunistic transmission scheduling with resource-sharing constraints in wireless networks. IEEE Journal on Selected Areas in Communications, 19(10), 2001.
 
19
 
20
M. Neely, E. Modiano, and C. Li. Fairness and optimal stochastic control for heterogeneous networks. In Proceedings of IEEE INFOCOM '05, Miami, FL, March 2005.
 
21
M. Neely, E. Modiano, and C. Rohrs. Power and server allocation in a multi-beam satellite with time varying channels. In Proceedings of IEEE INFOCOM '02, New York, NY, June 2002.
 
22
S. Shakkottai and A. Stolyar. Scheduling algorithms for a mixture of real-time and non-real-time data in HDR. In Proceedings of 17th International Teletraffic Congress (ITC-17), pages 793--804, Salvador da Bahia, Brazil, 2001.
 
23
S. Shakkottai and A. Stolyar. Scheduling for multiple flows sharing a time-varying channel: The exponential rule. Analytic Methods in Applied Probability, 207:185--202, 2002.
 
24
 
25
 
26
L. Tassiulas and A. Ephremides. Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks. IEEE Transactions on Automatic Control, 37(12):1936--1948, December 1992.
 
27
L. Tassiulas and A. Ephremides. Dynamic server allocation to parallel queues with randomly varying connectivity. IEEE Transactions on Information Theory, 30:466--478, 1993.
 
28
D. Tse. Multiuser diversity in wireless networks. http://www.eecs.berkeley.edu/~dtse/stanford416.ps, 2002.


Collaborative Colleagues:
Matthew Andrews: colleagues
Lisa Zhang: colleagues