Machine learning for physical layer link adaptation in multiple-antenna wireless networks

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Machine learning for physical layer link adaptation in multiple-antenna wireless networks

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International Conference on Mobile Computing and Networking archive
Proceedings of the third ACM international workshop on Wireless network testbeds, experimental evaluation and characterization table of contents

San Francisco, California, USA

DEMONSTRATION SESSION: Demonstrations table of contents

Pages 113-114

Year of Publication: 2008

ISBN:978-1-60558-187-3

Authors

Robert C. Daniels	The University of Texas at Austin, Austin, TX, USA
Ketan Mandke	The University of Texas at Austin, Austin, TX, USA
Steven W. Peters	The University of Texas at Austin, Austin, TX, USA
Scott M. Nettles	The University of Texas at Austin, Austin, TX, USA
Robert W. Heath, Jr.	The University of Texas at Austin, Austin, TX, USA

Sponsors

SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
ACM: Association for Computing Machinery

Publisher

ACM New York, NY, USA

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ABSTRACT

Prototyping and experimentation are key to understanding the operation of wireless systems in practice. In this extended abstract we present an implementation of physical layer link adaptation, or data rate selection, through machine learning on Hydra: an IEEE 802.11n draft standard multihop wireless networking prototype. This implementation highlights both the utility of learning-based link adaptation in practical networks as well as the flexibility of Hydra.

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	K. Mandke et al, "Early Results on Hydra: A Flexible MAC/PHY Multihop Testbed," in Proceedings of the 65th IEEE Vehicular Technology Conference, Apr. 2007, pp. 1896--1900.
	2	"GNU software radio." {Online}. Available: http://gnuradio.org/trac
	3	Eddie Kohler , Robert Morris , Benjie Chen , John Jannotti , M. Frans Kaashoek, The click modular router, ACM Transactions on Computer Systems (TOCS), v.18 n.3, p.263-297, Aug. 2000 [doi>10.1145/354871.354874]
	4	"GNU radio: universal software radio peripheral radio." {Online}. Available: http://gnuradio.org/trac/wiki/USRP
	5	S. Catreux, V. Erceg, D. Gesbert, and R. W. Heath, Jr., "Adaptive modulation and MIMO coding for broadband wireless data networks," IEEE Communications Magazine, vol. 40, no. 6, pp. 108--115, Jun 2002.
	6	R. C. Daniels, C. M. Caramanis, and R. W. Heath, Jr., "A supervised learning approach to adaptation in practical MIMO-OFDM wireless systems," in Proceedings of the IEEE Global Communications Conference, 2008.
	7	S. Kant and T. L. Jensen, "Fast link adaptation for IEEE 802.11n," Master's thesis, Aalborg University, February 2007.