Article

A general model of wireless interference

Authors:

Ratul MahajanAuthors Info & Claims

MobiCom '07: Proceedings of the 13th annual ACM international conference on Mobile computing and networking

Pages 171 - 182

https://doi.org/10.1145/1287853.1287874

Published: 09 September 2007 Publication History

Abstract

We develop a general model to estimate the throughput and goodput between arbitrary pairs of nodes in the presence of interference from other nodes in a wireless network. Our model is based on measurements from the underlying network itself and is thus more accurate than abstract models of RF propagation such as those based on distance. The seed measurements are easy to gather, requiring only O(N) measurements in an N-node networks. Compared to existing measurement-based models, our model advances the state of the art in three important ways. First, it goes beyond pairwise interference and models interference among an arbitrary number of senders. Second, it goes beyond broadcast transmissions and models the more common case of unicast transmissions. Third, it goes beyond homogeneous nodes and models the general case of heterogeneous nodes with different traffic demands and different radio characteristics. Using simulations and measurements from two different wireless testbeds, we show that the predictions of our model are accurate in a wide range of scenarios.

References

[1]

S. Agarwal, J. Padhye, V. N. Padmanabhan, L. Qiu, A. Rao, and B. Zill. Estimation of link interference in static multi-hop wireless networks. In Proc. of Internet Measurement Conference (IMC), Oct. 2005.

Digital Library

[2]

G. Bianchi. Performance analysis of the IEEE 802.11 distributed coordination function. In IEEE Journal on Selected Areas in Communications, Mar. 2000.

Digital Library

[3]

H. Chang, V. Misra, and D. Rubenstein. A general model and analysis of physical layer capture in 802.11 networks. In Proc. of IEEE INFOCOM, Apr. 2006.

[4]

Y. Cheng, J. Bellardo, P. Benko, A. C. Snoeren, G. M. Voelker, and S. Savage. Jigsaw: Solving the puzzle of enterprise 802.11 analysis. In Proc. of ACM SIGCOMM, Sept. 2006.

Digital Library

[5]

D. D. Couto, D. Aguayo, J. Bicket, and R. Morris. A high-throughput path metric for multi-hop wireless routing. In Proc. of ACM MOBICOM, Sept. 2003.

Digital Library

[6]

R. Draves, J. Padhye, and B. Zill. Routing in multi-radio, multi-hop wireless mesh networks. In Proc. of ACM MOBICOM, Sept. - Oct. 2004.

Digital Library

[7]

L. F. Fenton. The sum of lognormal probability distributions in scatter transmission systems. IRE Trans. Commun. Syst., CS-8, 1960.

[8]

Y. Gao, J. Lui, and D. M. Chiu. Determining the end-to-end throughput capacity in multi-hop networks: Methodolgy and applications. In Proc. of ACM SIGMETRICS, Jun. 2006.

Digital Library

[9]

M. Garetto, J. Shi, and E. Knightly. Modeling media access in embedded two-flow topologies of multi-hop wireless networks. In Proc. of ACM MOBICOM, Aug. - Sept. 2005.

Digital Library

[10]

P. Gupta and P. R. Kumar. The capacity of wireless networks. IEEE Transactions on Information Theory, 46(2), Mar. 2000.

[11]

K. Jain, J. Padhye, V. N. Padmanabhan, and L. Qiu. Impact of interference on multi-hop wireless network performance. In Proc. of ACM MOBICOM, Sept. 2003.

Digital Library

[12]

V. Kawadia and P. R. Kumar. Principles and protocols for power control in ad hoc networks. In IEEE Journal on Selected Areas in Communications (JSAC), Jan. 2005.

[13]

A. Kochut, A. Vasan, A. U. Shankar, and A. Agrawala. Sniffing out the correct physical layer capture model in 802.11b. In Proc. of ICNP, Oct. 2004.

Digital Library

[14]

D. Kotz, C. Newport, and C. Elliott. The mistaken axioms of wireless-network research. Technical Report TR2003-467, Dartmouth College, Computer Science, Jul. 2003.

[15]

J. B. Krawczyk and S. Berridge. Relaxation algorithms in finding Nash equilibria. In Computational Economics from Economics Working Paper Archive at WUSTL, Jul. 1997.

[16]

A. Kumar, E. Altman, D. Miorandi, and M. Goyal. New insights from a fixed point analysis of single cell IEEE 802.11 wireless LANs. In Proc. of IEEE INFOCOM, Mar. 2005.

[17]

V. S. A. Kumar and M. Marathe. Algorithmic aspects of capacity in wireless networks. In Proc. of ACM SIGMETRICS, Jun. 2005.

Digital Library

[18]

J. Li, C. Blake, D. S. J. D. Couto, H. I. Lee, and R. Morris. Capacity of ad hoc wireless networks. In Proc. of ACM MOBICOM, Jul. 2001.

Digital Library

[19]

Z. Li, S. Nandi, and A. K. Gupta. Improving fairness in IEEE 802.11 using enhanced carrier sensing. In IEEE Communications, Oct. 2004.

[20]

D. Malone, K. Duffy, and D. Leith. Modeling the 802.11 distributed coordination function in nonsaturated heterogeneous conditions. IEEE/ACM Transactions on Networking, 15(1), Feb. 2007.

Digital Library

[21]

A. Mishra, V. Brik, S. Banerjee, A. Srinivasan, and W. Arbaugh. A client-driven approach for channel management in wireless LANs. In Proc. of IEEE Infocom, Apr. 2006.

[22]

L. M. S. C. of the IEEE Computer Society. Wireless LAN medium access control (MAC) and physical layer (PHY) specifications. IEEE Standard 802.11, 1999.

[23]

C. C. Paige and M. A. Saunders. LSQR: An algorithm for sparse linear equations and sparse least squares. ACM Trans. Math. Soft., 1982.

Digital Library

[24]

C. Reis, R. Mahajan, M. Rodrig, D. Wetherall, and J. Zahorjan. Measurement-based models of delivery and interference. In Proc. of ACM SIGCOMM, Sept. 2006.

Digital Library

[25]

E. Rozner, Y. Mehta, A. Akella, and L. Qiu. Traffic-aware channel assignment in enterprise wireless networks. In Proc. of ICNP, Oct. 2007.

[26]

S. Schwartz and Y. Yeh. On the distribution function and moments of power sums with lognormal distributions. Bell Systems Technical Journal, 61, 1982.

[27]

M. Takai, J. Martin, and R. Bagrodia. Effects of wireless physical layer modeling in mobile ad hoc networks. In Proc. of ACM MOBIHOC, Oct. 2001.

Digital Library

Cited By

Zhao JHe LHu FKumar S(2024)Directional Multicast Routing in Mobile Networks Through Tracking of Directional Interference DynamicsIEEE Access10.1109/ACCESS.2024.346696712(144750-144763)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3466967
Oyedare TShah VJakubisin DReed J(2023)Keep It Simple: CNN Model Complexity Studies for Interference Classification TasksIEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)10.1109/INFOCOMWKSHPS57453.2023.10226045(1-6)Online publication date: 20-May-2023
https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10226045
Kim DLee JKim MKim JLee JHeo DKim S(2023)The Effect of Wireless Communication Interference on Wireless BCI2023 11th International Winter Conference on Brain-Computer Interface (BCI)10.1109/BCI57258.2023.10078549(1-4)Online publication date: 20-Feb-2023
https://doi.org/10.1109/BCI57258.2023.10078549
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Index Terms

A general model of wireless interference
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis
      1. Modeling methodologies

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cover image ACM Conferences

MobiCom '07: Proceedings of the 13th annual ACM international conference on Mobile computing and networking

September 2007

370 pages

ISBN:9781595936813

DOI:10.1145/1287853

General Chair:
Evangelos Kranakis
Carleton University, Canada
,
Program Chairs:
Jennifer Hou
University of Illinois, Urbana-Champaign, USA
,
Ram Ramanathan
BBN Technologies, USA

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 09 September 2007

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MobiCom/MobiHoc '07

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MobiCom/MobiHoc '07: The Thirteenth Annual International Conference on Mobile Computing and Networking and The 8th ACM International Symposium on Mobile Ad Hoc Networking and Computing

September 9 - 14, 2007

Québec, Montréal, Canada

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https://doi.org/10.1109/ACCESS.2024.3466967
Oyedare TShah VJakubisin DReed J(2023)Keep It Simple: CNN Model Complexity Studies for Interference Classification TasksIEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)10.1109/INFOCOMWKSHPS57453.2023.10226045(1-6)Online publication date: 20-May-2023
https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10226045
Kim DLee JKim MKim JLee JHeo DKim S(2023)The Effect of Wireless Communication Interference on Wireless BCI2023 11th International Winter Conference on Brain-Computer Interface (BCI)10.1109/BCI57258.2023.10078549(1-4)Online publication date: 20-Feb-2023
https://doi.org/10.1109/BCI57258.2023.10078549
Siapoush MAlves-Foss J(2023)Is Formal Verification of seL4 Adequate to Address the Key Security Challenges of Kernel Design?IEEE Access10.1109/ACCESS.2023.331603111(101750-101759)Online publication date: 2023
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