Learning interference strategies in cognitive ARQ networks

Sina Firouzabadi; Marco Levorato; Daniel O'Neill; Andrea Goldsmith

doi:10.1109/GLOCOM.2010.5683502

Learning interference strategies in cognitive ARQ networks

Sina Firouzabadi, Marco Levorato, Daniel O'Neill, Andrea Goldsmith

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

10 Scopus citations

Abstract

Cognitive radios, which enable the coexistence on the same bandwidth of licensed primary and unlicensed secondary users, have the potential for dramatically increasing the efficiency of wireless networks. In this paper, we propose an on line learning algorithm to optimize the transmission strategy of secondary users in interference mitigation scenarios, where the secondary users are allowed to superimpose their transmission onto those of the primary users. Due to practical limitations, the secondary users have access to only a fraction of the current state of the primary users' network. Therefore, the strategy of the secondary users is defined on a reduced state space. Numerical results show that the proposed practical learning algorithm operates close to the performance of the system under full knowledge.

Original language	English (US)
Title of host publication	2010 IEEE Global Telecommunications Conference, GLOBECOM 2010
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781424456383
DOIs	https://doi.org/10.1109/GLOCOM.2010.5683502
State	Published - 2010
Externally published	Yes
Event	53rd IEEE Global Communications Conference, GLOBECOM 2010 - Miami, FL, United States Duration: Dec 6 2010 → Dec 10 2010

Publication series

Name	GLOBECOM - IEEE Global Telecommunications Conference

Other

Other	53rd IEEE Global Communications Conference, GLOBECOM 2010
Country/Territory	United States
City	Miami, FL
Period	12/6/10 → 12/10/10

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

Access to Document

10.1109/GLOCOM.2010.5683502

Cite this

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title = "Learning interference strategies in cognitive ARQ networks",

abstract = "Cognitive radios, which enable the coexistence on the same bandwidth of licensed primary and unlicensed secondary users, have the potential for dramatically increasing the efficiency of wireless networks. In this paper, we propose an on line learning algorithm to optimize the transmission strategy of secondary users in interference mitigation scenarios, where the secondary users are allowed to superimpose their transmission onto those of the primary users. Due to practical limitations, the secondary users have access to only a fraction of the current state of the primary users' network. Therefore, the strategy of the secondary users is defined on a reduced state space. Numerical results show that the proposed practical learning algorithm operates close to the performance of the system under full knowledge.",

author = "Sina Firouzabadi and Marco Levorato and Daniel O'Neill and Andrea Goldsmith",

year = "2010",

doi = "10.1109/GLOCOM.2010.5683502",

language = "English (US)",

isbn = "9781424456383",

series = "GLOBECOM - IEEE Global Telecommunications Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2010 IEEE Global Telecommunications Conference, GLOBECOM 2010",

address = "United States",

note = "53rd IEEE Global Communications Conference, GLOBECOM 2010 ; Conference date: 06-12-2010 Through 10-12-2010",

}

Firouzabadi, S, Levorato, M, O'Neill, D & Goldsmith, A 2010, Learning interference strategies in cognitive ARQ networks. in 2010 IEEE Global Telecommunications Conference, GLOBECOM 2010., 5683502, GLOBECOM - IEEE Global Telecommunications Conference, Institute of Electrical and Electronics Engineers Inc., 53rd IEEE Global Communications Conference, GLOBECOM 2010, Miami, FL, United States, 12/6/10. https://doi.org/10.1109/GLOCOM.2010.5683502

Learning interference strategies in cognitive ARQ networks. / Firouzabadi, Sina; Levorato, Marco; O'Neill, Daniel et al.
2010 IEEE Global Telecommunications Conference, GLOBECOM 2010. Institute of Electrical and Electronics Engineers Inc., 2010. 5683502 (GLOBECOM - IEEE Global Telecommunications Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Learning interference strategies in cognitive ARQ networks

AU - Firouzabadi, Sina

AU - Levorato, Marco

AU - O'Neill, Daniel

AU - Goldsmith, Andrea

PY - 2010

Y1 - 2010

N2 - Cognitive radios, which enable the coexistence on the same bandwidth of licensed primary and unlicensed secondary users, have the potential for dramatically increasing the efficiency of wireless networks. In this paper, we propose an on line learning algorithm to optimize the transmission strategy of secondary users in interference mitigation scenarios, where the secondary users are allowed to superimpose their transmission onto those of the primary users. Due to practical limitations, the secondary users have access to only a fraction of the current state of the primary users' network. Therefore, the strategy of the secondary users is defined on a reduced state space. Numerical results show that the proposed practical learning algorithm operates close to the performance of the system under full knowledge.

AB - Cognitive radios, which enable the coexistence on the same bandwidth of licensed primary and unlicensed secondary users, have the potential for dramatically increasing the efficiency of wireless networks. In this paper, we propose an on line learning algorithm to optimize the transmission strategy of secondary users in interference mitigation scenarios, where the secondary users are allowed to superimpose their transmission onto those of the primary users. Due to practical limitations, the secondary users have access to only a fraction of the current state of the primary users' network. Therefore, the strategy of the secondary users is defined on a reduced state space. Numerical results show that the proposed practical learning algorithm operates close to the performance of the system under full knowledge.

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U2 - 10.1109/GLOCOM.2010.5683502

DO - 10.1109/GLOCOM.2010.5683502

M3 - Conference contribution

AN - SCOPUS:79551644208

SN - 9781424456383

T3 - GLOBECOM - IEEE Global Telecommunications Conference

BT - 2010 IEEE Global Telecommunications Conference, GLOBECOM 2010

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 53rd IEEE Global Communications Conference, GLOBECOM 2010

Y2 - 6 December 2010 through 10 December 2010

ER -

Learning interference strategies in cognitive ARQ networks

Abstract

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Other

All Science Journal Classification (ASJC) codes

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