TY - GEN

T1 - Belief propagation methods for intercell interference coordination

AU - Rangan, Sundeep

AU - Madan, Ritesh

PY - 2011

Y1 - 2011

N2 - We consider a broad class of interference coordination and resource allocation problems for wireless links where the goal is to maximize the sum of functions of individual link rates. Such problems arise in the context of, for example, fractional frequency reuse (FFR) for macro-cellular networks and dynamic interference management in femtocells. The resulting optimization problems are typically hard to solve optimally even using centralized algorithms but are an essential computational step in implementing rate-fair and queue stabilizing scheduling policies in wireless networks. We consider a belief propagation framework to solve such problems approximately. In particular, we construct approximations to the belief propagation iterations to obtain computationally simple and distributed algorithms with low communication overhead. Notably, our methods are very general and apply to, for example, the optimization of transmit powers, transmit beamforming vectors, and sub-band allocation to maximize the above objective. Numerical results for femtocell deployments demonstrate that such algorithms compute a very good operating point in typically just a couple of iterations.

AB - We consider a broad class of interference coordination and resource allocation problems for wireless links where the goal is to maximize the sum of functions of individual link rates. Such problems arise in the context of, for example, fractional frequency reuse (FFR) for macro-cellular networks and dynamic interference management in femtocells. The resulting optimization problems are typically hard to solve optimally even using centralized algorithms but are an essential computational step in implementing rate-fair and queue stabilizing scheduling policies in wireless networks. We consider a belief propagation framework to solve such problems approximately. In particular, we construct approximations to the belief propagation iterations to obtain computationally simple and distributed algorithms with low communication overhead. Notably, our methods are very general and apply to, for example, the optimization of transmit powers, transmit beamforming vectors, and sub-band allocation to maximize the above objective. Numerical results for femtocell deployments demonstrate that such algorithms compute a very good operating point in typically just a couple of iterations.

KW - Interference coordination

KW - belief propagation

KW - cellular systems

KW - femtocells

KW - wireless communications

UR - http://www.scopus.com/inward/record.url?scp=79960875407&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79960875407&partnerID=8YFLogxK

U2 - 10.1109/INFCOM.2011.5935079

DO - 10.1109/INFCOM.2011.5935079

M3 - Conference contribution

AN - SCOPUS:79960875407

SN - 9781424499212

T3 - Proceedings - IEEE INFOCOM

SP - 2543

EP - 2551

BT - 2011 Proceedings IEEE INFOCOM

T2 - IEEE INFOCOM 2011

Y2 - 10 April 2011 through 15 April 2011

ER -