TY - GEN

T1 - Local interference pricing for distributed beamforming in MIMO networks

AU - Shi, Changxin

AU - Berry, Randall A.

AU - Honig, Michael L.

PY - 2009

Y1 - 2009

N2 - We study a distributed algorithm for adjusting beamforming vectors in a peer-to-peer wireless network with multiple-input multiple-output (MIMO) channels. Each transmitter precoding matrix has rank one, and a linear minimum mean squared error (MMSE) filter is applied at each receiver. Our objective is to maximize the total utility summed over all users, where each user's utility is a function of the received signal-to-interference-plus-noise ratio (SINR). Given all users' beamforming vectors and receive filters, each receiver announces an interference price, representing the marginal cost of interference from other users. A particular transmitter updates its beamforming vector to maximize its utility minus the interference cost to other users. We show that if the utility functions satisfy certain concavity conditions, then the total utility is non-decreasing with each update. We also present numerical results that illustrate the effect of ignoring interference prices from all but the closest users, and relaxing requirements on the frequency of beam and price updates.

AB - We study a distributed algorithm for adjusting beamforming vectors in a peer-to-peer wireless network with multiple-input multiple-output (MIMO) channels. Each transmitter precoding matrix has rank one, and a linear minimum mean squared error (MMSE) filter is applied at each receiver. Our objective is to maximize the total utility summed over all users, where each user's utility is a function of the received signal-to-interference-plus-noise ratio (SINR). Given all users' beamforming vectors and receive filters, each receiver announces an interference price, representing the marginal cost of interference from other users. A particular transmitter updates its beamforming vector to maximize its utility minus the interference cost to other users. We show that if the utility functions satisfy certain concavity conditions, then the total utility is non-decreasing with each update. We also present numerical results that illustrate the effect of ignoring interference prices from all but the closest users, and relaxing requirements on the frequency of beam and price updates.

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U2 - 10.1109/MILCOM.2009.5379907

DO - 10.1109/MILCOM.2009.5379907

M3 - Conference contribution

AN - SCOPUS:77951469460

SN - 9781424452385

T3 - Proceedings - IEEE Military Communications Conference MILCOM

BT - MILCOM 2009 - 2009 IEEE Military Communications Conference

T2 - 2009 IEEE Military Communications Conference, MILCOM 2009

Y2 - 18 October 2009 through 21 October 2009

ER -