Distributed transmit beamforming in cellular networks - a convex optimization perspective

Ekbal, Amal; Cioffi, J.M.

doi:10.1109/icc.2005.1494837

Cited by 25 publications

(18 citation statements)

References 6 publications

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“…In [3], [4], intercell interference was reduced by minimizing the transmit power given a target signal-to-interferenceplus-noise ratio. Opportunistic beamforming approaches were analyzed in [5], [6] and dirty-paper coding was considered in [1], [7]- [9].…”

Section: Introductionmentioning

confidence: 99%

Circumventing base station cooperation through Kalman prediction of intercell interference

Bendlin

Huang

Ivrlač

et al. 2008

2008 42nd Asilomar Conference on Signals, Systems and Computers

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Abstract-We consider the downlink of a cellular multiple input single output (MISO) system with multiple users per cell. Fast scheduling and spatial signal processing at the base stations result in unpredictable non-stationary intercell interference when the base stations do not cooperate. We show how the per cell sum-rate can be increased when Kalman filters are employed to forecast the interference power for the next transmission. We compare these results for dirty-paper coding and beamforming to systems where the intercell interference powers are perfectly known through feedback channels or cooperating base stations and to systems where outdated information is used.

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Section: Introductionmentioning

confidence: 99%

Circumventing base station cooperation through Kalman prediction of intercell interference

Bendlin

Huang

Ivrlač

et al. 2008

2008 42nd Asilomar Conference on Signals, Systems and Computers

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“…Downlink beamforming utilising multiple BSs has been considered in [11], [13], [16]- [18], however the proposed solutions usually assume that there is a central processing centre or controller to process information or coordinate information exchange among BSs. Our main contribution in this paper is to demonstrate ways to implement the downlink beamformer in a truly distributed manner through message passing between neighbouring BSs, by exploiting the local interference structure of the channel.…”

Section: Introductionmentioning

confidence: 99%

Transmit beamforming with cooperative base stations

Evans

Hanly

et al. 2005

Proceedings. International Symposium on Information Theory, 2005. ISIT 2005.

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Abstract-We consider a cellular network where base stations can cooperate to determine the signals to be transmitted on the downlink. In such a scenario, it would be possible to use "macroscopic" transmit beamforming to improve system performance. The downlink beamformer of interest is generalised from some transmit beamformers that have been shown to meet various optimality criteria in the literature. The particular downlink beamformer structure enables us to recast our downlink beamforming problem as a virtual LMMSE estimation problem. Based on this virtual set up, we exploit the structure of the channel and develop distributed beamforming algorithms using local message passing between neighbouring base stations. Two algorithms are outlined, both of which are based on the Kalman smoothing framework. The first algorithm is a forward-backward algorithm that produces optimal performance, but it has the disadvantage of a delay that grows linearly with array size. The second algorithm, which is a limited extent algorithm, solves the delay problem by using only local information.

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“…Bounds to the sum-rate capacity supported by the downlink of the soft-handoff model has been reported in [22] [23] under per-cell power constraints. [52] consider multi-cell beamforming under minimum receive signal-to-interference ratio constraints, for a general cellular downlink channel model.…”

Section: Bibliographical Notesmentioning

confidence: 99%

An Information Theoretic View of Distributed Antenna Processing in Cellular Systems

2007

Wireless Networks and Mobile Communications

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Distributed transmit beamforming in cellular networks - a convex optimization perspective

Cited by 25 publications

References 6 publications

Circumventing base station cooperation through Kalman prediction of intercell interference

Circumventing base station cooperation through Kalman prediction of intercell interference

Transmit beamforming with cooperative base stations

An Information Theoretic View of Distributed Antenna Processing in Cellular Systems

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