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Practical decentralized high-performance coordinated beamforming

Authors: Enoch Lu; I-Tai Lu;

Practical decentralized high-performance coordinated beamforming

Abstract

Coordinated Beamforming (CBF) has been studied in hope of mitigating the inter-cell interference experienced by cell-edge users. Unfortunately, due to the limitations and/or impracticalities of the proposed designs, the expected performance gains have yet to be realized. In this work, a decentralized framework (and various example designs) is proposed for the practical transceiver and signaling design of a K-pair system desiring to employ CBF. Relying on channel soundings from the users and equivalent channel soundings from the cell sites (all on the same frequency), the optimum performance of centralized interference alignment designs is achieved (if not surpassed) when each pair's number of data streams is equal to its user's number of antennas. In addition, higher sum capacities than the generalized iterative approach, a centralized MMSE CBF design, are numerically observed. Clearly, practical CBF designs which can deliver the expected performance gains are finally available.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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