Globally optimal beamforming design for downlink CoMP transmission with limited backhaul capacity. Nguyen, K., G., Vu, Q., D., Juntti, M., & Tran, L., N. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pages 3649-3653, 2017.
abstract   bibtex   
This paper considers a multicell downlink channel in which multiple base stations (BSs) cooperatively serve users by jointly precoding shared data transported from a central processor over limited-capacity backhaul links. We jointly design the beamformers and BS-user link selection so as to maximize the sum rate subject to user-specific signal-to-interference-noise (SINR) requirements, per-BS backhaul capacity and per-BS power constraints. As existing solutions for the considered problem are suboptimal and their optimality remains unknown due to the lack of globally optimal solutions, we characterized this gap by proposing a globally optimal algorithm for the problem of interest. Specifically, the proposed method is customized from a generic framework of a branch and bound algorithm applied to discrete monotonic optimization. We show that the proposed algorithm converges after a finite number of iterations, and can serve as a benchmark for existing suboptimal solutions and those that will be developed for similar contexts in the future. In this regard, we numerically compare the proposed optimal solution to a current state-of-the-art, which show that this suboptimal method only attains 70% to 90% of the optimal performance.
@inProceedings{
 title = {Globally optimal beamforming design for downlink CoMP transmission with limited backhaul capacity},
 type = {inProceedings},
 year = {2017},
 identifiers = {[object Object]},
 keywords = {Multicell cooperation,discrete monotonic optimization,limited backhaul,sum rate maximization},
 pages = {3649-3653},
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 created = {2017-08-02T14:15:26.338Z},
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 last_modified = {2019-09-22T11:57:27.774Z},
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 abstract = {This paper considers a multicell downlink channel in which multiple base stations (BSs) cooperatively serve users by jointly precoding shared data transported from a central processor over limited-capacity backhaul links. We jointly design the beamformers and BS-user link selection so as to maximize the sum rate subject to user-specific signal-to-interference-noise (SINR) requirements, per-BS backhaul capacity and per-BS power constraints. As existing solutions for the considered problem are suboptimal and their optimality remains unknown due to the lack of globally optimal solutions, we characterized this gap by proposing a globally optimal algorithm for the problem of interest. Specifically, the proposed method is customized from a generic framework of a branch and bound algorithm applied to discrete monotonic optimization. We show that the proposed algorithm converges after a finite number of iterations, and can serve as a benchmark for existing suboptimal solutions and those that will be developed for similar contexts in the future. In this regard, we numerically compare the proposed optimal solution to a current state-of-the-art, which show that this suboptimal method only attains 70% to 90% of the optimal performance.},
 bibtype = {inProceedings},
 author = {Nguyen, Kien Giang and Vu, Quang Doanh and Juntti, Markku and Tran, Le Nam},
 booktitle = {ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings}
}
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