Energy efficient preceding C-RAN downlink with compression at fronthaul. Nguyen, K., G., Vu, Q., D., Juntti, M., & Tran, L., N. In IEEE International Conference on Communications, 2017.
abstract   bibtex   
© 2017 IEEE. This paper considers a downlink transmission of cloud radio access network (C-RAN) in which precoded baseband signals at a common baseband unit are compressed before being forwarded to radio units (RUs) through limited fronthaul capacity links. We investigate the joint design of precoding, multivariate compression and RU-user selection which maximizes the energy efficiency of downlink C-RAN networks. The considered problem is inherently a rank-constrained mixed Boolean nonconvex program for which a globally optimal solution is difficult and computationally expensive to find. In order to derive practically appealing solutions, we invoke some useful relaxation and transformation techniques to arrive at a more tractable (but still nonconvex) continuous program. To solve the relaxation problem, we propose an iterative procedure based on DC algorithms which is provably convergent. Numerical results demonstrate the superior of the proposed solution in terms of achievable energy efficiency compared to existing schemes.
@inProceedings{
 title = {Energy efficient preceding C-RAN downlink with compression at fronthaul},
 type = {inProceedings},
 year = {2017},
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 last_modified = {2019-09-22T11:57:28.907Z},
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 abstract = {© 2017 IEEE. This paper considers a downlink transmission of cloud radio access network (C-RAN) in which precoded baseband signals at a common baseband unit are compressed before being forwarded to radio units (RUs) through limited fronthaul capacity links. We investigate the joint design of precoding, multivariate compression and RU-user selection which maximizes the energy efficiency of downlink C-RAN networks. The considered problem is inherently a rank-constrained mixed Boolean nonconvex program for which a globally optimal solution is difficult and computationally expensive to find. In order to derive practically appealing solutions, we invoke some useful relaxation and transformation techniques to arrive at a more tractable (but still nonconvex) continuous program. To solve the relaxation problem, we propose an iterative procedure based on DC algorithms which is provably convergent. Numerical results demonstrate the superior of the proposed solution in terms of achievable energy efficiency compared to existing schemes.},
 bibtype = {inProceedings},
 author = {Nguyen, Kien Giang and Vu, Quang Doanh and Juntti, Markku and Tran, Le Nam},
 booktitle = {IEEE International Conference on Communications}
}
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