TY - JOUR
T1 - Coordinated SLNR based Precoding in Large-Scale Heterogeneous Networks
AU - Boukhedimi, Ikram
AU - Kammoun, Abla
AU - Alouini, Mohamed-Slim
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR).
PY - 2017/3/6
Y1 - 2017/3/6
N2 - This work focuses on the downlink of large-scale two-tier heterogeneous networks composed of a macro-cell overlaid by micro-cell networks. Our interest is on the design of coordinated beamforming techniques that allow to mitigate the inter-cell interference. Particularly, we consider the case in which the coordinating base stations (BSs) have imperfect knowledge of the channel state information. Under this setting, we propose a regularized SLNR based precoding design in which the regularization factor is used to allow better resilience with respect to the channel estimation errors. Based on tools from random matrix theory, we provide an analytical analysis of the SINR and SLNR performances. These results are then exploited to propose a proper setting of the regularization factor. Simulation results are finally provided in order to validate our findings and to confirm the performance of the proposed precoding scheme.
AB - This work focuses on the downlink of large-scale two-tier heterogeneous networks composed of a macro-cell overlaid by micro-cell networks. Our interest is on the design of coordinated beamforming techniques that allow to mitigate the inter-cell interference. Particularly, we consider the case in which the coordinating base stations (BSs) have imperfect knowledge of the channel state information. Under this setting, we propose a regularized SLNR based precoding design in which the regularization factor is used to allow better resilience with respect to the channel estimation errors. Based on tools from random matrix theory, we provide an analytical analysis of the SINR and SLNR performances. These results are then exploited to propose a proper setting of the regularization factor. Simulation results are finally provided in order to validate our findings and to confirm the performance of the proposed precoding scheme.
UR - http://hdl.handle.net/10754/622979
UR - http://ieeexplore.ieee.org/document/7872443/
UR - http://www.scopus.com/inward/record.url?scp=85017869857&partnerID=8YFLogxK
U2 - 10.1109/JSTSP.2017.2678108
DO - 10.1109/JSTSP.2017.2678108
M3 - Article
SN - 1932-4553
VL - 11
SP - 534
EP - 548
JO - IEEE Journal of Selected Topics in Signal Processing
JF - IEEE Journal of Selected Topics in Signal Processing
IS - 3
ER -