Multi-user hybrid precoding and decoding design for mm-wave large antenna systems

Osama Alluhaibi, Qasim Zeeshan Ahmed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Hybrid digital to analog (D-A) precoding and decoding design has recently been the focus of considerable fascination for reducing the number of costly radio- frequency (RF) chains in millimeter-wave (mm-Wave) systems. This paper investigates multi-user joint hybrid D-A precoding and decoding design for mm-Wave large antenna systems. The intrinsic focus of this work is to reduce the interference caused by users sharing the same scatterers during simultaneous uplink transmission. The analog precoder and decoder, firstly, are jointly designed using a Riemannian optimisation method based on Stiefel manifold (ROSt) in order to maximise the desired signal while reducing the interference. Then, the digital decoder is also designed jointly using Minimum Mean-Square Error (MMSE) based on effective channels. To significantly enhance the performance, an iterative algorithm is further presented that employs uplink and downlink effective channels. To accomplish this, the analog precoder and decoder are jointly designed based on downlink effective channels and steepest descent (SD) algorithm. Once again MMSE is applied for the digital decoder by exploiting effective channels. Extensive simulations demonstrate that the achievable rate of our proposed ROSt and SD algorithms surpasses the achievable rate of the existing algorithms in hybrid D-A paradigms.

LanguageEnglish
Title of host publication2018 IEEE 87th Vehicular Technology Conference, VTC Spring 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
Volume2018-June
ISBN (Electronic)9781538663554
DOIs
Publication statusPublished - 20 Jul 2018
Event87th IEEE Vehicular Technology Conference, VTC Spring 2018 - Porto, Portugal
Duration: 3 Jun 20186 Jun 2018

Conference

Conference87th IEEE Vehicular Technology Conference, VTC Spring 2018
CountryPortugal
CityPorto
Period3/06/186/06/18

Fingerprint

Precoding
Decoding
Antenna
Antennas
Analogue
Millimeter waves
Mean square error
Descent Algorithm
Steepest Descent
Millimeter Wave
Minimum Mean Square Error
Uplink
Interference
Stiefel Manifold
Iterative Algorithm
Optimization Methods
Sharing
Maximise
Paradigm
Design

Cite this

Alluhaibi, O., & Ahmed, Q. Z. (2018). Multi-user hybrid precoding and decoding design for mm-wave large antenna systems. In 2018 IEEE 87th Vehicular Technology Conference, VTC Spring 2018 - Proceedings (Vol. 2018-June). [8417789] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VTCSpring.2018.8417789
Alluhaibi, Osama ; Ahmed, Qasim Zeeshan. / Multi-user hybrid precoding and decoding design for mm-wave large antenna systems. 2018 IEEE 87th Vehicular Technology Conference, VTC Spring 2018 - Proceedings. Vol. 2018-June Institute of Electrical and Electronics Engineers Inc., 2018.
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Alluhaibi, O & Ahmed, QZ 2018, Multi-user hybrid precoding and decoding design for mm-wave large antenna systems. in 2018 IEEE 87th Vehicular Technology Conference, VTC Spring 2018 - Proceedings. vol. 2018-June, 8417789, Institute of Electrical and Electronics Engineers Inc., 87th IEEE Vehicular Technology Conference, VTC Spring 2018, Porto, Portugal, 3/06/18. https://doi.org/10.1109/VTCSpring.2018.8417789

Multi-user hybrid precoding and decoding design for mm-wave large antenna systems. / Alluhaibi, Osama; Ahmed, Qasim Zeeshan.

2018 IEEE 87th Vehicular Technology Conference, VTC Spring 2018 - Proceedings. Vol. 2018-June Institute of Electrical and Electronics Engineers Inc., 2018. 8417789.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Alluhaibi O, Ahmed QZ. Multi-user hybrid precoding and decoding design for mm-wave large antenna systems. In 2018 IEEE 87th Vehicular Technology Conference, VTC Spring 2018 - Proceedings. Vol. 2018-June. Institute of Electrical and Electronics Engineers Inc. 2018. 8417789 https://doi.org/10.1109/VTCSpring.2018.8417789