Gradient-Based Solution for Hybrid Precoding in MIMO Systems

Negin Bakhshi Zanjani*, Seyran Khademi, Geert Leus

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

6 Citations (Scopus)

Abstract

The combination of baseband and analog precoding for multiple-input multiple-output (MIMO) systems is considered in this paper which is referred to as hybrid precoding. The system capacity, as a design criterion, is maximized subject to unit modulus constraints on the elements of the analog precoder (phase shifters), and a total power constraint. This is a non-convex problem due to the product of the analog and baseband precoder variables. The proposed technique suggests computing non-trivial complex derivatives of the objective and constraints, analytically, in order to develop an iterative gradient-based sequential optimization algorithm to solve the non-convex problem. Promising simulation results show that the solution of the proposed algorithm is sufficiently close to the optimal (full-baseband) precoder solution, regardless of the channel characteristics.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
Subtitle of host publicationICASSP 2017
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages3489-3493
Number of pages5
ISBN (Electronic)978-1-5090-4117-6
DOIs
Publication statusPublished - 2017
EventICASSP 2017: 42nd IEEE International Conference on Acoustics, Speech and Signal Processing - The Internet of Signals - Hilton New Orleans Riverside, New Orleans, LA, United States
Duration: 5 Mar 20179 Mar 2017
Conference number: 42
http://www.ieee-icassp2017.org/

Conference

ConferenceICASSP 2017
Abbreviated titleICASSP
Country/TerritoryUnited States
CityNew Orleans, LA
Period5/03/179/03/17
Internet address

Keywords

  • hybrid precoding
  • multiple-input multiple-output (MIMO)
  • nonlinear optimization
  • sequential quadratic programming

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