Performance analysis of block diagonalization linear precoding technique on multi user MIMO-GFDM system using MMSE detector

Endah Wulansari*, Titiek Suryani, Endroyono

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The implementation of the MIMO system for services to multiple users (known as Multi User-MIMO) is required for 5G communication systems. Generalized Frequency Division Multiplexing (GFDM) is a flexible multi-carrier transmission with non-orthogonal waveforms and fewer subcarriers are able to overcome OFDM weaknesses, namely high peak-to-average power ratio (PAPR) and out-of-band (OOB) emissions. The existence of MU-MIMO cause interference among users that can be overcome with Block Diagonalization linear precoding technique. The use of multiple antennas on each user can be mitigated by detector techniques. In this paper, we analyze the combined performance of BD precoding on the transmitter and the Minimum Mean Square Error (MMSE) detector on the receiver of the MU MIMO-GFDM system. The simulation results show that MU MIMO-GFDM using root raised cosine (RRC) pulse superior to MU MIMO-OFDM using rectangular pulse in BER and PAPR performance.

Original languageEnglish
Title of host publicationAPWiMob 2017 - IEEE Asia Pacific Conference on Wireless and Mobile, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages94-100
Number of pages7
ISBN (Electronic)9781538623732
DOIs
Publication statusPublished - 2 Jul 2017
Event4th IEEE Asia Pacific Conference on Wireless and Mobile, APWiMob 2017 - Bandung, Indonesia
Duration: 28 Nov 201729 Nov 2017

Publication series

NameAPWiMob 2017 - IEEE Asia Pacific Conference on Wireless and Mobile, Proceedings
Volume2017-November

Conference

Conference4th IEEE Asia Pacific Conference on Wireless and Mobile, APWiMob 2017
Country/TerritoryIndonesia
CityBandung
Period28/11/1729/11/17

Keywords

  • Block Diagonalization (BD)
  • GFDM
  • MU-MIMO
  • Minimum Mean Square Error (MMSE)
  • PAPR

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