Opportunistic Matrix Precoding for Non-Separable Wireless MIMO-NOMA Networks

Hsiao Ting Chiu, Rung-Hung Gau

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

3 Scopus citations

Abstract

In this paper, we propose an opportunistic matrix precoding algorithm for non-separable wireless MIMO-NOMA networks. It is known that NOMA is beneficial when the difference between two channel gains is very large and therefore the two channels are separable. We study general wireless MIMO-NOMA networks in which the two channels might be non-separable. Based on channel state information, we formulate and solve a non-convex optimization problem in order to maximize the sum rate and provide guaranteed rate to the weaker user. We divide the non-convex optimization problem into two parts and propose algorithms for solving them. Our simulation results show that the proposed algorithm could significantly increase the sum rate for non-separable wireless MIMO- NOMA networks in comparison with a number of alternative approaches.

Original languageEnglish
Title of host publication2018 IEEE 87th Vehicular Technology Conference, VTC Spring 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538663554
DOIs
StatePublished - 20 Jul 2018
Event87th IEEE Vehicular Technology Conference, VTC Spring 2018 - Porto, Portugal
Duration: 3 Jun 20186 Jun 2018

Publication series

NameIEEE Vehicular Technology Conference
Volume2018-June
ISSN (Print)1550-2252

Conference

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

Keywords

  • matrix precoding
  • MIMO
  • NOMA
  • non-convex optimization
  • non-separable channels

Fingerprint Dive into the research topics of 'Opportunistic Matrix Precoding for Non-Separable Wireless MIMO-NOMA Networks'. Together they form a unique fingerprint.

Cite this