Non-Orthogonal Multiple Access with Improper Gaussian Signaling

Hoang Duong Tuan, Ali Arshad Nasir, Ha H. Nguyen, Trung Q. Duong, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Improper Gaussian signaling (IGS) helps to improve the throughput of a wireless communication network by taking advantage of the additional degrees of freedom in signal processing at the transmitter. This paper exploits IGS in a general multiuser multi-cell network, which is subject to both intra-cell and inter-cell interference. With IGS under orthogonal multiple access (OMA) or non-orthogonal multiple access (NOMA), designs of transmit beamforming to maximize the users' minimum throughput subject to transmit power constraints are addressed. Such designs are mathematically formulated as nonconvex optimization problems of structured matrix variables, which cannot be solved by popular techniques such as weighted minimum mean square error or convex relaxation. By exploiting the lowest computational complexity of 2× 2 linear matrix inequalities, lower concave approximations are developed for throughput functions, which are the main ingredients for devising efficient algorithms for finding solution of these difficult optimization problems. Numerical results obtained under practical scenarios reveal that there is an almost two-fold gain in the throughput by employing IGS instead of the conventional proper Gaussian signaling under both OMA and NOMA; and NOMA-IGS offers better throughput compared to that achieved by OMA-IGS.

Original languageEnglish (US)
Article number8653886
Pages (from-to)496-507
Number of pages12
JournalIEEE Journal on Selected Topics in Signal Processing
Volume13
Issue number3
DOIs
StatePublished - Jun 2019

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • 2 × 2 linear matrix inequality
  • Transmission beamforming
  • improper Gaussian signaling (IGS)
  • multi-cell networks
  • non-orthogonal multiple access (NOMA)
  • nonconvex optimization

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