4.7 Article

Non-Orthogonal Multiple Access With Improper Gaussian Signaling

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSTSP.2019.2901993

关键词

Transmission beamforming; improper Gaussian signaling (IGS); non-orthogonal multiple access (NOMA); multicell networks; nonconvex optimization; 2 x 2 linear matrix inequality

资金

  1. Institute for Computational Science and Technology, Hochiminh City, Vietnam
  2. Australian Research Councils Discovery Projects [DP190102501]
  3. Natural Sciences and Engineering Research Council of Canada (NSERC) [RGPIN-2017-05899]
  4. U.K. Royal Academy of Engineering Research Fellowship [RF1415\14\22]
  5. U.S. National Science Foundation [CCF-0939370, CCF-1513915]
  6. Vietnam National Foundation for Science and Technology Development (NAFOSTED) [102.04-2017.301]
  7. KFUPM Research Project [SB171005]

向作者/读者索取更多资源

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 x 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.

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