User Grouping, Precoding Design, and Power Allocation for MIMO-NOMA Systems

Byungjo Kim and Jae-Mo Kang ()
Additional contact information
Byungjo Kim: Electronics and Telecommunications Research Institute, Daejeon 34129, Republic of Korea
Jae-Mo Kang: Department of Artificial Intelligence, Kyungpook National University, Daegu 41566, Republic of Korea

Mathematics, 2023, vol. 11, issue 4, 1-10

Abstract: In this paper, we study user grouping, precoding design, and power allocation for multiple-input multiple-output (MIMO) nonorthogonal multiple access (NOMA) systems. An optimization problem is formulated to the maximize the sum rate under a transmit power constraint at a base station and rate constraints on users, which are nonconvex and combinatorial and thus very challenging to solve. To tackle this problem, we carry out the optimization in two steps. In the first step, exploiting the machine learning technique, we develop an efficient iterative algorithm for user grouping and precoding design. In the second step, we develop a power-allocation scheme in closed form by recasting the original problem into a useful and tractable convex form. The numerical results demonstrate that the proposed joint scheme, including user grouping, precoding design, and power allocation, considerably outperforms the existing schemes in terms of sum rate maximization, which increases the sum-rate up to 8–18%. In addition, the results show the larger the number of antennas or users, the bigger the performance gap, at the cost of less computational complexity.

Keywords: MIMO; machine learning; NOMA; power allocation; precoding design; user clustering; sum rate maximization; power resources (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/11/4/995/pdf (application/pdf)
https://www.mdpi.com/2227-7390/11/4/995/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:11:y:2023:i:4:p:995-:d:1069695

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().