Optimal Resource Allocation for Power-Efficient MC-NOMA With Imperfect Channel State Information

• Published in: IEEE transactions on communications Vol. 65; no. 9; pp. 3944 - 3961
• Main Authors: Zhiqiang Wei, Ng, Derrick Wing Kwan, Jinhong Yuan, Hui-Ming Wang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Complexity; Computational geometry; Computer simulation; Convex analysis; Convexity; Decoding; Design optimization; imperfect channel state information; Iterative methods; Mathematical programming; Noise measurement; Noise threshold; NOMA; Non-orthogonal multiple access; Nonorthogonal multiple access; Optimization; Power management; Quality of service; Resource allocation; Resource management; Silicon carbide; Subcarriers; User requirements
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2017.2709301

In this paper, we study power-efficient resource allocation for multicarrier non-orthogonal multiple access systems. The resource allocation algorithm design is formulated as a non-convex optimization problem which jointly designs the power allocation, rate allocation, user scheduling, and successive interference cancellation (SIC) decoding policy for minimizing the total transmit power. The proposed framework takes into account the imperfection of channel state information at transmitter and quality of service requirements of users. To facilitate the design of optimal SIC decoding policy on each subcarrier, we define a channel-to-noise ratio outage threshold. Subsequently, the considered non-convex optimization problem is recast as a generalized linear multiplicative programming problem, for which a globally optimal solution is obtained via employing the branch-and-bound approach. The optimal resource allocation policy serves as a system performance benchmark due to its high computational complexity. To strike a balance between system performance and computational complexity, we propose a suboptimal iterative resource allocation algorithm based on difference of convex programming. Simulation results demonstrate that the suboptimal scheme achieves a close-to-optimal performance. Also, both proposed schemes provide significant transmit power savings than that of conventional orthogonal multiple access schemes.