Resource Allocation for MC MISO-NOMA SWIPT-Enabled HetNets With Non-Linear Energy Harvesting

IEEE Access

Zhu Han¹  Siavash Bayat²  Ata Khalili² 

[1] Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA;Electronics Research Institute, Sharif University of Technology, Tehran, Iran;

关键词: Multi carrier (MC);    multiple input single output (MISO);    non-orthogonal multiple access (NOMA);    simultaneous wireless information and power transfer (SWIPT);    subcarrier assignment;    beamforming design;   

DOI  :  10.1109/ACCESS.2020.3032661

来源: DOAJ

【 摘 要 】

This article proposes a resource allocation for multi carrier (MC) multiple input single output (MISO) non-orthogonal multiple access (NOMA) enabling simultaneous wireless information and power transfer (SWIPT) where a separated architecture (SA)-based heterogeneous network (HetNet) is considered. More precisely, we focus on designing MC MISO-NOMA scheme in HetNets, where each base stations (BSs) serves multiple information decoding (ID) and energy harvesting (EH) users with a non-linear energy harvesting model which are equipped with multi antennas. For this configuration, we propose a joint subcarrier assignment, beamforming design, and energy beamforming to maximize the total rate of the network. Moreover, we take into account the condition of cross-layer interference constraints to coordinate interference, satisfying a minimum data rate requirement, fulfilling a minimum harvested energy, and respecting the maximum allowed power transfer constraints. We also consider successive interference cancellation (SIC) decoding order to detect the signal of each user due to coupling between SIC order, beamforming design, and subcarrier allocation. As a result of interference in the rate function, our optimization problem is non-convex and thus challenging to solve. Subsequently, first we adopt semi-definite relaxation (SDR) for beamforming design and then an efficient algorithm via the majorization minimization (MM) approach based on the difference of convex (DC) programming is proposed to obtain a locally optimal solution for the original problem. Simulation results reveal the superiority of our proposed scheme as compared to other existing works addressed in the literature.

【 授权许可】

Unknown