Resource Allocation Algorithm for NOMA-Enhanced D2D Communications with Energy Harvesting

Abstract

In this work, we propose a channel allocation and power control algorithm for energy harvesting (EH) device-to-device (D2D) communication based on nonorthogonal multiple access (NOMA). e algorithm considers users' quality of service (QoS) and energy causality constraint to maximize the total capacity of D2D groups. e optimal offline allocation of channel and power is realized firstly. en, the offline optimization results are taken as the training dataset to train the neural network to obtain the optimal model of the transmission power. e online power allocation optimization algorithm is further proposed. Simulation results show that the offline algorithm can improve the total capacity of D2D groups, and the performance of the online algorithm is close to the offline algorithm.

Max–Min Fairness Optimization for D2D Communications Coexisting with Cellular Networks

“…For example, the utilization of max-min fairness for the DBM combined with heuristic pairing gives 78% of cellular users and D2D devices with a higher rate than 1.5 bit/s/Hz. This is 28% better than the corresponding method in [29] with the fixed QoS.…”

“…Figure 6 shows the feasible probability that computes the fraction of the number of cellular users/D2D devices who are served by the QoS not less than 1.5 bit/s/Hz and the total number of existing cellular users and D2D devices among the 2000 realizations of different locations. The fixed QoS was proposed in [11,29]. Those results demonstrate the significant improvements of the proposed max-min fairness optimization than a fixed QoS assignment, which provides the better feasible probability.…”

“…Particularly, we focus on the max-min fairness optimization problem. The proposed optimization framework has been proven by using and evaluating in the same models given in [11,29]. It is worth to noting that these models only optimize the total transmit power subjective the required QoSs for both cellular users and D2D devices.…”

Ultrahigh‐Dimensional Model and Optimization Algorithm for Resource Allocation in Large‐Scale Intelligent D2D Communication System

“…Su et al proposed an approach to maximize the total D2D groups capacity by considering the requirement of QoS and energy causality constraints. Simulation results verified the effectiveness of their methodology [11]. In order to reduce the cross-tier interference in D2D communication, Khazali et al proposed a fractional frequency reuse (FFR)-based spectrum partitioning scheme.…”

Resource Allocation for Energy Harvesting D2D Communications Underlaying NOMA Cellular Networks

“…Finally, a DNN based algorithm is deployed and it is proved that the DNN based algorithm gets a near optimal solution with much lower computational complexity. [48] also uses a feed forward neural network to predict the system capacity of the energy harvesting D2D communications based on non-orthogonal multiple access (NOMA). The problem is first solved using an offline algorithm and the data obtained from the offline optimization algorithm is further fed to the neural network as the training dataset.…”