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

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Na Su ◽  
Qi Zhu ◽  
Ying Wang
Keyword(s):  
Energy Harvesting ◽  
Control Algorithm ◽  
Channel Allocation ◽  
Training Dataset ◽  
D2d Communications ◽  
Resource Allocation Algorithm ◽  
The Neural Network ◽  
Power Control Algorithm ◽  
Total Capacity

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). The algorithm considers users’ quality of service (QoS) and energy causality constraint to maximize the total capacity of D2D groups. The optimal offline allocation of channel and power is realized firstly. Then, the offline optimization results are taken as the training dataset to train the neural network to obtain the optimal model of the transmission power. The 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.

scholarly journals Power Control and Channel Allocation Algorithm for Energy Harvesting D2D Communications

Algorithms ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 93 ◽  
Author(s):  
Na Su ◽  
Qi Zhu
Keyword(s):  
Energy Harvesting ◽  
Power Control ◽  
Channel Allocation ◽  
Base Station ◽  
Transmission Power ◽  
D2d Communications ◽  
Harvesting Time ◽  
Allocation Algorithm ◽  
Total Capacity ◽  
Power And Energy

This paper assumes that multiple device-to-device (D2D) users can reuse the same uplink channel and base station (BS) supplies power to D2D transmitters by means of wireless energy transmission; the optimization problem aims at maximizing the total capacity of D2D users, and proposes a power control and channel allocation algorithm for the energy harvesting D2D communications underlaying the cellular network. This algorithm firstly uses a heuristic dynamic clustering method to cluster D2D users and those in the same cluster can share the same channel. Then, D2D users in the same cluster are modeled as a non-cooperative game, the expressions of D2D users’ transmission power and energy harvesting time are derived by using the Karush–Kuhn–Tucker (KKT) condition, and the optimal transmission power and energy harvesting time are allocated to D2D users by the joint iteration optimization method. Finally, we use the Kuhn–Munkres (KM) algorithm to achieve the optimal matching between D2D clusters and cellular channel to maximize the total capacity of D2D users. Simulation results show that the proposed algorithm can effectively improve the system performance.

Distributed Power Control for Cognitive Satellite Networks

2012 ◽  
Vol 490-495 ◽  
pp. 1156-1160 ◽  
Author(s):  
Li Na Wang ◽  
Bing Wang
Keyword(s):  
Power Control ◽  
Utility Function ◽  
Control Algorithm ◽  
Primary User ◽  
Satellite Networks ◽  
Distributed Power ◽  
Distributed Power Control ◽  
Power Control Algorithm ◽  
Simulation Results

In this paper, we considered the problem of distributed power control for cognitive satellite networks. We defined a utility function that measures the user’s satisfaction, as a function of signal to interference plus noise ratio. And then a distributed power control algorithm was proposed based on the defined utility function. This algorithm can guarantee the protection of the primary user and meet quality of service requirements of the cognitive users. Simulation results show the performance of the proposed power control algorithm.

An Efficient Power Control Algorithm with Dynamic Channel Allocation for TDD/CDMA Systems

2012 ◽  
Vol 562-564 ◽  
pp. 2049-2052
Author(s):  
Zhi Hua Zheng
Keyword(s):  
Power Control ◽  
Control Algorithm ◽  
Channel Allocation ◽  
Average Power ◽  
Base Stations ◽  
Dynamic Channel Allocation ◽  
Power Control Algorithm ◽  
Dynamic Channel ◽  
Inter Cell Interference ◽  
Efficient Power

Asymmetrical traffic service requirements between uplink (UL) and downlink (DL) will cause serious inter-cell interference in TDD/CDMA system. In this paper, an efficient power control algorithm with dynamic channel allocation (PC/DCA) is investigated, which is based on the average power control algorithms. In the uplink and downlink, PC/DCA scheme is addressed with channel reservation to resolve the interference between base-stations. Simulation results show that the performance of the PC/DCA scheme is improved 20% than that of the traditional DCA schemes for asymmetrical traffic service.

scholarly journals Resource Allocation for Downlink Full-Duplex Cooperative NOMA-Based Cellular System with Imperfect SI Cancellation and Underlaying D2D Communications

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2768
Author(s):  
Asmaa Amer ◽  
Abdel-Mehsen Ahmad ◽  
Sahar Hoteit
Keyword(s):  
Resource Allocation ◽  
Channel Assignment ◽  
Interference Cancellation ◽  
Channel Allocation ◽  
Base Station ◽  
Cellular System ◽  
Full Duplex ◽  
D2d Communications ◽  
Power Budget

In this paper, the interplay between non-orthogonal multiple access (NOMA), device-to-device (D2D) communication, full-duplex (FD) technology, and cooperation networks is proposed, and a resource allocation problem is investigated. Specifically, a downlink FD cooperative NOMA-based cellular system with underlaying D2D communications is proposed, where, in each NOMA group, the strong user assists the weak user as an FD relay with imperfect self interference (SI) cancellation. In terms of reaping spectral efficiency benefits, the system sum rate is to be maximized by optimizing channel allocation. This optimization is based on quality of service (QoS) constraints of D2D pairs and cellular users (CUs), power budget of base station and strong user (cooperative phase), and successive interference cancellation (SIC) constraints. Since the maximization formulated problem is computationally challenging to be addressed, a two-sided stable many-to-one matching algorithm, based on Pareto improvement, performs sub-channel assignment. Extensive simulations are implemented to demonstrate the system performance indicated by different metrics.

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