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.

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 Performance Comparison of Practical Resource Allocation Schemes for Device-to-Device Communications

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Gábor Fodor
Keyword(s):  
Resource Allocation ◽  
Power Control ◽  
Large Scale ◽  
Low Complexity ◽  
Base Station ◽  
Performance Comparison ◽  
Superior Performance ◽  
Channel Gain ◽  
D2d Communications ◽  
Device To Device

Device-to-device (D2D) communications in cellular spectrum have the potential of increasing the spectral and energy efficiency by taking advantage of the proximity and reuse gains. Although several resource allocation (RA) and power control (PC) schemes have been proposed in the literature, a comparison of the performance of such algorithms as a function of the available channel state information has not been reported. In this paper, we examine which large scale channel gain knowledge is needed by practically viable RA and PC schemes for network assisted D2D communications. To this end, we propose a novel near-optimal and low-complexity RA scheme that can be advantageously used in tandem with the optimal binary power control scheme and compare its performance with three heuristics-based RA schemes that are combined either with the well-known 3GPP Long-Term Evolution open-loop path loss compensating PC or with an iterative utility optimal PC scheme. When channel gain knowledge about the useful as well as interfering (cross) channels is available at the cellular base station, the near-optimal RA scheme, termed Matching, combined with the binary PC scheme is superior. Ultimately, we find that the proposed low-complexity RA + PC tandem that uses some cross-channel gain knowledge provides superior performance.

scholarly journals Energy-Efficient Power Allocation and Relay Selection Schemes for Relay-Assisted D2D Communications in 5G Wireless Networks

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2865 ◽  
Author(s):  
Md Rahman ◽  
YoungDoo Lee ◽  
Insoo Koo
Keyword(s):  
Wireless Networks ◽  
Power Allocation ◽  
Relay Selection ◽  
Base Station ◽  
Data Rate ◽  
Transmission Power ◽  
D2d Communications ◽  
Long Distance ◽  
Inference System ◽  
Efficient Power

Device-to-device (D2D) communications allows user equipment (UE) that are in close proximity to communicate with each other directly without using a base station. Relay-assisted D2D (RA-D2D) communications in 5G networks can be applied to support long-distance users and to improve energy efficiency (EE) of the networks. In this paper, we first establish a multi-relay system model where the D2D UEs can communicate with each other by reusing only one cellular uplink resource. Then, we apply an adaptive neuro-fuzzy inference system (ANFIS) architecture to select the best D2D relay to forward D2D source information to the expected D2D destination. Efficient power allocation (PA) in the D2D source and the D2D relay are critical problems for operating such networks, since the data rate of the cellular uplink and the maximum transmission power of the system need to be satisfied. As is known, 5G wireless networks also aim for low energy consumption to better implement the Internet of Things (IoT). Consequently, in this paper, we also formulate a problem to find the optimal solutions for PA of the D2D source and the D2D relay in terms of maximizing the EE of RA-D2D communications to support applications in the emerging IoT. To solve the PA problems of RA-D2D communications, a particle swarm optimization algorithm is employed to maximize the EE of the RA-D2D communications while satisfying the transmission power constraints of the D2D users, minimum data rate of cellular uplink, and minimum signal-to-interference-plus-noise-ratio requirements of the D2D users. Simulation results reveal that the proposed relay selection and PA methods significantly improve EE more than existing schemes.

scholarly journals Performance Analysis for Downlink MIMO-NOMA in Millimeter Wave Cellular Network with D2D Communications

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Jianguo Li ◽  
Xiangming Li ◽  
Aihua Wang ◽  
Neng Ye
Keyword(s):  
Outage Probability ◽  
Millimeter Wave ◽  
Cellular Network ◽  
High Reliability ◽  
Multiple Input Multiple Output ◽  
Ergodic Capacity ◽  
Base Station ◽  
Transmission Power ◽  
D2d Communications ◽  
Radio Access

Enabling nonorthogonal multiple access (NOMA) in device-to-device (D2D) communications under the millimeter wave (mmWave) multiple-input multiple-output (MIMO) cellular network is of critical importance for 5G wireless systems to support low latency, high reliability, and high throughput radio access. In this paper, the closed-form expressions for the outage probability and the ergodic capacity in downlink MIMO-NOMA mmWave cellular network with D2D communications are considered, which indicates that NOMA outperforms TDMA. The influencing factors of performance, such as transmission power and antenna number, are also analyzed. It is found that higher transmission power and more antennas in the base station can decrease the outage probability and enhance the ergodic capacity of NOMA.

scholarly journals Resource allocation for energy harvesting assisted D2D communications underlaying OFDMA cellular networks

2021 ◽  
Author(s):  
Shuo Yu ◽  
Ling Guan
Keyword(s):  
Resource Allocation ◽  
Energy Harvesting ◽  
Cellular Networks ◽  
Time Slot ◽  
Optimal Solution ◽  
Base Station ◽  
Multiple Time ◽  
Time Cost ◽  
D2d Communications ◽  
Transmission Process

D2D communications underlaying cellular networks has become very popular recently. Inter- ference between cellular users and D2D users is one of the tricky issues we need to solve. Another challenging issue is limited battery lives. In this thesis, we address these two issues together by introducing an energy harvesting (EH) assisted D2D model where the whole transmission process is divided into multiple time slots. At the beginning of every time slot, each D2D user will update the remaining energy level to the base station (BS) and the BS will then decide whether the D2D user should harvest energy or transmit data. The objective is to maximize sum throughput for all D2D users. To solve the problem, we first adopt the NOMAD algorithm, then propose a heuristic algorithm as sub-optimal solution. Numerical results show that our proposed algorithm can achieve almost the same sum throughput at a significantly smaller time cost.

WEIGHTED CHANNEL ALLOCATION AND POWER CONTROL FOR SELF-CONFIGURABLE INFRASTRUCTURE WLANS

2008 ◽  
Vol 09 (03) ◽  
pp. 299-316 ◽  
Author(s):  
SUPARERK MANITPORNSUT ◽  
BJÖRN LANDFELDT
Keyword(s):  
Power Control ◽  
Channel Assignment ◽  
Channel Allocation ◽  
Small Degree ◽  
Convergence Time ◽  
Transmission Power ◽  
Combined Method ◽  
Delay Sensitive ◽  
Assignment Algorithm ◽  
Large Channel

IEEE802.11 WLANs show increasing growth in popularity. Since these networks operate in the unlicensed ISM bands where the number of non-overlapping channels is limited, the growing number of wireless nodes leads to interference. It is well known that the interference leads to degraded performance of WLANs, especially in densely populated areas where the number of overlapping nodes is very large. Channel assignment algorithms have been proposed in recent years, in order to minimize or avoid interference between neighboring access points and hence alleviating the problem. In particular, weighted assignment algorithms have been frequently occurring in the literature. However, the effects of these algorithms are currently not well understood. In this paper, we present results, which show that weighted channel assignment algorithms that do not consider traffic categories can lead to heavy interference among WLANs with delay sensitive traffic, e.g. voice traffic. In order to overcome this, we instead propose a weighted access category channel assignment algorithm (WACCA). We present results from experiments, which show that WACCA achieves a small degree of Interference (DOI) as compared with a greedy algorithm. We also show that there is a tradeoff with convergence time. Furthermore, we propose an integration of WACCA with dynamic transmission power control and show how this combined method produces even more gain.

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