Efficient resource allocation scheme for visible-light communication system

2009 ◽  
Author(s):  
Woo-Chan Kim ◽  
Chi-Sung Bae ◽  
Dong-Ho Cho ◽  
Hong-Seok Shin ◽  
D. K. Jung ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Visible Light ◽  
Communication System ◽  
Visible Light Communication ◽  
Allocation Scheme ◽  
Efficient Resource ◽  
Resource Allocation Scheme

scholarly journals Cell Traffic Prediction Based on Convolutional Neural Network for Software-Defined Ultra-Dense Visible Light Communication Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Shanjun Zhan ◽  
Lisu Yu ◽  
Zhen Wang ◽  
Yichen Du ◽  
Yan Yu ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Energy Consumption ◽  
Visible Light ◽  
Visible Light Communication ◽  
High Energy ◽  
Training Dataset ◽  
Allocation Scheme ◽  
Control Plane ◽  
Data Plane ◽  
Resource Allocation Scheme

With the explosive growth of ubiquitous mobile services and the advent of the 5G era, ultra-dense wireless network (UDN) architectures have entered daily production and life. However, the massive access capacity provided by 5G networks and the dense deployment of micro base stations also bring challenges such as high energy consumption, high maintenance costs, and inflexibility. Fiber-based visible light communication (FVLC) has the advantages of large bandwidth and high speed, which provides an efficient connection option for UDN. Thus, in order to make up for the poor flexibility of UDN, we propose a new FVLC-UDN architecture based on software-defined networks (SDNs). Specifically, SDN decouples the data plane and the control plane of the device and centralizes the control of the LED in the cell through a unified control plane, which can not only improve the resource allocation ability of the network but also transmit the data only as the data plane, reducing the manufacturing and implementation costs of the LED. In order to get a better resource allocation scheme, this paper proposes a model for predicting cell traffic based on convolutional neural networks. By predicting the traffic of each cell in the control domain, the traffic trend and cells’ status in the future period of time in the control domain can be obtained, so that a much more efficient resource allocation scheme can be formulated proactively to reduce energy consumption and balance communication loads. The experimental results show that on the real cell traffic dataset, this method is better than the existing prediction methods when the size of training dataset is limited.

scholarly journals Energy-Efficient Incentives Resource Allocation Scheme in Cooperative Communication System

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Zi Yan Liu ◽  
Pan Mao ◽  
Li Feng ◽  
Shi Mei Liu
Keyword(s):  
Resource Allocation ◽  
Energy Efficiency ◽  
Cooperative Communication ◽  
Communication System ◽  
Allocation Scheme ◽  
Network Nodes ◽  
Intelligent Water Drops Algorithm ◽  
Water Drops ◽  
Resource Allocation Scheme ◽  
Qos Performance

Appropriate resource allocation has great significance to enhance the energy efficiency (EE) for cooperative communication system. The objective is to allocate the resource to maximize the energy efficiency in single-cell multiuser cooperative communication system. We formulate this problem as subcarrier-based resource allocation and solve it with path planning in graph theory. A two-level neural network model is designed, in which the users and subcarrier are defined as network nodes. And then we propose an improved intelligent water drops algorithm combined with Genetic Algorithm; boundary condition and initialization rules of path soil quantity are put forward. The simulation results demonstrate that the proposed resource allocation scheme can effectively improve the energy efficiency and enhance QoS performance.

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