Dynamic Compression Method Using Wireless Resource Allocation for Digitized Radio over TDM-PON System

2014 ◽  
Author(s):  
Naotaka Shibata ◽  
Shigeru Kuwano ◽  
Jun Terada ◽  
Naoto Yoshimoto
Keyword(s):  
Resource Allocation ◽  
Dynamic Compression ◽  
Compression Method ◽  
Wireless Resource Allocation

scholarly journals A Resource Allocation Algorithm for Ultra-Dense Networks Based on Deep Reinforcement Learning

2021 ◽  
Vol 16 (2) ◽  
Author(s):  
Huashuai Zhang ◽  
Tingmei Wang ◽  
Haiwei Shen
Keyword(s):  
Resource Allocation ◽  
Reinforcement Learning ◽  
Data Traffic ◽  
Wireless Data ◽  
Resource Allocation Algorithm ◽  
Allocation Algorithm ◽  
Q Learning ◽  
Dense Networks ◽  
Target Network ◽  
Wireless Resource Allocation

The resource optimization of ultra-dense networks (UDNs) is critical to meet the huge demand of users for wireless data traffic. But the mainstream optimization algorithms have many problems, such as the poor optimization effect, and high computing load. This paper puts forward a wireless resource allocation algorithm based on deep reinforcement learning (DRL), which aims to maximize the total throughput of the entire network and transform the resource allocation problem into a deep Q-learning process. To effectively allocate resources in UDNs, the DRL algorithm was introduced to improve the allocation efficiency of wireless resources; the authors adopted the resource allocation strategy of the deep Q-network (DQN), and employed empirical repetition and target network to overcome the instability and divergence of the results caused by the previous network state, and to solve the overestimation of the Q value. Simulation results show that the proposed algorithm can maximize the total throughput of the network, while making the network more energy-efficient and stable. Thus, it is very meaningful to introduce the DRL to the research of UDN resource allocation.

Deep-Learning-Based Wireless Resource Allocation With Application to Vehicular Networks

2020 ◽  
Vol 108 (2) ◽  
pp. 341-356 ◽  
Author(s):  
Le Liang ◽  
Hao Ye ◽  
Guanding Yu ◽  
Geoffrey Ye Li
Keyword(s):  
Resource Allocation ◽  
Deep Learning ◽  
Vehicular Networks ◽  
Wireless Resource Allocation
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