Multiple access techniques for intelligent and multi-functional 6G: Tutorial, survey, and outlook
Multiple access (MA) is a crucial part of any wireless system and refers to techniques that
make use of the resource dimensions to serve multiple users/devices/machines/services …
make use of the resource dimensions to serve multiple users/devices/machines/services …
Uplink power control framework based on reinforcement learning for 5G networks
FHC Neto, DC Araújo, MP Mota… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
In this work, we propose an uplink power control (PC) framework compliant with the
technical specifications of the fifth generation (5G) wireless networks. We apply the …
technical specifications of the fifth generation (5G) wireless networks. We apply the …
Reinforcement Learning-Based Resource Allocation for Coverage Continuity in High Dynamic UAV Communication Networks
Unmanned aerial vehicles mounted aerial base stations (ABSs) are capable of providing on-
demand coverage in next-generation mobile communication system. However, resource …
demand coverage in next-generation mobile communication system. However, resource …
Reinforcement learning-based interference coordination for distributed MU-MIMO
In our previous studies, we proposed a graph coloring algorithm (GCA) based on heuristics
to solve the interference coordination problem for distributed multi-user multi-input multi …
to solve the interference coordination problem for distributed multi-user multi-input multi …
密集异构网络中基于多目标优化的资源分配策略.
靳冬慧， 陈硕， 王占刚 - Telecommunication Engineering, 2023 - search.ebscohost.com
密集异构网络中基于多目标优化的资源分配策略 Page 1 DOI:10. 20079/ j. issn. 1001-893x.
211220001 引用格式:靳冬慧,陈硕,王占刚. 密集异构网络中基于多目标优化的资源分配策略[J]. 电讯 …
211220001 引用格式:靳冬慧,陈硕,王占刚. 密集异构网络中基于多目标优化的资源分配策略[J]. 电讯 …
Resource Allocation in High Dynamic Multi-UAV Networks for Coverage Continuity: A Reinforcement Learning Approach
In next-generation mobile communication system, unmanned aerial vehicles mounted aerial
base stations (ABSs) are capable of providing on-demand coverage. However, resource …
base stations (ABSs) are capable of providing on-demand coverage. However, resource …
Time-variant Resource Allocation in Multi-Ap802. 11be Network: A DDPG-based Approach
Z Du, Y Liu, Y Yu, L Cuthbert - 2023 8th International …, 2023 - ieeexplore.ieee.org
With the development of the 802.11 be standard which incorporates Orthogonal Frequency
Division Multiple Access (OFDMA), there will be more real-world scenarios which have more …
Division Multiple Access (OFDMA), there will be more real-world scenarios which have more …
Joint Subcarrier and Power Allocation in Mobile Scenario of the OFDM Systems Based on Deep Reinforcement Learning
X Li, W Zhou, H Zhang, J Zhao… - 2023 8th International …, 2023 - ieeexplore.ieee.org
The increasing number of base station (BS) service users has made spectrum resources
more valuable, leading to the need for efficient resource allocation. To address this issue …
more valuable, leading to the need for efficient resource allocation. To address this issue …
Q-Learning-Based Spatial Reuse Enhancement of Wireless Networks
GU Patil, GA Kulkarni - Mobile Computing and Sustainable Informatics …, 2022 - Springer
In systems based on reinforcement learning, there is an agent that is able to autonomously
learn an optimal action strategy through its interaction with the environment in which it is …
learn an optimal action strategy through its interaction with the environment in which it is …
Decentralized Deep Reinforcement Learning Approach for Channel Access Optimization
SC da SJ Cruz, FAP de Figueiredo, RAA de Souza - 2024 - researchsquare.com
Abstract The IEEE 802.11 standard's binary exponential back-off (BEB) algorithm is the
prevailing method for tackling the collision avoidance problem. Under the BEB paradigm …
prevailing method for tackling the collision avoidance problem. Under the BEB paradigm …