DDPG-based joint resource management for latency minimization in NOMA-MEC networks
In this letter, we consider the latency minimization problem in NOMA-MEC networks. Each
user offloads partial tasks to the MEC server for remote execution and processes the …
user offloads partial tasks to the MEC server for remote execution and processes the …
Intelligent resource allocation in backscatter-NOMA networks: a soft actor critic framework
With the use of power domain non-orthogonal multiple access (NOMA) and backscatter
communication (BAC), future sixth-generation ultra-massive machine-type communications …
communication (BAC), future sixth-generation ultra-massive machine-type communications …
Structure-enhanced DRL for optimal transmission scheduling
Remote state estimation of large-scale distributed dynamic processes plays an important
role in Industry 4.0 applications. In this paper, we focus on the transmission scheduling …
role in Industry 4.0 applications. In this paper, we focus on the transmission scheduling …
Novel Multi-feature Fusion Facial Aesthetic Analysis Framework
Machine learning has been used in facial beauty prediction studies. However, the integrity of
facial geometric information is not considered in facial aesthetic feature extraction, and the …
facial geometric information is not considered in facial aesthetic feature extraction, and the …
A DRL-Based Joint Scheduling and Resource Allocation Scheme for Mixed Unicast–Broadcast Transmission in 5G
With the ever-increasing demand for data services, the spectrum becomes precious
resource. The cooperative transmission mechanism, which allows broadcast and unicast to …
resource. The cooperative transmission mechanism, which allows broadcast and unicast to …
Outage performance for NOMA-based FSO-RF systems with transmit antenna selection and nonlinear energy harvesting
L Zhang, J Zhang, N Hu, X Li… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
In this article, we investigate the outage performance for a dual-hop free space optical-radio
frequency communication system, in which a source node communicates with two users on …
frequency communication system, in which a source node communicates with two users on …
Active RIS-aided EH-NOMA Networks: A Deep Reinforcement Learning Approach
Z Shi, H Lu, X Xie, H Yang, C Huang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
An active reconfigurable intelligent surface (RIS)-aided multi-user downlink communication
system is investigated, where non-orthogonal multiple access (NOMA) is employed to …
system is investigated, where non-orthogonal multiple access (NOMA) is employed to …
Energy and performance-efficient dynamic consolidate VMs using deep-Q neural network
Z Tong, J Wang, Y Wang, B Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With cloud computing facing higher levels of Big Data than ever, the processor scale is
rapidly expanding. Large clusters place a heavy burden on cloud service providers and the …
rapidly expanding. Large clusters place a heavy burden on cloud service providers and the …
Latency and energy aware rate maximization in MC-NOMA-based multi-access edge computing: A two-stage deep reinforcement learning approach
M Nduwayezu, JH Yun - Computer Networks, 2022 - Elsevier
Future network services are emerging with an inevitable need for high wireless capacity
along with strong computational capabilities, stringent latency and reduced energy …
along with strong computational capabilities, stringent latency and reduced energy …
Semi-data-aided channel estimation for MIMO systems via reinforcement learning
Data-aided channel estimation is a promising solution to improve channel estimation
accuracy by exploiting data symbols as pilot signals for updating an initial channel estimate …
accuracy by exploiting data symbols as pilot signals for updating an initial channel estimate …