SecBoost: Secrecy-aware deep reinforcement learning based energy-efficient scheme for 5G HetNets
In this article, we propose a secrecy-aware energy-efficient scheme for a two-tier
heterogeneous network (HetNet), consisting of a sub-6 GHz macrocell and multiple …
heterogeneous network (HetNet), consisting of a sub-6 GHz macrocell and multiple …
Secrecy rate maximization in THz-aided heterogeneous networks: A deep reinforcement learning approach
Densely deployed femtocells in heterogeneous networks (HetNets) improve the quality-of-
service (QoS) and quality-of-experience (QoE) for both next-generation networks and end …
service (QoS) and quality-of-experience (QoE) for both next-generation networks and end …
Secrecy rate maximization for THz-enabled femto edge users using deep reinforcement learning in 6G
Dense deployment of femtocells in heterogeneous networks (HetNets) is critical for
satisfying end-user quality-of-service (QoS) requirements. Femtocells can improve the …
satisfying end-user quality-of-service (QoS) requirements. Femtocells can improve the …
Physical layer security enhancement in energy harvesting-based cognitive internet of things: A GAN-powered deep reinforcement learning approach
R Lin, H Qiu, J Wang, Z Zhang, L Wu… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Cognitive radio (CR) is regarded as the key technology of the 6th-Generation (6G) wireless
network. Because 6G CR networks are anticipated to offer worldwide coverage, increase …
network. Because 6G CR networks are anticipated to offer worldwide coverage, increase …
Multi-antenna aided secrecy beamforming optimization for wirelessly powered HetNets
The new paradigm of wirelessly powered two-tier heterogeneous networks (HetNets) is
considered in this paper. Specifically, the femtocell base station (FBS) is powered by a …
considered in this paper. Specifically, the femtocell base station (FBS) is powered by a …
Deep reinforcement learning for secrecy energy efficiency maximization in ris-assisted networks
This paper investigates the deep reinforcement learning (DRL) for maximization of the
secrecy energy efficiency (SEE) in reconfigurable intelligent surface (RIS)-assisted …
secrecy energy efficiency (SEE) in reconfigurable intelligent surface (RIS)-assisted …
Secrecy energy efficiency in wireless powered heterogeneous networks: A distributed ADMM approach
This paper investigates the physical layer security in heterogeneous networks (HetNets)
supported by simultaneous wireless information and power transfer (SWIPT). We first …
supported by simultaneous wireless information and power transfer (SWIPT). We first …
Physical-layer security based mobile edge computing for emerging cyber physical systems
L Chen, S Tang, V Balasubramanian, J Xia… - Computer …, 2022 - Elsevier
This paper studies a secure mobile edge computing (MEC) for emerging cyber physical
systems (CPS), where there exist K eavesdroppers in the network, which can threaten the …
systems (CPS), where there exist K eavesdroppers in the network, which can threaten the …
Deep-reinforcement-learning-driven secrecy design for intelligent-reflecting-surface-based 6g-iot networks
The sixth-generation (6G) wireless communication has called for higher bandwidth and
massive connectivity of Internet of Things (IoT) devices. The increased connectivity also …
massive connectivity of Internet of Things (IoT) devices. The increased connectivity also …
Deep reinforcement learning based IRS for cooperative jamming networks under edge computing
Effective energy design and secure communications are critical in the Internet of Things
(IoT). A cooperative jamming (CJ) scheme based on deep reinforcement learning (DRL) is …
(IoT). A cooperative jamming (CJ) scheme based on deep reinforcement learning (DRL) is …