Secrecy Rate Maximization in THz-Aided Heterogeneous Networks: A Deep Reinforcement Learning Approach

H. Sharma; N. Kumar; I. Budhiraja; A. Barnawi

doi:10.1109/TVT.2023.3275968

Secrecy Rate Maximization in THz-Aided Heterogeneous Networks: A Deep Reinforcement Learning Approach

H. Sharma
, N. Kumar
, I. Budhiraja
, A. Barnawi

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	13490-13505
Number of pages	16
Journal	IEEE Transactions on Vehicular Technology
Volume	72
Issue number	10
DOIs	https://doi.org/10.1109/TVT.2023.3275968
Publication status	Published - 2023

Keywords

A3C
DDPG
THz
femto edge users
hetnets
secrecy rate

Access to Document

10.1109/TVT.2023.3275968Licence: Unspecified

Cite this

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title = "Secrecy Rate Maximization in THz-Aided Heterogeneous Networks: A Deep Reinforcement Learning Approach",

keywords = "A3C, DDPG, THz, femto edge users, hetnets, secrecy rate",

author = "H. Sharma and N. Kumar and I. Budhiraja and A. Barnawi",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.",

year = "2023",

doi = "10.1109/TVT.2023.3275968",

language = "English",

volume = "72",

pages = "13490--13505",

journal = "IEEE Transactions on Vehicular Technology",

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AU - Sharma, H.

AU - Kumar, N.

AU - Budhiraja, I.

AU - Barnawi, A.

PY - 2023

Y1 - 2023

KW - A3C

KW - DDPG

KW - THz

KW - femto edge users

KW - hetnets

KW - secrecy rate

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U2 - 10.1109/TVT.2023.3275968

DO - 10.1109/TVT.2023.3275968

M3 - Article

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VL - 72

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EP - 13505

JO - IEEE Transactions on Vehicular Technology

JF - IEEE Transactions on Vehicular Technology

IS - 10

ER -