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New trends in stochastic geometry for wireless networks: A tutorial and survey
Next-generation wireless networks are expected to be highly heterogeneous, multilayered,
with embedded intelligence at both the core and edge of the network. In such a context …
with embedded intelligence at both the core and edge of the network. In such a context …
[HTML][HTML] Trends in intelligent communication systems: Review of standards, major research projects, and identification of research gaps
The increasing complexity of communication systems, following the advent of
heterogeneous technologies, services and use cases with diverse technical requirements …
heterogeneous technologies, services and use cases with diverse technical requirements …
A deep-neural-network-based relay selection scheme in wireless-powered cognitive IoT networks
In this article, we propose an efficient deep-neural-network-based relay selection (DNS)
scheme to evaluate and improve the end-to-end throughput in wireless-powered cognitive …
scheme to evaluate and improve the end-to-end throughput in wireless-powered cognitive …
Enhancing PHY-security of FD-enabled NOMA systems using jamming and user selection: Performance analysis and DNN evaluation
In this article, we study the physical-layer security (PHY-security) improvement method for a
downlink nonorthogonal multiple access (NOMA) system in the presence of an active …
downlink nonorthogonal multiple access (NOMA) system in the presence of an active …
Opportunistic scheduling scheme to improve physical-layer security in cooperative NOMA system: Performance analysis and deep learning design
In this paper, we propose a novel opportunistic scheduling-based antenna-user selection
(OBAUS) scheme to improve the secrecy performance of cooperative non-orthogonal …
(OBAUS) scheme to improve the secrecy performance of cooperative non-orthogonal …
Secrecy outage performance of ground-to-air communications with multiple aerial eavesdroppers and its deep learning evaluation
In this letter, we study the secure information transmission from a ground base station (GBS)
to a legitimate unmanned aerial vehicle (UAV) user, in the presence of multiple UAV …
to a legitimate unmanned aerial vehicle (UAV) user, in the presence of multiple UAV …
Machine learning classifier approach with gaussian process, ensemble boosted trees, SVM, and linear regression for 5g signal coverage map**
A Gupta, K Ghanshala, RC Joshi - IJIMAI, 2021 - dialnet.unirioja.es
This article offers a thorough analysis of the machine learning classifiers approaches for the
collected Received Signal Strength Indicator (RSSI) samples which can be applied in …
collected Received Signal Strength Indicator (RSSI) samples which can be applied in …
Full-duplex cooperative NOMA network with multiple eavesdroppers and non-ideal system imperfections: Analysis of physical layer security and validation using deep …
In this work, we consider a full-duplex (FD) relay-assisted cooperative non-orthogonal
multiple access (FD-CNOMA) network and examine the physical layer secrecy (PLS) …
multiple access (FD-CNOMA) network and examine the physical layer secrecy (PLS) …
Terrain-based coverage manifold estimation: Machine learning, stochastic geometry, or simulation?
Given the necessity of connecting the unconnected, covering blind spots has emerged as a
critical task in the next-generation wireless communication network. A direct solution …
critical task in the next-generation wireless communication network. A direct solution …
Comparative analysis of machine learning algorithms for 5G coverage prediction: identification of dominant feature parameters and prediction accuracy
H Yuliana - IEEE Access, 2024 - ieeexplore.ieee.org
5G technology is a key factor in delivering faster and more reliable wireless connectivity.
One crucial aspect in 5G network planning is coverage prediction, which enables network …
One crucial aspect in 5G network planning is coverage prediction, which enables network …