A Deep Learning Method for Path Loss Prediction Using Geospatial Information and Path Profiles
T Hayashi, K Ichige - IEEE Transactions on Antennas and …, 2023 - ieeexplore.ieee.org
Beyond 5G/6G should provide services everywhere, and it is necessary to expand area
coverage and develop high-frequency bands from millimeter waves to terahertz waves …
coverage and develop high-frequency bands from millimeter waves to terahertz waves …
Cell-Level RSRP Estimation With the Image-to-Image Wireless Propagation Model Based on Measured Data
Wireless propagation models play a significant role in the deployments of base stations that
are used to the reference signal receiving power (RSRP) of signal receivers in a cell …
are used to the reference signal receiving power (RSRP) of signal receivers in a cell …
Channel Attention-Based Path Loss Prediction Model in Asymmetric Massive MIMO Systems
M Yuan, W Zhang, K Zhang… - 2022 IEEE Globecom …, 2022 - ieeexplore.ieee.org
In asymmetric massive multiple-input multiple-output (MIMO) systems, the transmitting (Tx)
and receiving (Rx) arrays are designed asymmetrically, resulting in nonreciprocal uplink …
and receiving (Rx) arrays are designed asymmetrically, resulting in nonreciprocal uplink …
ML-based delay–angle-joint path loss prediction for UAV mmWave channels
Path loss is important for the unmanned aerial vehicle (UAV) placement, trajectory
optimization, and power allocation in UAV-aided communications. By considering both the …
optimization, and power allocation in UAV-aided communications. By considering both the …
DeepChannel: Robust Multimodal Outdoor Channel Model Prediction in LTE Networks Using Deep Learning
Accurate channel model predictions are crucial in mobile communication systems to identify
the coverage area of cellular base stations. It also allows network operators to optimally …
the coverage area of cellular base stations. It also allows network operators to optimally …
[HTML][HTML] Measurement and evaluation method of radar anti-jamming effectiveness based on principal component analysis and machine learning
L Qi, J Zhang, ZF Qi, L Kong, Y Tang - EURASIP Journal on Wireless …, 2023 - Springer
With the development of modern electronic countermeasure technology, the fight between
radar jamming and anti-jamming has become increasingly fierce. Experts have done a lot of …
radar jamming and anti-jamming has become increasingly fierce. Experts have done a lot of …
Ultrahigh frequency path loss prediction based on K-nearest neighbors
M Tikaria, VS Nigam - International Journal of Microwave and …, 2024 - cambridge.org
Path loss prediction (PLP) is an important feature of wireless communications because it
allows a receiver to anticipate the signal strength that will be received from a transmitter at a …
allows a receiver to anticipate the signal strength that will be received from a transmitter at a …
[HTML][HTML] A brief review of path loss models for mmwave channels
N HAMDAN, BK Engiz - Avrupa Bilim ve Teknoloji Dergisi, 2021 - dergipark.org.tr
It is planned to use millimeter wave (mm-wave) communication in 5th Generation (5G)
communication systems, as it allows high bandwidth and accordingly high speed data …
communication systems, as it allows high bandwidth and accordingly high speed data …
Predicting AAM Path Loss through Neural Networks and Statistical Modeling
F Wielnad, S Khater, J Rebollo… - 2024 Integrated …, 2024 - ieeexplore.ieee.org
Advanced Air Mobility (AAM) aircraft are expected to travel urban and suburban routes at an
altitude not to exceed 3,000 feet above ground level (AGL). They will be required to transmit …
altitude not to exceed 3,000 feet above ground level (AGL). They will be required to transmit …
Spatial Prediction of Channel Signal Strength Map Using Deep Fully Convolutional Neural Network
M Torun, H Cai, Y Mostofi - 2022 56th Asilomar Conference on …, 2022 - ieeexplore.ieee.org
In this paper, we propose a deep learning pipeline to predict the signal strength map of a
wireless channel at unvisited locations over the space, based on very sparse channel …
wireless channel at unvisited locations over the space, based on very sparse channel …