Deep Learning-based Reference Signal Received Power Prediction for LTE Communication System

T Ngenjaroendee, W Phakphisut… - … on Circuits/Systems …, 2022 - ieeexplore.ieee.org
A highly accurate prediction of radio signal power is crucial for planning the coverage of
mobile networks. Currently, a path loss model is most widely used to predict the radio signal …

A throughput estimation model for IEEE 802.11 n MIMO link in wireless local-area networks

SK Debnath, M Saha, N Funabiki… - 2018 3rd International …, 2018 - ieeexplore.ieee.org
To design an efficient wireless local-area network (WLAN), we have studied the throughput
estimation model for the IEEE 802.11 n link both in indoor and outdoor environments. This …

FPGA-SDR integration and experimental validation of a joint DA ML SNR and doppler spread estimator for 5G cognitive transceivers

H Haggui, S Affes, F Bellili - IEEE Access, 2019 - ieeexplore.ieee.org
In a multi-connected, multi-technology, and pervasive mobile infrastructure, such as what is
being planned for 5G, artificial intelligence and cognition will play a major role. An important …

Deep neural network-based algorithm approximation via multivariate polynomial regression

C Liu, B Shi, C Li, J Zou, Y Chen… - 2019 IEEE Global …, 2019 - ieeexplore.ieee.org
Many communication tasks have been formulated as optimization problems that can be
solved by iterative algorithms. However, these algorithms are usually computationally …

Autoencoder-based characterisation of passive IEEE 802.11 link level measurements

P Neuhaus, M Henninger, A Frotzscher… - 2021 Joint European …, 2021 - ieeexplore.ieee.org
Wireless networks are indispensable in today's industrial manufacturing and automation.
Due to harsh signal propagation conditions as well as co-existing wireless networks …

Big data goes small: Real-time spectrum-driven embedded wireless networking through deep learning in the RF loop

F Restuccia, T Melodia - IEEE INFOCOM 2019-IEEE …, 2019 - ieeexplore.ieee.org
The explosion of 5G networks and the Internet of Things will result in an exceptionally
crowded RF environment, where techniques such as spectrum sharing and dynamic …

Learning based csi feedback prediction for 5g nr

S Kadambar, AR Godala, AKR Chavva… - 2021 IEEE 18th …, 2021 - ieeexplore.ieee.org
Acquisition of accurate channel state information (CSI) is critical in multiple-input and
multiple-output (MIMO) systems to achieve efficient link adaptation. As CSI is typically …

Towards 802.11 g signal strength estimation in an industrial environment: A practical study

DCG Valadares, JMFR de Araújo, Â Perkusich… - … : Proceedings of the …, 2020 - Springer
Abstract With Industry 4.0 and Industrial Internet of Things (IIoT), new communication
protocols are emerging or being updated. These protocols demand technological updates at …

Limited log-distance path loss model path loss exponent estimation using deep deterministic policy gradient

DP Grabowsky, JM Conrad, AF Browne - SoutheastCon 2021, 2021 - ieeexplore.ieee.org
Low-cost wireless devices often rely on the log-distance path loss model for determining the
distance between two devices based on radio signal strength. The log-distance path loss …

Deep-learning channel estimation for IRS-assisted integrated sensing and communication system

Y Liu, I Al-Nahhal, OA Dobre… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Integrated sensing and communication (ISAC), and intelligent reflecting surface (IRS) are
envisioned as revolutionary technologies to enhance spectral and energy efficiencies for …