ThomasLin8

ThomasLin8's Stars

• dromara/hertzbeat

  A real-time monitoring system with agentless, performance cluster, prometheus-compatible, custom monitoring and status page building capabilities.

  Language:Java4.5k54538783

• guolindev/booksource

  《第一行代码 第2版》全书源代码

  Language:Java3.1k198412.3k

• JsonChao/Awesome-WanAndroid

  :zap:致力于打造一款极致体验的 http://www.wanandroid.com/ 客户端，知识和美是可以并存的哦QAQn(*≧▽≦*)n

  Language:Java2.7k60129605

• sydney222/Python_CsiNet

  Python code for "Deep Learning for Massive MIMO CSI Feedback"

  Language:PureBasic232135107

• zoam/xmu-thesis-grd

  厦门大学研究生学位论文 LaTeX 模板

  Language:TeX15744241

• lasseufpa/5gm-data

  Datasets and code for machine learning in 5G mmWave MIMO systems involving mobility (5GMdata)

  Language:Python8013635

• HamedHojatian/HBF-Net

  Simulation code for "Unsupervised Deep Learning for Massive MIMO Hybrid Beamforming" by Hamed Hojatian, Jeremy Nadal, Jean-Francois Frigon, Francois Leduc-Primeau, 2020.

  Language:Python624214

• mauro-belgiovine/DL-channel-estimation-MaMIMO

  This repository contains the code needed to reproduce results in the paper by M. Belgiovine, et al. “Deep Learning at the Edge for Channel Estimation in Beyond-5G Massive MIMO,” accepted at IEEE Wireless Communications Magazine (WCM), April 2021.

  Language:MATLAB4414

• vlaxose/jstsp19

  Wideband MIMO Channel Estimation for Hybrid Beamforming Millimeter Wave Systems via Random Spatial Sampling

  Language:MATLAB3725

• dianixn/OFDM-and-MMSE

  OFDM banseband and MMSE/LMMSE for channel estimation

  Language:MATLAB311011

• LEON-REIN/channel_estimation

  A project which applies different channel-estimating approaches in an OFDM-4QAM communication system.

  Language:Python310

• tum-msv/learning-mmse-est

  Julia code for the paper "Learning the MMSE Channel Estimator"

  Language:Julia232012

• Mehrtash93/DL_DD_MIMO

  This project is to use deep neural network for channel estimation in MIMO communication systems

  Language:MATLAB1710

• YBen1/Autoencoder_communication_system_WGAN_Channel-estimation

  Master Thesis compairing Communicationsystems Baised on GAN and baised on MI

  Language:Jupyter Notebook169

• ozgeozaltin/Limited-Feedback-Channel-Estimation-in-Massive-MIMO-Systems

  Today, plenty of cellular systems utilize frequency-division duplexing (FDD). Downlink training for channel state information in FDD is difficult since training and feedback overhead is proportional to the number of antennas at the base station, which is large in a Massive MIMO systems. To deal with the limited feedback mechanism of downlink channel in FDD Massive MIMO system, we can adopt the double directional model. This is applicable for the 5G systems to get high capacity and data rate. We analyse and test the performance of the Limited feedback channel with DD model via the MATLAB and we had the better performance rather than other models.

  Language:Matlab1415

• pradeepshekhar/V2VchannelEstimator

  This repository has MATLAB codes used for simulating a Vehicle to Vehicle communication channel.

  Language:Matlab146

• engrazr/improved-CDP

  EEE 802.11p based Dedicated Short-Range Communication (DSRC) is considered a potential wireless technology to enable transportation safety and traffic efficiency. A major challenge in the development of IEEE 802.11p technology is ensuring communication reliability in highly dynamic Vehicle-to-Vehicle (V2V) environments. The design of IEEE 802.11p does not have a sufficient number of training symbols in the time domain and pilot carriers in the frequency domain to enable accurate estimation of rapidly varying V2V channels. The channel estimation of IEEE 802.11p is preamble based, which cannot guarantee a suitable equalization in urban and highway scenarios, especially for longer length data packets. This limitation has been investigated by some research works, which suggest that one major challenge is determining an accurate means of updating channel estimate over the course of packet length while adhering to the standard. The motivation behind this article is to overcome this challenge. We have proposed an improved Constructed Data Pilot (iCDP) scheme which adheres to the standard and constructs data pilots by considering the correlation characteristics between adjacent data symbols in time domain and adjacent subcarriers in frequency domain. It is in contrast to previous schemes which considered the correlation in the time domain. The results have shown that the proposed scheme performs better than previous schemes in terms of bit error rate (BER) and root-mean-square error (RMSE).

  Language:MATLAB101

• ITU-AI-ML-in-5G-Challenge/Channel-Estimation-ML-DOJO-2

  Language:MATLAB10102

• ksteensig/channel-estimation

  Massive MIMO DoA and Channel Estimation

  Language:Jupyter Notebook10106

• 617147567/Channel-Estimation-Based-on-DNN

  graduation project by Guanxiong Shen, Heriot-watt University

  Language:MATLAB910

• krbundy/LSTMChannelStateEstimation

  Using LSTM Model(s) to estimate the state of a deep fading channel

  Language:MATLAB64

• EricGJB/HAD_channel_estimation

  Language:Python5203

• hananshafi/channel-estimation

  Python code for estimating Channel parameter in Cognitive Radio

  Language:Jupyter Notebook5002

• mkokshoorn/mmWaveChannelEst

  MATLAB source code for several mmWave Channel Estimation Simulations

  Language:Matlab5201

• jain-nikunj/channel-estimation

  Estimate a channel's impulse response under constraints of simulation and input signal power.

  Language:Jupyter Notebook3101

• Janulxj/Two-stage-mmWave-channel-estimation-code-in-MATLAB

  3

• JiyunTao52Hz/massivemimobook

  Book PDF and simulation code for the monograph "Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency" by Emil Björnson, Jakob Hoydis and Luca Sanguinetti, published in Foundations and Trends in Signal Processing, 2017.

  Language:MATLAB21

• SheehabMuhammad/5g-beam-forming

  5g Network mmWave Beam Forming using Machine Learing

  Language:Jupyter Notebook2102

• krishnamraju286/ofdm-channel-estimation-using-deep-learning

  1100

• marianabaracat/DNN_based_channel_estimator

  Language:Jupyter Notebook1