arifkhaan Goto Github PK
Name: Arif Ullah Khan
Type: User
Bio: PhD Student (Faculty of Electrical Engineering) Ghulam Ishaq Khan (GIK) Institute of Engineering Sciences and Technology Topi, Pakistan
Name: Arif Ullah Khan
Type: User
Bio: PhD Student (Faculty of Electrical Engineering) Ghulam Ishaq Khan (GIK) Institute of Engineering Sciences and Technology Topi, Pakistan
Source code for the paper "Intelligent Base Station Association for UAV Cellular Users: A Supervised Learning Approach" by B. Galkin, R. Amer, E. Fonseca, and L.A. DaSilva, published in the IEEE 5G World Forum, September 2020.
Tri Nhu Do, Georges Kaddoum, Thanh Luan Nguyen, Daniel Benevides da Costa, and Zygmunt J. Haas, "Aerial Reconfigurable Intelligent Surface-Aided Wireless Communication Systems," IEEE PIMRC, 2021
This advanced and complex project implements an AI-powered optimization system for 5G Open RAN networks. Using machine learning and deep learning, the system optimizes network performance by detecting anomalies, predicting network traffic, and dynamically allocating resources.
Anudit Verma's blog:
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Tensorflow Implementation and result of Auto-encoder Based Communication System From Research Paper : "An Introduction to Deep Learning for the Physical Layer" http://ieeexplore.ieee.org/document/8054694/
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This code is for the paper Z. Wang, L. Liu, and S. Cui, "Channel estimation for intelligent reflecting surface assisted multiuser communications: framework, algorithms, and analysis," IEEE Trans. Wireless Commun., vol. 19, no. 10, pp. 6607-6620, Oct. 2020.
-Investigated the efficiency of different estimators to estimate and track channel parameters based on the Mean Squared Error (MSE) performance. The estimators employed in the simulation are LS and MMSE estimators and their performance in the transfer domain was evaluated. MATLAB was used for the simulation of the communication link and analyzing the error between the estimated channel parameters and actual modeled channel parameters.
TWC: Channel Estimation for Reconfigurable Intelligent Surface Aided Multi-User mmWave MIMO Systems
This project is to simulation in the paper "An Adaptive and Parameter-Free Recurrent Neural Structure for Wireless Channel Prediction"
Simulation code for “Making Cell-Free Massive MIMO Competitive With MMSE Processing and Centralized Implementation,” by Emil Björnson and Luca Sanguinetti, IEEE Transactions on Wireless Communications, To appear
This MATLAB code simulates a PPP wireless communication in the millimeter wave band (@28 GHz)
Dean Attali's website - R/Shiny Consultant
应用深度学习到OFDM通信系统中的论文文献汇总
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,近30万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06
Realization of MIMO-NOMA signal detection system based on **C. Lin et al., “A deep learning approach for MIMO-NOMA downlink signal detection,” MDPI Sensors, vol. 19, no. 11, pp. 2526, 2019.
Data-driven implementaion of soft iterative interference cancellation for MIMO detection
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Teaching material for Digital Communications
Source code for paper Deep Learning for Direct Hybrid Precoding in Millimeter Wave Massive MIMO Systems
Modelling of Base stations using a homogeneous Poisson point process. Computation of Signal to Noise and Interference ratio (SINR) and Coverage probability for downlink and uplink scenarios
A Dynamic Graph-Based Scheduling and Interference Coordination Approach in Heterogeneous Cellular Networks中的对偶方法,在与作者(周力,[email protected])邮件交流后,作者分享的。
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