Python code to reproduce most figures in the book Wireless Communications and Machine Learning written by Le Liang, Shi Jin, Hao Ye, and Geoffrey Ye Li and (to be) published by Cambridge University Press.

Feb 13, 2025 · Python For Wireless Digital Communications: In this course, you will learn how to rapidly implement and prototype wireless telecom methods and systems using Python and TensorFlow for machine learning based designs.

Oct 12, 2017 · Python code for the book 'Wireless Communications and Machine Learning' by Le Liang, Shi Jin, and Geoffrey Ye Li. Simulator for use in sharing and compatibility studies of wireless communication systems.

Rapidly learn, implement and prototype wireless telecom methods and systems. Before you start watching the recorded lectures of this course, you need first to build your fundamentals and strengthen your background in wireless digital communications. You can achieve this by taking the following free courses:

Python coding examples for wireless communication systems. This includes currently the topics of modulation such as 4-QAM, BPSK (2-PSK) with an AWGN channel and also Rayleigh fading. - TheWirelessC...

Rapidly learn, implement and prototype wireless telecom methods and systems. The course titled "Python For Wireless Digital Communications" covers the.

Share knowledge about wireless communication principles and algorithms. Provide step-by-step explanations of key concepts like MMSE, ZF, and NOMA. Enable practical understanding through Python/Matlab examples .

Part of the book series: Signals and Communication Technology (SCT) This textbook covers fundamental topics in Telecommunication including Channel Modeling, Modulation/Demodulation, Channel Coding/Decoding, Multicarrier, Capacity, Antenna Arrays, Diversity, and 4G/5G.

In this course, you will explore the fundamental principles of wireless communication, including modulation, coding, channel modeling, and protocols. You will learn how to use Python to simulate and analyze wireless communication systems, ranging from simple point-to-point links to complex network scenarios. Key topics covered in the course ...

Apr 4, 2012 · CommPy is an open source toolkit implementing digital communications algorithms in Python using NumPy and SciPy. Objectives To provide readable and useable implementations of algorithms used in the research, design and implementation of digital communication systems.