Wireless Communication Using Python

Master the Art of Wireless Communication with Python

What you'll learn

Understanding the fundamentals of wireless communication systems, including its history and development.

Proficiency in the simulation and analysis of various digital modulation schemes using Python.

Knowledge of error correction coding techniques and ARQ schemes, and their implementation in Python

Awareness of advanced topics in wireless communication, including advanced modulation and coding techniques, space-time coding, massive MIMO, and wireless secur

Experience in implementing real-world wireless communication systems such as Zigbee, Bluetooth, Wi-Fi, and cellular networks using Python.

Familiarity with wireless channel modeling and simulation, MIMO communications, IoT wireless communication protocols, and machine learning for wireless communic

Requirements

Basic knowledge of computer programming, specifically in Python

Basic understanding of digital signal processing, communication systems, and information theory.

Access to a computer and software required to complete the course, such as Python and relevant libraries.

Description

Wireless communication is a rapidly evolving field with widespread applications in various industries. This comprehensive course is designed to provide you with a deep understanding of wireless communication concepts and practical skills in implementing wireless systems using Python.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 include:Introduction to Wireless Communication: Understand the basics of wireless communication, including frequency bands, wireless propagation, and signal modulation techniques.Wireless Channel Modeling: Learn how to model wireless channels using path loss models, shadowing, and fading models.Modulation Techniques: Explore various modulation schemes such as amplitude modulation, frequency modulation, and digital modulation techniques.Error Control Coding: Discover coding techniques like Hamming codes, Reed-Solomon codes, and convolutional codes to improve the reliability of wireless communication systems.Multiple Access Techniques: Dive into multiple access techniques such as time-division multiple access (TDMA), frequency-division multiple access (FDMA), and code-division multiple access (CDMA).Wireless Network Protocols: Gain insights into wireless network protocols, including WiFi, Bluetooth, Zigbee, and cellular networks (4G/5G).Wireless Security: Understand the principles of wireless security and learn about encryption, authentication, and key management techniques.Throughout the course, you will have hands-on coding exercises and simulations using Python to reinforce your understanding of wireless communication concepts. By the end of this course, you will be equipped with the knowledge and skills to design, analyze, and implement wireless communication systems using Python.

Overview

Section 1: Welcome to the Course: Wireless Communication Using Python!

Lecture 1 Welcome- About the Course

Section 2: Chapter 1 : Introduction to wireless communication systems

Lecture 2 1.0 Introduction to wireless communication systems

Lecture 3 1.1. Overview of wireless communication technologies

Lecture 4 Python File Creation

Lecture 5 Python Script

Lecture 6 1.2. Historical developments in wireless communication

Lecture 7 Python Script

Section 3: Chapter 2 : Fundamentals of digital modulation

Lecture 8 2.0 Introduction

Lecture 9 2.1. Amplitude modulation (AM)

Lecture 10 Python script

Lecture 11 2.1.1. Python code for generating and demodulating AM signals

Lecture 12 Python Script

Lecture 13 2.2. Phase modulation (PM)

Lecture 14 Python Script

Lecture 15 2.2.1. Python code for generating and demodulating PM signals

Lecture 16 Python Script

Lecture 17 2.3 Quadrature amplitude modulation (QAM)

Lecture 18 Python Script

Lecture 19 2.3.1. Python code for generating and demodulating QAM signals

Lecture 20 Python Script

Section 4: Chapter 3 : Simulation of digital modulation schemes using Python

Lecture 21 3.0. Introduction

Lecture 22 3.1. Using Python libraries for simulating digital modulation schemes

Lecture 23 Python Script

Lecture 24 3.2. Python code for simulating and analyzing the performance of various digital

Lecture 25 Python Script

Section 5: Chapter 4 : Error correction coding

Lecture 26 4.0. Introduction

Lecture 27 4.1. Forward Error Correction (FEC)

Lecture 28 Python Script

Lecture 29 4.1.1. Python code for implementing convolutional and block codes

Lecture 30 Python Script

Lecture 31 4.2. Automatic Repeat reQuest (ARQ)

Lecture 32 Python Script

Lecture 33 4.2.1. Python code for simulating the performance of various ARQ schemes

Lecture 34 Python Script

Section 6: Chapter 5 : Wireless channel modeling and simulation

Lecture 35 5.0 Introduction

Lecture 36 5.1. Introduce the wireless channel and its properties

Lecture 37 Python Script

Lecture 38 5.2. Rayleigh, Rician, and Nakagami channels

Lecture 39 Python Script

Section 7: Chapter 6 : MIMO Communications

Lecture 40 6.0 Introduction

Lecture 41 6.1 Overview of MIMO Systems

Lecture 42 Python Script

Lecture 43 6.2. Python code for simulating MIMO systems

Lecture 44 6.3. Capacity and Diversity Gain

Lecture 45 Python Script

Section 8: Chapter 7 : Wireless Network simulation using Python

Lecture 46 7.0 Introduction

Lecture 47 7.1 Simulation of wireless ad-hoc networks

Lecture 48 Python Script

Lecture 49 7.1.1 Python code for simulating various routing protocols for wireless ad-hoc n

Lecture 50 Python Script

Lecture 51 7.2 Simulation of wireless sensor networks

Lecture 52 Python Script

Lecture 53 7.2.1 Python code for simulating energy-efficient routing protocols for wireless

Lecture 54 Python Script

Section 9: Chapter 8 : IoT wireless communication protocols

Lecture 55 8.0 Introduction

Lecture 56 8.1 Overview of IoT wireless protocols

Lecture 57 Python Script

Lecture 58 8.2 Python code for working with various IoT wireless protocols

Lecture 59 Python Script

Section 10: Chapter 9 : Machine learning for wireless communications

Lecture 60 9.0 Introduction

Lecture 61 9.1 Machine learning techniques for wireless communication systems

Lecture 62 Python Script

Lecture 63 9.2 Python code for implementing machine learning algorithms

Lecture 64 Python Script

Section 11: Chapter 10 : Real-world wireless communication systems with python

Lecture 65 10.0 Introduction

Lecture 66 Python Scripts

Lecture 67 10.1 Python code for implementing wireless communication systems

Lecture 68 10.1.1 Zigbee

Lecture 69 10.1.2 Bluetooth

Lecture 70 10.1.3 Wi-Fi

Lecture 71 10.1.4 Cellular networks (4G/5G)

Section 12: Chapter 11 : Advanced topic in Wireless communication

Lecture 72 11.0 Introduction

Lecture 73 11.1 Advanced modulation and Coding Techniques

Lecture 74 Python Script

Lecture 75 11.2 Space-Time coding

Lecture 76 Python Script

Lecture 77 11.3 Massive MIMO

Lecture 78 Python Script

Lecture 79 11.4 Wireless Security

Lecture 80 Python Script

Section 13: Python Coding Challenges in Wireless Communication

This course is intended for individuals who are interested in learning about wireless communication systems and want to gain hands-on experience with implementing these systems using Python. The course is suitable for students, researchers, and professionals in the field of computer science, electrical engineering, or related fields. The course is also suitable for individuals who are interested in machine learning techniques for wireless communication systems and want to learn how to implement these techniques using Python. Prerequisites for the course include a basic understanding of programming and a basic understanding of digital modulation and error correction coding.