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Wireless Communication using Python

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Wireless Communication using Python, available at $44.99, has an average rating of 3.3, with 80 lectures, 12 quizzes, based on 25 reviews, and has 93 subscribers.

You will learn about 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 This course is ideal for individuals who are 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. It is particularly useful for 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.

Enroll now: Wireless Communication using Python

Summary

Title: Wireless Communication using Python

Price: $44.99

Average Rating: 3.3

Number of Lectures: 80

Number of Quizzes: 12

Number of Published Lectures: 80

Number of Published Quizzes: 12

Number of Curriculum Items: 92

Number of Published Curriculum Objects: 92

Original Price: $22.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

  • 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.

Target Audiences

  • 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.

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:

  1. Introduction to Wireless Communication: Understand the basics of wireless communication, including frequency bands, wireless propagation, and signal modulation techniques.

  2. Wireless Channel Modeling: Learn how to model wireless channels using path loss models, shadowing, and fading models.

  3. Modulation Techniques: Explore various modulation schemes such as amplitude modulation, frequency modulation, and digital modulation techniques.

  4. Error Control Coding: Discover coding techniques like Hamming codes, Reed-Solomon codes, and convolutional codes to improve the reliability of wireless communication systems.

  5. 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).

  6. Wireless Network Protocols: Gain insights into wireless network protocols, including WiFi, Bluetooth, Zigbee, and cellular networks (4G/5G).

  7. 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.

Course Curriculum

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

Lecture 1: Welcome- About the Course

Chapter 2: Chapter 1 : Introduction to wireless communication systems

Lecture 1: 1.0 Introduction to wireless communication systems

Lecture 2: 1.1. Overview of wireless communication technologies

Lecture 3: Python File Creation

Lecture 4: Python Script

Lecture 5: 1.2. Historical developments in wireless communication

Lecture 6: Python Script

Chapter 3: Chapter 2 : Fundamentals of digital modulation

Lecture 1: 2.0 Introduction

Lecture 2: 2.1. Amplitude modulation (AM)

Lecture 3: Python script

Lecture 4: 2.1.1. Python code for generating and demodulating AM signals

Lecture 5: Python Script

Lecture 6: 2.2. Phase modulation (PM)

Lecture 7: Python Script

Lecture 8: 2.2.1. Python code for generating and demodulating PM signals

Lecture 9: Python Script

Lecture 10: 2.3 Quadrature amplitude modulation (QAM)

Lecture 11: Python Script

Lecture 12: 2.3.1. Python code for generating and demodulating QAM signals

Lecture 13: Python Script

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

Lecture 1: 3.0. Introduction

Lecture 2: 3.1. Using Python libraries for simulating digital modulation schemes

Lecture 3: Python Script

Lecture 4: 3.2. Python code for simulating and analyzing the performance of various digital

Lecture 5: Python Script

Chapter 5: Chapter 4 : Error correction coding

Lecture 1: 4.0. Introduction

Lecture 2: 4.1. Forward Error Correction (FEC)

Lecture 3: Python Script

Lecture 4: 4.1.1. Python code for implementing convolutional and block codes

Lecture 5: Python Script

Lecture 6: 4.2. Automatic Repeat reQuest (ARQ)

Lecture 7: Python Script

Lecture 8: 4.2.1. Python code for simulating the performance of various ARQ schemes

Lecture 9: Python Script

Chapter 6: Chapter 5 : Wireless channel modeling and simulation

Lecture 1: 5.0 Introduction

Lecture 2: 5.1. Introduce the wireless channel and its properties

Lecture 3: Python Script

Lecture 4: 5.2. Rayleigh, Rician, and Nakagami channels

Lecture 5: Python Script

Chapter 7: Chapter 6 : MIMO Communications

Lecture 1: 6.0 Introduction

Lecture 2: 6.1 Overview of MIMO Systems

Lecture 3: Python Script

Lecture 4: 6.2. Python code for simulating MIMO systems

Lecture 5: 6.3. Capacity and Diversity Gain

Lecture 6: Python Script

Chapter 8: Chapter 7 : Wireless Network simulation using Python

Lecture 1: 7.0 Introduction

Lecture 2: 7.1 Simulation of wireless ad-hoc networks

Lecture 3: Python Script

Lecture 4: 7.1.1 Python code for simulating various routing protocols for wireless ad-hoc n

Lecture 5: Python Script

Lecture 6: 7.2 Simulation of wireless sensor networks

Lecture 7: Python Script

Lecture 8: 7.2.1 Python code for simulating energy-efficient routing protocols for wireless

Lecture 9: Python Script

Chapter 9: Chapter 8 : IoT wireless communication protocols

Lecture 1: 8.0 Introduction

Lecture 2: 8.1 Overview of IoT wireless protocols

Lecture 3: Python Script

Lecture 4: 8.2 Python code for working with various IoT wireless protocols

Lecture 5: Python Script

Chapter 10: Chapter 9 : Machine learning for wireless communications

Lecture 1: 9.0 Introduction

Lecture 2: 9.1 Machine learning techniques for wireless communication systems

Lecture 3: Python Script

Lecture 4: 9.2 Python code for implementing machine learning algorithms

Lecture 5: Python Script

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

Lecture 1: 10.0 Introduction

Lecture 2: Python Scripts

Lecture 3: 10.1 Python code for implementing wireless communication systems

Lecture 4: 10.1.1 Zigbee

Lecture 5: 10.1.2 Bluetooth

Lecture 6: 10.1.3 Wi-Fi

Lecture 7: 10.1.4 Cellular networks (4G/5G)

Chapter 12: Chapter 11 : Advanced topic in Wireless communication

Lecture 1: 11.0 Introduction

Lecture 2: 11.1 Advanced modulation and Coding Techniques

Lecture 3: Python Script

Lecture 4: 11.2 Space-Time coding

Lecture 5: Python Script

Lecture 6: 11.3 Massive MIMO

Lecture 7: Python Script

Instructors

Rating Distribution

  • 1 stars: 7 votes
  • 2 stars: 0 votes
  • 3 stars: 6 votes
  • 4 stars: 3 votes
  • 5 stars: 9 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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