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Course Detail

Course Name Private Cellular Networks
Course Code 25WN747
Program M.Tech. Wireless Networks & Applications (Specialising in IoT, AI, 5G, Blockchain) (For Working Professionals & Regular Students)
Credits 3
Campus Amritapuri

Syllabus

Syllabus
  • Private Cellular Networks course has been designed to upskill the students pursuing the PG course in the University towards the future networks or the 5G era. This course aims to provide the students an in-depth understanding of Private LTE/5G networks that are compact, edge cloud-based low-cost energy-efficient sustainable dedicated coverage solutions to cover the wide-ranging use cases including public safety, disaster relief, and local community and industrial networks. The course will include the key private network concepts and enablers, advantages, and challenges. Throughout the course, a strong emphasis on the latest trends in the telecom industry, with a particular focus on Industry 4.0, spectrum usage for private networks, energy-efficient & sustainable network deployment models, and industry verticals will be lectured. The importance of Time-Sensitive Networking and Zero Touch Network Management that includes Machine Learning (ML) or Artificial Intelligence (AI) techniques will be addressed.  
  • The course follows a mixed mode of delivery including lectures, the study of research papers/industry white papers, assignments, interactive sessions, quizzes, lab exercises, case studies, and exams.  

Objectives and Outcomes

Course Outcomes (CO) 

CO1: 

Appreciation of the legacy mobile network technologies providing background to the advances in the Wireless technologies 

CO2: 

Understanding the difference between public and Non-Public Networks (NPN or Private Networks) 

CO3: 

Raise the awareness in latest technologies such as 5G, Blockchain, Artificial Intelligence (AI)

CO4: 

Specialist knowledge in the 4G LTE and 5G private networks. Understanding the key requirements for Private Network deployments for different uses case scenarios 

CO5: 

Prepare with skill set required for focussed R&D at industry or PhD level 

 

CO – PO Affinity Map 

PO 

PO1 

PO2 

PO3 

PO4 

PO5 

PO6 

PO7 

PO8 

PS01 

PSO2 

PSO3 

CO 

CO1 

CO2 

CO3 

CO4 

CO5 

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