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{ "item_title" : "Machine Learning in Next Generation Multiple Access (Ngma)", "item_author" : [" Mohammad Abdul Matin", "M. Rezwanul Mahmood "], "item_description" : "This book equips readers with the conceptual and practical knowledge they need to put into practice the design, development, and management of the next generation multiple access / non-orthogonal multiple access (NGMA/NOMA)-based network systems. The authors outline and evaluate NOMA technologies by exploiting AI/ML-based methodologies. The authors also discuss the role of NOMA in designing NGMA, and the applications/use cases of the next-generation NOMA. The book provides guidance for researchers, engineers and scientists in academia and industry working in the fields of telecom and computing, and artificial intelligence/machine learning.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/3/03/219/419/3032194199_b.jpg", "price_data" : { "retail_price" : "37.99", "online_price" : "37.99", "our_price" : "37.99", "club_price" : "37.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Machine Learning in Next Generation Multiple Access (Ngma)|Mohammad Abdul Matin

Machine Learning in Next Generation Multiple Access (Ngma)

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Overview

This book equips readers with the conceptual and practical knowledge they need to put into practice the design, development, and management of the next generation multiple access / non-orthogonal multiple access (NGMA/NOMA)-based network systems. The authors outline and evaluate NOMA technologies by exploiting AI/ML-based methodologies. The authors also discuss the role of NOMA in designing NGMA, and the applications/use cases of the next-generation NOMA. The book provides guidance for researchers, engineers and scientists in academia and industry working in the fields of telecom and computing, and artificial intelligence/machine learning.

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Details

  • ISBN-13: 9783032194190
  • ISBN-10: 3032194199
  • Publisher: Springer
  • Publish Date: May 2026
  • Page Count: 70

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