Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.
Please read the tutorial at this link: https://ebookbell.com/faq
We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.
For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.
EbookBell Team
4.4
42 reviewsIntelligent Spectrum Management: Towards 6G explores various aspects of spectrum sharing and resource management in 5G, beyond 5G, and the envisaged 6G networks. The book offers an in-depth exploration of intelligent and secure sharing of spectrum and resource management in existing and future mobile networks.
The book sets the stage by providing an insight to the evolution of mobile networks and highlights the importance of spectrum sharing and resource management in next-generation wireless networks. At the core, the book explores various promising technologies such as cognitive radio, reinforcement learning, deep learning, reconfigurable intelligent surfaces, and blockchain technology towards efficient, intelligent, and secure sharing of spectrum and resource management. Moreover, the book presents dynamic and decentralized resource management techniques, including network slicing, game theory, and blockchain-enabled approaches.
Topics covered include:
Spectrum, and why it must be utilized optimally and transparently
Future applications envisioned with 6G, such as digital twins, Industry 5.0, holographic telepresence, and Extended Reality (XR)
Challenges when Dynamic Spectrum Management (DSM) is enabled through Machine Learning (ML) techniques, including the complexity of received signals and the difficulty in obtaining accurate network data such as channel state information
Reinforcement learning and deep learning-assisted spectrum management
Synergy between Artificial Intelligence (AI) and blockchain technology for spectrum management
Private networks, including their prospects, architecture, enabling concepts, and techniques for efficient operation
In essence, various innovative technologies and approaches that can be leveraged to enhance spectrum utilization and efficiently manage network resources are discussed. The book is a potential reference
…