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Indigo AI-enabled Smart Antenna Design for 6G Wireless Systems | Erin Mills Town Centre
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A comprehensive guide to 6G wireless systems and artificial intelligence (AI)-powered smart antennas, this book explores how AI can transform antenna design and optimize and deploy next-generation networks. Readers will gain practical insights into integrating AI with advanced antenna technologies for ultra-fast, energy-efficient, and adaptive 6G networks. It combines theory with hands-on simulation, real-world use cases, and open-source resources, covering topics like beamforming, Reconfigurable Intelligent Surfaces (RIS), terahertz antennas, and edge AI. Key Features: Effectively bridges the gap between AI theory and practical smart antenna design for 6G networks. Comprehensively covers terahertz antennas, RIS, edge AI, and real-world deployment scenarios. Includes supplementary materials such as Python/MATLAB code, CST/HFSS simulation files, and curated datasets via a dedicated GitHub repository for reproducibility and practical learning. Ideal for graduate students, researchers, and industry professionals in wireless communications, antenna engineering, and AI applications. Also suited for instructors developing advanced courses on 6G, IoT, and smart antenna systems.
A comprehensive guide to 6G wireless systems and artificial intelligence (AI)-powered smart antennas, this book explores how AI can transform antenna design and optimize and deploy next-generation networks. Readers will gain practical insights into integrating AI with advanced antenna technologies for ultra-fast, energy-efficient, and adaptive 6G networks. It combines theory with hands-on simulation, real-world use cases, and open-source resources, covering topics like beamforming, Reconfigurable Intelligent Surfaces (RIS), terahertz antennas, and edge AI. Key Features: Effectively bridges the gap between AI theory and practical smart antenna design for 6G networks. Comprehensively covers terahertz antennas, RIS, edge AI, and real-world deployment scenarios. Includes supplementary materials such as Python/MATLAB code, CST/HFSS simulation files, and curated datasets via a dedicated GitHub repository for reproducibility and practical learning. Ideal for graduate students, researchers, and industry professionals in wireless communications, antenna engineering, and AI applications. Also suited for instructors developing advanced courses on 6G, IoT, and smart antenna systems.
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