This book offers a technical background to the design and optimization of wireless communication systems, covering optimization algorithms for wireless and 5G communication systems design. The book introduces the design and optimization systems which target capacity, latency, and connection density; including Enhanced Mobile Broadband Communication (eMBB), Ultra-Reliable and Low Latency Communication (URLL), and Massive Machine Type Communication (mMTC).
The book is organized into two distinct parts: Part I, mathematical methods and optimization algorithms for wireless communications are introduced, providing the reader with the required mathematical background. In Part II, 5G communication systems are designed and optimized using the mathematical methods and optimization algorithms.
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DR. HAESIK KIM (IEEE Senior Member, Series Editor and Associate Technical Editor of IEEE Communications Magazine) is Senior Scientist of 5G and beyond network team in VTT Technical Research Centre of Finland. He is the recipient of the International Conference on Wireless Communications and Signal Processing (WCSP) Best Paper Award in 2010. His current research interests include PHY and MAC layer system design, advanced coding theory, advanced MIMO, multi-carrier system, interference mitigation techniques, resource allocation schemes, machine-type communications, ultra-reliable low latency communications, and machine learning.
A technical introduction to the mathematical methods and optimization algorithms required to design 5G communication systems
This book offers a technical background to the design and optimization of wireless communication systems, covering optimization algorithms for wireless and 5G communication systems design. It introduces the design and optimization systems which target capacity, latency, and connection density, including Enhanced Mobile Broadband Communication (eMBB), Ultra-Reliable and Low Latency Communication (URLL), and Massive Machine Type Communication (mMTC).
Design and Optimization for 5G Wireless Communications is organized into two distinct parts: Part I introduces readers to mathematical methods and optimization algorithms for wireless communications, and provides them with all the mathematical background they need, including approximation theory, LS estimation, MMSE estimation, ML and MAP estimation, matrix factorization, linear programming, convex optimization, gradient descent method, supervised and unsupervised learning, reinforcement learning, and more. In Part II, 5G communication systems are designed and optimized using the mathematical methods and optimization algorithms. It covers 5G NR, MIMO, 5G waveforms (OFDM, FBMC, GFDM and UFMC), LDPC, short packet transmission theory, latency analysis of 4G and 5G networks, MEC optimizations, robust optimization, power control and management, wireless sensor networks, and so on.
Design and Optimization for 5G Wireless Communications is an ideal book for graduate students majoring in wireless communications or electrical engineering and researchers and developers of 5G communication systems. It will also benefit senior level undergraduate students and engineers working in the wireless communication industry.
A technical introduction to the mathematical methods and optimization algorithms required to design 5G communication systems
This book offers a technical background to the design and optimization of wireless communication systems, covering optimization algorithms for wireless and 5G communication systems design. It introduces the design and optimization systems which target capacity, latency, and connection density, including Enhanced Mobile Broadband Communication (eMBB), Ultra-Reliable and Low Latency Communication (URLL), and Massive Machine Type Communication (mMTC).
Design and Optimization for 5G Wireless Communications is organized into two distinct parts: Part I introduces readers to mathematical methods and optimization algorithms for wireless communications, and provides them with all the mathematical background they need, including approximation theory, LS estimation, MMSE estimation, ML and MAP estimation, matrix factorization, linear programming, convex optimization, gradient descent method, supervised and unsupervised learning, reinforcement learning, and more. In Part II, 5G communication systems are designed and optimized using the mathematical methods and optimization algorithms. It covers 5G NR, MIMO, 5G waveforms (OFDM, FBMC, GFDM and UFMC), LDPC, short packet transmission theory, latency analysis of 4G and 5G networks, MEC optimizations, robust optimization, power control and management, wireless sensor networks, and so on.
Design and Optimization for 5G Wireless Communications is an ideal book for graduate students majoring in wireless communications or electrical engineering and researchers and developers of 5G communication systems. It will also benefit senior level undergraduate students and engineers working in the wireless communication industry.
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