Zhen Gao – författare

This book addresses the technological contributions and developments of advanced hardware for Machine Learning (ML) computing systems. The authors discuss state-of-the-art progress in this area (and related topics) as well as reporting on their application to diverse fields. This is achieved by chapters covering the entire spectrum of research activities to include design and applications, with a focus on high performance and dependable operation. The entire hardware stack (from circuit, to architecture, up to the system level) is discussed in detail.  The book will cover innovative material as well as tutorials, reviews and surveys of current theoretical/experimental results, design methodologies and applications over a wide spectrum of scope for an enlarged readership, so to include engineers as well as scientists.

The Internet-of-Things (IoT) revolution has triggered the need of massive connectivity for billions of devices requiring a system capacity which is far beyond the current network designs that can be supported.

The Internet-of-Things (IoT) revolution has triggered the need of massive connectivity for billions of devices requiring a system capacity which is far beyond the current network designs that can be supported. This emerging requirement has reshaped the society and industry in pursuing efficient communication paradigm. In particular, massive machine-type communications (mMTC) will be a prime driver for enabling the vision of scalable IoT with heterogeneous applications, where the massive access is of paramount importance. This book discusses important massive IoT scenarios and the key technical requirements of the corresponding massive access. We review the state-of-the-art IoT standards and mMTC solutions, and summarize the limitations of the existing schemes from the perspectives of the network architecture, random access procedure, and multiple access techniques. Here, we specify the massive access challenges and reveal that the facilitation of MTC invokes a dramatically different access scheme from current ones mainly designed for human-centric communications. Moreover, we propose several promising massive access solutions to overcome the limitations, where sufficient theoretical model and algorithm design guidance are provided. Besides, detailed simulation and engineering implementation methods are also included.

Several case studies are given after introducing basic communication system components, and the simulation codes are open sourced in our book, which shows the reproducibility of our models and methods and provides convenience for readers such as researchers, engineers, and graduate students in the fields of wireless communications.

Several case studies are given after introducing basic communication system components, and the simulation codes are open sourced in our book, which shows the reproducibility of our models and methods and provides convenience for readers such as researchers, engineers, and graduate students in the fields of wireless communications.

The book focuses on utilizing sparse signal processing techniques in designing massive MIMO communication systems. This book provides in-depth discussions on compressive sensing techniques and simulates the performance on wireless systems.