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When machine learning engineers work with data sets, they may find the results aren't as good as they need. Instead of improving the model or collecting more data, they can use the feature engineering process to help improve results by modifying the data's features to better capture the nature of the problem. This practical guide to feature engineering is an essential addition to any data scientist's or machine learning engineer's toolbox, providing new ideas on how to improve the performance of a machine learning solution. Beginning with the basic concepts and techniques, the text builds up to a unique cross-domain approach that spans data on graphs, texts, time series, and images, with fully worked out case studies. Key topics include binning, out-of-fold estimation, feature selection, dimensionality reduction, and encoding variable-length data. The full source code for the case studies is available on a companion website as Python Jupyter notebooks.
Do you have the tools to address recent challenges and problems in modern computer networks? Discover a unified view of auction theoretic applications and develop auction models, solution concepts, and algorithms with this multidisciplinary review. Devise distributed, dynamic, and adaptive algorithms for ensuring robust network operation over time-varying and heterogeneous environments, and for optimizing decisions about services, resource allocation, and usage of all network entities. Topics including cloud networking models, MIMO, mmWave communications, 5G, data aggregation, task allocation, user association, interference management, wireless caching, mobile data offloading, and security. Introducing fundamental concepts from an engineering perspective and describing a wide range of state-of-the-art techniques, this is an excellent resource for graduate and senior undergraduate students, network and software engineers, economists, and researchers.
In this chapter, we have introduced existing solutions in the literature aiming to improve the performance of ambient backscattercommunication systems (ABCSs). We have first provided the reviews on several multiple access schemes that allows multiple transmitters backscatter data to the receiver. Then, solutions focusing on improving the communication range, bitrate, reliability, and robustness are presented in details. Finally, we have discussed challenges and future research directions to further improve the performance of ABCSs.
In this chapter, we have provided an overview of ambient backscatter communication systems. Firstly, we have introduced the fundamentals of modulated backscatter and its three main configurations, i.e., monostatic, bistatic, and ambient backscatter communication systems. Then, key channel-coding and modulation techniques in modulated backscatter communication systems are discussed. Two major types of backscatter communication channels and their link budgets are also introduced. Next, theoretical analyses and experimental measurements of backscatter channels are reviewed. Finally, we have discussed some research challenges of backscatter communication systems, especially ambient backscatter communication systems.
This chapter introduces some basic background and the development of ambient backscatter technology. Furthermore, objectives and organization of the book are presented in this chapter.
This chapter discussed open issues and potential research directions for future developemnt of ambient backscatter communication. Many emerging research directions are presented in this chapter such as full-duplex ambient backscatter, ultra-wideband backscatter, visible-light backscactter, and millimeter-wave backscatter.
The performance analysis for ambient backscatter communication systems is fundamentally different from that of traditional communication systems. The carrier signal of backscatter communication is opportunistically exploited from the existing active radio-frequency communication systems. As it is vulnerable to channel variations, different detection and encoding mechanisms have been proposed and analyzed to improve the system throughput or ergodic capacity. In this chapter, we have focused on the analysis of signal detection and bit-error rate (BER) performance for backscatter communication. We have reviewed the different system models for backscatter communication systems and various signal detection approaches under different resource and physical constraints.
In this chapter, we have introduced the fundamentals of self-sustaining wireless communication networks. We have first provided the overviews of conventional energy harvesting networks, i.e., wireless-powered transfer, wireless-powered communication network, and simultaneous wireless information and power transfer, as well as their applications in the literature. Then, we have introduced ambient backscatter communications in terms of architecture, design, advantages, and limitations. Finally, we have discussed potential applications and implementation of ambient backscatter communication system networks such as smart world, biomedical, and logistics.
In this chapter, we first give a brief overview about the development of cognitive radio networks (CRNs), from traditional CRNs to the recent development of wireless energy harvesting for CRNs. Then, we discuss how to integrate ambient backscatter communication techniques to radio-frequency (RF)-powered CRNs, and present two fundamental models for this integration. After that, we discuss recent advanced models of RF-powered CRNs with ambient backscatter communication with more details about system design, communication protocols, and performance optimization problems. Finally, some open issues for the development of RF-powered backscatter CRNs are presented.
Wireless backscatter shares some similarity with the radio-frequency (RF)-powered wireless communications. This motivates the design of a hybrid radio that can operate in either active RF communications or backscatter communications. The flexibility in the radio’s mode switching provides an additional degree of freedom to improve the overall network performance. In this chapter, we first review cooperative transmission strategies in conventional RF-powered wireless communicationsystems and then discuss the feasibility of cooperative relay transmission via backscatter communication. We propose the passive relaying scheme that leverages the backscatter radios to act as passive relays and assist the RF communications. The passive relays backscatter the RF signals from the source to the receiver which, by experiments, shows to improve the transmission rate due to the enhanced multi-path diversity gain.