Wireless Devices

With the growing interest in the use of technology in daily life, the potential for using wearable wireless devices across multiple segments, e.g., healthcare, sports, child monitoring, military, emergency, consumer electronics, etc., is rapidly increasing.

This book presents up-to-date information about WLAN antenna designs for students, researchers, and professionals who want to design radiating systems to be deployed for practical coverage. The book primarily focuses on pattern diversity antennas. Pattern diversity antennas are very vital in wireless communication. High correlation between multiple signals can result in low data throughput which can be solved by using antennas with pattern diversity. Beam scanning antennas and their variants are also described in detail. Pattern diversity antenna systems with multiport feeds are also comprehensively discussed in this book. For a multiport system to maintain a reasonable link budget, equal antenna gains are preferred for the required antenna coverage. The book further describes the latest techniques to enhance and equalize the antenna gain within a compact radiating system. With increasing demand for faster connectivity with minimum path loss, the demand for high-gain antennas is rapidly increasing. Thereby a detailed discussion on gain enhancement with the latest high-gain antenna designs is requisite while describing WLAN antennas. Some antenna designs discussed in the book are based on additive manufacturing for their design and fabrication. Additive manufacturing is a much sought-after technology today that allows rapid development of antennas at an affordable cost. Many recent WLAN antennas make use of this technology to develop versatile antenna designs. Finally, the book includes a section on wide-band antenna designs. Antenna designs that reduce the scanning loss are also discussed.

The explosive demand in wireless-capable devices, especially with the proliferation of multiple standards, indicates a great opportunity for adoption of wireless technology at a mass-market level. The communication devices of both today and the future will have not only to allow for a variety of applications, supporting the transfer of characters, audio, graphics, and video data, but they will also have to maintain connection with many other devices rather than with a single base station, in a variety of environments. Moreover, to provide various services from different wireless communication standards with higher capacities and higher data-rates, fully integrated and multifunctional wireless devices will be required.

The explosive demand in wireless-capable devices, especially with the proliferation of multiple standards, indicates a great opportunity for adoption of wireless technology at a mass-market level. The communication devices of both today and the future will have not only to allow for a variety of applications, supporting the transfer of characters, audio, graphics, and video data, but they will also have to maintain connection with many other devices rather than with a single base station, in a variety of environments. Moreover, to provide various services from different wireless communication standards with higher capacities and higher data-rates, fully integrated and multifunctional wireless devices will be required.

The explosive demand in wireless-capable devices, especially with the proliferation of multiple standards, indicates a great opportunity for adoption of wireless technology at a mass-market level. The communication devices of both today and the future will have not only to allow for a variety of applications, supporting the transfer of characters, audio, graphics, and video data, but they will also have to maintain connection with many other devices rather than with a single base station, in a variety of environments. Moreover, to provide various services from different wireless communication standards with higher capacities and higher data-rates, fully integrated and multifunctional wireless devices will be required.

Recently machine learning schemes have attained significant attention as key enablers for next-generation wireless systems. Currently, wireless systems are mostly using machine learning schemes that are based on centralizing the training and inference processes by migrating the end-devices data to a third party centralized location. However, these schemes lead to end-devices privacy leakage. To address these issues, one can use a distributed machine learning at network edge. In this context, federated learning (FL) is one of most important distributed learning algorithm, allowing devices to train a shared machine learning model while keeping data locally. However, applying FL in wireless networks and optimizing the performance involves a range of research topics. For example, in FL, training machine learning models require communication between wireless devices and edge servers via wireless links.