Modelling and characterisation of antennas and propagation for body-centric wireless communication

PhDBody-Centric Wireless Communication (BCWC) is a central point in the development of fourth generation mobile communications. The continuous miniaturisation of sensors, in addition to the advancement in wearable electronics, embedded software, digital signal processing and biomedical technologies, have led to a new concept of usercentric networks, where devices can be carried in the user’s pockets, attached to the user’s body or even implanted. Body-centric wireless networks take their place within the personal area networks, body area networks and body sensor networks which are all emerging technologies that have a broad range of applications such as healthcare and personal entertainment. The major difference between BCWC and conventional wireless systems is the radio channel over which the communication takes place. The human body is a hostile environment from radio propagation perspective and it is therefore important to understand and characterise the effect of the human body on the antenna elements, the radio channel parameters and hence the system performance. This is presented and highlighted in the thesis through a combination of experimental and electromagnetic numerical investigations, with a particular emphasis to the numerical analysis based on the finite-difference time-domain technique. The presented research work encapsulates the characteristics of the narrowband (2.4 GHz) and ultra wide-band (3-10 GHz) on-body radio channels with respect to different digital phantoms, body postures, and antenna types hence highlighting the effect of subject-specific modelling, static and dynamic environments and antenna performance on the overall body-centric network. The investigations covered extend further to include in-body communications where the radio channel for telemetry with medical implants is also analysed by considering the effect of different digital phantoms on the radio channel characteristics. The study supports the significance of developing powerful and reliable numerical modelling to be used in conjunction with measurement campaigns for a comprehensive understanding of the radio channel in body-centric wireless communication. It also emphasises the importance of considering subject-specific electromagnetic modelling to provide a reliable prediction of the network performance

Neural Radiance Fields: Past, Present, and Future

The various aspects like modeling and interpreting 3D environments and surroundings have enticed humans to progress their research in 3D Computer Vision, Computer Graphics, and Machine Learning. An attempt made by Mildenhall et al in their paper about NeRFs (Neural Radiance Fields) led to a boom in Computer Graphics, Robotics, Computer Vision, and the possible scope of High-Resolution Low Storage Augmented Reality and Virtual Reality-based 3D models have gained traction from res with more than 1000 preprints related to NeRFs published. This paper serves as a bridge for people starting to study these fields by building on the basics of Mathematics, Geometry, Computer Vision, and Computer Graphics to the difficulties encountered in Implicit Representations at the intersection of all these disciplines. This survey provides the history of rendering, Implicit Learning, and NeRFs, the progression of research on NeRFs, and the potential applications and implications of NeRFs in today's world. In doing so, this survey categorizes all the NeRF-related research in terms of the datasets used, objective functions, applications solved, and evaluation criteria for these applications.Comment: 413 pages, 9 figures, 277 citation