Despite an error based on a false assumption in the 1950’s, which had severely underestimated the efficiency of magneto-dielectric antennas, recently demonstrated magnetic-antennas have been shown to exhibit extraordinary efficiency in conformal applications. Whereas conventional metal-and-dielectric antennas carrying radiating electric currents suffer a significant disadvantage when placed conformal to the conducting surface of a platform, because they induce opposing image currents in the surface, magnetic-antennas carrying magnetic radiating currents have no such limitation. Their magnetic currents produce co-linear image currents in electrically conducting surfaces.
However, the permeable antennas built to date have not yet attained the wide bandwidth expected because the magnetic-flux-channels carrying the wave have not been designed to guide the wave near the speed of light at all frequencies. Instead, they tend to lose the wave by a leaky fast-wave mechanism at low frequencies or they over-bind a slow-wave at high frequencies. In this dissertation, we have studied magnetic antennas in detail and presented the design approach and apparatus required to implement a flux-channel carrying the magnetic current wave near the speed of light over a very broad frequency range which also makes the design of a frequency independent antenna (spiral) possible. We will learn how to construct extremely thin conformal antennas, frequency-independent permeable antennas, and even micron-sized antennas that can be embedded inside the brain without damaging the tissue.
Electric fields have historically been notoriously difficult to work with due to how intrinsically noisy the data is in electric field sensors. As a first contribution, an in-depth study demonstrates just how prevalent electric field noise is. In field tests, various cables were placed underneath power lines. Despite being shielded, the 60 Hz power line signal readily penetrated several types of cables.
The challenges of high noise levels were largely addressed by connecting the output of an electric field sensor to a lock-in amplifier. Using the more accurate means of collecting electric field data, D-dot sensors were arrayed in a compact grid to resolve electric field images as a second contribution. This imager has successfully captured electric field images of live concealed wires and electromagnetic interference.
An active method was developed as a third contribution. In this method, distortions created by objects when placed in a known electric field are read. This expands the domain of what can be imaged because the object does not need to be a time-varying electric field source. Images of dielectrics (e.g. bodies of water) and DC wires were captured using this new method.
The final contribution uses a collection of one-dimensional electric field images, i.e. projections, to reconstruct a two-dimensional image. This was achieved using algorithms based in computed tomography such as filtered backprojection. An algebraic approach was also used to enforce sparsity regularization with the L1 norm, further improving the quality of some images.
etwork states to the structure of the signal itself. Under the common thread of characterizing the role of information, this dissertation investigates opportunistic scheduling, relaying and multicast in wireless networks. To assess the role of channel state information, the problem of opportunistic distributed opportunistic scheduling (DOS) with incomplete information is considered for ad-hoc networks in which many links contend for the same channel using random access. The objective is to maximize the system throughput. In practice, link state information is noisy, and may result in throughput degradation. Therefore, refining the state information by additional probing can improve the throughput, but at the cost of further probing. Capitalizing on optimal stopping theory, the optimal scheduling policy is shown to be threshold-based and is characterized by either one or two thresholds, depending on network settings. To understand the benefits of side information in cooperative relaying scenarios, a basic model is explored for two-hop transmissions of two information flows which interfere with each other. While the first hop is a classical interference channel, the second hop can be treated as an interference channel with transmitter side information. Various cooperative relaying strategies are developed to enhance the achievable rate. In another context, a simple sensor network is considered, where a sensor node acts as a relay, and aids fusion center in detecting an event. Two relaying schemes are considered: analog relaying and digital relaying. Sufficient conditions are provided for the optimality of analog relaying over digital relaying in this network. To illustrate the role of information about the signal structure in joint source-channel coding, multicast of compressible signals over lossy channels is studied. The focus is on the network outage from the perspective of signal distortion across all receivers. Based on extreme value theory, the network outage is characterized in terms of key parameters. A new method using subblock network coding is devised, which prioritizes resource allocation based on the signal information structure.
The Fourier representation of a signal or image is equivalent to its native representation in the sense that the signal or image can be reconstructed exactly from its Fourier transform. The Fourier transform is generally complex-valued, and each value of the Fourier spectrum thus possesses both magnitude and phase. Degradation of signals and images when Fourier phase information is lost or corrupted has been studied extensively in the signal processing research literature, as has reconstruction of signals and images using only Fourier magnitude information. This thesis focuses on the case of images, where it examines the visual effect of quantifiable levels of Fourier phase loss and, in particular, studies the merits of introducing varying degrees of phase information in a classical iterative algorithm for reconstructing an image from its Fourier magnitude.