A systematic method based on the Theory of Characteristic Modes (TCM) for finding orthogonal radiation patterns of any electronically steerable parasitic array radiator (ESPAR) is described. This method can be useful for designing single-RF front-end multiple-input multiple-output (MIMO) systems in which orthogonal patterns can be utilized as a basis set for space modulation (SM) or full multiplexed MIMO systems. The method is based on the$N$-port formulation of TCM and is not restricted to antenna type or array configuration. It can also provide closed formed solutions for the antenna element currents required to generate the orthogonal patterns. In addition an approach to finding the required load reactances in ESPAR for generating the orthogonal patterns is provided and is based on the quasi-Newton method utilizing a closed form expression for the initial approximate solution. Approximate estimation of the effective aerial degrees of freedom of the ESPARs is also discussed. Two simulation examples of ESPARs, a 4-element linear dipole array and an 8-element rectangular planar inverted-F antenna array, using SM as well as full multiplexed MIMO are provided, demonstrating the effectiveness of the proposed method.

In this work we consider the one-dimensional (1D) inverse scattering problem of super-resolving the location of discrete point scatters satisfying the 1D Helmholtz equation. This inverse problem has important applications in the detection of shunt faults in electrical transmission lines and leaks in water pipelines where usually only low frequency spectral information is available from measurements. We formulate the inverse scattering problem as a sparse reconstruction problem and apply convex optimization to super-resolve the location of point scatters. We extend previous results and prove that we can super-resolve up to 4 points and 5-18 points with infinite precision if the points are separated by 1/(2fc) and 1/fcrespectively (fcis the maximum frequency we can measure). This is over 4 times closer than previous results. Simulation results are used to demonstrate the effectiveness of the approach.

In this article, three low complexity multiple-input multiple-output (MIMO) receivers using energy detection and multilevel amplitude-shift keying (ASK) for Internet of Things (IoT) applications are described. To circumvent the inherent nonlinearity of the noncoherent MIMO system, an equivalent linear system model for the channel is introduced. This allows the proposed receivers to be configured analogously to coherent-based approaches. The tradeoff is that increased numbers of receive antennas need to be used but the overall complexity is decreased compared to existing noncoherent approaches. The receivers can also easily be integrated with energy harvesting systems. The three receiver structures considered are zero forcing (ZF), ZF with ordered successive interference cancellation (ZF-OSIC), and weighted envelope detection (WENVD), and their performance in flat Rayleigh fading channels with multilevel ASK is investigated. For the WENVD receiver, the error performance under the condition of high signal-to-noise ratio is also analyzed, and closed form approximations of the conditional (conditioned on the channel matrix) symbol vector error probability (SEP) and the average of the conditional SEP are derived. It is found that the ZF receiver has the lowest complexity and the WENVD receiver the highest; however, error performance comparison through numerical results reveals that the WENVD receiver has the best performance and the ZF-OSIC receiver has the next best. When combined with multiport energy harvesting technology the receivers have significant potential for use in IoT.

We propose the use of subcarrier delay spread based adaptive orthogonal frequency division multiplexing (OFDM) for communication through wideband waveguide channels. The technique has important communication applications when robots or vehicles are traveling inside waveguide channels such as tunnels or pipes. The delay spread in these mobile wideband waveguide channels varies significantly across subcarriers because propagation occurs in modes whose characteristics change significantly with frequency. Using knowledge of the delay spread in each subcarrier can then be used to adaptively select and avoid subcarriers with delay spread exceeding the cyclic prefix length. With this approach it is possible to create an OFDM system that is more efficient than systems satisfying the delay spread of all subcarriers. In this paper, we therefore propose subcarrier delay spread based adaptive OFDM to enhance the performance of OFDM systems operating in mobile wideband waveguide channels. To identify the delay spread of individual subcarriers we propose two methods. Using these methods, we provide simulation results to demonstrate the effectiveness of the technique. We also make use of experimental waveguide channel measurements to demonstrate the technique in realistic settings. Results show that performance can be significantly improved by using the proposed approach.

A novel low complexity energy detection receiver, which utilizes knowledge of the magnitudes of the fading gains of the receive diversity branches, is presented. Its error performance in flat Rayleigh fading with multi-level amplitude-shift keying is analyzed, resulting in a closed form expression for the symbol error probability (SEP) as well as analytical results for high signal-to-noise ratios. These show that the receiver has the same diversity order as that of coherent receivers but maintains the low complexity structure of energy detectors. Numerical results show that the SEP performance of the energy detection receiver is much closer to that of a coherent receiver than to that of a noncoherent one. Furthermore, we also consider transmit constellation optimization and conclude that an equally spaced amplitude level constellation performs close to the optimal solution in Rayleigh fading. A significant advantage of this receiver is that it performs much better than noncoherent detection but maintains the low complexity structure of noncoherent detectors. Training to obtain the channel magnitudes is, however, required but the low complexity receiver can be used to perform that with the only additional overhead being the training time.