Partitioning surface wave propagation on reconfigurable porous plane.

This paper introduces a novel reconfigurable technique for partitioning the propagation of surface waves by utilizing a T-shaped structure and pathways established through the introduction of fluid metal or metal pins into evenly spaced cylindrical cavities within a porous surface wave platform. Notably, the co-printing of metal and dielectric materials via 3D printing is employed, resulting in an expedited fabrication process. Extensive 3D electromagnetic simulations and experimental investigations validate the proposed approach's efficacy in achieving surface wave division while minimizing interference. The study encompasses an exploration of diverse power distribution ratios achievable within the distributed surface waves. Critical physical parameters of the T-junction are comprehensively examined, including partition depth, junction geometry, output port symmetry, and asymmetry. Additionally, the research delves into the frequency-dependent behaviours of asymmetric T-junctions and pathways. These findings establish the groundwork for adaptable architectures, facilitating concurrent communication among multiple devices within a unified surface wave communication network. This innovation holds potential to enhance various applications through improved communication capabilities.

Signal Separation and Tracking Algorithm for Multi-Person Vital Signs by Using Doppler Radar.

Noninvasive monitoring is an important Internet-of-Things application, which is made possible with the advances in radio-frequency based detection technologies. Existing techniques however rely on the use of antenna array and/or frequency modulated continuous wave radar to detect vital signs of multiple adjacent objects. Antenna size and limited bandwidth greatly limit the applicability. In this paper, we propose our system termed 'DeepMining' which is a single-antenna, narrowband Doppler radar system that can simultaneously track the respiration and heartbeat rates of multiple persons with high accuracy. DeepMining uses a number of signal observations over a period of time as input and returns the trajectory of the respiration and heartbeat rates of each person. The extraction is based on frequency separation algorithms using successive signal cancellation. The proposed system is implemented using the self-injection locking radar architecture and tested in a series of experiments, showing accuracies of 90% and 85% for two and three objects, respectively, even for closely located persons.

Joint source and relay optimization for interference MIMO relay networks.

This paper considers multiple-input multiple-output (MIMO) relay communication in multi-cellular (interference) systems in which MIMO source-destination pairs communicate simultaneously. It is assumed that due to severe attenuation and/or shadowing effects, communication links can be established only with the aid of a relay node. The aim is to minimize the maximal mean-square-error (MSE) among all the receiving nodes under constrained source and relay transmit powers. Both one- and two-way amplify-and-forward (AF) relaying mechanisms are considered. Since the exactly optimal solution for this practically appealing problem is intractable, we first propose optimizing the source, relay, and receiver matrices in an alternating fashion. Then we contrive a simplified semidefinite programming (SDP) solution based on the error covariance matrix decomposition technique, avoiding the high complexity of the iterative process. Numerical results reveal the effectiveness of the proposed schemes.