A Compact Dynamic Omnidirectional Antenna

We propose a novel omnidirectional antenna design incorporating directional modulation for secure narrow planar information transmission. The proposed antenna features a compact size and stable omnidirectional radiation performance by employing two tightly spaced, printed meander line monopole antennas, acting as a single radiating element. To achieve a narrow information secure region, the proposed antenna is fed by differential power excitation of two ports with real-time dynamic switching. This leads to phase pattern modulation only along the electrical polarization, resulting in directionally confined information recoverable region in the E-plane, while maintaining highly constant or static omnidirectional H-plane pattern, inducing a $360^\circ$ information recoverable region. The dynamic antenna is designed and fabricated on a single layer of Rogers RO4350B which provides a miniaturized planar size of $0.36 \times 0.5 , \lambda_0^2$ at 2.7 GHz and easy integration. To validate the wireless communication performance, the fabricated antenna is directly fed with a 10 dB power ratio by a radio frequency (RF) switching system and evaluated for 16-QAM and 256-QAM transmission in a high signal-to-noise ratio (SNR) environment. Experimental results demonstrate that for 16-QAM transmission, a narrow E-plane information beam (IB) of approximately $34^\circ$ and omnidirectional H-plane IB are obtained, and a narrower E-plane IB is achieved around $15^\circ$ for 256-QAM. These results confirm that the proposed antenna offers a simple yet effective approach to enhance planar physical information security with a compact dynamic antenna system.

A Compact Narrowband Antenna Design for RF Fingerprinting Applications

Radio frequency (RF) fingerprinting is widely used for supporting physical layer security in various wireless applications. In this paper, we present the design and implementation of a small antenna with low-cost fabrication that can be directly integrated with nonlinear passive devices, forming a passive RF tag providing unique nonlinear signatures for RF fingerprinting. We first propose a miniaturized meander line dipole, achieved by two folded arms on two sides of the substrate. This leads to antenna with a simple feeding structure and compact size, making it ideal for planar integration. Two antennas on Rogers 4350B and ultra-thin flexible Panasonic Felios are fabricated, achieving small size at $0.21 \times 0.06 \times 0.004 \lambda_0^3$ and $0.14 \times 0.1 \times 0.0008 \lambda_0^3$ with realized gain of 1.87 dBi and 1.46 dBi. The passive tag consists of the proposed antenna structure and an integrated RF diode, and is further developed on both substrates, aiming to generate inter-modulation products (IMP) due to the nonlinearity of the diode, which can be used for device identification through classification algorithms. We investigate the nonlinearity of the designed tags for transmission at 15 dBm using two-tone signals. All tags produce a significant increased power at IMP frequencies at a range of 0.4 m. The tags on Rogers substrate provide around 23 dB IMP power increase and tags on flexible substrate embedded in lossy material provide around 16 dB power increase. These findings confirm that the proposed solution offers a simple passive tag design to support unique nonlinear signatures for RF fingerprinting applications in a simple, low-cost device.

Motion Classification Based on Harmonic Micro-Doppler Signatures Using a Convolutional Neural Network

We demonstrate the classification of common motions of held objects using the harmonic micro-Doppler signatures scattered from harmonic radio-frequency tags. Harmonic tags capture incident signals and retransmit at harmonic frequencies, making them easier to distinguish from clutter. We characterize the motion of tagged handheld objects via the time-varying frequency shift of the harmonic signals (harmonic Doppler). With complex micromotions of held objects, the time-frequency response manifests complex micro-Doppler signatures that can be used to classify the motions. We developed narrow-band harmonic tags at 2.4/4.8 GHz that support frequency scalability for multi-tag operation, and a harmonic radar system to transmit a 2.4 GHz continuous-wave signal and receive the scattered 4.8 GHz harmonic signal. Experiments were conducted to mimic four common motions of held objects from 35 subjects in a cluttered indoor environment. A 7-layer convolutional neural network (CNN) multi-label classifier was developed and obtained a real time classification accuracy of 94.24%, with a response time of 2 seconds per sample with a data processing latency of less than 0.5 seconds.