The application of Radio Frequency (RF) sensors in human-centric perception has attracted considerable attention. Human pose estimation (HPE) using millimeter-wave (mmWave) radar holds promise for use in private and sensitive environments, such as medical monitoring and domestic rehabilitation assessment. Recent methods that utilize mmWave point clouds for pose estimation rely on raw 3D coordinate input data, failing to effectively utilize key velocity information. Additionally, existing research primarily focuses on reflection point clouds from a single person in a fixed position, making it difficult to apply in practical multi-person environments with interference. In this paper, we introduce the first multi-person mmWave radar point cloud dataset (mmVPose) focused on rehabilitation training. To effectively leverage velocity information for enriching point cloud features, we propose a velocity-dependent heatmap generation method, which represents input point clouds and predicted joint distributions as heatmaps in 3D voxel space. Furthermore, to preserve the complete latent human body structure while reducing computational complexity, we design a sparse attention mechanism for voxelized point clouds. Extensive experiments demonstrate that our method mmVPE achieves state-of-the-art performance in multi-person scenarios.

In this paper, we investigate a novel physical layer secure (PLS) potential technique which is summarized into a category of index modulation (IM) scheme, namely the spatial field digital modulation (SFDM). In an SFDM communication system, bit streams are modulated in the spatial distribution of electromagnetic (EM) field. Orbital angular momentum (OAM) mode groups can be utilized for beamforming and thus realize an OAM based SFDM (OAM-SFDM) system. This kind of IM systems that utilize the distribution of EM field to transmit information can radiate different signals to different directions and possess inherent anti-eavesdropping capability. Since an eavesdropper lacks prior knowledge, it is difficult to construct appropriate and effective estimators for signal demodulation. However, such system is vulnerable when potential eavesdroppers adopt clustering algorithm, a type of non-realtime demodulation. We propose two PLS strategies with different computational complexity, the power hopping (PH) method and the symbol variation (SV) method, to confront single-antenna eavesdroppers and multi-antenna eavesdroppers, respectively. Both approaches are key-free, and do not require any prior channel state information (CSI) about eavesdroppers. The mentioned methods could constantly disrupt the statistical properties of eavesdroppers’ channels and even their received signals. Theoretical analysis and numerical simulations have been conducted to validate the feasibility of these two schemes. Furthermore, a prototype of OAM-SFDM based PLS communication system is built in a realistic scenario. The experimental results demonstrate that both PH method and SV method can effectively resist clustering algorithm in their corresponding application scenarios.

Users of wearable devices often hope to collect continuous personal vital signs such as heartrates, blood pressures, respiration rates and breath efforts with comfort and free movement. Current approaches are however hindered by their accuracy, comfort, convenience, power consumptions and sensing capabilities. The requirement of direct skin contacts in electrocardiogram (ECG) and acoustic methods limits their sensation of comfort, wearing convenience, body motion and hence long-term use. Photo-plethysmography (PPG) in wrist watches and finger clamps do not require immediate skin touch but its signal can be severely degraded by relative movement. In this paper, we introduce a new method modulating the external and internal motion of the wearer body directly onto multiplexed radio frequency (RF) signals by near-field coherent sensing (NCS). To minimize the deployment and maintenance cost of NCS vital-sign monitoring, passive (battery-free) RF identification (RFID) tags can be integrated into garments at the chest and wrist areas as laundry-ready wearable devices. NCS utilizes both amplitude and phase of the RF signals to sense and isolate the vital signs, which significantly increases the signal quality in comparison to methods based solely on signal strength. The high frequency components of the NCS signal is employed to mitigate the body movement interference to obtain more accurate heartrates.

Continuous monitoring of vital signs including heart rates, blood pressures, respiration rates and breath efforts is critical for eHealth. Current approaches are limited in accuracy, convenience and sensing capabilities. Some methods such as electrocardiogram (ECG) is difficult for long-term applications due to the requirement of direct skin contact, which is uncomfortable to wearers, restricts body motion and disrupts circadian rhythms. Meanwhile accurate measurement of the inter-heartbeat timing features is important for wellness monitoring and human emotion studies. In this paper, we introduce a new method to modulate the external and internal mechanical motion of the wearer body directly onto multiplexed radio frequency (RF) signals by near- field coherent sensing (NCS). To minimize the deployment and maintenance cost of NCS vital-sign monitoring, passive RF identification (RFID) tags can be integrated into garments at the chest and wrist areas. The unique ID of each tag helps discriminate its signal against interferences from ambient interferences and other tags. NCS utilizes both amplitude and phase of the electromagnetic field to couple the motion, which significantly increases the signal quality in comparison to methods based solely on signal strength. The tag backscattering signal is then processed with spectral equalization to amplify the high frequency components to recover not only the waveform details originally submerged in the low-frequency components but also the sharp peaks for precise heartbeat intervals with improved peak detection certainty. The derived heartbeat interval shows improved stability in comparison with synchronous ECG.

Mode division multiplexing (MDM) using orbital angular momentum (OAM) is a recently developed physical layer transmission technique, which has obtained intensive interest among optics, millimeter-wave, and radio frequency due to its capability to enhance communication capacity while retaining an ultra-low receiver complexity. In this paper, the system model based on OAM-MDM is mathematically analyzed and it is theoretically concluded that such system architecture can bring a vast reduction in receiver complexity without capacity penalty compared with conventional line-of-sight multiple-in-multiple-out systems under the same physical constraint. Furthermore, a$4\times 4$OAM-MDM communication experiment adopting a pair of easily realized Cassegrain reflector antennas capable of multiplexing/demultiplexing four orthogonal OAM modes of$l = {-3}$, −2, +2, and +3 is carried out at a microwave frequency of 10 GHz. The experimental results show high spectral efficiency as well as low receiver complexity.

We propose and demonstrate accurate 3D real-time indoor localization via broadband nonlinear backscatter in passive devices. The proposed method does not need any relative motion between a reader and a tag or the use of reference anchor nodes. In the conventional radio frequency identification (RFID) system, a passive tag responds to a reader by switching its antenna "on" and "off". The operation of such conventional backscatter is essentially "linear", since the reader-to-tag (downlink) and tag-to-reader (uplink) signals overlap on the same carrier frequency. Although linear backscatter is straightforward, the self-jamming problem caused by strong leakage signals from the transmitter to the receiver is notorious and poses many constraints on the received signal quality, operation bandwidth, modulation flexibility and system complexity. To enable high-accuracy real-time 3D indoor localization for passive devices, we show that nonlinear backscatter is more effective than linear backscatter. Nonlinear backscatter exploits nonlinear elements in passive devices to generate second or higher-order harmonics as the uplink response. Separation of downlink and uplink on different carriers allows immediate self-jamming cancellation and direct un-modulated carrier phase decoding, hence resulting in better received signal quality and broad bandwidth of operation, both of which are critical for the localization system. The broad bandwidth allows the design of an efficient phase-based ranging algorithm - heuristic multi-frequency continuous wave (HMFCW) ranging which resolves ambiguous phase cycles with heuristically optimized sparse carrier frequencies. HMFCW ranging can correctly pin down the phase cycle integer with 100% reliability as long as the phase error falls within ±90° × BW% (percentage bandwidth). In our present implementation, we achieved a median ranging error below 1 cm under phase error bounds of ±50°. We realized real-time 3D localization from differential ranging by nonlinear conjugate gradient (CG) search for hyperboloids intersection in a multi-static transceiving system with 1 Tx antenna and 4 Rx antennas. The measured 3D localization median error was 3.5 cm in the indoor environment. Presently, the measurement latency was less than 0.155 seconds. We will present system design, algorithms and a prototype with experimental evaluation.