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The identification of vital signs is becoming increasingly important in various applications, including healthcare monitoring, security, smart homes, and locating entrapped persons after disastrous events, most of which are achieved using continuous-wave radars and ultra-wideband systems. Operating frequency and transmission power are important factors to consider when conducting earthquake search and rescue (SAR) operations in urban regions. Poor communication infrastructure can also impede SAR operations. This study proposes a method for vital sign detection using an integrated sensing and communication (ISAC) system where a unified orthogonal frequency division multiplexing (OFDM) signal was adopted, and it is capable of sensing life signs and carrying out communication simultaneously. An ISAC demonstration system based on software-defined radios (SDRs) was initiated to detect respiratory and heartbeat rates while maintaining communication capability in a typical office environment. The specially designed OFDM signals were transmitted, reflected from a human subject, received, and processed to estimate the micro-Doppler effect induced by the breathing and heartbeat of the human in the environment. According to the results, vital signs, including respiration and heartbeat rates, have been accurately detected by post-processing the reflected OFDM signals with a 1 MHz bandwidth, confirmed with conventional contact-based detection approaches. The potential of dual-function capability of OFDM signals for sensing purposes has been verified. The principle and method developed can be applied in wider ISAC systems for search and rescue purposes while maintaining communication links.
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http://dx.doi.org/10.3390/s25123766 | DOI Listing |
Sensors (Basel)
August 2025
School of Information and Communication Engineering, Communication University of China, Beijing 100024, China.
Integrated Sensing And Communication (ISAC) has been applied to the Internet of Things (IoT) network as a promising 6G technology due to its ability to enhance spectrum utilization and reduce resource consumption, making it ideal for high-precision sensing applications. However, while the introduction of millimeter Wave (mmWave) and massive Multiple-Input Multiple-Output (MIMO) technologies can enhance the performance of ISAC systems, they extend the near-field region, rendering traditional channel parameter estimation algorithms ineffective due to the spherical wavefront channel model. Aiming to address the challenge, we propose a tensor-based channel parameter estimation and localization algorithm for the near-field mmWave massive MIMO-Orthogonal Frequency Division Multiplexing (OFDM) ISAC systems.
View Article and Find Full Text PDFEntropy (Basel)
July 2025
Xiamen Key Laboratory of Mobile Multimedia Communications, College of Information Science and Engineering, Huaqiao University, Xiamen 361021, China.
An analog joint source-channel coding (AJSCC) based on Shannon-Kotel'nikov (S-K) mapping transmitting discrete-time encoded samples in orthogonal frequency division multiplexing (OFDM) systems over wireless channel has exhibited excellent performance. However, the phenomenon of carrier frequency offset (CFO) caused by the frequency mismatch between the transmitter's and receiver's local oscillators often exists in actual scenarios; thus, in this paper the performance of AJSCC-OFDM with CFO is analyzed and the S-K mapping is optimized. A joint optimization strategy is developed to maximize the signal-to-distortion ratio (SDR) subject to CFO constraints.
View Article and Find Full Text PDFSci Rep
August 2025
School of Electronics and Information Engineering, Tongji University, Shanghai, 200000, China.
This study investigates a large-scale dynamic Vehicle-to-Everything (V2X) communication network, in which multiple Roadside Units (RSUs) are deployed along highways to enable high-speed vehicular links. To ensure robust and adaptive performance under fast-varying conditions, we propose an integrated framework that combines resource block-based MC-CDMA modulation with dynamic beamforming optimized for complex propagation environments. A custom code mapper and resource element (RE) allocator are introduced to support interference-aware transmission and enhance signal robustness in dense deployment scenarios.
View Article and Find Full Text PDFNatl Sci Rev
September 2025
School of Electronic Engineering, Xidian University, Xi'an 710071, China.
The increasing demand for public safety has created an urgent need for high-performance technologies capable of detecting hazardous liquids with high accuracy, efficiency, and cost-effectiveness. Conventional liquid detection methods often fall short in addressing these requirements due to limitations in precision, operational complexity, and scalability. This study introduces a wireless intelligent system for the detection of suspicious liquids, leveraging advancements in programmable metasurface and software defined radio technologies.
View Article and Find Full Text PDFSensors (Basel)
July 2025
Department of Computer Science, College of Computer and Information Sciences, Jouf University, Sakaka 72341, Saudi Arabia.
Modulation identification plays a crucial role in contemporary wireless communication systems, especially within 5G and future-generation networks that utilize a variety of multicarrier waveforms. This study introduces an innovative algorithm for automatic modulation classification (AMC) built on a deep residual network (DRN) architecture. The approach is tailored to accurately identify advanced 5G waveform types such as Orthogonal Frequency-Division Multiplexing (OFDM), Filtered OFDM (FOFDM), Filter Bank Multicarrier (FBMC), Universal Filtered Multicarrier (UFMC), and Weighted Overlap and Add OFDM (WOLA), using both 16-QAM and 64-QAM modulation schemes.
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