Real-Time Symbol-Domain OFDM Radar in an OpenAirInterface 5G Base Station With O-RAN Sensing Services

This paper presents a real-time orthogonal frequency-division multiplexing (OFDM) radar embedded in the OpenAirInterface (OAI) 5G base-station process. The radar removes communication symbols by regularized element-wise division and performs range-Doppler processing and ordered-statistic constant-false-alarm-rate detection online without modifying the 5G waveform. The implemented system provides 2.57 m nominal range resolution and 0.28 m/s velocity resolution. Hardware measurements identify and mitigate several implementation-specific limitations, most notably a deterministic carrier-dependent transmit-receive phase rotation on a Universal Software Radio Peripheral (USRP) X300. Selecting a tuning-grid-aligned carrier improves mean-removal clutter suppression from -16.4 dB to 38.0 dB and reduces coherent-integration loss from 19.81 dB to 0.27 dB. The measured processing gain closely agrees with its predicted value. Instrumented worker timing confirms real-time operation, with a conservative 58.4 percent utilization bound and no dropped soundings. A custom E2 service model, E2SM-RADAR, exports detections and a compact slow-time product to a near-real-time RAN Intelligent Controller. Live end-to-end operation demonstrates reliable delivery and supports controller-side tracking, micro-Doppler analysis, and classification. With a commercial user equipment connected on the same carrier, measurements show no measurable difference in downlink throughput estimate with sensing enabled, while the radar sensing bandwidth follows the scheduler allocation.

Activity Recognition Using mm-Wave Radar and Deep Learning: Prayer Tracker Case Study

The issue of privacy has gained significant attention in recent times. Many real-world applications increasingly require the use of sensitive data, such as in surveillance or tracking and assistance systems. To address these concerns, we propose a framework based on mm-wave radar technology that not only meets privacy requirements but also provides the necessary capabilities for these systems, including reliable current position tracking, sequence tracking, and feedback to the user. While the use of radar technology for surveillance purposes is gaining momentum, there has been no research to date on its application for prayer tracking and assistance systems. Furthermore, there is a lack of comprehensive research that covers all aspects of implementing such a system. Proposed approach offers a versatile solution that can be applied to a broad range of scenarios. Instead of utilizing raw I-Q data, we addressed the challenge of classification based on point cloud information generated by the conventional processing chain of the frequency-modulated continuous wave radar. This information contains corresponding range, reflection amplitude, Doppler and angular values. We have developed and compared different machine-learning classification algorithms to identify the most effective one. Our findings reveal that the convolutional neural network ResNet achieves the best results, with accuracy rates reaching up to 95.4 percent when applied to unknown data. The demonstration video of the developed system can be viewed at the following link: https://youtu.be/PnpGQZWqCr4.

Communications over Unlicensed sub-8 GHz Spectrum: Opportunities and Challenges

The utilization of unlicensed spectrum presents a promising solution to the issue of spectrum scarcity in densely populated areas, while also offering a cost-effective means to connect underserved regions. In response to this potential, both academia and industry are actively exploring innovative applications of unlicensed spectrum. This work offers a thorough overview of unlicensed spectrum bands below 8 GHz, including TV White Spaces, Civil Broadband Radio Services, Industrial Scientific Medical bands, and the Unlicensed National Information Infrastructure. The paper focuses on three key aspects: regulations, existing technologies, and applications. It is essential to recognize that "unlicensed" does not equate to "unregulated"; therefore, a clear understanding of permissible and prohibited activities is crucial. From a technological perspective, we examine the current technologies, their capabilities, and relevant applications. Additionally, the shared nature of this spectrum introduces challenges related to interference among users. These collisions can be managed through two primary strategies, that we described: a database-driven approach and coexistence mechanisms at the MAC and PHY layers. This work may serve as a starting point for those who are interested in the unlicensed spectrum, both in academia and industry.