Monitoring Respiratory Motion With Wi-Fi CSI: Characterizing Performance and the BreatheSmart Algorithm.

Respiratory motion (i.e., motion pattern and rate) can provide valuable information for many medical situations. This information may help in the diagnosis of different health disorders and diseases. Wi-Fi-based respiratory monitoring schemes utilizing commercial off-the-shelf (COTS) devices can provide contactless, low-cost, simple, and scalable respiratory monitoring without requiring specialized hardware. Despite intense research efforts, an in-depth investigation on how to evaluate this type of technology is missing. We demonstrated and assessed the feasibility of monitoring and extracting human respiratory motion from Wi-Fi channel state information (CSI) data. This demonstration involves implementing an end-to-end system for a COTS-based hardware platform, control software, data acquisition, and a proposed processing algorithm. The processing algorithm is a novel deep-learning-based approach that exploits small changes in both CSI amplitude and phase information to learn high-level abstractions of breathing-induced chest movements and to reveal the unique characteristics of their difference. We also conducted extensive laboratory experiments demonstrating an assessment technique that can be replicated when quantifying the performance of similar systems. The results indicate that the proposed scheme can classify respiratory patterns and rates with an accuracy of 99.54% and 98.69%, respectively, in moderately degraded RF channels. Comprehensive data acquisition revealed the capability of the proposed system in detecting and classifying respiratory motions. Understanding the feasible limits and potential failure factors of Wi-Fi CSI-based respiratory monitoring scheme - and how to evaluate them - is an essential step toward the practical deployment of this technology. This study discusses ideas for further expansion of this technology.

Bi-Criteria Radio Spectrum Sharing With Subspace-Based Pareto Tracing.

Radio spectrum is a scarce resource. To meet demands, new wireless technologies must operate in shared spectrum over unlicensed bands (coexist). We consider coexistence of Long-Term Evolution (LTE) License-Assisted Access (LAA) with incumbent Wi-Fi systems. Our scenario consists of multiple LAA and Wi-Fi links sharing an unlicensed band; we aim to simultaneously optimize performance of both coexistence systems. To do this, we present a technique to continuously estimate the Pareto frontier of parameter sets (traces) which approximately maximize all convex combinations of network throughputs over network parameters. We use a dimensionality reduction approach known as active subspaces to determine that this near-optimal parameter set is primarily composed of two physically relevant parameters. A choice of two-dimensional subspace enables visualizations augmenting explainability and the reduced-dimension convex problem results in approximations which dominate random grid search.

Continuous-capture microwave imaging.

Light-in-flight sensing has emerged as a promising technique in image reconstruction applications at various wavelengths. We report a microwave imaging system that uses an array of transmitters and a single receiver operating in continuous transmit-receive mode. Captures take a few microseconds and the corresponding images cover a spatial range of tens of square meters with spatial resolution of 0.1 meter. The images are the result of a dot product between a reconstruction matrix and the captured signal with no prior knowledge of the scene. The reconstruction matrix uses an engineered electromagnetic field mask to create unique random time patterns at every point in the scene and correlates it with the captured signal to determine the corresponding voxel value. We report the operation of the system through simulations and experiment in a laboratory scene. We demonstrate through-wall real-time imaging, tracking, and observe second-order images from specular reflections.

A Case Study of Medical Device Wireless Coexistence Evaluation.

This article aims to provide a narrative for addressing wireless coexistence in medical devices to help medical device developers, test engineers, and regulatory affairs personnel throughout the device life cycle. Accordingly, we present a case-study covering the coexistence evaluation process including the risk analysis of the wireless functionality of a hypothetical medical device, determining the corresponding risk category, specification of the device functional wireless performance (FWP), wireless coexistence testing, and measurement of the intended/untended signal ratio. Also, we propose a simple method for translating the test outcome into user recommendations for minimum/maximum separation distances between the device, its intended companion, and the source of unintended signals.

Slot Jamming Effect and Mitigation Between LTE-LAA and WLAN Systems With Heterogenous Slot Durations.

To improve spectrum sharing between long-term evolution (LTE) license assisted access (LAA) and incumbent systems such as wireless local area networks (WLANs) in unlicensed spectrum, listen before talk (LBT) has been proposed as a candidate for LAA channel access. To allow for a robust spectrum sensing performance, LBT may use a backoff-slot duration that is substantially larger than its WLAN counterpart. There is potential for an unknown backoff slot-jamming (SJ) effect, which may significantly decrease channel access probability (CAP) and throughput of LAA-LBT links. In this paper, we study the SJ effect and propose an effective anti-SJ (ASJ) LBT scheme. To gain theoretical insight, we develop a new performance analysis approach on coexisting systems with different slot durations. We model the LAA backoff process with super-counters, provide an in-depth analysis of the backoff process, and derive key performance indicator (KPI) statistics. These KPIs include backoff hold time, successful transmission probability, CAP, and throughput. Simulation results thoroughly validate our analytical results, and show that the ASJ-LBT scheme is effective in mitigating the SJ effect. These results fill a major technical gap in spectrum sharing research and may be extended to support system optimization and coexistence analysis of other heterogeneous systems.