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5G technology can enable novel healthcare applications and augment existing medical device use of wireless technology to improve healthcare delivery. Having the dual role of medical device and cellular user equipment (UE), 5G-enabled devices navigate a plethora of rules and tests before they can operate on a 5G network to deliver their intended medical function. In this paper, we review the state-of-the-art of 5G UE certification programs and testing specifications. We then identify test challenges and discuss the relevance of existing test practices to support the 5G-enabled medical device safety and effectiveness. This information is useful to medical device developers planning to incorporate 5G technology in their products and wireless engineers working to expand mobile services into the healthcare vertical.

5G and beyond networks will transform the healthcare sector by opening possibilities for novel use cases and applications. Service level agreements (SLAs) can enable 5G-enabled medical device use cases by documenting how a medical device communication requirements are met by the unique characteristics of 5G networks and the roles and responsibilities of the stakeholders involved in offering safe and effective 5G-enabled healthcare to patients. However, there are gaps in this space that should be addressed to facilitate the efficient implementation of 5G technology in healthcare. Current literature is scarce regarding SLAs for 5G and is absent regarding SLAs for 5G-enabled medical devices. This paper aims to bridge these gaps by identifying key challenges, providing insight, and describing open research questions related to SLAs in 5G and specifically 5G-healthcare systems. This is helpful to network service providers, users, and regulatory authorities in developing, managing, monitoring, and evaluating SLAs in 5G-enabled medical systems.

Exploiting unlicensed spectrum bands for cellular communication is a rapidly embraced trend by industry stakeholders. Accordingly, the specifications of Long Term Evolution (LTE) were extended in Release 13 to allow unlicensed spectrum operation, also known as LTE-Licensed Assisted Access (LAA). LTE is widely adopted, and there is a potential for significant coexistence impact of LTE-LAA on users of unlicensed spectrum including wireless medical devices, whether adopters of the new technology or incumbents. Therefore, work was initiated to revise and update the American National Standards Institute (ANSI) C63.27 standard for evaluation of wireless coexistence. This paper details the experimental work conducted at the Electromagnetic Compatibility and Wireless Laboratory, U.S. Food and Drug Administration, to investigate the use of LAA signals for wireless coexistence testing. A software defined radio platform was deployed to generate realistic LAA signals and measure the wireless coexistence impact on the LAA communication link. The equipment under test (EUT) used IEEE 802.11ac as an example incumbent technology in the 5 GHz band. The standardized radiated anechoic chamber method was used for testing. Results highlight the mutual coexistence impact of LAA in the 5 GHz band and suggest that selecting an LAA signal with the maximum possible channel time occupancy and the highest possible modulation and coding scheme (MCS) yields the most impactful coexistence situation on both the EUT and the LAA system.

This article aims to provide a narrative for addressing wireless coexistence in medical devices to help medical device developers, test engineers, and regulatory affairs per-sonnel 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.

The 2.4 GHz spectrum is home to several Radio Access Technologies (RATs), including ZigBee, Bluetooth Low Energy (BLE), and Wi-Fi. Accordingly, the technologies’ spectrum-sharing qualities have been extensively studied in literature. License-Assisted Access (LAA) Listen-Before-Talk (LBT) has been identified in technical reports as the foundation for the channel access mechanism for 5G New Radio-Unlicensed (NR-U) operating in the 2.4 GHz Industrial, Scientific, and Medical (ISM) band. The introduction of NR-U into this band raises new concerns regarding coexistence of the newcomer with traditional incumbents. This article reports an investigation of BLE 5 and cellular LBT coexisting systems by means of empirical evaluation. The importance of this study stems from that the studied LBT mechanism is indicative of how 5G NR-U would perform in the 2.4 GHz band. Tests were performed in conformity with the American National Standards Institute (ANSI) C63.27 standard for evaluation of wireless coexistence, and results were reported in terms of throughput and interframe delays. In accordance with the standard and under different BLE physical layers (PHYs) and LBT priority classes, three setups were investigated. These pertain to the three tiers of evaluation, which correspond to the criticality of the device under test. Results demonstrated how BLE throughput dropped as the intended-to-unintended signal ratio decreased, and LBT classes exhibited a diminishing effect as the class priority descended. Long Range BLE PHY was found to sustain longer gap times (i.e., delay) than the other two PHYs; however, it showed less susceptibility to interference. Results also demonstrated that low data rate BLE PHYs hindered the LBT throughput performance since they correspond to longer airtime durations.

Integrating wireless technology in medical devices has proved beneficial for both patients and caregivers. However, the use of shared, unlicensed spectrum bands by both medical and non-medical wireless devices has raised concerns about wireless coexistence. The challenge of incorporating wireless communication into a medical device is to ensure reasonable medical device effectiveness and patient safety. Consequently, work to develop a standardized process to assess wireless coexistence, primarily for wireless medical devices, was carried by Subcommittee 7 of American National Standards Institute (ANSI)-accredited standards committee (ASC) C63 and the Wireless Working Group (SM-WG06) of the Association for the Advancement of Medical Instrumentation (AAMI). Both groups have recently released their respective documents. In this article, we discuss practical aspects of wireless coexistence testing—in the realm of ANSI C63.27 and AAMI TIR69—to help answer basic, yet important, questions such as what to test, how to test, and how to present results.

This article details the experimental work conducted at the Electromagnetic Compatibility and Wireless Laboratory, U.S. Food and Drug Administration, to investigate the use of Licensed Assisted Access (LAA) signals for wireless coexistence testing. A software-defined radio platform was deployed to generate realistic LAA signals and measure the wireless coexistence impact on the LAA communication link. The equipment under test (EUT) used IEEE 802.11ac as an example of incumbent technology in the 5-GHz band. The standardized radiated anechoic chamber method was used for testing. Results highlight the mutual coexistence impact of LAA in the 5-GHz band and suggest that selecting an LAA signal with the maximum possible channel time occupancy and the highest possible modulation and coding scheme yields the most impactful coexistence situation on both the EUT and the LAA system. Additionally, an analysis of the internal LAA system states during coexistence testing is presented to document the inverse relationship between LAA transmit and wait times during coexistence and the adverse impact of challenging coexistence scenarios on successful channel access. Finally, the risk management process of wireless coexistence for medical devices is summarized and associated with coexistence testing.

Wireless communication is an essential part of daily life for users globally with applications in medical devices, cellular phones, Internet of Things nodes, and others. Accordingly, there is a need to understand the patterns and properties of radio-frequency spectrum use by acquiring accurate spectrum utilization measurements. However, the massive storage volume needed to execute spectrum surveys—especially when a fast sampling rate is used—is an impeding factor in terms of cost and ease-of-access. In this paper, a probabilistic efficient storage algorithm (PESA) is proposed to facilitate high-accuracy, time-domain spectrum surveys conducted at a fast sample acquisition rate to detect sporadic spectrum occupancy patterns that could be in the order of microseconds. PESA divides the dynamic range of monitoring equipment into bins—each represented by one component of a Gaussian mixture model (GMM). Windows of activity and inactivity in the measurements are established by comparing with a threshold, and then indicators to the GMM component that best describes a window are recorded, hence reducing the required storage volume. Results demonstrate that ${\approx}99$ % reduction in the storage volume is achievable while maintaining an accurate estimation of channel utilization (CU) and activity/inactivity periods. Furthermore, a LabVIEW implementation of PESA on a hardware platform was executed and used to survey Wi-Fi channel 1 in a healthcare environment for seven consecutive hours. Although more than 25 billion samples were observed, the resulting data only occupied 96.28 MB.

Current technical reports indicate License-Assisted Access (LAA) Listen-Before-Talk (LBT) as the preferred channel access scheme for the upcoming 5G New Radio-Unlicensed. Various studies have examined heterogeneous coexistence of WiFi/LTE-LAA systems. This paper investigates the homogeneous coexistence of intra-network LAA-LBT devices operating in dense deployment scenarios. Results relevant to ETSI-specified priority classes are reported in terms of channel utilization, collision probability, and channel access delay. The framework presented in this paper is then employed to investigate wireless coexistence in a 5G-enabled intensive care unit employing remote patient monitoring over 5G NR-U.

Fifth generation (5G) mobile communication technology can enable novel healthcare applications and augment existing ones. However, 5G-enabled healthcare applications demand diverse technical requirements for radio communication. Knowledge of these requirements is important for developers, network providers, and regulatory authorities in the healthcare sector to facilitate safe and effective healthcare. In this paper, we review, identify, describe, and compare the requirements for communication key performance indicators in relevant healthcare use cases, including remote robotic-assisted surgery, connected ambulance, wearable and implantable devices, and service robotics for assisted living, with a focus on quantitative requirements. We also compare 5G-healthcare requirements with the current state of 5G capabilities. Finally, we identify gaps in the existing literature and highlight considerations for this space.

The use of shared and unlicensed radio spectrum has been the impetus of innovative and widely used technologies (e.g., Wi-Fi, Bluetooth, and others) — driving the scene of ubiquitous connectivity for devices, sensors, and peripherals in an encompassing Internet of Things (IoT). However, coexisting technologies operating in unlicensed bands need to share limited spectrum resources while attempting to offer desired performance. This could prove challenging as channel access is not guaranteed, which raises concerns for wireless coexistence in sensitive applications like medical devices. In this article, we provide a brief review of topics forming the current stage of wireless coexistence in research, industry, and regulatory circles. We present the standardization activities for the evaluation of wireless coexistence, and recent advancements of unlicensed spectrum technologies such as Wi-Fi, Bluetooth, and Long Term Evolution (LTE) in unlicensed bands, along with proposed evaluation methods.

Long term evolution (LTE) technology leveraging the unlicensed band is anticipated to provide a solution for the challenges stemming from the rapid growth of mobile wireless services, the scarcity of available licensed spectrum, and the expected significant increase in mobile data traffic. Ensuring fair operation in terms of spectrum sharing with current unlicensed spectrum incumbents is a key concern relative to the success and viability of Unlicensed LTE (U-LTE). This paper addresses the problem of modeling and evaluating the coexistence of LTE license-assisted-access in the unlicensed band. The paper presents a novel analytical model using Markov chain to accurately model the LAA listen-before-talk scheme, as specified in the final technical specification 36.213 of 3GPP release 13 and 14. Furthermore, model validation is demonstrated through numerical and simulation results comparison. Model performance evaluation is examined and contrasted with IEEE 802.11 distributed coordination function. Finally, a comprehensive coexistence performance analysis is conducted for both homogeneous and heterogeneous network scenarios and coexistence results are presented and discussed herein.

Sharing spectrum resources in unlicensed bands grants vehicular applications inexpensive and ubiquitous access to wireless services. However, wireless technology coexistence concerns are gaining increased attention. In response, coexistence test methods are now being reported in the literature, and novel solutions are considered in the American National Standards Institute C63.27 Standard for Evaluation of Wireless Coexistence. Furthermore, the IEEE 802 standards committee formed a new study group, named wireless automotive coexistence, operating under the umbrella of 802.19 working group to highlight the increasing concerns of wireless coexistence in the automotive domain. The radiated open environment coexistence test (ROECT) method offers high flexibility to test wireless devices for coexistence. Radio signal propagation during testing is over the air, reducing access to the signal path. Consequently, monitoring instantaneous device performance is a challenge yet to be addressed. This paper introduces a novel method for estimating the channel utilization of multiple, concurrent wireless transmitters sharing the 2.4-GHz ISM band in the context of ROECT. Passively received power measurements were collected during testing, and then a Gaussian mixture model was used to build a classifier for labeling observed power samples relative to their source. Case studies utilizing IEEE 802.11n as an interfering system with an under test system based on either IEEE 802.11n or ZigBee are detailed. Findings demonstrate the mutual effect of spectrum sharing on both interfering and under test systems in terms of per-second channel utilization and frame collision. Experimental results show an overall accuracy exceeding 98%.

The connected car is ushering in a new era of automotive design. Driven by increasing customer demand for connectivity and advances in electronics, connected cars are now equipped with advanced infotainment systems with a variety of applications. Seamless integration of consumer electronic (CE) devices into car infotainment systems is crucial for mimicking home and office user experience. Because wireless communication is more user-friendly than wired communication, it has become the preferred method for connecting CE devices to car infotainment systems. WLAN 1 and Bluetooth 2 are the most promising technologies for this purpose. Both systems operate in the spectrum-scarce 2.4 GHz unlicensed industrial, scientific and medical (ISM) radio band. The coexistence between WLAN and Bluetooth has garnered a significant amount of attention from both academic and industry researchers. However, the unique features of vehicle mobility and the high density of devices in a limited roadway area necessitate further investigation in the automotive domain. This paper focuses on the coexistence between WLAN and Bluetooth systems among vehicle infotainment applications, and on WLAN co-channel interference. Performance is evaluated using experimental measurements in real-world scenarios. The mobility effect is studied in detail. Results show that an onboard WLAN network is strongly affected by the surrounding networks. Coexistence duration decreases exponentially with relative speed between automobile networks. WLAN effect on Bluetooth is extremely high when WLAN's non-overlapped channels 1, 6, and 11 are simultaneously occupied. WLAN interference leads to a significant number of clippings in Bluetooth audio signals, especially in high WLAN traffic load situations. An exponential decease in the number of clipping events as a function of speed is observed.

Summary This paper presents novel vehicle classification technology by utilizing a single-element piezoelectric sensor placed diagonally on a traffic lane to accurately identify vehicles. Novelty of this technique originates from using diagonally placed piezoelectric strip sensor and machine learning technology to provide a highly accurate and cost-effective alternative to current vehicle classification systems. Diagonal placements of the piezoelectric strip sensor ensure detection of passing vehicle tires by facilitating vehicle classification process. Presented technology is capable of accurately classifying vehicles into a relatively large number of classifications, including motorcycle, which has proven to be a challenging category in present-day commercial vehicle classifiers. Vehicle classification is a vital intelligent transportation systems application. Accurate data reporting aids suitable roadway design for safety and capacity and can also support other purposes, such as reporting highway congestion to the general public or providing area denseness data to interested businesses. To make a classification decision, a vehicle's signal is acquired from diagonal piezoelectric strip sensor, processed, and then applied to a machine learning algorithm. A speed estimation technique using the same single-element piezoelectric sensor was also developed, tested, and compared with an embedded vehicle classifier currently used by the Oklahoma Department of Transportation. Testing on several highway sites indicated up to 97% classification accuracy. This paper presents a complete description of the developed system, including sensor installation, data acquisition and processing, and classification algorithm. Overall, the system offers a high-performance cost-effective solution for vehicle classification that minimizes roadwork typically required for loop and sensor installations of current systems. Copyright © 2016 John Wiley & Sons, Ltd.

Medical device manufacturers incorporate wireless technology in their designs to offer convenience and agility to both patients and caregivers. However, the use of unlicensed radio spectrum bands by both medical devices and other equipment raises concerns about wireless coexistence. Work by the accredited standards committee C63 of the American National Standards Institute (ANSI) to provide the community with a consensus standard for coexistence evaluation resulted in the publication of the ANSI C63.27 standard, which was later recognized by the U.S. Food and Drug Administration. Estimating the likelihood of wireless coexistence of a system under test (SUT) in a given environment is central to the evaluation and reporting of wireless coexistence, as made clear in the C63.27 standard. However, no method to perform this estimation is provided. In this paper, we propose the use of logistic regression (LR) to estimate the likelihood of wireless coexistence of a medical device in its intended environment. Radiated open environment coexistence testing was used to realize a test scenario in which the interfering network was IEEE 802.11n Wi-Fi and the SUT was ZigBee; exemplary wireless technologies for interfering network and medical device, respectively. LR model fitting was then performed to derive a model that describes the performance of SUT under a range of wireless coexistence phenomena. Finally, results were incorporated with the outcome of a spectrum survey using Monte Carlo simulation to estimate the SUT likelihood of wireless coexistence in a hospital environment.

The increasing use of shared, unlicensed spectrum bands by medical devices and nonmedical products highlights the need to address wireless coexistence to ensure medical device safety and effectiveness. This paper provides the first step to approximate the probability of a device coexisting in its intended environment by providing a generalized framework for modeling the environment. The application of this framework is shown through an 84-day spectrum survey of the 2.4–2.48 GHz industrial, scientific, and medical band in a hospital environment in the United States. A custom platform was used to monitor power flux spectral density and record received power. Channel utilization of three nonoverlapping channels of 20 MHz bandwidth—relative to IEEE 802.11 channels 1, 6, and 11—were calculated and fitted to a generalized extreme value distribution. Low channel utilization was observed ( $ 10%) in the surveyed environment with sporadic occurrences of higher channel utilization ( $ >$ 50%). Reported findings can be complementary to wireless coexistence testing. This paper can provide input to the development of a consensus standard for wireless device coexistence test methods and a consensus document focused on wireless medical device coexistence risk management.

The demand for increasingly challenging data rates in cellular networks has motivated the pursuit to exploit abundant bandwidth at the millimeter waves (mmWave) spectrum, which offers large bandwidths and near free-space path loss for line of sight links. However, this solution comes at the cost of limited communication range. Thus, mmWave basestations (BS) are expected to be densely deployed to maximize offered service. As the energy consumed in a network is roughly proportional to the number of nodes, how energy efficient a mmWave network will be is a question that remains unanswered so far. In this paper, we compare the performance of mmWave cellular networks in terms of energy efficiency (EE) to that of networks operating at 2 GHz. We start from the link budget to determine the average cell radius of two mmWave systems operating at 28 GHz and 60 GHz. Afterwards, intensity of a Poisson Point Process that models mmWave BS locations pertaining to expected operational network parameters is calculated. The probability of coverage offered by investigated systems is evaluated using analytical expressions. Finally, EE is calculated using consumed power model that assumes actual mmWave components. Results suggest that when the deployment environment allows for high signal to interference and noise ratio (SINR) to be achieved at the receiver, mmWave system EE outperforms a 2 GHz system. Conversely, when only low SINR is achievable, 2 GHz system EE is superior to mmW system.

Wireless technology has become an invaluable facilitator in many aspects of daily life. Healthcare environments in particular have gained noticeable agility and flexibility by integrating wireless functionality into various medical equipment. As of late, chipsets designed to implement communication standards in the Industrial, Scientific and Medical (ISM) band have become inexpensive and widely available, making wireless-enabled medical devices reach increased number of users. However, the sharp increase in the number of operating nodes now occupying the ISM band has resulted in a cluttered spectrum with limited resources in many environments. In this paper, we report on a long term spectrum survey of the ISM band in both an intensive care unit (ICU) and a post-surgery recovery room (RR). Both spaces were concurrently surveyed for 28 consecutive days capturing spectrum occupancy on every weekday four times. Results indicate that spectrum occupancy patterns are location dependent. Examined sub-channels with significant correlation in activity pattern corresponded mainly to IEEE 802.11 channels 1, 6, and 11. Low daily duty cycle is indicated at a maximum of 5.17% at RR and 3.11% at ICU.

The 2.4 GHz ISM band is crowded with a wide variety of wireless devices operating under various access protocols, Bluetooth Low Energy (BLE) among them. Low power requirements, low cost, and ease of integration have promoted BLE's rapidly growing popularity. BLE applications range from providing wireless interface for monitoring household equipment status to reporting critical information from medical devices that might have less tolerance for transmission errors to function properly. In this paper, we identify risks in a real world wireless environment that adversely affect BLE system functionality. We also propose a methodology utilizing spectrum surveys to quantify probability of transmission failure relative to the system's interference detection threshold. Spectrum surveys were conducted in a basketball sport facility, a university student union and a hospital intensive care unit (ICU). Results demonstrate how a BLE system selects data transmission channels in the presence of interference. Moreover, findings of this study confirm that a BLE system is able to maintain a low probability of failed transmission while operating in the presence of high interference unless the environment noise floor is close to the employed interference detection threshold.

ISM spectrum is becoming increasingly populated with various wireless technologies, rendering it a scarce resource. Consequently, wireless coexistence is increasingly vulnerable to new wireless devices attempting to access the same spectrum. This paper presents a novel method for identifying wireless technologies through the use of simple energy detection techniques. Energy detection is used to measure the channel statistical temporal characteristics including activity and inactivity probability distributions. Features uniquely belonging to specific wireless technologies are extracted from the probability distributions and fed into a machine-learning algorithm to identify the technologies under evaluation. Wireless technology identification enables situational awareness to improve coexistence and reduce interference among the devices. An intelligent wireless device is capable of detecting wireless technologies operating within same vicinity. This can be performed by scanning energy levels without the need for signal demodulation and decoding. In this work, a wireless technology identification algorithm was assessed experimentally. Temporal traffic pattern for 802.11b/g/n homogeneous and heterogeneous networks were measured and used as algorithm input. Identification accuracies of up to 96.83% and 85.9% were achieved for homogeneous and heterogeneous networks, respectively.

Bluetooth Low Energy (BLE) is a ubiquitous technology allowing applications in healthcare, wellness and house-hold sensors to have wireless functionality. Even though a frequency hopping mechanism is employed by BLE to combat fading and interference in the 2.4 GHz Industrial, Scientific and Medical (ISM) band, a noticeable probability of collision is expected to arise when the number of communicating BLE devices in the same vicinity increases. In this paper, an analytical model to find the selection probability of each of the 37 BLE data channels is presented. The results, which are confirmed by brute-force simulation, are then used to find the probability of collision between collocated BLE pairs and their maximum achievable aggregate throughput.