Search

Energy harvesting combined with spectrum sharing offers a promising solution to the growing demand for spectrum while keeping energy costs low. New Radio Unlicensed (NR-U) technology enables telecom operators to utilize unlicensed spectrum in addition to the licensed spectrum already in use. Along with this, the energy demands for the Internet of Things (IoT) can be met through energy harvesting. In this regard, the ubiquity and ease of implementation make the RF-powered NR-U network a sustainable solution for cellular IoT. Using a Markov chain, we model the NR-U network with nodes powered by the base station (BS). We derive closed-form expressions for the normalized saturated throughput of nodes and the BS, along with the mean packet delay at the node. Additionally, we compute the transmit outage probability of the node. These quality of service (QoS) parameters are analyzed for different values of congestion window size, TXOP parameter, maximum energy level, and energy threshold of the node. Additionally, the effect of network density on collision, transmission, and energy harvesting probabilities is observed. We validate our model through simulations. [ABSTRACT FROM AUTHOR]

New Radio Unlicensed (NR-U) is the key representative access technology beyond 5G implementation to alleviate the spectrum crunch. NR-U shares a 5 GHz unlicensed band with WiFi, which has contention challenges for the coexisting systems due to physical and link layer protocols disparity. Being a scheduled access system, NR-U transmissions can only start at strict periodic time slots, which requires introducing a synchronization gap period in the listen-before-talk (LBT) approach. In this paper, we address these issues and analyze the impact of various gap-based NR-U approaches to the fair and efficient coexistence of the two networks. The dependency of successful spectrum access of the two systems on the gap period is also investigated. We also present a machine learning data-driven approach to unlicensed channel selection for spectrum sharing by NR-U. The results based on actual data collected from real-life WiFi deployment scenarios indicate significant improvement in coexistence performance and spectrum utilization of the unlicensed band with the proposed approach. It is shown through simulation results that the gap period before the backoff procedure provides better coexistence performance compared to the gap-based approach, where the synchronization gap is introduced after the LBT backoff. Further, the results indicate that if the gap interval exceeds a certain threshold value for each coexistence scenario, the WiFi network starts dominating the unlicensed channel, completely blocking the NR-U transmissions.

Unlicensed cellular networks and spectrum-sharing standards assist operators in meeting the ever-increasing demand for mobile data. However, several incumbents are already operational in these frequencies, rendering the wireless environment extremely dynamic and unpredictable. The challenges associated with unlicensed Licensed Assisted Access (LAA) operations in the 5 GHz band and New Radio in Unlicensed (NR-U) in the 6 GHz band are best addressed through a data-driven approach. This requires operator data from current cellular deployments. Further, from an operator’s perspective, the precision and reliability of predictive models must be analyzed before deployment. Counterfactual machine learning is ideal for quantifying causal impact in a dynamic, unlicensed cellular environment. However, the literature lacks a framework that combines data-driven solutions, counterfactual analysis, and conventional optimization. This work contributes a dataset from the LAA networks of three major cellular operators in Chicago consisting of 15 features and 9676 samples. Additionally, it proposes a framework for analyzing the performance of unlicensed networks that leverages machine learning for predictive modeling, employs counterfactual analysis for model explainability and network performance enhancement, and utilizes optimization for validation. We show that operator data is necessary to build reliable prediction models for network throughput, and signal strength, among others. Further, the impact of network parameters is shown to differ in unlicensed and licensed cellular network models. Next, a counterfactual machine learning framework is proposed to explain and analyze the predictive models. The framework proposes counterfactual policies to enhance unlicensed cellular network performance. Finally, we validate the suggested counterfactual policies through joint network optimization.

Energy harvesting combined with spectrum sharing offers a promising solution to the growing demand for spectrum while keeping energy costs low. New Radio Unlicensed (NR-U) technology enables telecom operators to utilize unlicensed spectrum in addition to the licensed spectrum already in use. Along with this, the energy demands for the Internet of Things (IoT) can be met through energy harvesting. In this regard, the ubiquity and ease of implementation make the RF-powered NR-U network a sustainable solution for cellular IoT. Using a Markov chain, we model the NR-U network with nodes powered by the base station (BS). We derive closed-form expressions for the normalized saturated throughput of nodes and the BS, along with the mean packet delay at the node. Additionally, we compute the transmit outage probability of the node. These quality of service (QoS) parameters are analyzed for different values of congestion window size, TXOP parameter, maximum energy level, and energy threshold of the node. Additionally, the effect of network density on collision, transmission, and energy harvesting probabilities is observed. We validate our model through simulations.

To alleviate the shortage of 5G licensed spectrum resources, using unlicensed spectrum has become an important solution.With the large-scale access of power terminals, NR-U and Wi-Fi spectrum sharing for power services quality guaranteeing has become an important research hotspot.Firstly, an NR-U uplink transmission mechanism was proposed, which ensured the average throughput of Wi-Fi users and realized the data uplink transmission of power service terminals.In addition, a resource optimization algorithm for joint transmission time and subcarrier allocation (TTSA) was proposed to ensure the quality of service (QoS) of various types of power services and maximize the total throughput of terminals.The optimization problem was decoupled, and proximal policy optimization (PPO) was used to allocate subcarriers to terminals.The simulation results show that compared with the existing algorithms, the proposed resource optimization algorithm for TTSA has superior performance in guaranteeing the service quality of power services and maximizing the total terminals throughput.

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the exponential increase in mobile users, mobile data demand has grown tremendously. To meet these demands, cellular operators are constantly innovating to enhance the capacity of cellular systems. Consequently, operators have been reusing the licensed spectrum "spatially," by deploying 4G/Long-term Evolution (LTE) small cells (e.g., Femto Cells) in the past. However, despite the use of small cells, the licensed spectrum will be unable to meet the consistently rising data traffic because of data-intensive applications such as augmented reality/virtual reality (AR/VR) and on-the-go high-definition video streaming. Applications such as AR/VR and online gaming not only place extreme data demands on the network but are also latency-critical. To meet the QoS guarantees, cellular operators have begun leveraging the unlicensed spectrum by coexisting with Wi-Fi in the 5 GHz band. The standardizing body Third Generation Partnership Project, has prescribed cellular standards for fair unlicensed coexistence with Wi-Fi, namely LTE Licensed Assisted Access (LAA), New Radio in unlicensed (NR-U), and NR in Millimeter. The rapid roll-out of LAA deployments in developed nations like the USA offers an opportunity to study and analyze the performance of unlicensed coexistence networks through real-world ground truth. Thus, this paper presents a high-level overview of past, present, and future of research in small cell and unlicensed coexistence communication technologies. It outlines the vision for future research work in the recently allocated unlicensed spectrum: The 6 GHz band, where the latest Wi-Fi standard, IEEE 802.11ax, will coexist with the latest cellular technology, 5G New Radio in unlicensed. At the end, we present a comparison of the performance between standards ranging from LTE to NR-U based on realistic assumptions. [ABSTRACT FROM AUTHOR]

New Radio Unlicensed (NR-U) enables 5G networks to operate in unlicensed channels, including the sub-7 GHz bands where transmitters are required to adhere to a set of contention resolution rules known as listen before talk (LBT). NR-U derives from a scheduled radio access technology where transmissions are expected to begin at fixed slot boundaries. The end of an LBT procedure, however, may not coincide with such a boundary. One solution to this problem is to have the NR-U base station wait a gap period to align with the slot boundary. We design, implement, and validate a simulator of NR-U channel access and conduct a performance analysis to assess several important issues: slot boundary synchronization between NR-U base stations, gap placement methods, impact of transmission settings, and performance under dense deployments. We also propose a method for improving the fairness of contending NR-U base stations and conclude our research with guidelines for configuring NR-U networks operating under gap-based channel access.

Providing ubiquitous connectivity for people and equipment with a wide range of service conditions is regarded as the major design goal of 6G networks. Moreover, the future 6G networks need to be extremely flexible to enable reliable and low-latency access for the dynamic number of mobile user equipment. The current base stations (BSs) and remote relay antennas are mostly, on the other hand, installed at fixed geographic locations based on long-term traffic patterns with little re-deployment flexibility. For most 6G applications, where dynamic data traffic occurs in both spatial and temporal domains, such rigid radio access networks (RANs) are unable to maintain ubiquitous connectivity. On the other hand, the rapid advancement of unmanned aerial vehicle (UAV) technology is creating a unique opportunity for the cellular operator to realize flying wireless infrastructure called wireless infrastructure UAV (WI UAV). WI UAV supports wireless connectivity and can stir itself to improve spectral efficiency, coverage, and quality of service of the end-users. This paper introduces 6G new radio in the unlicensed band (NR-U)-based WI UAV that can be used as a base station, relay, or data collector/disseminator. UAV are categorized based on their characteristics, applications, and operations. Further, this paper discusses various regulatory and standardization initiatives for integrating UAVs into the cellular network. Non-standalone NR-U network architecture is designed and explained for WI UAV. Several opportunities and design challenges of NR-U for the WI UAV are discussed and future scopes of WI UAVs are presented.

Cellular operators deploy 4G License Assisted Access (LAA) and 5G NR-U base stations in the unlicensed spectrum to enhance overall network capacity. This work highlights a unique phenomenon related to Physical Cell Id (PCI) that is observed in public LAA operator deployments. Notably, the licensed and unlicensed carriers of a device may have the same PCI or different PCIs. The phenomenon is triggered by the combined effect of unlicensed deployment architectures and cell selection mechanisms. Consequently, the phenomenon will intensify in the 5G NR-U, whose public deployment will soon begin. Unfortunately, the impact of this phenomenon on coexistence network performance is unexplored. It is also desirable to accurately identify the PCI scenarios at the device for improved cell selection and network performance. However, the data imbalance makes the classification problem challenging. This work addresses these problems through the following approach. Operator data from three LAA cellular providers is gathered and analyzed using machine learning algorithms. The impact of the phenomenon on LTE, LAA, and Wi-Fi components is demonstrated in three steps: First, the variation in network performance prediction accuracy in the PCI scenarios is examined. Second, the efficacy of numerosity reduction techniques used in data-driven cell selection is evaluated in both PCI scenarios. The third step entails a comparison of operator data analysis with network measurements. On-site experiments are conducted at the same PCI and different PCI sites to study differences in real-time network performance. A controlled LTE-WiFi coexistence environment is created and multiple traffic categories are considered. Finally, a class-weight-based solution is proposed for PCI scenario identification. F-score of 0.75 and AUC-ROC of 0.84 is achieved for LAA, with a minimalist feature set consisting of SINR and Throughput.

The use of multichannel transmissions significantly improves the performance of New Radio Unlicensed (NR-U) networks. The NR-U specification describes a multichannel access method using which a base station performs a backoff procedure only in one channel called the primary channel. Other channels are called secondary channels and sensed immediately before data transmission. In coexistence scenarios of several NR-U operators in the same frequency band, this may result in asymmetrical distribution of channel resources among operators. In this paper, with simulation, different options of selecting primary and secondary channels of two operators are studied. Normalized throughput and equality of channel resources sharing are estimated. Based on the results, an enhancement of the multichannel access method is proposed to provide equal distribution of channel resources between operators and high total throughput. [ABSTRACT FROM AUTHOR]

New Radio Unlicensed (NR-U), a fifth-generation cellular communication technology, allows base stations to use multichannel transmissions in the unlicensed frequency band, which is of great practical interest. However, the simultaneous operation of several NR-U operators in the same frequency channels leads to an increase in the number of collisions in the network when gaining access to an unlicensed channel. In this paper, we study the effectiveness of the collision resolution method previously proposed for single-channel transmissions when base stations use the multi-channel access method of access of Type A defined in the NR-U specification. Scenarios of coexistence of two NR-U operators with a various choice of active channels are considered. The normalized network throughput and the uniformity of the distribution of channel resources between the base stations of operators are estimated. It is shown that the use of the collision resolution method makes it possible to increase the total throughput by up to 20% compared to the standard method. [ABSTRACT FROM AUTHOR]

To achieve higher throughputs in cellular networks, 3GPP proposes to use unlicensed frequency bands and develops technologies — the latest one is NR-U — allowing a cellular base station to transmit in unlicensed bands, which are already occupied by Wi-Fi networks. To enable fair channel sharing between two technologies, the base station uses a sort of CSMA/CA with binary exponential backoff similar to Wi-Fi. However, the base station can start data transmission only at strictly periodic time moments. Many papers propose sending a reservation signal between the end of the backoff procedure and such a moment to prevent nearby devices from accessing the channel. However, this approach significantly reduces Wi-Fi performance. The paper proposes a novel method CR-LBT of transmitting a reservation signal that greatly decreases channel resource waste caused by collisions and improves channel resource sharing fairness. With developed analytical models and simulations, it is shown that CR-LBT may simultaneously increase the throughput of both NR-U and Wi-Fi networks. The effect is more noticeable for the Wi-Fi network, the throughput of which may rise three times compared with the traditional method of sending the reservation signal. Finally, the influence of various factors on CR-LBT performance is studied. [ABSTRACT FROM AUTHOR]

A widely deployed cellular network, supported by direct connections, can offer a promising solution that supports new services with strict requirements on access availability, reliability, and end-to-end (E2E) latency. The communications between vehicles can be made using different radio interfaces: One for cellular communication (i.e., cellular communication over the cellular network based on uplink (UL)/downlink (DL) connections) and the other for direct communication (i.e., D2D-based direct communications between vehicles which allows vehicular users (V-UEs) to communicate directly with others). Common cellular systems with licensed spectrum backed by direct communication using unlicensed spectrum can ensure high quality of service requirements for new intelligent transportation systems (ITS) services, increase network capacity and reduce overall delays. However, selecting a convenient radio interface and allocating radio resources to users according to the quality of service (QoS) requirements becomes a challenge. In this regard, let's introduce a new radio resource allocation strategy to determine when it's appropriate to establish the communication between the vehicles over a cellular network using licensed spectrum resources or D2D-based direct connections over unlicensed spectrum sharing with Wi-Fi. The proposed strategy aims at meeting the quality of service requirements of users, including reducing the possibility of exceeding the maximum delay restrictions and enhancing network capacity utilization in order to avoid service interruption. The proposed solution is evaluated by highlighting different conditions for the considered scenario, and it is demonstrated that the proposed strategy improves network performance in terms of transmitted data rate, packet success rate, latency, and resource usage. [ABSTRACT FROM AUTHOR]

To improve the capacity of cellular systems without additional expenses on licensed frequency bands, the 3GPP consortium has designed cellular technologies that use the unlicensed spectrum. The important peculiarity of the usage models of these technologies, the latest of which is New Radio Unlicensed (NR-U), is the coexistence with Wi-Fi networks deployed in the same frequency band. That is why NR-U uses channel access methods similar to those of Wi-Fi. However, the performance of Wi-Fi networks notably deteriorates in coexistence scenarios. One of the reasons is the slotted structure of transmissions of cellular base stations in the unlicensed spectrum, which may imply the use of a reservation signal. The paper proposes two novel channel access methods for NR-U, in which an NR-U base station randomly stops sending the reservation signal to listen to the channel to detect and resolve collisions. Analytical models are developed to validate the proposed methods and evaluate their efficiency, taking into account important features of NR-U networks, such as flexible numerology and mini-slot transmissions. The obtained numerical results show that the proposed methods significantly improve the performance of the Wi-Fi or NR-U network without degradation of the throughput of the other technology in coexistence scenarios.

New Radio-based access to Unlicensed spectrum (NR-U) intends to expand the applicability of 5G NR access technology to support operation in unlicensed bands by adhering to Listen-Before-Talk (LBT) requirement for accessing the channel. As the NR-U specification is being developed, simulations to assess the performance of NR-U and IEEE 802.11 technologies coexistence in unlicensed spectrum bands are crucial. In this paper, we report on extensions to a popular and open source network simulator, ns-3, to build an NR-U system-level simulator and to model the NR-U and IEEE 802.11 technologies coexistence in the currently available unlicensed spectrum bands. The proposed NR-U model capitalizes on an NR Release-15 based model that has been extended to operate in unlicensed bands, while meeting its regulatory requirements. For the coexistence analysis, we pay particular attention to the millimeter-wave bands and provide a complete set of simulation campaigns evaluating the coexistence of NR-U and IEEE 802.11ad Wireless Gigabit (WiGig) in the 60 GHz bands. In particular, we focus on determining whether NR-U fulfills its coexistence objective in terms of a fairness criterion by testing different NR-U parameters, such as the numerology, the bandwidth, the channel access scheme, the energy detection threshold, and the beamforming method.

3GPP cellular communications in unlicensed spectrum allow transmission only after completing listen-before-talk (LBT) operation. For downlink, the LBT operation helps cellular traffic to coexist well with Wi-Fi traffic. However, cellular uplink transmission is attempted only at the time specifically determined by the base station after having a successful LBT and the user equipment (UE) may suffer transmission failure and delayed transmission due to Wi-Fi interference. As a result, cellular uplink traffic does not coexist well with Wi-Fi traffic. This article mathematically analyzes the problem of unfairness between cellular and Wi-Fi for uplink channel access. To address the coexistence problem in unlicensed spectrum, we propose a standard-compliant approach, termed UpChance, which allows the UE to use a minimum length of uplink reservation signal and the base station to determine the optimal timing for the UE's uplink transmission. Through ns-3 simulation, we verify that UpChance improves the performance of fairness and random access completion time by up to 88% and 99%, respectively.

The emerging 5G New Radio (NR) cellular systems that may operate in millimeter-wave (mmWave) frequency bands are expected to offer larger bandwidths. They are to be deployed in densely crowded environments, where the traffic load has a high degree of variability, which may introduce capacity bottlenecks. One of the options to alleviate the latter is to concurrently utilize the radio resources available in unlicensed mmWave bands, e.g., at 60 GHz. In this work, we address the coexistence of mmWave-based NR Unlicensed (NR-U) and WiGig technologies and account for the mmWave-specific directionality, propagation, and blockage effects. By further incorporating the features of duty cycling and random access operation, we construct a mathematical framework, which is capable of characterizing the achievable data rates of the NR-U users that operate over both licensed and unlicensed mmWave spectrum simultaneously. Our numerical results demonstrate that the rate attained by such devices is primarily regulated by the initial contention window size that, in its turn, heavily depends on the system and environmental parameters. We report the optimal contention window values for a wide range of blocker and user densities as well as antenna array configurations. [ABSTRACT FROM AUTHOR]

New radio in unlicensed spectrum (NR-U) and network slicing have been emerged as two promising technologies to meet with the demand of enormous traffic volume, extreme transmission speed, and highly heterogeneous service requirements in future 5 G networks. Additionally, spurred by both economic considerations and environmental concerns, green communication becomes a new prominent figure of merit in the design of future 5 G networks. In this paper, we investigate an energy consumption scheduling for unlicensed heterogeneous networks, namely NR-U and WiFi, by leveraging the network slicing technology. First, we introduce a network slice broker, which enables virtual heterogeneous network operators to request and lease resources cooperatively via signaling means. Then, we investigate a joint network selection and resource allocation scheduling to minimize the network energy consumption in real time environment, taking into account various user data rate and delay requirements. An online Lyapunov optimization algorithm has been introduced to solve the proposed problem with low computational complexity and rapid convergence. We show that there exists a tradeoff between energy consumption and traffic delay, which can be adjusted through control parameters. Numerical results are presented to confirm our analyses and demonstrate the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Featuring unprecedentedly high data rates and high connection densities, 3GPP New Radio (NR) vehicle-to-everything (V2X) communications have been regarded as the most promising remedy to support the next generation driving use cases. For this purpose, although dedicated bands on 5.9 GHz spectrum have been allocated for Intelligent Transportation Systems (ITS), the limited bandwidth may not afford the desired service requirements. This engineering concern thus drives the utilization of unlicensed bands on 5 GHz spectrum adjacent to the ITS bands. However, subject to the fairness constraint in sharing unlicensed spectrum, various communication regulations have been imposed, and four different types of multi-band channel access procedures are consequently developed both in 3GPP LTE-A Licensed-Assisted Access (LAA) and NR on unlicensed spectrum (NR-U), to lead to a phenomenon that occupying more unlicensed bands may not suggest a proportional growth in the throughput. To empower high-throughout and high-density V2X communications, in this paper, we consequently propose the optimum channel access strategies for each V2X transmitter to decide the optimum number of unlicensed bands to access. To this end, analytic models for four types of multi-band channel access procedures in 3GPP NR-U are provided, which capture both inter-system and intra-system interference from coexisting WiFi transmitters and V2X transmitters. Subsequently, game-theoretically optimum strategies for each type of multi-band channel access procedures are derived. Performance evaluation results fully demonstrate the optimality of the proposed strategies, to serve the urgent demands in supporting the next generation driving use cases on unlicensed spectrum. [ABSTRACT FROM AUTHOR]

This paper aims to unlock the unlicensed band potential in realizing the Industry 4.0 communication goals of the Fifth-Generation (5G) and beyond. New Radio in the Unlicensed band (NR-U) is a new NR Release 16 mode of operation that has the capability to offer the necessary technology for cellular operators to integrate the unlicensed spectrum into 5G networks. NR-U enables both uplink and downlink operation in unlicensed bands, supporting 5G advanced features of ultra-high-speed, high bandwidth, low latency, and improvement in the reliability of wireless communications, which is essential to address massive-scale and highly-diverse future industrial networks. This paper highlights NR-U as a next-generation communication technology for smart industrial network communication and discusses the technology trends adopted by 5G in support of the Industry 4.0 revolution. However, due to operation in the shared/unlicensed spectrum, NR-U possesses several regulatory and coexistence challenges, limiting its application for operationally intensive environments such as manufacturing, supply chain, transportation systems, and energy. Thus, we discuss the significant challenges and potential solution approaches such as shared maximum channel occupancy time (MCOT), handover skipping, the self-organized network (SON), the adaptive back-off mechanism, and the multi-domain coexistence approach to overcome the unlicensed/shared band challenges and boost the realization of NR-U technology in mission-critical industrial applications. Further, we highlight the role of machine learning in providing the necessary intelligence and adaptation mechanisms for the realization of industrial 5G communication goals.

The rapid proliferation of user devices with access to mobile broadband has been a challenge from both the operation and deployment points of view. With the incorporation of new services with high demand for bandwidth such as video in 4K, it has been deemed necessary to expand the existing capacity by including new bands, among which the unlicensed 5-GHz band is a very promising candidate. The operation of future 3GPP (Third Generation Partnership Project) mobile network standards deployments in this band implies the coexistence with other technologies such as WiFi, which is widespread. In this context, the provision of Quality of Service (QoS) or Quality of Experience (QoE) becomes an essential asset and is a challenge that has yet to be overcome. In this sense, 3GPP has proposed a traffic prioritization method based on the Listen Before Talk access parameters, defining a series of priorities. However, it does not specify how to make use of them, and even less so in potentially conflicting situations. This paper assesses the end-to-end performance of downlink unlicensed channel priorities in dense scenarios via implementing a novel simulation setup in terms of both multi-service performance and coexistence. [ABSTRACT FROM AUTHOR]

This paper aims to unlock the unlicensed band potential in realizing the Industry 4.0 communication goals of the Fifth-Generation (5G) and beyond. New Radio in the Unlicensed band (NR-U) is a new NR Release 16 mode of operation that has the capability to offer the necessary technology for cellular operators to integrate the unlicensed spectrum into 5G networks. NR-U enables both uplink and downlink operation in unlicensed bands, supporting 5G advanced features of ultra-high-speed, high bandwidth, low latency, and improvement in the reliability of wireless communications, which is essential to address massive-scale and highly-diverse future industrial networks. This paper highlights NR-U as a next-generation communication technology for smart industrial network communication and discusses the technology trends adopted by 5G in support of the Industry 4.0 revolution. However, due to operation in the shared/unlicensed spectrum, NR-U possesses several regulatory and coexistence challenges, limiting its application for operationally intensive environments such as manufacturing, supply chain, transportation systems, and energy. Thus, we discuss the significant challenges and potential solution approaches such as shared maximum channel occupancy time (MCOT), handover skipping, the self-organized network (SON), the adaptive back-off mechanism, and the multi-domain coexistence approach to overcome the unlicensed/shared band challenges and boost the realization of NR-U technology in mission-critical industrial applications. Further, we highlight the role of machine learning in providing the necessary intelligence and adaptation mechanisms for the realization of industrial 5G communication goals. [ABSTRACT FROM AUTHOR]

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.