DECT-2020 NR is a radio access technology designed for 5G Internet of Things (IoT) applications. By leveraging multi-hop communications and listen-before-talk (LBT) mechanisms, DECT-2020 NR offers a flexible and cost-effective deployment solution for massive machine-type communications (mMTC). The ETSI standardization committee currently considers extending use-case options to ultra-reliable low-latency communications by enabling scheduled access along with LBT. However, this approach can increase the cost of the end systems. The aim of this study is to investigate whether standardized physical and medium access control (MAC) mechanisms, including power control, LBT, and priority queuing, can provide near-URLLC operation over multihop topologies. Our results show that to improve loss performance one needs to disable power control, use a shorter back-off window, and enable priority data transmission. For improving latency performance it is critical to use shorter acknowledgement (ACK) timeout and send ACKs immediately after data packet reception. Applying these techniques allows us to improve multi-hop URLLC latency performance by up to 30-80% and loss performance by up to 10-20% depending on URLLC and mMTC traffic conditions with only negligible impact on mMTC traffic performance.

DECT-2020 NR is a recently standardized radio access technology (RAT) for massive machine-type 5G communications operating in the license-exempt and licensed bands. By relying on multi-hop communications and listen-before-talk (LBT) medium access, DECT-2020 NR allows for cost-controlled flexible deployments. However, the medium access procedures for some of the bands currently used by classic DECT systems are strictly regulated by long-standing policies in the USA. The goal of this study was to evaluate and compare the performance of DECT-2020 NR and medium access specified by the Federal Communications Commission (FCC) for the Unlicensed Personal Communications Service (UPCS) band. Our results demonstrate that in a mesh system, the use of FCC access rules leads to drastic performance degradation, resulting in less than 85% of delivered packets compared to 98-99% for DECT-2020 NR. This results in a slight 1-2% degradation for coexisting classic DECT devices. For efficient use of the UPCS band, we recommend revisiting current FCC rules, allowing for LBT-based operations.

DECT-2020 is a recently standardized enabling technology for 5G massive machine-type communications operating in the unlicensed band. By relying upon multi-hop communications, DECT-2020 allows for cost-controlled flexible deployments, it requires an efficient solution for topology design, including the relay selection and next-hop selection mechanisms. The goal of this paper is to evaluate the impact of these algorithms on the fraction of successfully delivered packets for DECT-2020 technology. To this aim, we utilize the system-level simulation tool to capture the functionality of the physical and data-link DECT-2020 solutions. Our numerical results illustrate that the system is susceptible to the choice of the energy conservation parameters with the difference in the fraction of delivered packets reaching 10% and may effectively lead to non-operational conditions. Without simple analytical models, these parameters must be set with caution. The relay-selection mechanism procedure is generally insensitive to the parameters of the relay selection procedure, resulting in a deviation of at most 3%. Finally, the power control feature gives an additional gain of around 2-4% compared to the system without power control.

The swarms of unmanned aerial vehicles (UAV) are nowadays finding numerous applications in different fields. While performing their missions, UAVs have to rely on external positioning information to maintain connectivity and communications between units in a swarm. However, some of the critical applications such as rescue missions are performed in locations, where this information is partially or fully not available, e.g., deep woods, mountains, indoors. In this paper, we propose a method for dynamic topology organization and maintenance in UAV swarms. In addition to the baseline functionality, we also design advanced features required for dynamic swarms merging and disjoining, making it suitable for practical applications. Specifically, the proposal is based on the virtual coordinates system allowing for the utilization of conventional geographical routing algorithms. We test the proposed algorithm in different swarm conditions to illustrate that: (i) it is insensitive to distance estimates up to at least 30% allowing for simple estimation techniques, (ii) the accuracy of the topology inference is at least 90% even under impairments caused by mobility and temporal loss of connectivity, and (iii) the impact of the developed merging algorithm for swarms lasts for multiple tens of time steps that correspond to just few seconds in practice. The set of developed algorithms can be utilized to ensure always connected topology in conditions where positioning information is partially or fully unavailable.

5G New Radio (NR) millimeter wave (mmWave) and future sub-terahertz (sub-THz) 6G systems are designed for rate-greedy multimedia applications. Such applications often utilize rate adaptation allowing to vary the rate according to the network conditions. Unreliable nature of these bands subject to blockage may induce persistent user behavior resulting in repeated attempts (retrials) to continue the service. These effects may lead to the loss of sessions during the service and service provisioning at reduced rate. In this paper, by using the stochastic geometry and queuing theory, we characterize performance of adaptive rate-greedy applications at mmWave/sub-THz base stations. We consider user- and system-centric performance including new and ongoing session drop probabilities, resource utilization, and the amount of wasted resources. Our results show that the user persistence improves the new and ongoing session drop probabilities: making two retrials brings both down by$20-70$% while for fully persistent behavior the gain is 300%. The impact is more pronounced in underloaded system conditions. User persistence also increases the usage of system resources by$20-40$% and decreases the percentage of wasted resources by two/three times. However, these gains come at the expense of decreased successful session completion probability without retrials negatively affecting the overall user experience.

The recently standardized ETSI DECT-2020 New Radio (NR) technology promises to enable operator-independent Internet-of-Things (IoT) services. One of the supported operating bands is the 1880 − 1900 MHz band where IoT devices use one or more 1.728 MHz wide channels for multi-hop communications. It has been shown that such systems scale well to satisfy the requirements of 5G massive machine-type communications (mMTC). During the standardization process, the coexistence with classic DECT technology was addressed but the benefits of different options have not been deeply explored. In this paper, by utilizing system-level simulation techniques we evaluate several coexistence solutions for DECT-2020 and classic DECT systems including conventional listen-before-talk access (LBT), last-minute scan, and scheduling-based mechanisms. Our numerical results illustrate that the standard LBT operation ensures excellent performance with no more than 2% of packet drops for classic DECT, and still results in satisfactory DECT-2020 operation under 25% of resources allocated to classic DECT. The use of last-minute-scan leads to drastic performance degradation of DECT-2020 (by more than 10% in terms of packet drops) as compared to the standard LBT-only operation. Finally, a scheduling-based mechanism allows to improve the LBT performance for DECT-2020 devices by 2-5%.

Fifth-generation (5G) mobile communications are expected to integrate multiple radio access technologies (RATs) within a unified access network by allowing the user equipment (UE) to utilize them concurrently. As a consequence, mobile users face even more heterogeneous connectivity options, which creates challenges for efficient decision-making when selecting a network dynamically. In this work, with the tools of queuing theory, integral geometry, and optimization theory, we develop a novel mobility-centric analytical methodology for multi-RAT deployments. Particularly, we first contribute a framework for optimal data rate allocation in the network-assisted regime. Then, we characterize the convergence time of the distributed optimization algorithms based on reinforcement learning to reduce the signaling overheads. Our findings suggest that network-assisted strategies may improve the UE throughput by up to 60% depending on the considered deployment, where the gains increase with a higher density of millimeter-wave New Radio (NR) base stations. A user-centric solution based on reinforcement learning mechanisms is capable of approaching the performance of the network-assisted scheme. However, the associated convergence time may be prohibitive, on the order of several minutes. To improve the latter, we further propose and evaluate a transfer learning-based algorithm that allows to decrease the convergence time by up to 10 times, thus becoming a simple solution for rate-optimized operation in future 5G NR deployments.

Modern mobile handheld devices, such as smartphones and tablets, feature multiple wireless interfaces, some of which can support device-to-device communications, which enable mesh networks on even when the infrastructure is unavailable. One of the key technological challenges hampering the use of multi-hop mesh networks is the extremely high communication overhead of route discovery and maintenance algorithms. The problem is especially pronounced under dynamic network conditions caused by user mobility and nodes joining and leaving the network. In this paper, we propose a fully distributed algorithm for constructing a virtual coordinate system used for geo-like routing by approximating the physical network nodes coordinate. The proposed algorithm, called gradient assisted routing (GAR), builds upon two-hop neighbors’ information exchanged in beacons in contrast to conventional geographic routing protocols which rely on external positioning information. We evaluate the proposed solution using algorithmic, topological, and routing-related metrics of interest. We further numerically quantify how the node mobility increases the time needed for topology stabilization, and how network size affects the route discovery success rate. Our comparison also shows that for small to mid-size mesh networks (up to 60 nodes), the performance of the proposed routing procedure is similar to the conventional geographic routing protocols that exploit external positioning information. The proposed solution may efficiently supplement the traditional on-demand routing in small to mid-size mesh systems by independently establishing 50 to 70% of paths and thereby reducing the discovery overheads.

To alleviate the impact of outages caused by dynamic blockage of propagation paths in millimeter wave (mmWave) systems, 3GPP has proposed multi-connectivity operation, where user equipment (UE) maintains simultaneous links to both sub-6 GHz and mmWave BSs. We address one of the most challenging prospective deployments – multi-lane street deployment with intra- and inter-RAT multi-connectivity. By utilizing the mixture of analytical and simulation tools, we first characterize the outage characteristics at mmWave layer. These characteristics further serve as an input to the queuing model characterizing service performance of sub-6 GHz BS serving sub-6 GHz and temporarily offloaded mmWave sessions and implementing traffic protection strategies. Our numerical results show that the use of inter-RAT multi-connectivity to offload mmWave sessions decreases sub-6 GHz session rate multiple times while utilizing multi-connectivity at the mmWave layer allows to partially compensate it. Traffic “jam” road conditions affect the sub-6 GHz session rate reducing it by approximately 20% compared to “normal” road traffic conditions. Furthermore, reserving shares of resources to sub-6 GHz and mmWave traffic favors “heavy-weight” mmWave sessions. On the other hand, individual session resource allocation leads to fair performance. However, this option induces the trade-off between the attained rate and the session drop probability.

Blockage of millimeter-wave (mmWave) radio propagation paths in dense mobile scenarios requires advanced techniques to preserve session continuity in 5G New Radio (NR) systems. In this work, we employ the tools of stochastic geometry and queuing theory as well as rely on 3GPP cluster-based propagation modeling to formulate a mathematical framework, which captures session-level service dynamics of user equipment (UE) that supports multi-band operation. Accordingly, the sub-6 GHz NR base station (BS) is used to temporarily serve the sessions with strict throughput requirements that experience an outage at the mmWave NR BSs. We derive user- and system-centric key performance indicators, including new and ongoing session drop probabilities as well as radio resource utilization. Our numerical results confirm that the use of microwave BSs to serve mmWave sessions is only feasible in light traffic conditions. Particularly, the presence of throughput-hungry mmWave traffic increases the session drop probability at the sub-6 GHz band as well as decreases its utilization. Further, the support of sub-6 GHz radio may not improve the mmWave BS resource utilization, as many mmWave sessions are dropped during their service as a consequence of frequent blockage-induced outage situations.

Spatial correlation has been recognized by 3GPP as one of the key elements in millimeter-wave (mmWave) channel modeling. Correlated channel behavior is induced by macro objects, such as buildings, as well as by micro objects, including humans around the mmWave receivers. The 3GPP's three-dimensional (3D) spatially consistent channel model designed to capture these phenomena assumes a-priori knowledge of the correlation distance between the receivers. In this paper, we propose a novel spatially-consistent human body blockage state generation procedure, which extends the standardized 3D channel model by 3GPP to capture the correlation between the line-of-sight (LoS) links and the reflected cluster states affected by human body blockage. The proposed model is based on analytical expressions for the conditional link state probability, thus permitting the parametrization of the spatial field of receivers. It also does not require any a-priori information on the correlation distance as the latter is identified explicitly based on the environmental parameters. We compare the results for the proposed model with those obtained with the uncorrelated blockage model and conclude that in many special cases correlation manifests itself in quantitatively different propagation conditions experienced at the nearby receivers.

The use of highly directional antenna radiation patterns for both the access point (AP) and the user equipment (UE) in the emerging millimeter-wave (mmWave)-based New Radio (NR) systems is inherently beneficial for unicast transmissions by providing an extension of the coverage range and eventually resulting in lower required NR AP densities. On the other hand, efficient resource utilization for serving multicast sessions demands narrower antenna directivities, which yields a trade-off between these two types of traffic that eventually affects the system deployment choices. In this work, with the tools from queuing theory and stochastic geometry, we develop an analytical framework capturing both the distance- and traffic-related aspects of the NR AP serving a mixture of multicast and unicast traffic. Our numerical results indicate that the service process of unicast sessions is severely compromised when (i) the fraction of unicast sessions is significant, (ii) the spatial session arrival intensity is high, or (iii) the service time of the multicast sessions is longer than that of the unicast sessions. To balance the multicast and unicast session drop probabilities, an explicit prioritization is required. Furthermore, for a given fraction of multicast sessions, lower antenna directivity at the NR AP characterized by a smaller NR AP inter-site distance (ISD) leads to a better performance in terms of multicast and unicast session drop probabilities. Aiming to increase the ISD, while also maintaining the drop probability at the target level, the serving of multicast sessions is possible over the unicast mechanisms, but it results in worse performance for the practical NR AP antenna configurations. However, this approach may become feasible as arrays with higher numbers of antenna elements begin to be available. Our developed mathematical framework can be employed to estimate the parameters of the NR AP when handling a mixture of multicast and unicast sessions as well as drive a lower bound on the density of the NR APs, which is needed to serve a certain mixture of multicast and unicast traffic types with their target performance requirements.

Multicasting is widely used in conventional wired and wireless networks as it allows to significantly improve resource utilization in presence of users interested in the same content. However, the support of this type of service in prospective 5G New Radio (NR) systems has received only little attention so far. In this paper, merging the tools of queuing theory and stochastic geometry we develop a model of 5G NR base station (BS) serving a mixture of unicast and multicast traffic. We validate our model against computer simulations using multicast/unicast session drop probabilities and system resource utilization as metrics of interest. Our numerical results illustrate that the presence of multicast type of traffic severely compromises performance of unicast sessions. Furthermore, this effect is amplified when the inter-site distance (ISD) between BSs increases. Thus, in order to satisfy prescribed performance guarantees in terms of unicast and multicast session drop probabilities, explicit resource reservation mechanism at NR BS might be required.

Recently, new opportunities for utilizing extremely high frequencies have become instrumental to designing the fifth-generation mobile technology. The use of highly directional antennas in millimeter-wave (mm-wave) bands poses an important question of whether 2D modeling suffices to capture the resulting system performance accurately. In this paper, we develop a novel mathematical framework for performance assessment of the emerging 3D mm-wave communication scenarios, which takes into account vertical and planar directivities at both ends of a radio link, blockage effects in three dimensions, and random heights of the communicating entities. We also formulate models having different levels of details and verify their accuracy for a wide range of system parameters. We show that capturing the randomness of both the transmitting and receiving heights as well as the vertical antenna directivities becomes crucial for accurate system characterization. The conventional planar models provide overly optimistic results that overestimate performance. For instance, the model with fixed heights that disregards the effect of vertical exposure is utterly pessimistic. The other two models, one having random heights and neglecting vertical exposure and another one characterized by fixed heights and capturing vertical exposure are less computationally expensive and can be used as feasible approximations for certain ranges of input parameters.

The intermittent millimeter-wave radio links as a result of human-body blockage are an inherent feature of the 5G New Radio (NR) technology by 3GPP. To improve session continuity in these emerging systems, two mechanisms have recently been proposed, namely, multi-connectivity and guard bandwidth. The former allows to establish multiple spatially-diverse connections and switch between them dynamically, while the latter reserves a fraction of system bandwidth for sessions changing their state from non-blocked to blocked, which ensures that the ongoing sessions have priority over the new ones. In this paper, we assess the joint performance of these two schemes for the user- and system-centric metrics of interest. Our numerical results reveal that the multi-connectivity operation alone may not suffice to increase the ongoing session drop probability considerably. On the other hand, the use of guard bandwidth significantly improves session continuity by somewhat compromising new session drop probability and system resource utilization. Surprisingly, the 5G NR system implementing both these techniques inherits their drawbacks. However, complementing it with an initial AP selection procedure effectively alleviates these limitations by maximizing the system resource utilization, while still providing sufficient flexibility to enable the desired trade-off between new and ongoing session drop probabilities.

The Internet of Things (IoT) undergoes a fundamental transformation by augmenting its conventional sensor network deployments with more advanced and mobile devices, such as connected and self-driving cars. This fusion of embedded and automotive domains promises to deliver unprecedented mutual benefits, where vehicles will receive timely updates from their proximate sensors while assisting them in delivering their sensory data to the remote network infrastructure. In this paper, we put forward the vision of opportunistic crowdsensing applications, in which the ubiquitous deployments of low-cost and battery-constrained IoT sensors take advantage of more capable and energy-abundant vehicle-mounted mobile relays. In particular, we consider the use of the emerging narrowband IoT radio technology recently ratified by 3GPP and offering efficient means for underlying wireless connectivity. Our rigorous mathematical analysis supported with comprehensive system-level evaluations reveals the effects of vehicle-based relays on the important metrics of interest, such as connection reliability, transmission latency, and communication energy efficiency. These systematic findings advocate for an extensive utilization of vehicular relays as part of the next-generation IoT ecosystem.

Network softwarization is a major paradigm shift, which enables programmable and flexible system operation in challenging use cases. In the fifth-generation (5G) mobile networks, the more advanced scenarios envision transfer of high-rate mission-critical traffic. Achieving end-to-end reliability of these stringent sessions requires support from multiple radio access technologies and calls for dynamic orchestration of resources across both radio access and core network segments. Emerging 5G systems can already offer network slicing, multi-connectivity, and end-to-end quality provisioning mechanisms for critical data transfers within a single software-controlled network. Whereas these individual enablers are already in active development, a holistic perspective on how to construct a unified, service-ready system as well as understand the implications of critical traffic on serving other user sessions is not yet available. Against this background, this paper first introduces a softwarized 5G architecture for end-to-end reliability of the mission-critical traffic. Then, a mathematical framework is contributed to model the process of critical session transfers in a softwarized 5G access network, and the corresponding impact on other user sessions is quantified. Finally, a prototype hardware implementation is completed to investigate the practical effects of supporting mission-critical data in a softwarized 5G core network, as well as substantiate the key system design choices.

Recently, new opportunities for utilizing extremely high frequencies have become instrumental in developing fifth-generation (5G) mobile technology. The use of highly directional antennas in millimeter-wave (mmWave) bands poses an important question of whether two-dimensional modeling suffices to capture the resulting system performance. Accounting for the effects of human body blockage by mmWave transmissions, in this work we compare the performance of the conventional two-dimensional and the proposed three- dimensional modeling. With our stochastic geometry based approach, we consider the aggregate interference and signal-to-interference ratio (SIR) to be the main metrics of interest. Both counterpart models attempt to capture the inherent behavior of 5G mmWave systems by incorporating the effects of human body blockage and antenna directivity. We thus deliver a realistic numerical assessment by comparing the three-dimensional modeling with its two-dimensional projection to reveal the resulting discrepancy.

Leveraging multiple simultaneous small cell connections is an emerging and promising solution to enhance session continuity in millimeter-wave (mmWave) cellular systems that suffer from frequent link interruptions due to blockage in ultra-dense urban deployments. However, the available performance benefits of feasible multi-connectivity strategies as well as the tentative service quality gains that they promise remain an open research question. Addressing it requires the development of a novel performance evaluation methodology, which should consider: 1) the intricacies of mmWave radio propagation in realistic urban environments; 2) the dynamic mmWave link blockage due to human mobility; and 3) the multi-connectivity network behavior to preserve session continuity. In this paper, we construct this much needed methodology by combining the methods from queuing theory, stochastic geometry, as well as ray-based and system-level simulations. With this integrated framework, both user- and network-centric performance indicators together with their underlying scaling laws can be quantified in representative mmWave scenarios. To ensure modeling accuracy, the components of our methodology are carefully cross verified and calibrated against the current considerations in the standards. Building on this, a thorough comparison of alternative multi-connectivity strategies is conducted, as this paper reveals that even simpler multi-connectivity schemes bring notable improvements to session-level mmWave operation in realistic environments. These findings may become an important reference point for subsequent standardization in this area.

As next-generation mobile networks are rapidly taking shape driven by the target standardization requirements and initial trial implementations, a range of accompanying technologies prepare to support them with more reliable wireless access and improved service provisioning. Among these are more advanced spectrum sharing options enabled by the emerging Licensed Shared Access (LSA) regulatory framework, which aims to efficiently employ the capacity of underutilized frequency bands in a controlled manner. The concept of LSA promises to equip network operators with the much needed additional spectrum on the secondary basis and thus brings changes to the existing cellular network management. Hence, additional research is in prompt demand to determine the required levels of Quality of Service (QoS) and service provisioning reliability, especially in cases of dynamic geographical and temporal LSA sharing. Motivated by this recent urge and having at our disposal a fully-functional 3GPP LTE cellular deployment, we have committed to implement and trial the principles of dynamic LSA-compatible spectrum management. This paper is our first disclosure on the comprehensive experimental evaluation of this promising technology. We expect that these unprecedented practical results together with the key lessons learned will become a valuable reference point for the subsequent integration of flexible LSA-based services, suitable for inter-operator and multi-tenant spectrum sharing.

The use of extremely high frequency (EHF) or millimeter-wave (mmWave) band has attracted significant attention for the next generation wireless access networks. As demonstrated by recent measurements, mmWave frequencies render themselves quite sensitive to “blocking” caused by obstacles like foliage, humans, vehicles, etc. However, there is a dearth of analytical models for characterizing such blocking and the consequent effect on the signal reliability. In this paper, we propose a novel, general, and tractable model for characterizing the blocking caused by humans (assuming them to be randomly located in the environment) to mmWave propagation as a function of system parameters like transmitter-receiver locations and dimensions, as well as density and dimensions of humans. Moreover, the proposed model is validated using a ray-launcher tool. Utilizing the proposed model, the blockage probability is shown to increase with human density and separation between the transmitter-receiver pair. Furthermore, the developed analysis is shown to demonstrate the existence of a transmitter antenna height that maximizes the received signal strength, which in turn is a function of the transmitter-receiver distance and their dimensions.