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.

The increasing demand for power distribution systems in terms of control with nearly immediate response requires deploying a new type of user equipment (UE) that demands permanent connectivity. In Narrowband Internet of Things (NB-IoT) systems, the traffic generated by such UEs may constitute a large part of the overall load. In this article, we first propose a detailed 2-D Markov chain model to capture the system’s behavior with the mixture of conventional stochastic and regular traffic types. To provide a computationally efficient solution, we then apply the state aggregation technique to reduce it to a 1-D model and develop approximations and associated numerical algorithms for assessing the mean delay when transmitting the considered traffic. Our results show that a single NB-IoT cell remains stable for up to$72\times {}10^{4}$conventional UEs and$9\times {}10^{3}$UEs demanding permanent connectivity. The presence of the latter UEs type has a linear effect on their delay, but affects conventional UEs more drastically. A delay bound of 10 s specified in ITU-R M.2410 is met for the conventional UEs, even under a high number of permanently connected UEs$({10^{3}})$. However, the delay on the side of the latter UEs is violated even for 100 permanently connected UEs requiring redesigning the NB-IoT channel access mechanism or expanding resources.

The Age of Information (AoI) is a metric for state update applications, which plays a crucial role in the Internet of Things (IoT). In many environments, such as factories and energy grid deployment, end sensing nodes tend to be naturally clustered, resulting in high variability and autocorrelation in the packet arrival process. In this paper, we assess the impact of variability and autocorrelation of packet arrivals in one cluster on the performance of other clusters in 5G cellular systems by explicitly accounting for the batch nature of the packet arrival and service processes arising as a a result of discrete nature of the scheduling process and the autocorrelational properties of the arrival processes. We show that not only the mean arrival rates but coefficient of variation (CoV) and autocorrelation in the arrival processes from tagged and competing clusters affect both the mean and distribution of the peak AoI (PAoI). Although the impact of these second-order properties depends heavily on their relative loads, it is tagged cluster properties that produces the most impact on its own performance metrics. Notably, the worst performance is observed when the competing traffic takes on the properties of the Poisson process – unit variability and no memory. The main practical takeaway is that increase in either tagged or background sources variability can raise the PAoI by 40-60%, but it also makes it more stable around the mean value reducing the jitter at the destination.

The use of millimeter-wave (mmWave) frequencies by 5G/5G+ technology results in increased signal attenuation naturally requiring dense network deployments. However, traditional fiber-based backhauling proves costly for network operators. To address this issue, 3GPP proposed the Integrated Access and Backhaul (IAB) concept to enable wireless backhaul and reduce deployment costs. However, system dynamics such as user mobility and traffic variations challenge system optimization and may shift the performance from its optimized state. On top of this, in-band mmWave IAB networks are subject to the half-duplex constraint, which prevents simultaneous transmission and reception. These limitations present challenges in optimizing the IAB network. Therefore, the goal of this study is to provide a computationally-efficient methodology for resource allocation and user scheduling in mm Wave IAB networks considering the aforementioned system limitations and constraints. Moreover, we evaluate the influence of system-specific factors and dynamics on the optimization of IAB networks and the time that it takes for the system to deviate from its optimized state. Our results show that by employing an optimally-parametrized scheduler, the throughput gain is 55% as compared to the baseline, where the radio resources are split equally among the users. The cell size is the primary parameter affecting the optimization gain, i.e., smaller cell sizes result in diminishing benefits when utilizing optimized algorithms.

In the current 5G system architecture, the use cases around user plane security enforcement are oriented and limited to security configuration towards the NG-RAN, based on the integrity and/or ciphering protection activation or deactivation in the air interface between user equipment (UE) and gNB. Security features between gNB and User Plane Function (UPF) are optional, configured by the network provider, and there is no end-to-end protection for the user plane data. However, the gNB is more vulnerable to attacks due to its physical location, which leads to data and privacy leakage. Additionally, the mapping from service data flow to QoS flow is mainly based on QoS requirements rather than security, which means the service data flows with similar QoS but different security requirements will be mapped to the same QoS flow and then be processed with the same security protection on the air interface. Moreover, 3GPP only supports coarse-grained Packet Data Unit (PDU) session level integrity protection, i.e., all QoS flows in the same PDU session have to share the same security configuration at the UEgNB interface. This will lead to either high security overhead if only a few QoS flows need protection or inadequate protection if protection is disabled since the majority of the flows do not require it. In this paper, we propose a backward-compatible differentiated (per-QoS flow) end-to-end security mechanism allowing the protection of only those QoS flows that require ciphering and/or integrity protection. The security options can be changed dynamically during the QoS flow lifetime. Our numerical results show that the proposed solution allows us to decrease the computational burden imposed at UE.

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.

The 5G millimeter wave (mmWave) New Radio (NR) systems are prone to blockage and micromobility effects. To improve service reliability, 3GPP proposed a dual-connectivity allowing UE to maintain links to two base stations (BS). However, this functionality is power-hungry resulting in a trade-off between performance and power efficiency. In this paper, we compare user equipment (UE) power efficiency, consumption, and battery lifetime for different intra- and inter-radio access technologies single- and dual-connectivity under different UE usage scenarios, micromobility, and blockage impairments. We evaluate five schemes: (i) BSs in FR1 and FR2 bands (NR-DC FR1/FR2), (ii) BSs in FR2 band (NR-DC FR2/FR2), and (iii) LTE BS and NR BS in FR2 band (EN-DC LTE/FR2), (iv) NR FR1, and (iv) LTE. Our results show that the LTE-only scheme provides three times longer battery lifetime as compared to its nearest rival-NR FR1 single-connectivity option. For dual-connectivity options, the best lifetime is observed for EN-DC FR2/LTE, and the worst – for NR-DC FR2/FR1. The difference between NR-DC FR2/FR1 and NR-DC FR2/FR2 schemes is negligible. Densification negatively affects all the dual-connectivity schemes as it forces UEs to switch between master and backup technologies more often. We recommend EN-DC FR2/LTE for low-traffic outage-sensitive applications, while NR-DC FR2/FR2-for heavy-traffic outage non-sensitive applications.

Network slicing is a technique introduced by 3GPP to enable multi-tenant operation in 5 G systems. However, the support of slicing at the air interface requires not only efficient optimization algorithms operating in real time but also its tight integration into the 5 G control plane. In this paper, we first present a priority-based mechanism enabling defined performance isolation among slices competing for resources. Then, to speed up the resource arbitration process, we propose and compare several supervised machine learning (ML) techniques. We show how to embed the proposed approach into the ITU-T standardized ML architecture. The proposed ML enhancement is evaluated under realistic traffic conditions with respect to the performance criteria defined by GSMA while explicitly accounting for 5 G millimeter wave channel conditions. Our results show that ML techniques are able to provide suitable approximations for the resource allocation process ensuring slice performance isolation, efficient resource use, and fairness. Among the considered algorithms, polynomial regressions show the best results outperforming the exact solution algorithm by 5–6 orders of magnitude in terms of execution time and both neural network and random forest algorithms in terms of accuracy (by 20–40 %), sensitiveness to workload variations and training sample size. Finally, ML algorithms are generally prone to service level agreements (SLA) violation under high load and time-varying channel conditions, implying that an SLA enforcement system is needed in ITU-T's 5 G ML framework.

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.

Recently proposed by 3GPP, Integrated Access and Backhaul (IAB) technology promises to deliver a cost-efficient and flexible solution for network densification in 5G/6G systems. Since IAB architecture is based on multi-hop topology and advanced functionalities, such as multi-connectivity transmission and multi-routing, the potential utilization of IAB systems raises an issue of efficient system design. In this paper, we develop an optimization framework capable of jointly selecting transmission paths and allocating radio resources in compliance with half-duplexing and interference constraints. The presented numerical results illustrate that directional mm Wave beams employed at the wireless backhaul are essential for capacity boosting, thus allowing to fully exploit the radio resources in self-backhauled systems. We also establish that the multi-hop IAB topology provides advantages in terms of end-to-end user throughput as compared to single-hop systems.

In this paper, we propose a new service orchestration approach for in-network fully distributed dynamic compute composition with limited involvement from the consumer and no centralized coordinator. The service is composed fully inside the network including assembling data and software, and compute node selection, leveraging standardized NDN functionalities. The use of the proposed approach will enable smooth support of dynamic compute services over wireless/mobile edge and edge/fog NDN-based systems, where the use of conventional IP approach faces fundamental difficulties related to dynamic allocation of IP addresses. We will also outline extensions of the proposed approach for streaming data, function chaining and re-use of partially computed results. Our numerical results show that the proposed method improves service reliability at the edge by increasing the Interest satisfaction by 5-10 times depending on the considered deployment, network topology, and resources.

Unmanned aerial vehicles (UAVs) have attracted significant attention. Many potential applications are predicted to bring abundant business opportunities in the next decade thanks to the ubiquitous connectivity of the 4G and 5G cellular networks. Unlike terrestrial deployments, airborne infrastructures have diverse attributes, e.g., increased deployment flexibility, line-of-sight (LoS) connections, and controlled mobility. These attributes bring new research questions and challenges, including LoS dominant ground channels together with increased aerial-terrestrial network interference, the exploitation of the degree of freedom (DoF) provided by the UAV mobility, and the different and tighter quality of service (QoS) requirements for purposes of unmanned traffic management (UTM). Further challenges stem from existing infrastructure oriented towards service availability in low altitudes and low data transfer costs. A key challenge in this context is to achieve and guarantee sufficient service reliability in all altitudes where UTM is planned to be used. Obtained results from the measurement campaign at Twente airport indicate the performance of the 4G cellular network is stable and equals the terrestrial use cases up to 60 m of altitude. However, if the altitude increases more, the network performance degrades significantly. In detail, the analysis revealed the fact the performance drop is significant, especially for downlink transmissions (from ground to UAVs), as the strong interference and connection outages were observed in increased numbers.

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%.

With the rapid growth in number of connected devices, edge and fog computing paradigms become promising solutions for handling computation with low latency and reduced bandwidth usage. They allow to execute a computation across IoT devices, e.g., cameras, an edge aggregator/processor, and on the cloud. In this paper, we consider a pervasive computing scenario where end devices such as laptops, smart phones or roadside units are willing to offer compute services along with the traditional infrastructure-based edge computing resources. Our work uses an Information Centric Network (ICN), which is a promising technique for resource-constrained end devices to offload time-sensitive computing tasks to nearby distributed network resources, e.g., to an edge server. We expand the Named Data Networking (NDN), which is an ICN implementation, to operate in a dynamic resource-constrained multi-hop environment and propose i) a fast and efficient capability discovery scheme to assist each node in discovering other nodes’ capabilities in a distributed manner; and ii) efficient schemes for server/path selection, to optimize the end-to-end latency including discovery, data transmission and computation. Our results show that the proposed solutions can improve the total latency by around 50% for most of the tasks.

The support of multicast communications in the fifth-generation (5G) New Radio (NR) system poses unique challenges to system designers. Particularly, the highly directional antennas do not allow to serve all the user equipment devices (UEs) that belong to the same multicast session in a single transmission. The capability of modern antenna arrays to utilize multiple beams simultaneously, with potentially varying half-power beamwidth, adds a new degree of freedom to the UE scheduling. This work addresses the challenge of optimal multicasting in 5G millimeter wave (mmWave) systems by presenting a globally optimal solution for multi-beam antenna operation. The optimization problem is formulated as a special case of multi-period variable cost and size bin packing problem that allows to not impose any constraints on the number of the beams and their configurations. We also propose heuristic solutions having polynomial time complexity. Our results show that for small cell radii of up to 100 meters, a single beam is always utilized. For higher cell coverage and practical ranges of the number of users (5-50), the optimal number of beams is upper bounded by 3.

Sub-terahertz (sub-THz, 100–300 GHz) communications promise to bring extraordinary rates in future 6G systems. High path loss and blockage effects will limit the coverage of base stations (BS) to a few hundred meters making deployment of such systems along the roads expensive. As a way to decrease the BS density, relaying has been proposed. However, vehicle-to-vehicle (V2V) propagation is characterized by different sets of communications paths depending on the antenna locations raising the question of their optimal positions. In this paper, by utilizing IEEE 802.15.3d parameters and 300 GHz propagation measurements, we develop a mathematical framework for comparison of multi-hop relaying systems with different antenna locations. We utilize coverage, BS availability, and the data rate over a multi-hop path as metrics of interest. Our results show that the windshield location is characterized by lower data rates and larger coverage while bumper and engine levels are similar in terms of these metrics. For the windshield location, the coverage is extended by 50% with BS availability 0.95. The windshield location is recommended as it is less sensitive to the technology penetration rate and is characterized by larger coverage. The proposed approach shows gains of up to 32% in terms of required BS density for the range of vehicles density (10-40 units/km).

Energy efficiency and service reliability are two critical requirements for 5G New Radio cellular access. To address the latter, 3GPP has proposed multiconnectivity operation allowing user equipment (UE) to maintain active links to more than a single base station. However, the use of this technique compromises the energy efficiency of UE. In this paper, we develop a mathematical model capturing key energy and performance indicators as a function of system and environmental conditions. Then, we apply it to investigate the trade-offs between user performance and energy efficiency as well as the effect of scaling of discontinuous reception (DRX) timers. For a considered set of system parameters, our results reveal that for low micromobility speed$\leq 0.1^{\circ}$/s and blockers density,$\leq 0.1$bl./$\text{m}^{2}$two simultaneously supported links with minimal DRX timers lead to optimal performance. For higher blockers density more than two links are needed to optimize energy efficiency while for high micromobility speed multiconnectivity does not allow to improve energy efficiency at all. Thus, the optimal degree of multiconnectivity and DRX timer scaling coefficients depend on the environmental characteristics including both micromobility speed and density of blockers and need to be dynamically updated during UE operation.

The new types of industry-driven applications that need to be supported by low-power wide-area networks (LP-WANs), such as remote control or metering of devices within the massive machine-type infrastructures (e.g., Smart Grids), require a permanent connection to the remote server. In addition, there is also a shift in the communication paradigm, as the user equipment (UE) nodes are queried in regular and frequent intervals. Notably, the presence of this type of traffic may drastically deteriorate the performance of LPWAN technologies initially developed to support conventional use-cases characterized by non-synchronized transmissions. Though none of the LPWAN technologies is inherently designed to handle such demanding communication patterns, the narrowband Internet of things (NB-IoT) still stands for the best candidate as it operates within the license frequency spectrum. To optimize the delay performance of both types of traffic coexisting at the NB-IoT air interface, we propose an approach based on spreading the message transmission time instants of regular and stochastic traffic. We show an optimal value of the spreading interval minimizing the message transmission delay of regular traffic and propose a mathematical model to estimate its value. By parameterizing the model using a detailed measurements campaign of NB-IoT, we show that the optimal value of spreading interval and associated mean message delay is a linear function of the number of UEs. We report these values for a wide range of UEs in the coverage area of the NB-IoT base station and show that conventional stochastic traffic does not influence regular traffic performance.

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.

Network slicing is a promising technique to enable multi-tenant operation in fifth generation (5G) cellular systems. However, efficient implementation of this technique at the air interface requires an adequate resource allocation policy that provides slice isolation and takes into account the heterogeneity of services and their performance requirements. We propose a new slicing scheme aimed at slice performance isolation, efficient capacity utilization, and fair resource allocation among all users. The policy ensures a slice-specific minimum data rate to all slice users as long as their number remains within a contracted limit, yet provides higher data rates whenever capacity is available. Specifically, we incorporate the best features of the complete partitioning and complete sharing policies, while ensuring flexibility and customization for network operators. The proposed scheme is based on an iterative solution of a convex programming problem characterized by polynomial complexity, which makes it suitable for on-line implementation. Associated algorithms are also proposed. Our numerical results demonstrate that the proposed slicing scheme is capable to accommodate heterogeneous traffic and provides performance isolation of slices while maintaining resource utilization at the level of complete sharing. Depending on the system parameters, the proposed scheme allows to improve session loss probability by an order of magnitude as compared to static slicing, while keeping the user data rates comparable to that of the complete sharing scheme and improving the average user satisfaction index by up to 90%. Overall, the proposed scheme results in efficient resource utilization compared to slicing policies in which slice isolation is provided via reservation by setting fixed upper or lower capacity bounds.

An assessment of radio network coverage, usually in the form of a measurement campaign, is essential for multibase-station (multi-BS) network deployment and maintenance. It can be conducted by a network operator or its served consumers. However, the number of measurement points and their locations may not be known in advance for an efficient and accurate evaluation. The main goal of this study is to propose a new methodology for understanding the selection of measurement points during coverage and signal quality assessment. It is particularly tailored to multi-BS low-power wide-area network (LPWAN) deployments without explicit knowledge of BS locations. To this aim, we first conduct a large-scale measurement campaign for three popular LPWAN technologies, namely, narrowband IoT (NB-IoT), Sigfox, and LoRaWAN. Utilizing this baseline data, we develop a procedure for identifying the minimum set of measurement points for the coverage assessment with a given accuracy as well as study which interpolation algorithms produce the lowest approximation error. Our results demonstrate that a random choice of measurement points is on par with their deterministic selection. Out of the candidate interpolation algorithms, the Kriging method offers attractive performance in terms of the absolute error for NB-IoT deployments. In contrast, for Sigfox and LoRaWAN infrastructures, less complex techniques, such as the natural neighbor, linear interpolation, or inverse-distance weighting, can achieve comparable (and occasionally even better) accuracy levels.

Considering the dynamically changing nature of the radio propagation environment, the envisioned battery lifetime of the end device (ED) for massive machine-type communication (mMTC) stands for a critical challenge. As the selected radio technology bounds the battery lifetime, the possibility of choosing among several low-power wide-area network (LPWAN) technologies integrated at a single ED may dramatically improve its lifetime. In this article, we propose a novel approach of battery lifetime extension utilizing reinforcement learning (RL) policies. Notably, the system assesses the radio environment conditions and assigns the appropriate rewards to minimize the overall power consumption and increase reliability. To this aim, we carry out extensive propagation and power measurements campaigns at the city-scale level and then utilize these results for composing real-life use cases for static and mobile deployments. Our numerical results show that RL-based techniques allow for a noticeable increase in EDs’ battery lifetime when operating in the multi-RAT mode. Furthermore, out of all considered schemes, the performance of the weighted average policy shows the most consistent results for both considered deployments. Specifically, all RL policies can achieve 90% of their maximum gain during the initialization phase for the stationary EDs while utilizing less than 50 messages. Considering the mobile deployment, the improvements in battery lifetime could reach 200%.

Terahertz (THz) communications systems are expected to become a major enabling technology at the air interface in sixth-generation (6G) cellular systems. However, utilizing extremely narrow antenna radiation patterns at both base station (BS) and user equipment (UE) sides, these systems are affected by not only dynamic blockage but micromobility of UEs. To alleviate the impact of both factors one may utilize the multiconnectivity mechanism allowing for UE to remain connected to several BSs simultaneously and switch between them in case the active connection is lost. In this work, we develop a mathematical framework to characterize the outage probability and spectral efficiency associated with different degrees of multiconnectivity in dynamic blockage and micromobility environment for different beamsearching design options. Our results demonstrate that the presence of UE micromobility may have a positive impact on system performance. Particularly, multiconnectivity allows improving outage and spectral efficiency for small and medium blockers density (up to 0.5 bl./m2) up to that of an ideal system with zero beamsearching times. Furthermore, higher gains are observed for higher degrees of multiconnectivity (e.g., greater than two) as compared to the system with only blockage impairments. For higher blockers densities, however, the reverse effect is observed.

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.

Terahertz (THz) band is considered as the main candidate for new radio access technology in sixth-generation (6G) cellular systems. However, the performance of these systems will be severely affected by not only blockage but user equipment (UE) micromobility in hands of a user. The negative effects of these phenomena can be alleviated by utilizing the multi-connectivity functionality that allows UE to maintain two or more links to nearby base stations (BS) and use them when the currently active link is lost. By accounting for THz specific propagation, antenna and beamsearching design, the density of THz BS deployment, and multi-connectivity operation, we investigate the successful session completion probability under both types of impairments. Our results indicate that the gains of multi-connectivity are observed up to 5 simultaneously supported links and heavily depend on the application outage tolerance time and is mostly affected by micromobility. To improve it, one needs to ensure that the application may tolerate outage caused by beamsearching time which is on the order of milliseconds.

The high propagation losses and sensitivity to link blockage naturally require dense deployments of millimeter-wave (mmWave) 5G New Radio (NR) systems. One of the inherent challenges in these deployments is cost-efficient backhauling. Addressing this issue, 3GPP has recently proposed the concept of integrated access and backhaul (IAB) to reduce the deployment costs by enabling wireless backhaul. The efficient utilization of spectrum in these systems is conditional on the ability of IAB nodes to simultaneously receive signals on their sectoral antennas. In this paper, we investigate the interference caused by this functionality and identify countermeasures including angular and spatial diversities. Our numerical results demonstrate that the angular distance of 25° between the user equipment (UE) served by adjacent sectoral antennas is sufficient to efficiently mitigate interference. A comparable reduction in the interference level can also be achieved by utilizing spatial diversity with antenna separation of at least 20 m. By combining these methods, one can identify the target levels of angular and spatial diversities suitable for the particular deployment restrictions.

Wireless communications in the low terahertz band (0.1 THz-1 THz) is a promising candidate to enable ultra-high-rate vehicular networks beyond 5G. The successful design and adoption of such systems require a deep understanding of the low THz channel specifics in complex vehicular scenarios. In this paper, a comprehensive measurement campaign is reported with the aim of analyzing the wave propagation at 300 GHz in typical vehicular deployments. Following a modular approach, the generic vehicular scenario is decomposed into basic propagation setups that are further analyzed in detail. The obtained measurement data are then applied to derive the mathematical approximations that characterize the low THz band channel properties for each scenario. Finally, the combination of measurement and modeling results is used to identify the critical propagation effects that has to be accounted for in the applied studies. The presented approach, raw and processed data, as well as the contributed analysis, serve as building blocks for future analytical and simulation tools to model prospective vehicular communication systems in the low THz band.

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.

The network operators will soon be accommodating a new type of users: unmanned aerial vehicles (UAVs). 5G New Radio (NR) technology operating in the millimeter-wave (mmWave) frequency bands can support the emerging bandwidth-hungry applications facilitated by such aerial devices. To reliably integrate UAVs into the NR-based network infrastructure, new system models that capture the features of UAVs in urban environments are required. As city building blocks constitute one of the primary sources of blockage on the links from the UAV to its serving base station (BS), the corresponding line-of-sight (LoS) probability models are essential for accurate performance evaluation in realistic scenarios. We propose a LoS probability model in UAV communication setups over regular urban grid deployments, which is based on a Manhattan Poisson line process. Our approach captures different building height distributions as well as their dimensions and densities. Under certain characteristic distributions, closed-form expressions for the LoS probability are offered. Our numerical results demonstrate the importance of accounting for the building height distribution type as well as the orientation of the UAV with respect to its BS. By comparing our model with the standard ITU and 3GPP formulations, we establish that the latter provide an overly optimistic approximation for various deployments.

5G millimeter wave (mmWave) New Radio (NR) base stations (BS) are expected to be deployed in areas with extremely high and drastically fluctuating traffic demands resulting in frequent quality-of-service violations in terms of the provided rate at the access interface, especially, during busy hour conditions. As a cost-efficient countermeasure we consider NR unlicensed (NRU) technology encompassing both NR and WiGiG at a single NR-U BS. To ultimate goal of this study is to determine the required density of these NR-U BSs in an area characterized by a certain density of NR and WiGiG users, where NR users may utilize WiGiG technology as long as their rate requirements are met. Joining the tools of stochastic geometry, queuing theory and Markov chains we characterize the sought metric of interest. We then report the dependency of eventual NR UE session loss probability that can be used to deduce the sought density of NR-U BSs as a function of system parameters. Among other conclusions, we reveal that the effect of the antenna array at NR part of NR-U BS is non-uniform and needs to be taken into account planning NR-U deployments.

This article aims to put forward the utilization of onshore narrowband IoT (NB-IoT) infrastructure for tracking of containers transported by marine cargo vessels while operating near the coastline. We introduce and evaluate three connectivity strategies, including direct sensor-to-onshore base station (BS) transmission as well as two relay-aided schemes using dedicated vessel-BS or unmanned-aerial-vehicle (UAV)-mounted BS as intermediate nodes. To assess and compare the proposed schemes in terms of the message loss and delay metrics as well as sensor lifetimes, we first employ stochastic geometry to characterize the connectivity process with the onshore deployment and then resort to system-level simulations. Our results indicate that the direct access option suffers from the poorest performance. The relay-based alternatives allow to dramatically improve the system operation by effectively distributing the transmission requests over time at the relay side and thus mitigating contention. Furthermore, gains enabled with UAV relaying are due to extended coverage that increases the available BS density. The considered relaying operation may help tolerate intermittent connectivity across a broad range of system parameters.

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.

The capability of smarter networked devices to dynamically select appropriate radio connectivity options is especially important in the emerging millimeter-wave (mmWave) systems to mitigate abrupt link blockage in complex environments. To enrich the levels of diversity, mobile mmWave relays can be employed for improved connection reliability. These are considered by 3GPP for on-demand densification on top of the static mmWave infrastructure. However, performance dynamics of mobile mmWave relaying is not nearly well explored, especially in realistic conditions, such as urban vehicular scenarios. In this paper, we develop a mathematical framework for the performance evaluation of mmWave vehicular relaying in a typical street deployment. We analyze and compare alternative connectivity strategies by quantifying the performance gains made available to smart devices in the presence of mmWave relays. We identify situations where the use of mmWave vehicular relaying is particularly beneficial. Our methodology and results can support further standardization and deployment of mmWave relaying in more intelligent 5G+ "all-mmWave" cellular networks.

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.

As the Internet of Vehicles matures and acquires its social flavor, novel wireless connectivity enablers are being demanded for reliable data transfer in high-rate applications. The recently ratified New Radio communications technology operates in millimeter-wave (mmWave) spectrum bands and offers sufficient capacity for bandwidth-hungry services. However, seamless operation over mmWave is difficult to maintain on the move, since such extremely high frequency radio links are susceptible to unexpected blockage by various obstacles, including vehicle bodies. As a result, proactive mode selection, that is, migration from infrastructure- to vehicle-based connections and back, is becoming vital to avoid blockage situations. Fortunately, the very social structure of interactions between the neighboring smart cars and their passengers may be leveraged to improve session continuity by relaying data via proximate vehicles. This paper conceptualizes the socially inspired relaying scenarios, conducts underlying mathematical analysis, continues with a detailed 3-D modeling to facilitate proactive mode selection, and concludes by discussing a practical prototype of a vehicular mmWave platform.

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.

To satisfy the stringent capacity and scalability requirements in the fifth generation (5G) mobile networks, both wireless access and backhaul links are envisioned to exploit millimeter wave (mmWave) spectrum. Here, similar to the design of access links, mmWave backhaul connections must also address many challenges such as multipath propagation and dynamic link blockage, which calls for advanced solutions to improve their reliability. To address these challenges, 3GPP New Radio technology is considering a flexible and reconfigurable backhaul architecture, which includes dynamic link rerouting to alternative paths. In this paper, we investigate the use of aerial relay nodes carried by e.g., unmanned aerial vehicles (UAVs) to allow for such dynamic routing, while mitigating the impact of occlusions on the terrestrial links. This novel concept requires an understanding of mmWave backhaul dynamics that accounts for: 1) realistic 3-D multipath mmWave propagation; 2) dynamic blockage of mmWave backhaul links; and 3) heterogeneous mobility of blockers and UAV-based assisting relays. We contribute the required mathematical framework that captures these phenomena to analyze the mmWave backhaul operation in characteristic urban environments. We also utilize this framework for a new assessment of mmWave backhaul performance by studying its spatial and temporal characteristics. We finally quantify the benefits of utilizing UAV assistance for more reliable mmWave backhaul. The numerical results are confirmed with 3GPP-calibrated simulations, while the framework itself can aid in the design of robust UAV-assisted backhaul infrastructures in future 5G mmWave cellular.

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.

Today, the number of interconnected Internet of Things (IoT) devices is growing tremendously followed by an increase in the density of cellular base stations. This trend has an adverse effect on the power efficiency of communication, since each new infrastructure node requires a significant amount of energy. Numerous enablers are already in place to offload the scarce cellular spectrum, thus allowing utilization of more energy‐efficient short‐range radio technologies for user content dissemination, such as moving relay stations and network‐assisted direct connectivity. In this work, we contribute a new mathematical framework aimed at analyzing the impact of network offloading on the probabilistic characteristics related to the quality of service and thus helping relieve the energy burden on infrastructure network deployments.

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.

The fifth generation wireless systems are expected to rely on a large number of small cells to massively offload traffic from the cellular and even from the wireless local area networks. To enable this functionality, mm-wave (EHF) and Terahertz (THF) bands are being actively explored. These bands are characterized by unique propagation properties compared with microwave systems. As a result, the interference structure in these systems could be principally different to what we observed so far at lower frequencies. In this paper, using the tools of stochastic geometry, we study the systems operating in the EHF/THF bands by explicitly capturing three phenomena inherent for these frequencies: (1) high directivity of the transmit and receive antennas;( 2) molecular absorption; and (3) blocking of high-frequency radiation. We also define and compare two different antenna radiation pattern models. The metrics of interest are the mean interference and the signal-to-interference-plus-noise (SINR) ratio at the receiver. Our results reveal that: (1) for the same total emitted energy by a Poisson field of interferers, both the interference and SINR significantly increase when simultaneously both transmit and receive antennas are directive and (2) blocking has a profound impact on the interference and SINR creating much more favorable conditions for communications compared with no blocking case.

The fifth generation wireless systems are expected to rely on a large number of wideband small cells to offload traffic from the cellular and wireless local area networks. To create such small cells, EHF and THF bands are actively explored. These frequencies are characterized by fundamentally different propagation characteristics resulting in different interference structure at the receiver compared to, e.g., microwave systems. In this paper, we study the interference structure for systems operating in EHF/THF bands by explicitly capturing three major phenomena: (i) extreme directivity of the transmit and/or receive antennas, (ii) pass loss component caused by molecular absorption and (iii) blocking of high-frequency radiation. The metric of interest is the mean interference at the receiver. Our results reveal that (i) for the same emitted energy in a Poisson field of interferers, the interference increases with the directivity of the transmit or receive antennas, (ii) blocking has a profound impact on the interference creating much more favorable conditions for communications compared to lower frequencies and (iii) the choice of the antenna model is of crucial importance for accurate performance assessment.

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.

To efficiently utilize ultra-short range wireless technologies providing extreme data rates at the air interface, the concept of “information shower” (IS) has been proposed to complement typical small cell deployments. Although the concept was introduced several years ago, the benefits of ISs is still an open question. We propose an analytical framework for performance evaluation of ISs operating in the terahertz (THz) frequency band. Taking into account different THz bandwidth allocations resulting in different IS coverages and capacities and assuming applications capable of data prefetching, we estimate both user- and network-centric metrics as a function of input parameters including mobility of users. Our study reveals that initiating heavy traffic sessions upon entering THz ISs allows to offload up to 95% of traffic from long-range networks even for low IS sizes and high user densities as the THz IS data rates efficiently compensates for large inter-IS visit times. Such massive offloading also results in considerable improvements in mobile terminal energy efficiency as the fraction of time the radio interfaces have to be active drastically decreases.

Utilizing bacteria as information carriers is a promising technique for molecular communication to establish connections and networking capabilities between micro- and nanoscale devices. A particular process, that is of interest in this paper, and vital to achieve reliable networking performance in bacterial nanonetwork, is conjugation. Conjugation is a process where bacteria come within close range to form physical connections to allow plasmids to be transferred. However, there are a number of processes that could cause loss or damage during the transfer process, such as external vibrations. Message encoding techniques are envisioned as a promising technique to mitigate these effects. In this study we first define the concept of optimal message encoding for bacterial nanonetworks providing the upper bound on the message delivery time and the probability of message delivery within the specified time. We then investigate the effect of encoding on the performance of these metrics by proposing and numerically comparing several feasible encoding techniques. The performance comparison has been done using a specifically developed simulation environment capturing bacteria movement and interactions. Numerical results demonstrate that even the simple encoding strategies allow to significantly improve the performance compared to the baseline system.

Wireless communications in the terahertz (THz) frequency band, 0.1-10THz, promises a rapid increase of channel capacity in next- generation networks. However, the advantages of this technology depend not only on the single link performance, but also on the possibility of several THz links to coexist in the same area. Thus, the efficiency of spatial channel reuse has to be studied. Due to the presence of specific effects in the THz band, such as molecular absorption and molecular noise, existing performance evaluation techniques are not straightforwardly applicable. In this paper, the approach for network-level analysis of THz wireless communications is proposed. This approach is based on the tools of stochastic geometry and takes into account the specific signal propagation features of the THz frequency band. The presented technique is used to derive the distribution of SINR and spectral efficiency as well as to estimate the optimal distance between receiving nodes and maximize the area capacity.

The recent interest in the use of THz band, 0:1-10THz, for communications purposes stimulates development of new models for performance assessment of prospective technologies. One of the unique properties of this band is molecular noise generated by water vapor in response to absorption of electromagnetic radiation. In this paper we specify a model capturing the behavior of the molecular noise in the frequency domain and propose the associated parameters fitting algorithm. The model has a simple structure and can be used as a building block for bit error rate (BER) performance assessment.

Given the importance of multi-radio heterogeneous networks (HetNets) in delivering more throughput and better connectivity experience to today's wireless users, we investigate the prioritized centrally-controlled resource allocation mechanisms in such systems. First, we theoretically formulate the problem of assisted rate allocation across multiple radio access technologies (RATs) as a special case of relative max-min fairness problem with bifurcated (splittable) traffic flows, which can then be solved by employing the standard linear optimization techniques. Our proposed solution delivers certain minimum guarantees to all the network users, while the rest of system resources are divided proportionally to the preset priority of the users. The priorities in our system may correspond to different subscription/pricing plans of a network operator. Finally, we demonstrate the practical benefits of the proposed resource allocation scheme with system-level simulations, as well as discuss its implementation within a testbed prototype based on the OpenFlow architecture.

Over the last decade short-range communications in the terahertz band have been extensively studied as a technology-enabler for dense and ultra-dense wireless networks. Recent advances in miniaturized terahertz transceivers design promise wireless connectivity and simultaneous interaction between thousands of devices. However, the feasibility of network-wide communications is still an open issue due to specific features of the terahertz band and inherent properties of dense deployments. We address this issue developing an analytical model for interference and SINR assessment in dense terahertz networks obtaining the first two moments and density functions for both metrics. Our results demonstrate that the presence of molecular noise does not qualitatively affect the behavior of SINR, while its quantitative effect is of secondary importance compared to interference. The presented approach provides the so-far missing building block for performance analysis of prospective dense terahertz networks.

We propose a model for computing the optimal message length in delay tolerant networks with long propagation delays. As a protocol of interest we use CCSDS File Delivery Protocol operating in differed NAK mode. The proposed model is based on the absorbing Markov chain framework allowing to get not only the mean performance metrics but the probability mass function of time it takes to transmit a message. The latter is due to the special structure of the absorbing Markov chain allowing for simple estimation of the first passage time till absorbtion. Using the pmf one can determine the maximum message length that can be delivered with a certain reliability when two nodes remain in coverage range of each other for a given time.

As throughput of wireless technologies had improved rapidly over the last decade, handheld devices became more attractive to the end users enabling multimedia applications "on-the-move". The uptime of mobile devices depends on their battery power that is not growing at the pace of communication technologies. In this study we describe the trade-offs between the power consumption, compression and the quality of video streaming in wireless environment. We show that using scalable baseline profile of H.264 codec the careful choice of encoding parameters may result in significant energy and bitrate savings at the expense of only slight degradation in quality, if at all. The amount of motion in a sequence plays a crucial role for energy savings when packet loss probability is non-negligible.

In this paper, we address the emerging 5G heterogeneous networks, which comprise several tiers of small cells of various sizes and by different radio access technologies. As industry has recently been targeting efficient mechanisms for tighter coordination between the tiers of such heterogeneous network, where multiple radios may be utilized simultaneously, we argue that the corresponding problem of assisted resource allocation has not been as widely investigated analytically. To this end, we propose a novel mathematical methodology allowing to deliver the optimal rate distribution for users across the next-generation N-tier wireless network. In particular, we demonstrate that the considered problem of assisted rate allocation can be formulated as a special case of a network flow optimization problem and solved by employing linear programming routines. We also discuss a range of important practical extensions to our baseline model.

The positive effect of traffic localization in P2P systems is widely praised as it allows to decrease the amount of traffic crossing inter-ISP links. At the same time its negative effect is often overlooked. In this paper we concentrate on the biased choice of peers as a way to localize traffic in P2P BitTorrent-like file sharing systems. We demonstrate, evaluate and discuss the negative effect of traffic localization expressing itself in the increase of the average file downloading time as the level of localization increases.

In this paper we consider call admission control in cellular environment for data sessions and voice calls of high priority. A cell is divided into two zones with different average signal to noise ratio, and each zone uses its own modulation and coding. A dynamic resource allocation scheme is further considered, which allows communication systems to utilize their resources more efficiently. All the idle channels, which are left after the voice calls, are allocated to elastic data sessions to increase their transmission rate. When a voice call arrives, required channels can be released to serve it if only elastic data calls have a minimum required bandwidth to continue their sessions. To evaluate the role of elastic traffic, analytical models with elastic and fixed data sessions are formulated and solved. For both cases we derive blocking probabilities as well as other performance metrics of interest. According to numerical results, elastic data sessions achieve higher channel utilization and their mean transmission time is ten times less than that of fixed data sessions. As a result, the mean number of elastic data sessions in the system is twice less than that of fixed data sessions.

In this paper performance modeling for a mobile stations operating according to CSMA/CA with binary exponential back-off (BEB) is discussed. Unlike the previous studies we concentrate on delay and loss performance metrics experienced by individual stations. To obtain delay distribution of an arbitrary packet we use Geo(i)/G(i)/1/K queuing system representing the number of stations having a frame for transmission. In this system both arrival and service process depend on the number of active station. Delay distribution is obtained as a weighted sum of delay distributions in each state of the system. Individual performance metrics are obtained by formulating and solving a separate Geo/G/1/K queuing system.

Wireless channels are characterized by time-varying characteristics that often lead to incorrect reception of protocol data units. Automatic repeat request and forward error correction try to prevent it providing reliable service to higher layers. Most models proposed to date assumed that ARQ is fully reliable meaning that a frame is successfully transmitted irrespective of time it takes. In this paper we study the effect of ARQ reliability on performance experienced at higher layers. We propose a model for semi-reliable ARQ operation when a certain frame can be lost due to excessive amount of retransmissions. We also take into account IP packet losses due to limited buffer space. Using numerical results we show that the effect of maximum number of retransmissions depends on channel characteristics and other protocolspsila parameters. Dynamic tuning of this parameter might be beneficial for optimized performance of wireless channels.

Based on the differentiated services (DiffServ, [S. Blake, et al., December 1998]) model we develop implementation-ready transmission service for video-on-demand (VoD) traffic. In order to satisfy the demands of real-time nature of VoD traffic we propose to use assured forwarding (AF, [B. Davie, et al., March 2002]) per-hop behavior (PHB) group. We provide specific traffic profile parameters which adequately fit to VoD traffic requirements. Using these parameters and AF PHB class we show how to construct a well-defined transmission service that is suitable for VoD traffic delivery. Our service is analytically tractable. It means that using the quality of service (QoS) parameters which should be provided to VoD traffic we can evaluate the required capacity not only within the DiffServ ingress node, but within the interior nodes too. Our transmission service is designed in such way that it is fully characterized by the parameters of DiffServ ingress node, bounds the losses and delay along the path of behavior aggregate and allows us to predict the QoS degradation which can be experienced by both behavior aggregate and single microflows.