Future 5G/6G cellular Internet of Things (CIoT) technologies need to be able to multiplex a number of traffic types having different arrival patterns, resource requirements, and directions. To this aim, the random access (RA) and data transmission (DT) phases in such technologies should be appropriately optimized. In this paper, we develop a computationally efficient and accurate model accounting for both RA and DT phases and the different nature of traffic types in uplink and downlink directions. We establish the stability criterion for the considered system and then utilize this model to optimize resources allocated to RA and DT phases under different traffic loads in uplink and downlink directions. We show that the proposed model provides accurate assessment of the delay at both RA and DT phases with an error of less than 1%, while its fully analytical structure makes it computationally efficient. Our results also indicate that modern CIoT system are not optimized for different load conditions and even a 5 % decrease in the amount of resources allocated to RA or DT phase changes the supported packet arrival rate by up to 80 %. The model developed in this paper allows optimal tuning RA and DT phases for any offered load conditions in the uplink and downlink directions.

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.

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 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.

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.

The adoption of abundant millimeter-wave (mmWave) spectrum offers higher capacity for short-range connectivity in various Unmanned Aerial Vehicle (UAV)-centric communications scenarios. In contrast to the conventional cellular paradigm, where the coordination of connected nodes is highly centralized, the distributed deployments, such as those operating over unlicensed frequency bands, maintain robust interactions in the absence of central control. These agile decentralized systems are being naturally created by dynamic UAV swarms that form a temporary 3D structure without reliance on remote management or pre-established network infrastructures. While much effort has been invested in the performance assessment of distributed, directional, and 3D systems individually, a combination of these three angles allows capturing more realistic UAV swarm scenarios and produces a novel research perspective. This work addresses one of the fundamental challenges in mmWave-based 3D networks– directional deafness– which is known to adversely affect the overall system performance. Particularly, we develop a mathematical framework by taking into account the peculiarities of 3D directional and distributed deployments. We provide a holistic analytical assessment of directional deafness and propose several powerful approximations that capture realistic antenna patterns.

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.

Comparing to cloud computing, fog computing performs computation and services at the edge of networks, thus relieving the computation burden of the data center and reducing the task latency of end devices. Computation latency is a crucial performance metric in fog computing, especially for real-time applications. In this article, we study a peer computation offloading problem for a fog network with unknown dynamics. In this scenario, each fog node (FN) can offload its computation tasks to neighboring FNs in a time slot manner. The offloading latency, however, could not be fed back to the task dispatcher instantaneously due to the uncertainty of the processing time in peer FNs. Besides, peer competition occurs when different FNs offload tasks to one FN at the same time. To tackle the above difficulties, we model the computation offloading problem as a sequential FN selection problem with delayed information feedback. Using the adversarial multiarm bandit framework, we construct an online learning policy to deal with delayed information feedback. Different contention resolution approaches are considered to resolve peer competition. Performance analysis shows that the regret of the proposed algorithm, or the performance loss with suboptimal FN selections, achieves a sublinear order, suggesting an optimal FN selection policy. Besides, we prove that the proposed strategy can result in a Nash equilibrium (NE) with all FNs playing the same policy. Simulation results validate the effectiveness of the proposed policy.

Fog computing provides computation and services to the edge of networks to support real-time applications. The latency performance is a crucial metric in fog computing. In this article, we consider a computation offloading problem in a fog network with unknown dynamics. In this network, mobile users can offload their computational tasks to neighborhood fog nodes (FNs) in each time slot. The queue of arrival tasks at each FN follows a Markov model with unknown statistics. In order to provide a satisfactory quality of experience, the network latency needs to be minimized. In this article, we construct an offloading policy with interleaved exploration and exploitation epochs to solve the sequential FN selection problem. An upper bound of regret is derived to show the effectiveness of the proposed method. The proposed policy is optimal in the sense that it achieves a regret with sublinear order. In addition, the proposed policy can be applied to both single-user setting and multiuser setting. Simulation results show that when compared with the existing offloading algorithms, the proposed algorithm can reduce the average latency by 7%–47% in the single-user setting, and 91% in the multiuser setting.

Sensor fusion has attracted a lot of research attention during the few last years. Recently, a new research direction has emerged dealing with sensor fusion without knowledge of the ground truth. In this article, we present a novel solution to the latter pertinent problem. In contrast to the first reported solutions to this problem, we present a solution that does not involve any assumption on the group average reliability which makes our results more general than previous works. We devise a strategic game where we show that a perfect partitioning of the sensors into reliable and unreliable groups corresponds to a Nash equilibrium of the game. Furthermore, we give sound theoretical results that prove that those equilibria are indeed the unique Nash equilibria of the game. We then propose a solution involving a team of learning automata (LA) to unveil the identity of each sensor, whether it is reliable or unreliable, using game-theoretic learning. The experimental results show the accuracy of our solution and its ability to deal with settings that are unsolvable by legacy works.

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.

Fog computing brings computation and services to the edge of networks enabling real time applications. In order to provide satisfactory quality of experience, the latency of fog networks needs to be minimized. In this paper, we consider a peer computation offloading problem for a fog network with unknown dynamics. Peer competition occurs when different fog nodes offload tasks to the same peer FN. In this paper, the computation offloading problem is modeled as a sequential FN selection problem with delayed feedback. We construct an online learning policy based on the adversary multi-arm bandit framework to deal with peer competition and delayed feedback. Simulation results validate the effectiveness of the proposed policy.

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.

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.

In this paper, we address a problem of 3D directional deafness, which may arise for millimeter-wave (mmWave) devices, e.g., in the contention-based access period of the IEEE 802.11ad/ay protocols. To evaluate the probability of 3D deafness, we develop an analytical framework based on stochastic geometry methods. In particular, we study a minimal feasible set of devices equipped with highly directional antennas with an arbitrary antenna pattern and provide an analytical expression for the distance-dependent 3D directional deafness probability.To abstract away from particular antenna patterns, we propose an analytically tractable model of an antenna pattern that is given by a piece-wise linear function of the beamwidth. Using this tractable equation, we derive a corresponding closed-form lower bound for the deafness probability that serves as an approximation for an arbitrary antenna with the same half-power beamwidth. Finally, we study the effects of antenna settings on the deafness probability and derive a scaling law for its lower values.

Social networks are the most preferred mean for the people to communicate. Therefore, it is quite usual that experts use them to carry out Group Decision Making processes. One disadvantage that recent Group Decision Making methods have is that they do not allow the experts to use free text to express themselves. On the contrary, they force them to follow a specific user–computer communication structure. This is against social network nature where experts are free to express themselves using their preferred text structure. This paper presents a novel model for experts to carry out Group Decision Making processes using free text and alternatives pairwise comparisons. The main advantage of this method is that it is designed to work using social networks. Sentiment analysis procedures are used to analyze free texts and extract the preferences that the experts provide about the alternatives. Also, our method introduces two ways of applying consensus measures over the Group Decision Making process. They can be used to determine if the experts agree among them or if there are different postures. This way, it is possible to promote the debate in those cases where consensus is low.

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 coexistence of human type communications (HTC) with an ever-increasing number of machine type communications (MTC) is a challenge that the forthcoming Fifth Generation (5G) network is claimed to tackle. Ultra-Reliable and Low Latency Communications (URLLC) are among the most demanding services that 5G network will support. Also referred to as mission-critical services, URLLC often requires group communications. The evolved Multimedia Broadcast and Multicast Services (eMBMS) architecture, currently specified by 3GPP to support group-based services in cellular networks, needs a revision to deliver future mission-critical services. In this paper, we analyze the performance of different machine-type multicast service (MtMS) scenarios and we compare three subgroup based approaches for multicast data delivery to MTC devices with limited channel bandwidth. Achieved simulation results provide useful guidelines for the design of multicasting schemes able to support delay-sensitive applications in 5G networks.

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.

A diversity of wireless technologies will collaborate to support the fifth‐generation (5G) communication networks with their demanding applications and services. Despite decisive progress in many enabling solutions, next‐generation cellular deployments may still suffer from a glaring lack of bandwidth due to inefficient utilization of radio spectrum, which calls for immediate action. To this end, several capable frameworks have recently emerged to all help the mobile network operators (MNOs) leverage the abundant frequency bands that are utilized lightly by other incumbents. Along these lines, the recent Licensed Shared Access (LSA) regulatory framework allows for controlled sharing of spectrum between an incumbent and a licensee, such as the MNO, which coexist geographically. This powerful concept has been subject to several early technology demonstrations that confirm its implementation feasibility. However, the full potential of LSA‐based spectrum management can only become available if it is empowered to operate dynamically and at high space‐time‐frequency granularity. Complementing the prior efforts, we in this work outline the functionality that is required by the LSA system to achieve the much needed flexible operation as well as report on the results of our respective live trial that employs a full‐fledged commercial‐grade cellular network deployment. Our practical results become instrumental to facilitate more dynamic bandwidth sharing and thus promise to advance on the degrees of spectrum utilization in future 5G systems without compromising the service quality of their users.

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.

Significant increase in multimedia traffic challenges 5G networks in terms of capacity and correspondent QoS parameters. Device-to-device communication paradigm has already become an integral part of 3GPP standards; nevertheless it has not yet been widely deployed due to many different reasons. D2D is expected to leverage implementation of many qualitatively new services and to efficiently accomplish it D2D devices are supposed to form clusters. Due to practical limitations, current D2D implementations are mostly out-of-band and use Wi-Fi Direct. In this paper, we propose a novel model for throughput optimization in out-of-band D2D clusters. We delivered numerical results for different typical cluster member distributions and revealed key functional dependencies. Further, for the first time we compare clustering algorithms for out-of-band D2D and identify effective clustering algorithm that increases network resource utilization rate.

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 rapid development of services provided on SIP networks not only define the necessity of creating new equipment and standards but also requires the development of new methods and programming software tools for modeling and analyzing the effectiveness of the overload control mechanisms in SIP-server networks. The modeling process utilizes mathematical and simulation models as well as simulators. Only simulators or simulation tools make it possible to solve problems related to the analysis and optimization of the control parameters. The most appropriate modeler is the simulators reflecting the protocols and functions, which are fully or partially built into the original system. At present, there are no simulators for modeling the work of SIP servers in overload conditions with an application of mechanisms, which are currently under development by IETF SIP Overload Control workgroup. Simulation tool that supports the main SIP RFCs such as RFC 3261 are proposed in the paper. The architecture of SIP node is developed, and numerical example is presented.

Providing multimedia services to users assumes perfect quality of transfer and modern processing equipment that involves need of development of new methods of the analysis and forecasting of functioning of a communication network. In the paper we investigate the problem of the overload that occurs on a SIP (Session Initiation Protocol) server. SIP overload mitigation is based on RBOC (Rate-based overload control) schema, which was designed by IETF SIP overload control workgroup. The aim of RBOC schema is to restrict signaling message flow rate from the client side towards the server side. Hysteretic overload control algorithm is used to define trigger point for sending control information by the server to the client. Token bucket algorithm is applied to restrict the number of the tokens that the server grants the client. Simulation model for estimation main performance metrics is developed. Traffic with different type of distribution is used for investigation the behavior of the system with tandem servers. The optimization problem for maximization of processor utilization of SIP server on the dependence of threshold values and the number of token is formulated.

Major standards organizations, ITU, ETSI, and 3GPP have all adopted SIP as a basic signalling protocol for NGN. The current SIP overload control mechanism is unable to prevent congestion collapse and may spread the overload condition throughout the network. In this paper, we investigate one of the implementations of loss based overload control scheme developed by IETF work group which uses hysteretic load control technique on the server side for preventing its overloading. Two different approaches to calculate performance measure of SIP server are introduced. We follow an analytical modelling approach to construct and analyse SIP server model in the form of queuing system with finite buffer occupancy and two-level hysteretic overload control. The formulas for stationary probabilities and the mean return time in the set of normal states were obtained. Simulation is the other approach which allows to eliminate disadvantages of analytical modelling. At present, there is no simulator for modelling of SIP servers in overload conditions with an application of overload control mechanisms which are currently under development by IETF. Approaches to its programming implementations which reflects the protocols and functions that are fully or partially built into the original SIP systems are proposed in the paper.

The rapid development of services provided on SIP networks not only define the necessity of creating new equipment and standards but also requires the development of new methods and programming software tools for modeling and analyzing the effectiveness of the overload control mechanisms in SIP-server networks. The modeling process utilizes mathematical and simulation models as well as simulators. Only simulation tools make it possible to solve problems related to the analysis and optimization of the control parameters. The most appropriate modeler is the simulators reflecting the protocols and functions which are fully or partially built into the original system. Over the last few years, IETF working group SOC (SIP Overload Control) has been actively conducting research aimed at developing an effective mechanism for server overload control in SIP networks. At present, there are no simulators for modeling the work of SIP servers in overload conditions with an application of mechanisms which are currently under development by SOC. A model for a SIP server simulator and approaches to its programming implementation are proposed in the paper.