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We consider the downlink of a cooperative cellular communications system, where several base-stations around each mobile cooperate and perform zero-forcing to reduce the received interference at the mobile. We derive, for the first time, closed-form expressions for the asymptotic performance of the network as the number of antennas per base station grows large. These expressions capture the trade-offs between various system parameters, and characterize the joint effect of noise and interference (where either noise or interference is asymptotically dominant and where both are asymptotically relevant). The presented analysis is significantly more challenging than the uplink analysis due to the dependence between beamforming vectors of nearby base stations. This statistical dependence is handled by introducing novel bounds on marked shot-noise point processes with dependent marks, which are also useful in other contexts. The asymptotic results are verified using Monte Carlo simulations, which indicate that they are useful even when the number of antennas per base station is only moderately large. Based on these expressions, we present a novel power allocation algorithm that is asymptotically optimal while significantly reducing the coordination overhead between base stations.

We study the interference resulting from transmissions from terrestrial cellular networks on passive satellite receivers. This has important implications for the future allocation and terrestrial use of spectrum on a shared basis with satellite systems, in particular above 100 GHz. We develop an extensive, general model for the interference received at a typical passive satellite. Utilizing a stochastic geometry framework, we precisely characterize the outage probability for a set of satellites – which is the distribution of the interference with respect to spatial and temporal randomness inherent in the aforementioned interference model. We obtain upper and lower bounds on the outage probability using a new analytical method based on a matrix function generalization of the Laplace transform of the interference model. This analytical method allows for the distribution of the interference to be tightly bounded while affording a similar level of tractability to that encountered in the more typical coverage probability analysis of wireless networks using stochastic geometry. Using the analytical characterizations for outage probability, we investigate design choices and constraints such as the antenna gain and positioning at the passive satellite receiver and terrestrial nodes, out-of-band rejection, terrestrial network density, and the scan pattern of the passive receiver. Our analysis indicates that spectrum coexistence is feasible with minimal spectral separation, and that in-band coexistence may even be possible with low, but non-negligible, outage probability. A key insight from our analysis is that outage events are largely driven by spatial events corresponding to the presence of large clusters of transmitters as opposed to temporal fluctuations in interference power. The impact of these spatial events on EESS sensors may be mitigated by varying the boresight direction of the receive beam over the measurement duration.

In this paper, we consider a distributed antenna system (DAS) with polarized antennas for the industrial internet-of-things, where distributed sensor nodes (SNs) with a single antenna are served by the closest distributed antenna (DA) port having multiple antennas. By using stochastic geometry, the interference in the polarized DAS is analyzed and the channel outage probability (OP) of the polarized DAS is also derived in a closed form. From the analytic results, the optimal vertically/horizontally polarized node densities are derived to minimize the channel OP. Furthermore, by investigating the effects of node density and polarization on the channel OP, we also develop a dual-polarized DAS, in which the effective density of co-polarized DA ports is the same with the density of all DA ports and, simultaneously, the interference from the active cross-polarized DA ports is effectively mitigated. By analyzing the channel OP for the dual-polarized DAS, the optimal node densities to minimize the overall channel OP and the effect of network design parameters on the channel OP is also investigated, which gives us a useful insight into the design of the polarized DAS.

With the deployment of satellite constellations, Internet-of-Things (IoT) devices in remote areas have gained access to low-cost network connectivity. In this paper, we investigate the performance of IoT devices connecting in up-link through low Earth orbit (LEO) satellites to geosynchronous equatorial orbit (GEO) links. We model the dynamic LEO satellite constellation using the stochastic geometry method and provide an analysis of end-to-end availability with low-complexity and coverage performance estimates for the mentioned link. Based on the analytical expressions derived in this research, we make a sound investigation on the impact of constellation configuration, transmission power, and the relative positions of IoT devices and GEO satellites on end-to-end performance.

In this paper, we present a novel reliability analysis of massive Internet of Things (IoT) connectivity in cellular networks. In massive IoT networks, IoT devices sporadically and unpredictably send short data packets to nearby base stations (BSs), potentially interfering with other IoT devices with whom they share the uplink channel. Assuming slotted ALOHA random access policy, we investigate the probability that an IoT device transmitting a short data packet is not decoded at the nearest BS under Nakagami fading. We derive error probability expressions combining the tools of finite block-length (FBL) information theory and stochastic geometry. Derived FBL-based results are confirmed by Monte Carlo simulations and further compared with the asymptotic expressions available in the previous studies that are obtained under assumption that a device transmits asymptotically long data packets. Numerical results confirm the accuracy of the obtained expressions and their applicability to the massive IoT system design and performance evaluation under a wide range of system parameters. For example, the matching between the values obtained by numerical integration and approximation results of the FBL error probability is in the range between 97.6-99.4 % for different choices of the parameters.

The inclusion of the sensing functionality in the coming generations of cellular networks, necessitates a rethink of dense cell deployments. In this paper, we analyze and optimize dense cell topologies for dual-functional radar-communication (DFRC) cellular networks. With the aid of tools from stochastic geometry, we derive new analytical expressions of the potential area spectral efficiencies in $(\textrm {bit}/\textrm {sec}/m^{2})$ of radar and communication systems using zero-forcing precoding scheme. Based on the new formulations of the potential area spectral efficiencies, the energy efficiency (bit/Joule) of DFRC systems is provided in a closed-form formula. Then, an optimization problem to obtain the optimal base station (BS) density that maximizes the network-level energy efficiency is formulated and investigated. Our analytical and numerical results demonstrate that the inclusion of the sensing functionality clearly differentiates the optimal BS topologies for the DFRC systems against classical communication-only systems.

This study analyzes the performance of 3rd Generation Partnership Project (3GPP)-inspired multi-cell wideband single-hop backhaul millimeter-wave-in-band-full-duplex (IBFD)-integrated access and backhaul (IAB) networks using stochastic geometry. We modeled the wired-connected Next Generation NodeBs (gNBs) as the Matérn hard-core point process (MHCPP) to meet real-world deployment requirements and reduce the cost caused by wired connections in the network. We first derive association probabilities that reflect the likelihood that typical user-equipment is served by a gNB or an IAB-node based on the maximum long-term averaged biased-received-desired-signal power criteria. Furthermore, by leveraging the composite Gamma-Lognormal distribution, we derived the closed-form signal to interference plus noise ratio coverage, capacity with outage, and ergodic capacity of the network. To avoid underestimating the noise, we consider the sidelobe gain on the inter-cell interference links and analog-to-digital converter quantization noise. Compared with half-duplex transmission, the numerical results show an enhanced capacity with outage and ergodic capacity provided by the IBFD under successful self-interference cancellation. We also study how the power bias and density ratio of the IAB-node to gNB and the hard-core distance can affect system performance.

We hereby present a novel interference mitigation strategy specifically designed to enhance the quality of service that a typical terrestrial user equipment (UE) would experience after the occurrence of a calamity. In particular, we devise a novel stochastic geometry framework where the functioning ground base stations are modeled as an inhomogeneous Poisson point process, and promote proper silencing as an effective solution to improve both coverage and reliability (which is usually overlooked in emergency scenarios); in particular, the latter is evaluated by means of the signal-to-interference-plus-noise ratio (SINR) meta distribution performance metric. The derived downlink performances assume Rayleigh fading conditions for all wireless links. The numerical results show insightful trends in terms of both average coverage probability (which is optimized by choosing the best area for applying the silencing strategy) and SINR meta distribution, depending on: distance of the UE from the disaster epicenter (henceforth intended as the center of the area where the BS can be damaged), disaster radius (also referring to the latter area), and quality of resilience of the terrestrial network. The aim of this paper is therefore to prove the effectiveness of proper silencing in emergency scenarios, at least from the coverage and reliability perspectives.

Given the necessity of connecting the unconnected, covering blind spots has emerged as a critical task in the next-generation wireless communication network. A direct solution involves obtaining a coverage manifold that visually showcases network coverage performance at each position. Our goal is to devise different methods that minimize the absolute error between the estimated coverage manifold and the actual coverage manifold (referred to as accuracy), while simultaneously maximizing the reduction in computational complexity (measured by computational latency). Simulation is a common method for acquiring coverage manifolds. Although accurate, it is computationally expensive, making it challenging to extend to large-scale networks. In this paper, we expedite traditional simulation methods by introducing a statistical model termed line-of-sight probability-based accelerated simulation. Stochastic geometry is suitable for evaluating the performance of large-scale networks, albeit in a coarse-grained manner. Therefore, we propose a second method wherein a model training approach is applied to the stochastic geometry framework to enhance accuracy and reduce complexity. Additionally, we propose a machine learning-based method that ensures both low complexity and high accuracy, albeit with a significant demand for the size and quality of the dataset. Furthermore, we describe the relationships between these three methods, compare their complexity and accuracy as performance verification, and discuss their application scenarios.

An unmanned aerial vehicle-mounted base station (UAV-BS), also known as an aerial base station (ABS), is a viable technology for the next 6G wireless networks due to its adaptability and affordability. Furthermore, the concept of tethered UAVs (TUAVs), can be used to circumvent the limited network operating time of UAV-BS networks. TUAVs are UAVs powered by a ground energy source via a tether that restrain their mobility while providing unlimited power. In this work, we propose a system where ABSs are deployed in user hotspots to offload the traffic and assist terrestrial base stations (TBSs). We will analyze three different scenarios and compare them in terms of coverage performance and energy efficiency. For a more realistic system, we offer a system model that considers the dynamic spatial distribution of users. First of all, we start by determining the optimal locations of TUAVs that minimize the average pathloss for each scenario. Next, using tools from stochastic geometry and an approach of dividing the space into concentric rings and slices to quantify the locations and orientations of ground stations (GSs), we analyze both coverage and energy performance for each scenario. We verify our findings using Monte-Carlo simulations and draw multiple useful insights. For instance, we show that deploying a TUAV with attachment and detachment capability for each pair of clusters outperforms deploying a normal TUAV for each cluster in terms of energy efficiency but not in terms of coverage performance.

Reconfigurable intelligent surface (RIS) technology and its integration into existing wireless networks have recently attracted much interest. While an important use case of said technology consists in mounting RISs onto unmanned aerial vehicles (UAVs) to support the terrestrial infrastructure in post-disaster scenarios, the current literature lacks an analytical framework that captures the networks' topological aspects. Therefore, our study borrows stochastic geometry tools to estimate both the average and local coverage probability of a wireless network aided by an aerial RIS (ARIS); in particular, the surviving terrestrial base stations (TBSs) are modeled by means of an inhomogeneous Poisson point process, while the UAV is assumed to hover above the disaster epicenter. Our framework captures important aspects such as the TBSs' altitude, the fact that they may be in either line-of-sight or non-line-of-sight condition with a given node, and the Nakagami-m fading conditions of wireless links. By leveraging said aspects we accurately evaluate three possible scenarios, where TBSs are either: (i) not aided, (ii) aided by an ARIS, or (iii) aided by an aerial base station (ABS). Our selected numerical results reflect various situations, depending on parameters such as the environment's urbanization level, disaster radius, and the UAV's altitude.

Visible light communication (VLC)-enabled unmanned aerial vehicle (UAV) networks have emerged as a novel approach for simultaneous illumination and communication. Among the prominent challenges in VLC are shadowing and low reflected energy. Light-emitting diode (LED) beam-steering is a promising technique to overcome these challenges. In this paper, we consider the problem of joint UAV deployment, LED beam-steering, cell association, and power allocation to satisfy a set of illumination and data rate requirements for stochastically distributed users. Towards addressing this problem, we develop SteerVLC, a novel scheme for UAV networks equipped with steerable LEDs that jointly optimizes UAV deployment, LED beam-steering, cell association, and power allocation. While accounting for illumination interference, SteerVLC minimizes the number of UAVs needed to satisfy the illumination and data rate requirements of stochastically distributed users and minimizes the total transmission power of the steerable LEDs. Using an $\epsilon $ -controlled two-stage mixed-integer linear programming approach, SteerVLC can effectively manage the tradeoff between the required number of UAVs and the required transmission power. SteerVLC is evaluated under various system parameters, user demands, and user distributions. Our results demonstrate the superiority of SteerVLC in managing the resources of a VLC-enabled UAV network and optimizing its performance.

In this paper, with the aid of the mathematical tool of stochastic geometry, we introduce analytical and computational frameworks for the distribution of three different definitions of delay, i.e., the time that it takes for a user to successfully receive a data packet, in large-scale cellular networks. We also provide an asymptotic analysis of one of the delay distributions, which can be regarded as the packet loss probability of a given network. To facilitate the computation of the obtained analytical formulations, we propose efficient numerical approximations based on the numerical inversion method, the Riemann sum, and the beta distribution. Finally, we demonstrate the accuracy of the obtained analytical formulations and the corresponding approximations against Monte Carlo simulations, and unveil insights on the delay performance with respect to several design parameters, such as the decoding threshold, the transmit power, and the deployment density of the base stations. The proposed methods can facilitate the analysis and optimization of cellular networks, subject to reliability constraints on the network packet delay, that are not restricted to the local (average) delay, e.g., in the context of delay sensitive applications.

The surging capacity demands of 5G networks and the limited coverage distance of high frequencies like millimeter-wave (mmW) and sub-terahertz (THz) bands have led to consider the upper 6 GHz (U6G) spectrum for radio access. However, due to the presence of the existing satellite (SAT) services in these bands, it is crucial to evaluate the impact of the interference of terrestrial U6G stations to SAT systems. A comprehensive study on the aggregated U6G-to-SAT interference is still missing in the literature. In this paper, we propose a stochastic model of interference (SMI) to evaluate the U6G-to-SAT interference, including the statistical characterization of array gain and clutter-loss and considering different interference modes. Furthermore, we propose an approximate geometrical-based stochastic model of interference (GSMI) as an alternative method to SMI when the clutter-loss distribution is unavailable. Our results indicate that given the typical international mobile telecommunication (IMT) parameters, the aggregated interference power toward the geostationary (GEO) SATs, is well below the relevant protection criterion, and we prove numerically that the GSMI method overestimates the aggregated interference power with only 2 dB compared to the SMI method.

In this paper, we present the energy efficiency (EE) analysis of a multi-tier cellular network, where intra- and inter-tier dependence in the base station (BS) locations are captured via point processes, i.e., three variants of hard-core point processes (HCPPs) and the Poisson hole process (PHP). The analytical expression for EE is derived by approximating both the average power consumption of BSs and the coverage probability using an approximate signal-to-interference ratio analysis based on the Poisson point process (PPP). It is demonstrated that the proposed Matérn HCPP Type-I-PHP model provides better EE results compared to the other HCPP-PHP and PPP models.

The Terahertz (THz) band (0.1–10 THz) contains abundant spectrum resources that can offer ultra-high data rates. Despite these potential benefits, the adoption of THz communication has been stagnant until very recently due to the poor penetrability and limited coverage of the THz links. To overcome the aforementioned obstacles and take full advantage of the THz band, we introduced a hybrid network consisting of THz and millimeter-wave (mmWave) nodes deployed within a finite area. Furthermore, the mmWave nodes are spatially distributed by a Poisson Point Process (PPP), whereas the THz nodes are clustered around the mmWave nodes, forming a Poisson Cluster Process (PCP) with the parent process of mmWave tier. We derive the Laplace transform of the interference in a closed form and evaluate the coverage probability (CP) based on the maximum biased power (Max-BRP) association strategy. The proposed framework provides insights into how the spatial dependence between THz and mmWave tier and clustering setting affects network performance. We quantitatively reveal its impact on the network performance. It is revealed that this inter-tier spatial dependence introduces the flexibility of nodes deployment by tuning the scattering variance and the number of nodes per cluster. Furthermore, we use numerical simulation to demonstrate the significant impact of bias ratio, density, and blockage on the CP, indicating the importance of choosing the optimal combination of the parameters.

In this paper, we study the co-design of full-duplex (FD) radio with joint communication and radar sensing (JCAS) techniques in millimeter-wave (mmWave) heterogeneous networks (HetNets). Spectral co-existence of radar and communication systems causes mutual interference between the two systems, compromising both the data exchange and sensing capabilities. Focusing on the detection performance, we propose a cooperative detection technique, which exploits the sensing information from multiple base stations (BSs), aiming at enhancing the probability of successfully detecting an object. Three combining rules are considered, namely the OR, the Majority and the AND rule. In real-world network scenarios, the locations of the BSs are spatially correlated, exhibiting a repulsive behavior. Therefore, we model the spatial distribution of the BSs as a $\beta$ β -Ginibre point process ($\beta$ β -GPP), which can characterize the repulsion among the BSs. By using stochastic geometry tools, analytical expressions for the detection performance of $\beta$ β -GPP-based FD-JCAS systems are expressed for each of the considered combining rule. Furthermore, by considering temporal interference correlation, we evaluate the probability of successfully detecting an object over two different time slots. Our results demonstrate that our proposed technique can significantly improve the detection performance when compared to the conventional non-cooperative technique. [ABSTRACT FROM AUTHOR]

The number of disasters has increased over the past decade where these calamities significantly affect the functionality of communication networks. In the context of 6G, airborne and spaceborne networks offer hope in disaster recovery to serve the underserved and to be resilient in calamities. Therefore, our paper reviews the state-of-the-art literature on post-disaster wireless communication networks and provides insights for the future establishment of such networks. In particular, we first give an overview of the works investigating the general procedures and strategies for facing any large-scale disaster. Then, we present technological solutions for post-disaster communications, such as the recovery of the terrestrial infrastructure, installing aerial networks, and using spaceborne networks. Afterwards, we shed light on the technological aspects of post-disaster networks, primarily the physical and networking issues. We present the literature on channel modeling, coverage and capacity, radio resource management, localization, and energy efficiency in the physical layer part, and discuss the integrated space-air-ground architectures, routing, delay-tolerant/software-defined networks, and edge computing in the networking layer part. This paper also includes interesting simulation results which can provide practical guidelines about the deployment of ad hoc network architectures in emergency scenarios. Finally, we present several promising research directions, namely backhauling, cache-enabled and intelligent reflective surface-enabled networks, placement optimization of aerial base stations (ABSs), and the mobility-related aspects that come into play when deploying aerial networks, such as planning their trajectories and the consequent handovers (HOs).

The automobile industry has been evolving with rapid growth over the last two decades. Conventionally, the narrow band dedicated short-range communications is used for the wireless connectivity of vehicular networks in the automobile industry. However, due to its shorter wireless range, higher latency, and lower capacity; cellular-assisted vehicular communications can be adopted to improve networks performance by disrupting the nearby infrastructure. The performance of cellular-assisted vehicular communications is typically compromised if jammers are present in their vicinity. Thus, it is important to characterize the interference in cellular-assisted vehicular communications with jammers. In this paper, we investigate jamming interference due to clustered-jammers for vehicular networks by considering that vehicles, road-side units, and pedestrians are modeled using an independent one-dimensional Poisson line process while cellular base stations are modeled using an independent two-dimensional homogeneous Poisson point process. The results show that jamming disrupts the performance of the vehicular networks and that this performance is severely compromised by increasing the density of jamming clusters and their transmission power. Therefore, the prime focus of the system designers should be to introduce anti-jamming scenario, when the transmission power and the number of jamming clusters in a network increase.

Integrating unmanned aerial vehicles (UAVs) as the base station is a recent progress and a promising solution to assist cellular networks to improve coverage. In this paper, an analytical framework is proposed to analyze coverage probability and capacity, using stochastic geometry. We incorporate the air-to-ground (A2G), and two-piece path loss model that undergoes millimeter wave (mmWave) channel fading in both line-of-site (LOS) and non-line-of-site (NLOS). Furthermore, we assume that all users’ equipment’s (UEs) are clustered around Terrestrial Base Stations (TBS) and UAVs, according to Poisson Cluster Process (PCP), i.e., Matern cluster process. We also propose Multiple-Input-Multiple-Output (MIMO) transmission where multiple single-antenna UAVs simultaneously communicate with TBS. Initially, we obtain expressions for association probability with each tier. After that, we derive downlink coverage expression based on signal-to-interference-plus-noise-ratio (SINR), by assuming 3D directional beamforming with UAV height being not fixed. Numerical results demonstrate the efficiency and accuracy of the proposed approach.

IoT networks are more and more present nowadays. Some IoT protocols share the same bandwidth leading to interference on neighboring networks and decrease of overall coverage. To contribute to this problem, an analytical study of the coverage of a LoRa network with underlying uncoordinated IoT networks for uplink transmissions is presented in this paper. Using stochastic geometry, closed form analytical expressions are proposed allowing to analyze the success and coverage probabilities for a LoRa network. An appropriate model of the path loss including real-life values is used to characterize the log-distance propagation parameters. The interference comes from both the LoRa network itself and the underlying IoT networks, modeled with an $\alpha $ -stable distribution based on recent measurements. It is shown that for an environment with a huge amount of surrounding uncoordinated IoT networks, the gateways deployment should be doubled to reach a decent coverage probability, compared to an environment where the underlying interfering networks are not considered.

This work introduces the concept of angular distance distributions of the nodes in a Binomial point process-based model for wireless networks. The need for the derivation of these distributions is motivated by the use of high-frequency bands in the mmWave or even in the sub-THz bands. These frequencies are closely related to the beamforming capabilities of the transceivers in wireless networks. Therefore, the directional characteristics of the beams utilized by the communicating nodes, along with the random location of the latter, lead to an increasing demand for the distributions derived in this paper. A direct consequence of the Binomial process utilized to model the random location of a fixed number of nodes in a ball, is that the extracted distributions are based on the generalized beta distribution. The presented results are applicable to two- and three-dimensional networks and can be used to study various network characteristics among which are the interference, and the beam management.

In this article, we focus on the pilot-assisted transmission design for secure ultra-reliable and low-latency communication (URLLC) systems, which has not yet been studied in the existing literatures. In each transmission period of this system, the multi-antenna controller sends confidential URLLC messages integrated with artificial noise (AN) to a single-antenna actuator for some mission-critical operations (e.g., remote control), and while an unknown number of passive eavesdroppers attempt to intercept this confidential message in a non-colluding manner. Since the conventional ergodic secrecy capacity is not accurate to describe the maximal achievable secrecy rate of URLLC with short blocklength coding, we establish the concept of achievable effective secrecy rate (AESR) to measure the secrecy performance of our URLLC system, which is defined as the average number of information bits can be transmitted per channel use under given reliability and information leakage constraints. Due to the exact expression of AESR has an intractable form, we derive a closed-form approximation on the AESR to simplify the calculation, via leveraging the Laplace approximation and Gaussian-Chebyshev quadrature method. Following by this approximation, we propose an efficient two-dimensional search algorithm to determine the optimal transmission parameters that maximize the AESR, i.e., the training pilot length and the power allocation ratio between confidential data signals and AN. Furthermore, the asymptotic performance of AESR in the high-SNR regime is also analyzed to gain more insights. Numerical results validate the accuracy of theoretical approximations presented in this paper, and illustrate how the particular system parameters impact the AESR of our considered URLLC system. [ABSTRACT FROM AUTHOR]

The stochastic geometry modeling and analysis of mobile edge computing (MEC) networks contribute to the effective network configuration. Most prior works investigate the MEC network performance by spatial averaging the topological randomness, which can hide the differences among users and result in inaccurate analytical results. To address this limitation, an analytical framework is developed to study the meta distribution of the task offloading performance. We consider the Poisson MEC network where the users with dynamic task requests offload the tasks to the MEC server. Given the model, the $b$ -th moment and the meta distribution of the success task offloading probability are first analyzed. Further, the exact yet convenient approximation of the MEC computing load is derived, based on which the edge computing delay is obtained. Our results demonstrate that the proposed meta-analytical framework allows tractable yet accurate analytical results, and provides additional fine-grained information about MEC-network planning. [ABSTRACT FROM AUTHOR]

In this paper, we aim to improve the connectivity, scalability, and energy efficiency of machine-type communication (MTC) networks with different types of MTC devices (MTCDs), namely Type-I and Type-II MTCDs, which have different communication purposes. To this end, we propose two transmission schemes called connectivity-oriented machine-type communication (CoM) and quality-oriented machine-type communication (QoM), which take into account the stochastic geometry-based deployment and the random active/inactive status of MTCDs. Specifically, in the proposed schemes, the active Type-I MTCDs operate using a novel Bernoulli random process-based simultaneous wireless information and power transfer (SWIPT) architecture. Next, utilizing multi-user power-domain non-orthogonal multiple access (PD-NOMA), each active Type-I MTCD can simultaneously communicate with another Type-I MTCD and a scalable number of Type-II MTCDs. In the performance analysis of the proposed schemes, we prove that the true distribution of the received power at a Type-II MTCD in the QoM scheme can be approximated by the Singh-Maddala distribution. Exploiting this unique statistical finding, we derive approximate closed-form expressions for the outage probability (OP) and sum-throughput of massive MTC (mMTC) networks. Through numerical results, we show that the proposed schemes provide a considerable sum-throughput gain over conventional mMTC networks. [ABSTRACT FROM AUTHOR]

In this paper, we investigate physical-layer security of the uplink millimeter wave communications for a cellular vehicle-to-everything (C-V2X) network comprised of a large number of base stations (BSs) and different categories of V2X nodes, including vehicles, pedestrians, and road side units. Considering the dynamic change and randomness of the topology of the C-V2X network, we model the roadways, the V2X nodes on each roadway, and the BSs by a Poisson line process, a 1D Poisson point process (PPP), and a 2D PPP, respectively. We propose two uplink association schemes for a typical vehicle, namely, the smallest-distance association (SDA) scheme and the largest-power association (LPA) scheme, and we establish a tractable analytical framework to comprehensively assess the security performance of the uplink transmission, by leveraging the stochastic geometry theory. Specifically, for each association scheme, we first obtain new expressions for the association probability of the typical vehicle, and then derive the overall connection outage probability and secrecy outage probability by calculating the Laplace transform of the aggregate interference power. Numerical results are presented to validate our theoretical analysis, and we also provide interesting insights into how the security performance is influenced by various system parameters, including the densities of V2X nodes and BSs. Moreover, we show that the LPA scheme outperforms the SDA scheme in terms of secrecy throughput. [ABSTRACT FROM AUTHOR]

Beamforming with high dimensional antenna arrays provides the gain needed to enable high bandwidth communication in the sub-terahertz (THz) band. The resulting narrow beams, however, come at the cost of increased sensitivity to beam alignment errors. A potential remedy to this problem is to introduce a form a macrodiversity through non-coherent joint transmission (NC-JT). We employ a stochastic geometry framework to analyze the performance of a THz network employing user-centric base station clustering and NC-JT. We derive semi-closed form lower bounds for the coverage probability and ergodic capacity experienced by a typical user in the network. Our model includes THz networks without joint transmission as a special case. Overall, our analysis indicates that joint transmission from a few base stations improves coverage and capacity by mitigating the impact of beam misalignment. Moreover, in certain settings, NC-JT is a more efficient usage a network access points compared to the non-cooperative case, and reduces the sensitivity of coverage and capacity to the choice of user beamwidth. [ABSTRACT FROM AUTHOR]

With the dense deployment of small cells, the impact of height difference between base stations (BSs) and user equipment (UE) on the performance of heterogeneous networks (HetNets) becomes significant. The traditional two-dimensional models are no longer sufficient to capture the three-dimensional (3D) features of dense HetNets. On the other hand, deploying multiple antennas on BSs is a promising approach to improve network capacity. In this paper, we propose a 3D model for a $K$ -tier HetNet with multi-antenna BSs, where different tiers share the same frequency band but may differ in BS height, BS density, number of antennas per BS, BS transmit power, association bias, and path loss exponent. We analytically derive the per-tier association probability under both the strongest received signal and the closest BS cell-association strategies. Based on that, we derive the expressions for the downlink ergodic rate, area spectral efficiency (ASE) and energy efficiency. The numerical results reveal that in the presence of macrocell BSs, for low to medium small-cell BS (SBS) densities, the closest BS cell-association strategy leads to low ergodic rate, ASE and energy efficiency regardless of the SBS height; while at very high SBS densities, under both cell-association strategies, SBSs should be deployed at the same height as UE to achieve high ergodic rate, ASE and energy efficiency. Moreover, we find that for a given SBS height, there exists an optimal combination of SBS density and number of antennas per SBS that maximizes the system energy efficiency. [ABSTRACT FROM AUTHOR]

In order to evaluate the impacts of swarm distribution characteristics of unmanned aerial vehicles (UAVs) and the complexity of millimeter wave (mmWave) propagations on the coverage performance of UAV networks, this paper develops a stochastic geometry-based approach for the modeling and analysis of single- and multi-swarm UAV networks with mmWave communications. We first utilize binomial point processes (BPPs) to model the locations of UAVs in a finite area as a single-swarm UAV network and allow for arbitrary user locations. Then, we define multi-BPPs and extend our model to multi-swarm UAV networks. We consider an open-access strategy, where users access the closest UAV in all swarms, and derive the distance distributions of serving and interfering UAVs. Moreover, a three-dimensional (3D) blockage model and a 3D sectorized antenna model are introduced to completely depict the characteristics of air-to-ground channel in mmWave band. Based on the distance distributions and the Laplace transform of interference, coverage probabilities in considered networks are derived. Our results reveal that, there exists optimal height and density of UAV swarms that maximize the coverage probability. When densely deployed, the interference from inter-swarm cannot be negligible in the multi-swarm UAV network. [ABSTRACT FROM AUTHOR]

This paper investigates the power coverage probability in cooperative wireless powered communication networks, where multiple access points collaborate to meet the energy demands of low-power devices. Based on the theory of Poisson-Delaunay triangulation, the probability density functions (PDF) of the Euclidean distance between the access points of the Poisson-Delaunay triangular cell and typical devices are derived. By using the theory of stochastic geometry and the obtained PDFs, the closed-form expressions of the wireless power coverage probability are obtained for three typical locations of the devices. As the wireless power coverage probability expressions involve the extended generalized multivariate MeijerG function (EGMMGF), a new implementation enabling numerical calculation of the EGMMGF is also proposed. The impacts of the main network parameters on the performance of the proposed framework are analyzed. In particular, comparative results show the significant gains that can be achieved in the wireless power coverage when multiple access points participate in the wireless power transfer or when the density of the network’s access points is increased, as compared to the non-cooperative scheme. [ABSTRACT FROM AUTHOR]

The emergence of infectious disease COVID-19 has challenged and changed the world in an unprecedented manner. The integration of wireless networks with edge computing (namely wireless edge networks) brings opportunities to address this crisis. In this paper, we aim to investigate the prediction of the infectious probability and propose precautionary measures against COVID-19 with the assistance of wireless edge networks. Due to the availability of the recorded detention time and the density of individuals within a wireless edge network, we propose a stochastic geometry-based method to analyze the infectious probability of individuals. The proposed method can well keep the privacy of individuals in the system since it does not require to know the location or trajectory of each individual. Moreover, we also consider three types of mobility models and the static model of individuals. Numerical results show that analytical results well match with simulation results, thereby validating the accuracy of the proposed model. Moreover, numerical results also offer many insightful implications. Thereafter, we also offer a number of countermeasures against the spread of COVID-19 based on wireless edge networks. This study lays the foundation toward predicting the infectious risk in realistic environment and points out directions in mitigating the spread of infectious diseases with the aid of wireless edge networks. [ABSTRACT FROM AUTHOR]

This letter explores key parameters of a massive MIMO system and their impact on energy efficiency at transmission. In particular, the effect of the digital to analog converter resolution and peak to average power ratio reduction techniques are addressed, in the context of practical user location distributions for both line and non line of sight channels. Results show interesting design trade-offs, and highlight the relevance of an accurate model for the user locations for the correct evaluation of the achievable performance. [ABSTRACT FROM AUTHOR]

This letter characterizes the contact angle distribution based on the condition that the relay low earth orbit (LEO) satellite is in the communication range of both the ground transmitter and the ground receiver. As one of the core distributions in stochastic geometry-based routing analysis, the analytical expression of the Cumulative Distribution Function (CDF) of the conditional contact angle is derived. Furthermore, the conditional contact angle is applied to analyze the inaccessibility of common satellites between the ground transmitter and receiver. Finally, with the help of the conditional contact angle, coverage probability and achievable data rate in LEO satellite-relayed transmission are studied. [ABSTRACT FROM AUTHOR]

Existing cellular network is designed mainly for terrestrial users (TUs) with down-tilted antennas, which couldn’t provide efficient 3D coverage for UAV users. This letter proposes up-tilted antenna model to provide 3D seamless coverage for cellular-connected UAVs, and derives coverage probability for both aerial users (AUs) and TUs via stochastic geometry, where the mutual interference between up-tilted and down-tilted antennas is characterized. Specifically, practical antenna model with tunable half power beamwidth $\theta _{k}$ is adopted and power constraint between up-tilted and down-tilted antenna is considered by modelling power allocation parameter $\alpha $ , where the interference Laplace transform is rederived considering the mutual interference. In addition, the theoretical analysis is based on semi-closed expression of coverage probability, which can be used to explore the impact of various system parameters. Numerical results show that when 10% of the power is allocated to up-tilted antenna ($\alpha =0.9$), coverage probability of AUs can be significantly increased by 192%, while coverage probability of TUs reduced by less than 1%, compared with only down-tilted antenna. [ABSTRACT FROM AUTHOR]

In this article, the routing in massive low earth orbit (LEO) satellite networks is studied. When the satellite-to-satellite communication distance is limited, we choose different relay satellites to minimize the latency in a constellation at a constant altitude. First, the global optimum solution is obtained in the ideal scenario when there are available satellites at all the ideal locations. Next, we propose a nearest neighbor search algorithm for realistic (nonideal) scenarios with a limited number of satellites. The proposed algorithm can approach the global optimum solution under an ideal scenario through a finite number of iterations and a tiny range of searches. Compared with other routing strategies, the proposed algorithm shows significant advantages in terms of latency. Furthermore, we provide two approximation techniques that can give tight lower and upper bounds for the latency of the proposed algorithm, respectively. Finally, the relationships between latency and constellation height, satellites' number, and communication distance are investigated. [ABSTRACT FROM AUTHOR]

This paper proposes a cascade blockage model for analyzing the vision that a user has of a wireless network. This model, inspired by the classical multiplicative cascade models, has a radial structure meant to analyze blockages seen by the receiver at the origin in different angular sectors. The main novelty is that it is based on the geometry of obstacles and takes the joint blockage phenomenon into account. We show on a couple of simple instances that the Laplace transforms of total interference satisfies a functional equation that can be solved efficiently by an iterative scheme. This is used to analyze the coverage probability of the receiver and the effect of blockage correlation and penetration loss in both dense and sparse blockage environments. Furthermore, this model is used to investigate the effect of blockage correlation on user beamforming techniques. Another functional equation and its associated iterative algorithm are proposed to derive the coverage performance of the best beam selection in this context. In addition, the conditional coverage probability is also derived to evaluate the effect of beam switching. The results not only show that beam selection is quite efficient for multi-beam terminals, but also show how the correlation brought by blockages can be leveraged to accelerate beam sweeping and pairing. [ABSTRACT FROM AUTHOR]

We propose using Carrier Sensing (CS) for distributed interference management in millimeter-wave (mmWave) cellular networks where spectrum is shared by multiple operators that do not coordinate among themselves. In addition, even the base station sites can be shared by the operators. We describe important challenges in using traditional CS in this setting and propose enhanced CS protocols to address these challenges. Using stochastic geometry, we develop a general framework for downlink coverage probability analysis of our shared mmWave network in the presence of CS and derive the downlink coverage probability expressions for several CS protocols. Our work is the first to investigate and analyze (using stochastic geometry) CS for mmWave networks with spectrum and BS sites shared among non-coordinating operators. We evaluate the downlink coverage probability of our shared mmWave network using simulations as well as numerical examples based on our analysis. Our evaluations show that our proposed approach leads to an improvement in coverage probability, compared to the coverage probability with no CS, for higher values of signal-to-interference and noise ratio (SINR). Interestingly, our evaluations also reveal that for lower values of SINR, not using any CS is the best strategy in terms of the downlink coverage probability. [ABSTRACT FROM AUTHOR]

Visible light communication (VLC) has recently emerged as an affordable and scalable technology supporting very high data rates for short range vehicle-to-vehicle (V2V) communication. In this work, we advocate the use of vehicular-VLC (V-VLC) for basic safety messages (BSMs) dissemination in lieu of conventional vehicular radio frequency (V-RF) communication in road intersection applications, where the reception performance is affected by interference from the concurrent transmissions of other vehicles. We make use of stochastic geometry to characterize the interference from the same lane as well as the perpendicular lane for various network configurations, i.e., standalone V-VLC, stand-alone V-RF and hybrid V-VLC/V-RF network. Specifically, by modelling the interfering vehicles’ locations as a spatial Poisson point process (PPP), we are able to capture a static two-dimensional road geometry as well as the impact of interference due to vehicles clustering in the vicinity of road intersection in terms of outage probability and throughput. In addition to above, the performance of spatial ALOHA and carrier sense multiple access with collision avoidance medium access control (CSMA/CA MAC) protocol for standalone V-VLC, standalone V-RF and hybrid V-VLC/V-RF network configuration for relaying BSMs at road intersection is also compared. The performance metrics such as delay outage rate (DOR) and information outage rate (IOR) are utilized to investigate the impact of latency associated with various network configurations. Our numerical results reveal that our proposed hybrid V-VLC/V-RF leads to significant improvement in terms of outage performance, throughput and latency as compared to stand-alone V-VLC or stand-alone V-RF network. [ABSTRACT FROM AUTHOR]

This letter investigates the accuracy of recently proposed stochastic geometry-based modeling of low earth orbit (LEO) satellite networks. In particular, we use the Wasserstein Distance-inspired method to analyze the distances between different models, including Fibonacci lattice and orbit models. We propose an algorithm to calculate the distance between the generated point sets. Next, we test the algorithm’s performance and analyze the distance between the stochastic geometry model and other more widely acceptable models using numerical results. [ABSTRACT FROM AUTHOR]

This article proposes a one-tier ultra-dense cellular network framework based on the characteristics of directional beamforming to explore the downlink signal-to-interference ratio (SIR) performance. The features of the proposed cellular network include: small base stations (SBSs) are equipped with directional antennas; the beam boresight directions of antennas are adaptively adjusted with the locations of users on the two-dimensional horizontal plane while the boresight directions are perfectly aligned with their associated users. In addition, an angle fading model, which follows from the exponential distribution, is developed to simulate the signals attenuation of interference links. The angle fading of the interference signals depends on the angle offset between the locations of users and the beam boresight directions of their interfering SBSs. With the assistance of stochastic geometry, the analytical expressions of coverage probability and average ergodic rate are derived by combining with the probability density function of angle offset variable. Then, the meta distribution of SIR is obtained to capture the performance changes of individual links for users. The numerical results indicate that the performance advantages of the proposed directional network obviously exceed that of the conventional isotropic antennas case. Monte-Carlo simulations validate the correctness of numerical results. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) have emerged as a promising technology for millimeter wave (mmWave) networks. In this paper, we utilize tools from stochastic geometry to study the performance of a RIS-assisted mmWave cellular network. Specifically, the locations of the base stations (BSs) and the midpoints of the blockage are modeled as two independent Poisson point processes (PPPs), where the blockages are modeled by a Boolean model and a fraction of the blockages are coated with RISs. The particular characteristics of mmWave communications, i.e., directional beamforming and different path loss laws for line-of-sight (LOS) and non-line-of-sight (NLOS) propagation, are incorporated into our analysis. We derive analytical expressions for the success probability and the area spectral efficiency. The success probability under the special case where the blockage parameter is sufficiently small is also derived. Numerical results demonstrate that better coverage performance and higher energy efficiency can be achieved by a large-scale deployment of RISs. In addition, the tradeoff between the BS and RIS densities is investigated and the results show that the RISs can indeed enable the traditional networks to improve the success probability, especially for the cell-edge region, with limited power consumption. [ABSTRACT FROM AUTHOR]

The reconfigurable intelligent surface (RIS) is a promising technology that is anticipated to enable high spectrum and energy efficiencies in future wireless communication networks. This paper investigates optimum location-based RIS selection policies in RIS-aided wireless networks to maximize the end-to-end signal-to-noise ratio for product-scaling and sum-scaling path-loss models where the received power scales with the product and sum of the transmitter-to-RIS and RIS-to-receiver distances, respectively. These scaling laws cover the important cases of end-to-end path-loss models in RIS-aided wireless systems. The random locations of all available RISs are modeled as a Poisson point process. To quantify the network performance, the outage probabilities and average rates attained by the proposed RIS selection policies are evaluated by deriving the distance distribution of the chosen RIS node as per the selection policies for both product-scaling and sum-scaling path-loss models. We also propose a limited-feedback RIS selection framework to achieve distributed network operation. The outage probabilities and average rates obtained by the limited-feedback RIS selection policies are derived for both path-loss models as well. The numerical results show notable performance gains obtained by the proposed RIS selection policies. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper comprehensively studies the physical layer security in frequency division duplex multi-antenna cellular systems, where the multi-antenna base stations (BSs), legitimate users (LUs), and eavesdroppers are all randomly located. Each BS employs artificial-noise (AN)-aided multi-user linear beamforming with limited channel state information feedback. Based on the stochastic geometry theory, we first derive an analytical expression of a lower bound on the ergodic secrecy rate (ESR) of the typical LU without assuming asymptotes for any system parameter. We then develop a tight closed-form approximation on the optimal number of feedback bits to maximize a lower bound on the per-user net ESR, which takes into consideration the cost of uplink spectral efficiency for limited feedback. Moreover, the power allocation coefficient between message-bearing signals and AN can be optimized by using a bisection search method. Our main finding is that, the optimum number of feedback bits scales linearly with the path-loss exponent and the number of antennas, and scales logarithmically with the channel coherence time. The derived analytical results can also provide system-level insights into the ESR performance of the multi-antenna random cellular networks with limited feedback and the optimal system design. Numerical results are also presented to verify the obtained results. [ABSTRACT FROM AUTHOR]

Future smart grids represent interdependent cyber-physical systems that involve multiple interactions between a power grid and a communication network. Such a mutual dependence increases the risk of large-scale cascading failures. Thus, it is important to conduct a joint vulnerability analysis. Unfortunately, existing works failed to identify the combination of power nodes and communication nodes that present the greatest damage impact. In this article, we first present a model that captures the interdependence between the two subsystems using stochastic geometry; then, we conduct a joint vulnerability analysis. We propose an attack strategy that targets the most influential nodes in both subsystems. We show that, based on six joint targeted nodes, this strategy presents a comparable and, in some cases, larger damage impact compared to the traditional exhaustive search attack and with very low complexity. Our investigations reveal that 1) the proposed joint attack strategy presents a large damage impact at a significantly small simulation runtime and 2) attacking the most influential communication nodes solely or the most influential power nodes solely achieves a comparable damage impact to that of the proposed joint attack. [ABSTRACT FROM AUTHOR]

Cooperative vehicle safety (CVS) systems have been receiving significant attention as key enablers of important intelligent transportation system (ITS) applications, such as cooperative collision warning, emergency braking, and auto driving. In CVS systems, vehicles periodically broadcast short packets that include various types of vehicular information, e.g., position and speed. In this paper, we propose an optimization method for the broadcast rate in vehicle-to-vehicle (V2V) broadcast communications at an intersection based on theoretical analysis. We consider a model in which the locations of vehicles are modeled separately as queuing, and running segments and derive key performance metrics of V2V broadcast communications through a stochastic geometry approach. We develop closed-form approximate formulas for the theoretical expressions because they are mathematically intractable. Based on approximate analysis, we optimize the broadcast rate such that the interference at an intersection is mitigated and the overall performance of V2V communications is maximized. Because of the closed-form approximation, the optimal rate can be used as a guideline for a real-time control-method, which cannot be achieved through time-consuming simulations. We evaluate our method through numerical examples and demonstrate its effectiveness. [ABSTRACT FROM AUTHOR]

Traffic safety at road intersections can be enhanced by improving opportunistic exchange of safety messages between vehicles. In urban intersection scenario, obstacles such as buildings and road side installations/signboards block the line-of-sight communication between vehicles. In order to enhance the reliability of communication link, the existing vehicular solution utilizes relay placement at road intersection. However, as the vehicular density increases, the existing vehicular-radio frequency (V-RF) communication with relaying tends to suffer from higher interference, lower packet reception rate, and longer communication delays due to channel congestion. In contrast to the existing solutions, we propose to use practical deployment strategies namely hybrid vehicular-visible light communication (V-VLC)/V-RF with relaying and reconfigurable intelligent surface (RIS) aided V-RF solutions to improve the communication range for urban vehicle-to-vehicle (V2V) communication. We present stochastic geometry based analytical framework to analyze the performance of proposed solutions in terms of outage probability, throughput and delay outage rate (DOR). Numerical results illustrate that the proposed solutions can achieve considerable performance improvement in outage, throughput while ensuring low latency as compared to conventional V-RF with relaying. These deployment strategies may also serve as a preferred alternative for Intelligent Transportation System (ITS) to meet ultra-high reliable and ultra-low latency communication for beyond 5 G (B5G) vehicular networks. [ABSTRACT FROM AUTHOR]

The recent advances and unprecedented ubiquity of computation-intensive applications such as virtual reality and mobile augmented reality force new approaches to handle the accompanying challenges. Ultra-Dense Network (UDN) as a leading direction in 5G and beyond offers an opportunistic degree of freedom to be exploited where a massive number of low-power and low-cost Small Cells (SCs) are deployed. In particular, integrating Edge Computing Servers (ECSs) within the SCs at the edge of the cellular network paves the way to tackle several challenges including the processing of computation-intensive tasks with low latency. To exploit the full potentials of UDNs and ECSs, we deploy multiple associations of SCs to the same user while partitioning and offloading its computation-intensive task to the integrated ECSs therein. In this regard, we formulate a mathematical framework using tools from stochastic geometry to evaluate the average processing delay per user. Extensive Monte-Carlo simulations are conducted to verify the accuracy of our analytical results under different system parameters. Results show the existence of an optimal order of multiple-association. In addition, we propose a novel offline task division approach which significantly reduces the overall delay. [ABSTRACT FROM AUTHOR]

The simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is capable of providing full-space coverage of smart radio environments. This work investigates STAR-RIS aided downlink non-orthogonal multiple access (NOMA) multi-cell networks, where the energy of incident signals at STAR-RISs is split into two portions for transmitting and reflecting. We first propose a fitting method to model the distribution of composite small-scale fading power as the tractable Gamma distribution. Then, a unified analytical framework based on stochastic geometry is provided to capture the random locations of RIS-RISs, base stations (BSs), and user equipments (UEs). Based on this framework, we derive the coverage probability and ergodic rate of both the typical UE and the connected UE. In particular, we obtain closed-form expressions of the coverage probability in interference-limited scenarios. We also deduce theoretical expressions in conventional RIS aided networks for comparison. The analytical results show that optimal energy splitting coefficients of STAR-RISs exist to simultaneously maximize the system coverage and ergodic rate. The numerical results demonstrate that: 1) STAR-RISs are able to meet different demands of UEs located on different sides; 2) STAR-RISs with appropriate energy splitting coefficients outperform conventional RISs in the coverage and the rate performance. [ABSTRACT FROM AUTHOR]

The terahertz (THz) waves with enormous bandwidth can be used along with the existing sub-6GHz and millimeter wave (mmWave) bands to achieve the ever evolving ecosystem of applications that need to be supported by the modern wireless networks. This paper investigates a user-centric dynamic base station (BS) clustering design for a hybrid network where THz, mmWave, and sub-6GHz BSs coexist. Invoking the proposed clustering model, the BS cooperation within each band is made possible by considering long term channel variations and all the surrounding BSs within a cluster with tunable size. A typical user is associated with the best BS cluster, from either a sub-6GHz, mmWave or THz tier based on the maximum signal-to-interference-plus-noise-ratio (SINR) criterion or the maximum rate criterion. Using tools from stochastic geometry, we assess the performance of the proposed user-centric hybrid system in terms of SINR and rate coverage performances, while accounting for: band specific propagation models, directional beamfroming, and BSs random locations. The accuracy of the analytical results is validated with Monte-Carlo simulations. The obtained results recognize a clear coverage/rate trade-off where a high fraction of THz BSs improves the rate significantly but may degrade the coverage performance. Thus, with carefully planned networks, enabling user-centric BS cooperation for hybrid wireless systems can achieve ultra-high rates while maintaining sufficient coverage in sixth-generation (6G) networks. [ABSTRACT FROM AUTHOR]