Coverage Probability Analysis Research Articles

Coverage Probability Analysis of a Double IRS Assisted SISO Communication System

Intelligent reflecting surface (IRS) improves wireless communication efficiency and coverage probability. Existing studies focus on IRS deployment but overlook optimal fading channels. This research aims to identify and analyze the most effective channel fading estimation for the double IRS system model. The coverage probability using two-IRS is derived under different fading channels like Rayleigh and Rician to find the optimal solution in a Single-Input-Single-Output (SISO) system. Additionally, a closed-form expression for the coverage probability using statistical channel state information is derived while assuming no direct path between the transmitter and receiver. The analytical results are validated through simulations. It offers valuable insights into the modeling and analysis of double IRS-assisted wireless communication systems.

Coverage Probability Analysis for Uplink/Downlink Decoupled Access in Heterogeneous Cellular Networks

Coverage Probability Analysis for Uplink/Downlink Decoupled Access in Heterogeneous Cellular Networks

Downlink Coverage Probability and Rate Analysis Based on Backhaul-Access Pair in Moving Networks

Downlink Coverage Probability and Rate Analysis Based on Backhaul-Access Pair in Moving Networks

Performance Analysis and Optimization of Worst Case User in CoMP Ultra Dense Networks

In the cellular system, the Worst Case User (WCU), whose distances to three nearest BSs are the similar, usually achieves the lowest performance. Improving user performance, especially the WCU, is a big problem for both network designers and operators. This paper works on the WCU in terms of coverage probability analysis by the stochastic geometry tool and data rate optimization with the transmission power constraint by the reinforcement learning technique under the Stretched Pathloss Model (SPLM). In analysis, only fast fading from the WCU to the serving Base Stations (BSs) is taken into the analysis to derive the lower bound coverage probability. Furthermore, the paper assumes that the Coordinated Multi-Point (CoMP) technique is only employed for the WCU to enhance its downlink signal and avoid the explosion of Intercell Interference (ICI). Through the analysis and simulation, the paper states that to improve the WCU performance under bad wireless environments, an increase in transmission power can be a possible solution. However, in good environments, the deployment of advanced techniques such as Joint Transmission (JT), Joint Scheduling (JS), and reinforcement learning is an suitable solution.

Scene- and pixel-level analysis of Landsat cloud coverage and image acquisition probability in South and Southeast Asia

Scene- and pixel-level analysis of Landsat cloud coverage and image acquisition probability in South and Southeast Asia

Coverage Probability Analysis of Amplify and Forward Based Multi-user Hybrid Satellite Terrestrial Relay Network

This article examines coverage probability for a multi-user hybrid satellite terrestrial relay network (HSTRN) with opportunistic user scheme. Better quality information are gathered via HSTRN-based networks for users on the ground. Simultaneous satellite signals are amplified by relays and relayed to terrestrial users with the highest instantaneous signal-to-noise ratio (SNR) on an individual channel. Analytically approximate coverage probability is derived for fixed and variable gain relaying. The multi-user relay network is analyzed under Nakagami-m fading, and Rician shadowed fading. We perform simulation and analytical validation to validate our study and compare the performance of fixed and variable gain relaying.

Modeling and Analysis of UAV-Assisted Mobile Network with Imperfect Beam Alignment

With the rapid development of emerging 5G and beyond (B5G), Unmanned Aerial Vehicles (UAVs) are increasingly important to improve the performance of dense cellular networks. As a conventional metric, coverage probability has been widely studied in communication systems due to the increasing density of users and complexity of the heterogeneous environment. In recent years, stochastic geometry has attracted more attention as a mathematical tool for modeling mobile network systems. In this paper, an analytical approach to the coverage probability analysis of UAV-assisted cellular networks with imperfect beam alignment has been proposed. An assumption was considered that all users are distributed according to Poisson Cluster Process (PCP) around base stations, in particular, Thomas Cluster Process (TCP). Using this model, the impact of beam alignment errors on the coverage probability was investigated. Initially, the Probability Density Function (PDF) of directional antenna gain between the user and its serving base station was obtained. Then, association probability with each tier was achieved. A tractable expression was derived for coverage probability in both Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) condition links. Numerical results demonstrated that at low UAVs altitude, beam alignment errors significantly degrade coverage performance. Moreover, for a small cluster size, alignment errors do not necessarily affect the coverage performance.

Uncoordinated Spectrum Sharing in Millimeter Wave Networks Using Carrier Sensing

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.

Coverage Probability Analysis of Passive Reflectors in Indoor Environments

Since millimeter wave (mmWave) and sub-terahertz bands are highly vulnerable to blockage and penetration loss effects, wireless coverage enhancement is one of the critical challenges in indoor mmWave deployments. In particular, when the line-of-sight (LoS) link is blocked, a strong non-LoS (NLoS) path can provide a stable link quality. One of the efficient ways to improve the NLoS link is the use of strategically placed passive reflectors. In this letter, we study the indoor coverage improvement by using a transparent passive reflector attached on a wall. We consider an indoor open-door scenario, where the LoS link is blocked by the walls for receivers inside the room, and the coverage can only be achieved via an NLoS link through a passive reflector. We analytically derive closed-form equations of the reflection visibility probability and the coverage probability. By simulation and analytical results, we show the coverage dependency on the location and size of the reflector.

Coverage Analysis of Vehicular Safety Messages-Prioritized C-V2X Communications

For safety applications in intelligent transportation system (ITS), it is essential for vehicles and pedestrians to decode the safety messages from nearby moving vehicles through direct sidelink in the presence of cellular link. This article presents the coverage probability analysis of vehicular safety messages-prioritized cellular vehicle-to-everything (C-V2X) communications. We model the spatial layout of macro base stations (MBSs) and vehicles as a 2-D Poisson point process (PPP) and a Poisson line Cox point process (PLCPP). Since vehicles can be regarded as mobile base stations, we assume that the MBSs and vehicles share the same spectrum. In a similar way, we consider two kinds of users, i.e., planar users and linear users, which are also modeled by a 2-D PPP and a PLCPP, respectively. Using a stochastic geometry tool, we derive the signal-to-interference ratio (SIR)-based coverage probability of four links (i.e., downlink of planar user, sidelink of planar user, downlink of linear user, and sidelink of linear user) according to the vehicle-prioritized association scheme. We assume that the users are required to decode the vehicular safety messages if they are within a certain distance from vehicles. Then, we derive the conditioned coverage probability of four links to study their reliability. In addition, we explore the impacts of several key parameters on the coverage probability and provide some design insights.

Finite Point Processes in a Truncated Octahedron-Based 3D UAV Network

In this paper, stochastic geometry tools are utilized to analyze the performance of a wireless network with Unmanned Aerial Vehicles (UAVs). The evaluation is based on the concept of a truncated octahedron that is the fundamental three-dimensional (3D) shape that models the basic cell in an entirely aerial cellular structure with UAV nodes only. The spatial locations of the aerial users, are modeled as a 3D Binomial Point Process (BPP). Subsequently, stochastic geometry analysis in a reference truncated octahedron located at the origin is performed and exact expressions for the distances between aerial users, are derived. To this end, expressions for evaluating the volume of the regions of the 3D cell in which an aerial user may fall, are derived. Then, by defining the signal-to-interference-plus-noise (SINR) ratio at the reference UAV-base station (UAV-BS) receiver, a performance analysis in terms of coverage probability is conducted under two interference scenarios, i.e., a pure intra-cell interference and an intra- plus inter-cell interference case. As intermediate step in the coverage probability analysis, expressions for relevant distance distributions and the Laplace transform of the aggregate interference power distribution are derived. For the sake of completeness, coverage probability analysis under intra-cell interference is also performed and compared to a 3D cell modeled as a sphere. The analytical expressions are also compared to simulation results to validate the accuracy of the proposed framework and reveal valuable insights.

Stochastic geometry analysis of coverage probability in energy efficient dense heterogeneous network with sleep control mechanism

The upsurge of data traffic in the macrocell networks has led to the massive deployment of small cells (SCs) for load sharing. Though small cell power consumption is low individually, significant aggregate power consumption, together with the MBS transmission power that is exponentially increasing over its served user load, deteriorates the network energy efficiency (EE). Consequently, EE is seen as a critical requirement for wireless network design in future. The challenge of EE maximization in dense heterogeneous networks is investigated in this research through a strategic small cell sleeping technique. A heuristic method based on distance and load awareness strategy in which the small cells with fewer users near the macrocell will be put into sleep mode. User equipments (UEs) under the service of the sleep small cells will be offloaded to the MBS. A dense heterogeneous network is considered with overlapped small cell coverage regions. All the edge area SCs will be kept ON to avoid QoS degradation. Simulation analysis on the stochastic geometry model indicates that the proposed sleep strategy significantly improves the network EE than the prevailing sleep control strategies while assuring seamless, efficient coverage in the sleep cell areas.

Coverage Probability Analysis for Device-to-Device Communication Underlaying Cellular Networks

As one of the most promising techniques in wireless communication systems, device-to-device (D2D) has drawn much attention due to its superior performance. Meanwhile, the interference between cellular users and D2D users is still a challenging problem and needs to be mitigated effectively. A large number of simulation experiments for D2D communications have been studied to reduce the impact of the interference in the existing literature. However, theoretical research is still lacking. Thus, in this paper, we use stochastic geometry to evaluate the uplink performance of users by considering the impact of the previous moment on the next moment, which captures the effect of temporal and the spatial correlation of the interference in D2D communication underlaying cellular networks. Using a Poisson point process to model locations of D2D users, we derive an analytic expression for conditional probability and unconditional probability of link success, and prove that the probability of link success is temporally correlated. Moreover, we provide a theoretical framework for interference mitigation in D2D underlaying cellular networks.

Quantile regression as a generic approach for estimating uncertainty of digital soil maps produced from machine-learning

Digital soil mapping (DSM) techniques have provided soil information that has revolutionized soil management across multiple spatial extents and scales. DSM practitioners have been increasingly reliant on machine-learning (ML) techniques; yet, methods to generate uncertainty maps from ML predictions are limited. To address this issue, this study integrates ML-based DSM with quantile regression (QR) in a methodological framework for estimating uncertainty. We test the proposed framework on two case study areas in Canada: (1) a dry-forest ecosystem in the Kamloops region of British Columbia, Canada; and (2) an agricultural system in the Ottawa region of Ontario, Canada. Four ML techniques (Random Forest, Cubist decision tree, k-nearest neighbors, and support vector machine) were compared using repeated cross-validation. Maps showing the 90% prediction interval (PI) were produced. Regardless of the case study, ML approach, and predicted soil variable, the uncertainty estimates were reliable and stable, according to the PI coverage probability analysis.

Coverage Analysis for 3D Terahertz Communication Systems

We conduct novel coverage probability analysis of downlink transmission in a three-dimensional (3D) terahertz (THz) communication (THzCom) system. In this system, we address the unique propagation properties in THz band, e.g., absorption loss, super-narrow directional beams, and high vulnerability towards blockage, which are fundamentally different from those at lower frequencies. Different from existing studies, we characterize the performance while considering the effect of 3D directional antennas at both access points (APs) and user equipments (UEs), and the joint impact of the blockage caused by the user itself, moving humans, and wall blockers in a 3D environment. Under such consideration, we develop a tractable analytical framework to derive a new expression for the coverage probability by examining the regions where dominant interferers (i.e., those can cause outage by themselves) can exist, and the average number of interferers existing in these regions. Aided by numerical results, we validate our analysis and reveal that ignoring the impact of the vertical heights of THz devices in the analysis leads to a substantial underestimation of the coverage probability. We also show that it is more worthwhile to increase the antenna directivity at the APs than at the UEs, to produce a more reliable THzCom system.

Coverage Modeling and Analysis for Outdoor THz Networks With Blockage and Molecular Absorption

Terahertz (THz) communication has been envisioned as a key technology for providing ultra-wide bandwidth and high-speed data transmission in future networks. However, THz band signal suffers from frequency-dependent path-loss, molecular absorption and line-of-sight (LoS) blockage. Thus, coverage modelling for THz networks has essential difference from low-band networks. In this letter, considering blockage, directional antennas and molecular absorption, we develop an analytical model for coverage probability analysis in outdoor THz networks based on stochastic geometry. Accuracy of the proposed model is validated through Monte-Carlo simulations. Based on the proposed model, we further uncover the impact of nodes density, transmission distance and atmosphere on network coverage and available transmission bandwidth. Numerical results reveal that denser nodes, longer transmission distance, lower latitude and more humid seasons result in lower coverage probability and narrower transmission windows.

Performance Analysis of Millimeter Wave SWIPT System Using Ginibre Point Process

This paper deals with the coverage probability analysis of mmWave simultaneous wireless information and power transfer (SWIPT) system using stochastic geometry. mmWaves are higher frequency waves results in dense deployment of base stations (BS) leading to a higher data rate. Stochastic geometry provides a mathematical model to the randomly distributed nodes in the network. The Poisson point process (PPP) is the most analytically tractable and widely used model for the location of BSs, but it fails to capture the underlying separation between the BSs of cellular networks. Ginibre point process (GPP) model is used for the repulsion between the two nodes and provides a realistic model compared to PPP. In this paper, mmWave interfering base stations are considered to be GPP for deriving the coverage probability analysis. The proposed model considers the interfering base stations for analyzing the coverage probability. The closed form expression for the coverage probability is derived and is analyzed. The theoretical results are validated through simulation results.

SNR Coverage Probability Analysis of RIS-Aided Communication Systems

The reconfigurable intelligent surface (RIS) technique has received many interests, thanks to its advantages of low cost, easy deployment, and high controllability. It is acknowledged that the RIS can significantly improve the quality of signal transmission, especially in the line-of-sight-blocked scenarios. Therefore, it is critical to analyze the corresponding signal-to-noise ratio (SNR) coverage probability of RIS-aided communication systems. In this correspondence, we consider many practical issues to analyze the SNR coverage probability. We employ the realistic path loss model and Rayleigh fading model as large-scale and small-scale channel models, respectively. Meanwhile, we take the number and size of the RIS elements, as well as the placement of the RIS plane into considerations. We first derive the exact closed-form SNR coverage probability for a single element. Afterward, with the moment matching method, a highly accurate approximation of SNR coverage probability is formulated as the ratio of the upper incomplete Gamma function and Gamma function, allowing an arbitrary number of elements in the RIS. Finally, we comprehensively evaluate the impacts of essential factors on the SNR coverage probability, such as the number and size of the element, the coefficients of fading channel, and the angles of incidence and RIS plane. Overall, this work provides a succinct and general expression of SNR coverage probability, which can be helpful in the performance evaluation and practical implementation of the RIS.

On Distance Statistics of First Arriving Multi-Paths in Indoor mm-Wave Communications

This paper presents a mathematical framework to evaluate distance statistics of first arriving multi-path components at millimeter wave (mm-Wave) frequencies in a typical indoor environment. The proposed modeling approach is based on a numerically tractable channel model that accounts for the line-of-sight (LoS) component and first-order reflection components from surrounding walls. Based on the derived statistics, an approximation for coverage probability of mm-Wave indoor wireless local area networks (WLAN)s is obtained. Further, the coverage probability for an access point (AP) to user node link is determined after accounting for blockage of LoS component and optimal antenna beamforming in the modeling framework. The analysis of coverage probability provides useful insights which can be applied to plan optimum AP location layout in a typical mm-Wave indoor WLAN.

The analysis of coverage probability, ASE and EE in heterogeneous ultra-dense networks with power control

The ultra-dense network is a promising technology to increase the network capacity in the forthcoming fifth-generation (5G) mobile communication networks by deploying lots of low power Small Base Stations (SBSs) which overlap with Macro Base Stations (MBSs). The interference and energy consumption increase rapidly with the number of SBSs although each SBS transmits with small power. In this paper, we model a downlink heterogeneous ultra-dense network where a lot of SBSs are randomly deployed with MBSs based on the Poisson point process. We derive the coverage probability and its variance, and analyze the area spectral efficiency and energy efficiency of the network considering three Fractional Power Control (FPC) strategies. The numerical results and Monte Carlo simulation results show that power control can mitigate the interference and balance the performances of inner-user and edge-user equipments. Especially, a great improvement of energy efficiency is archived with a little loss of area spectral efficiency when FPC is adopted. Finally, we analyze the effect of base stations’ (BSs’) sleeping on the performance of the network when it is partially loaded.