Base Station Configuration Research Articles

Integration of attention mechanism and CNN-BiGRU for TDOA/FDOA collaborative mobile underwater multi-scene localization algorithm

The aim of this study is to address the issue of TDOA/FDOA measurement accuracy in complex underwater environments, which is affected by multipath effects and variations in water sound velocity induced by the challenging nature of the underwater environment. To this end, a novel cooperative localisation algorithm has been developed, integrating the attention mechanism and convolutional neural network-bidirectional gated recurrent unit (CNN-BiGRU) with TDOA/FDOA and two-step weighted least squares (ImTSWLS). This algorithm is designed to enhance the accuracy of TDOA/FDOA measurements in complex underwater environments. The algorithm initially makes use of the considerable capacity of a convolutional neural network (CNN) to extract profound spatial and frequency domain characteristics from multimodal data. These features are of paramount importance for the characterisation of underwater signal propagation, particularly in complex environments. Subsequently, through the use of a bidirectional gated recurrent unit (BiGRU), the algorithm is able to effectively capture long-term dependencies in time series data. This enables a more comprehensive analysis and understanding of the changing pattern of signals over time. Furthermore, the incorporation of an attention mechanism within the algorithm enables the model to focus more on the signal features that have a significant impact on localisation, while simultaneously suppressing the interference of extraneous information. This further enhances the efficiency of identifying and utilising the key signal features. ImTSWLS is employed to resolve the position and velocity data following the acquisition of the predicted TDOA/FDOA, thereby enabling the accurate estimation of the position and velocity of the mobile radiation source. The algorithm was subjected to a series of tests in a variety of simulated underwater environments, including different sea states, target motion speeds and base station configurations. The experimental results demonstrate that the algorithm exhibits a deviation of only 2.88 m/s in velocity estimation and 2.58 m in position estimation when the noise level is 20 dB. The algorithm presented in this paper demonstrates superior performance in both position and velocity estimation compared to other algorithms.

Short‐term power forecasting method for 5G photovoltaic base stations on non‐sunny days based on SDN‐integrated INGO‐BP and RGAN

AbstractIn response to the suboptimal efficiency observed in the network configuration and administration of 5G photovoltaic base stations (PVBSs), as well as the inherent limitations in accurately forecasting photovoltaic power during inclement weather conditions, this research article introduces a concise and effective method for short‐term power prediction of PVBSs when subjected to non‐sunny weather conditions, leveraging the paradigm of software defined networking. This method ingeniously amalgamates the improved Northern Goshawk optimized back propagation neural network (INGO‐BP) and recurrent generative adversarial networks (RGAN). The investigation commences by delineating a comprehensive PVBS system framework underpinned by SDN principles. Subsequently, it employs the Pearson correlation coefficient technique and principal component analysis for the judicious selection of pertinent features from the PVBS photovoltaic dataset, thereby ameliorating the issue of multicollinearity within the predictive model. To culminate the research endeavour, the INGO algorithm is enlisted to optimize the weightings and bias parameters of the BP neural network, while RGAN is harnessed for the acquisition of distinctive distribution patterns in photovoltaic data across diverse meteorological conditions. This augmentation enhances the model's capacity to discern the intricate long‐term mappings between photovoltaic power and meteorological data. The empirical findings substantiate the elevated accuracy of the INGO‐BP prediction model across sunny, cloudy, and rainy weather conditions, with a discernible enhancement in predictive accuracy for PVBS performance under non‐sunny weather conditions facilitated by data augmentation via RGAN.

Optimization of Communication Base Station Battery Configuration Considering Demand Transfer and Sleep Mechanism under Uncertain Interruption Duration

In the communication power supply field, base station interruptions may occur due to sudden natural disasters or unstable power supplies. This work studies the optimization of battery resource configurations to cope with the duration uncertainty of base station interruption. We mainly consider the demand transfer and sleep mechanism of the base station and establish a two-stage stochastic programming model to minimize battery configuration costs and operational costs. To transform the uncertainty expression in the first stage into a deterministic model, we design the K-Means-SAA algorithm to accelerate problem-solving and to compare it with the SAA algorithm. The case study results indicate that the proposed two-stage stochastic programming model can save 17.02% of the total cost compared to the expected value model. The proposed demand transfer and sleep mechanism can reduce the total cost by 41.92% compared to no mechanism. The results of numerical experiments and sensitivity analysis also verify the superiority of the designed algorithm in terms of running efficiency and solving time. Therefore, the model and algorithm proposed in this work provide valuable application guidance for large-scale base station configuration optimization of battery resources to cope with interruptions in practical scenarios.

Performance Analysis of Connection Establishment Procedure Under Beamforming in 5G NR Networks

High demand for reliability, low latency, seamless connectivity lead to the 5 G era. 5 G cellular networks employ a random access based preamble transmission procedure for the initial locking of User Equipment (UEs) to a base station (gNB) and uplink resource scheduling. It is of utmost importance that we evaluate the factors that aid and those that limit the random access procedure in achieving its envisaged goal. In this paper, we develop an analytical model for random access procedure for connection establishment in 5 G when beamforming is employed. The random access medium is modelled as a multi-channel slotted Aloha system. We use an equilibrium point analysis framework to derive the performance metrics namely, the rate at which UEs can lock on to a gNB and the average and variance of the time taken by a new UE to establish connection with the base station. We analyse the impact of the retransmission limit and the number of available preambles for random access on the performance of connection establishment of a UE. Our analysis brings out the importance of the choice of base station configurations with respect to the user demographics of a 5 G NR cell.

Analyses of ping-pong handovers in real 4G telecommunication networks

The last decade has been characterized by a rapid increase in the usage of mobile communications. One of the main aspects of mobile communications is mobility. This means that mobile phones have to switch between base station cells in order to support the uninterrupted usage of all available services within the area of the mobile network coverage. The process of switching user devices between base station cells is called a handover. Accordingly, base stations are optimized to serve mobile phones with certain moving velocities based on an area and user characteristics to better handle handovers. However, issues appear when a mobile phone starts switching rapidly between two different cells in a short period of time, referred to as ping-pong handover. These occurrences cause negative effects in terms of increased telecom operators signaling overhead and user dissatisfaction. The 3rd Generation Partnership Project (3GPP) defines a metric called ping-pong rate in order to analyze what is the most adequate base station configuration concerning different user velocities and how well base stations handle handovers. The ping-pong rate is defined as a share of ping-pong handovers in total handovers, without taking into consideration the conditions under which they occur. In this paper, the conditions under which ping-pong handovers occur are analyzed by using live, non-simulated data. Findings show that the handovers under different conditions have different probabilities to become ping-pong handovers. Furthermore, these findings are utilized for defining a new empiric metric used for evaluating the handover handling of pre-configured base stations. Consequently, the novel empiric metric provides better insights into the base station handling of handovers than the ping-pong rate defined by 3GPP.

Positioning with GNSS and 5G: Analysis of Geometric Accuracy in Urban Scenarios.

GNSS positioning in urban scenarios suffers for the scarce visibility of satellites. Integration with 5G services for positioning could improve this situation. In this paper, the digital surface models (DSMs) relevant to different urban scenarios, namely residential streets and urban canyons, are simulated around one observer in northern Italy (Milano) for one day of the year chosen as an example. The time series of the number of in-view GNSS satellites, their geometry and the derived quality indexes (position dilution of precision (PDOP)) are computed and analyzed. As expected, in urban canyons, a significant number of epochs does not provide four satellites within view, and many more epochs present really mediocre PDOPs. In residential streets, the situation is always quite fair. Different geometric configurations of 5G base stations are simulated around the observer. The availability of 5G times of arrival (ToAs) and their differences (TDoAs) is hypothesized, and the integration of these observations with GNSS pseudoranges is analyzed, again in terms of the PDOPs. In residential streets, 5G availability improves the positioning. In urban canyons, the optimal configuration of 5G base stations (five base stations around the observer) completely solves the positioning problem for all the epochs of the day. Less favorable configurations (four and three base stations) improve epochs with poor PDOPs in a GNSS-only configuration. They allow the positioning of epochs with few satellites but cannot completely replace the GNSS.

Resilience of long chain under disruption

Despite being sparse and therefore economical, long chains are repeatedly observed to be almost as effective as fully flexible manufacturing systems in dealing with demand uncertainty. Motivated by a string of events that have globally impacted supply chains, our objective is to study the resiliency of long chains when there is a positive probability of plant disruptions. To achieve this, we first investigate the connection between long and open chains. Then, we propose a simple greedy algorithm for characterizing the performance of an open chain for a given scenario of plant disruptions and product demands. When such information is uncertain, we develop a pair of Markov chains for computing the load of the open chain’s dedicated and flexible arcs, respectively, which in turn enables us to have an elaborate look at the long chain’s expected performance. We further argue that the long chain is indeed a viable alternative of the full flexibility system that provides a significant improvement over the dedicated design when the demand distribution is symmetric or right-skewed and that all three designs are similarly competitive otherwise. Finally, we report a case study on a flexible configuration of cellular base stations in the People’s Republic of China.

5G/5G+ network management employing AI-based continuous deployment

Purpose:The paper proposes a novel concept of deployment process dedicated to continuous development, integration, testing, and upgrading the software-defined AI/ML-based functionalities in 5G/5G+ cellular networks, reliable and minimally invasive for network infrastructure, users, and service quality, automating DevOps and performance management towards the zero-touch networks. The idea is demonstrated by the continuous deployment framework, where a virtual cluster of representative cellular network resources coexists synchronously with the operator network serving the thousands-to-millions of end-users. Performance KPIs measured in this twinning subnetwork is the time series exhibiting the complex interrelations governing a temporal state of the whole system. Methods:One of the crucial problems is the detection when the changes of configuration of individual base station impacted its performance, which was realized by change points identification using an enhanced-PELT (e-PELT) algorithm. This yielded a sequence of complex data patterns (between successive change points) into sections of unique waveforms corresponding to stable network conditions. The e-PELT scheme includes a peak removal and an ACPO module for automatic penalty search. Results:e-PELT algorithm, validated against experimental data in comparative studies, outperforms the AMOC, Binary Segmentation, and BOCPD schemes, increasing the F1-score by more than 12% and the Accuracy by 10% over the PELT baseline. Conclusion:The results obtained in a CD cluster with fixed and automated penalty search show that e-PELT provides outstanding results, proving that the proposed approach can be successfully applied to analyze data sequences from different 5G network configurations. The concept of AI/ML-featured Continuous Deployment Framework dedicated to cellular networks can impact the development and integration of new telecommunication features, including possible extension for the role of standardized NWDAF module in customer networks, enhanced with the application of methodology outlined in the paper.

Energy-Efficient Resource Optimization for Massive MIMO Networks Considering Network Load

This paper investigates the resource optimization problem for a multi-cell massive multiple-input multiple-output (MIMO) network in which each base station (BS) is equipped with a large number of antennas and each base station (BS) adapts the number of antennas to the daily load profile (DLP). This paper takes into consideration user location distribution (ULD) variation and evaluates its impact on the energy efficiency of load adaptive massive MIMO system. ULD variation is modeled by dividing the cell into two coverage areas with different user densities: boundary focused (BF) and center focused (CF) ULD. All cells are assumed identical in terms of BS configurations, cell loading, and ULD variation and each BS is modeled as an M/G/m/m state dependent queue that can serve a maximum number of users at the peak load. Together with energy efficiency (EE) we analyzed deployment and spectrum efficiency in our adaptive massive MIMO system by evaluating the impact of cell size, available bandwidth, output power level of the BS, and maximum output power of the power amplifier (PA) at different cell loading. We also analyzed average energy consumption on an hourly basis per BS for the model proposed for data traffic in Europe and also the model proposed for business, residential, street, and highway areas.

Resiliency of Long Chains under Plant Disruptions

Despite being sparse and therefore economical, long chains are repeatedly observed to be almost as effective as fully flexible manufacturing systems in dealing with demand uncertainty. Motivated by a string of events that have globally impacted supply chains, our objective is to study the resiliency of long chains when there is a positive probability of plant disruptions. To achieve this, we first investigate the connection between long and open chains. Then, we propose a simple greedy algorithm for characterizing the performance of an open chain for a given scenario of plant disruptions and product demands. When such information is uncertain, we develop a pair of Markov chains for computing the load of the open chain’s dedicated and flexible arcs, respectively, which in turn enables us to have an elaborate look at the long chain’s expected performance. We further argue that the long chain is indeed a viable alternative of the full flexibility system that provides a significant improvement over the dedicated design when the demand distribution is symmetric or right-skewed and that all three designs are similarly competitive otherwise. Finally, we report a case study on a flexible configuration of cellular base stations in the People’s Republic of China.

Exploiting heterogeneity for cost efficient 5G base station deployment using meta‐heuristics

A key concern in the design of 5G is the radio access network, which is expected to be significantly denser and more advanced, with considerably higher infrastructure and power consumption cost than that of conventional mobile network standards. Novel algorithms/approaches for optimal planning of the radio access network are required for tackling the additional complexity of the problem of cost-efficient radio access planning in 5G, which cannot be properly handled by conventional approaches. This study proposes a novel optimisation framework for the cost-efficient deployment and configuration of 5G base stations. The main idea of the proposed optimisation framework is to exploit heterogeneity in three key 5G technologies, heterogeneous base station architecture, cell range extension and multiple-input–multiple-output spatial multiplexing, by jointly optimising their configurations during network design. In addition, the proposed optimisation framework includes generic steps for applying meta-heuristic algorithms to the problem, which are necessary to overcome the problem's complexity, especially for large problem instances. The authors’ results show that their novel optimisation framework improves the cost efficiency of the network planning both in terms of power and infrastructural cost to operators.

Full-duplex WDM-RoF system based on OFC with dual frequency microwave signal generation and wavelength reuse

Abstract A novel full-duplex wavelength division multiplexing radio-over-fiber (WDM-RoF) system based on optical frequency comb (OFC), which can generate dual frequency microwave signal simultaneously and realize wavelength reuse for uplink transmission, is proposed. In this proposal, OFC, which serves as the optical carriers of the WDM-RoF network, is performed by cascading two electro-absorption modulators (EAMs) and a frequency modulator (FM). The optical carriers are modulated by the radio frequency (RF) signal in LiNbO3 Mach-Zehnder modulator (LN-MZM) to produce multiple optical single sidebands (OSSB). The multiple OSSB signals are divided into multiple individual channels by AWG, and each channel contains two optical carriers and two corresponding +1 order sidebands. The first optical carrier of each channel is reflected by fiber bragg grating (FBG) and reused to provide the optical source for the uplink transmission in the base station (BS), which simplify the configuration of base station. Dual-frequency microwave signals are generated in the downlink by beating the remaining second optical carrier and two +1 order sidebands. In the simulation, 6 WDM channels each carrying 2.5 Gb/s downlink data have been up-converted to 15 GHz and 25 GHz microwave signals simultaneously, and 6 WDM channels each carrying 2.5 Gb/s uplink baseband data are sent to the central station. Both downlink and uplink transmission with less than 1 dB power penalty on average after 20 km SMF transmission. This full-duplex WDM-RoF system shows high spectral-efficiency, large communication capacity, simple cost-efficient configuration and good performance over long distance transmission.

Analysis of the Applicability of Dilution of Precision in the Base Station Configuration Optimization of Ultrawideband Indoor TDOA Positioning System

With the increasing demand for location awareness, indoor positioning has gradually become one of the research hotspots. In recent years the indoor positioning research field generally introduced dilution of precision (DOP) in the field of satellite navigation to the optimization of base station (BS) configuration, but in practice, the distribution of DOP and the distribution of errors is far from the same. This paper analyzes the applicability of DOP in the indoor time difference of arrival (TDOA) positioning systems from various aspects. Then, according to the ultrawideband (UWB) ranging error model, the TDOA time-difference measurement error model is derived and used as the BS configuration optimization metric. Finally, the experiments are conducted in 8 m $\ast ~8$ m $\ast ~3$ m small-scale scene and 100 m $\ast ~30$ m $\ast ~10$ m large-scale scene respectively to compare the positioning accuracy of the three BS configurations under different receiving signal-to-interference ratio (SIR). At the same time, the experiment is conducted in outdoor standard football field to compare the influence of multipath on the positioning accuracy of the three BS configurations under the conditions of two SIR. The experimental results show that the optimized BS configuration with DOP as the optimized target is not the best BS configuration, and the positioning accuracy is not as good as the commonly used cuboid 8-BS configuration in low SIR environment. It proves that DOP cannot be used as a decisive metric for the BS configuration optimization of UWB indoor positioning, but can be used as a reference index, and the optimized BS configuration with TDOA time-difference measurement error as the optimization target has higher positioning accuracy.

Digital Twin for Metasurface Reflector Management in 6G Terahertz Communications

The performance demands from data-intensive applications, such as multimedia streaming, as well as the growing number of devices connecting to the Internet, will increase the need for higher capacity wireless communication links. The research community has recently explored regions of the spectrum, including the Terahertz band (0.1 THz to 10 THz), that are underutilised for communications. THz frequencies come with a plethora of special challenges, one of which is the very narrow effective beam, thereby requiring a Line of Sight (LoS) between sender and receiver. Researchers have explored the use of reflectors that can redirect beams around blockages. In this paper, we propose a THz signal guidance system where a Digital Twin is used to model, predict and control the signal propagation characteristics of an indoor space. Our approach finds the best THz signal path from the base station to the mobile target via the tunable metamaterial walls, avoiding obstacles as needed, using geometric (ray tracing), path loss and Terahertz Potential Field (THzPF) models. With this knowledge, the digital twin guides the selection of antenna strips at a base station and the reflectors along the signal path. A top-view camera, with advanced image processing, provides context updates (obstacle and mobile target locations) to the digital twin. The image processing system also senses factors like water vapour concentration, and the material composition and surface roughness of obstacles. Such factors affect propagation strength, and the digital twin modifies the beam paths to adapt. Simulation results have shown the efficiency of our control system to maintain a reliable signal connection while minimising the use of antenna and reflector strips. Our system is the first proposal that maximises THz signal-to-noise ratio (SNR) through such a dynamic and robust control system, which integrates image processing of a room with base station configuration.

UWB Channel Characterization for Compact L-Shape Configurations for Body-Centric Positioning Applications

This letter presents an analysis on the body-centric channel parameter classification for various compact three-base-station L-shape configurations utilizing only a two-dimensional (2-D) plane for installation. Four different L-shape configurations ( xz / yz plane) are studied (facing-front/side/back) by varying the position of the base stations in an indoor environment. Results and analyses highlight the variation of the channel parameters with respect to the orientation of the base station configurations and the presence of the human subject. Channel parameter values (peak power delay profile/rms delay spread $({{\boldsymbol{\sigma }_{\boldsymbol{\tau }}}})$ /Kurtosis $(\boldsymbol {\kappa })$ ) are reported for line-of-sight (LOS: −65 to −50 dB/0.5–5 ns/40–60) and non-line-of-sight (NLOS: −80 to −65 dB/10–25 ns/5–25). The three dimensional (3-D) localization accuracy obtained is highest (1–3 cm) for the xz plane L-shape configuration facing-front, which has maximum number of LOS links (70%). The accuracy decreases by 1–2 cm for the xz plane L-shape configuration facing-back due to the increase in NLOS links (70%) between the wearable antennas and the base stations.

Performance evaluation of millimeter wave 5G networks for variable antennas configurations

In this paper, two scenarios have been considered for millimetre wave base station configuration. In the first scenario, the approach of Distributed Base Station (DBS) with remote radio units (RRU) is chosen as the envisioned architecture for future 5G network. This approach is compatible with cloud radio access network (C-RAN), as it has easier scalability and compatibility with future network expansions and upgrades. RRU has been used in this work as a way to sidestep the limited coverage and poor channel condition, which characterise millimetre wave band. This will minimise the number of required sites installation for the same quality of service (QoS). The results of this approach have shown significant improvements in terms of User Equipment (UE) throughput, average cell throughput, and spectral efficiency. In the second scenario, optimising antenna element spacing is considered in the base station array. The results show significant improvement in the network performance and provide better performance for cell-edge users in terms of data throughput.

Nonlinear Energy Harvesting for Millimeter Wave Networks With Large-Scale Antennas

In this paper, an analytical framework is proposed to explore the potential of wireless power transfer (WPT) for a millimeter wave (mmWave) network with large-scale antennas. Prior works mostly focus on WPT systems with a linear energy harvesting (EH) model, which cannot properly capture the power dependent EH efficiency. On the other hand, based on a nonlinear EH model, the effect of practical EH circuit specifications on the EH performance can be analyzed. By using stochastic geometry approach, analytical and asymptotic expressions for the energy coverage probability, average harvested energy, and achievable rate are derived under different base station (BS) configuration and deployment scenarios. Numerical results provide interesting design insights that the EH circuit specifications significantly affect the network performance. Increasing the BS density and number of BS antennas can improve the network performance. Due to saturation of EH circuits, the typical receiver can only achieve finite maximum amount of harvested energy and achievable rate even when the BS has a large number of antennas.

Analysis and performance evaluation of Relay Assisted OFDMA cellular systems with different Beamforming techniques

This paper addresses the Co-Channel Interference (CCI) reduction in Relay Assisted (R-A) cellular systems using Beamforming (BF) techniques. Analytical treatments are conducted. The network performance improvements through reducing the CCI are evaluated using three different configurations of applying BF. These configurations represent Relay Station (RS) do BF only, Base Station (BS) do BF only and both RS and BS do BF. Additionally, the considered BF techniques denote the horizontal, vertical, and Three Dimensional (3D) BF techniques. Therefore, each configuration consists of three different scenarios. Accordingly, nine different scenarios are studied. A comparison of these scenarios is introduced to enhance the network Quality of Service (QoS). Moreover, closed-form expressions for worst-cases Cell Edge User’s (CEU’s) Signal to Interference Ratio (SIR), Cell Center User’s (CCU’s) SIR and inner radius are implemented. Furthermore, various performance evaluation metrics are used to compare the different scenarios. The results reveal, that the performance of vertical BF is close to that of the 3D BF in low Path-loss (PL) exponent range. Therefore, applying vertical BF is preferable from the network cost and power consumption perspectives. Furthermore, it is observed, that the configuration of RS do BF is superior to other configurations when horizontal or vertical BF technique is employed. Additionally, the configuration of both RS and BS do BF outperforms the other configurations when 3D BF is applied. However, as unexpected it performs worse than them when the other BF techniques are applied. The work outcomes attain much higher CEU’s SIR improvement. Therefore, the coverage probability is increased. Thus, more users can be served by the network. Accordingly, the total network cost is reduced. So, this treatment not only improves the network performance, but also it reduces the total network cost.

Base-Station Random Placement Effect on the Accuracy of Ultrawideband Body-Centric Localization Applications

This letter presents an investigation on the effect of random placement of base stations on three-dimensional body-centric localization in the ultrawideband frequency range. Different base station configurations are studied (varied in xyz -axis, xy -axis, and z -axis direction), keeping the same range estimation error values as obtained from the body-centric localization experimental data in order to keep the main focus on the influence of the base-station configurations. It is observed that random positions of the base stations in the z- axis lead to higher localization error (3–8 cm) as the target nodes are spread out more in the z -axis direction. The localization error is analyzed in terms of geometric, horizontal, vertical dilution of precision (DOP), which is a measure of effectiveness of the placement of the base stations. For the DOP values (5–15), 1–3 cm error reduction is observed, and for higher DOP (>20) values, the error increases by 3–5 cm for short-range communication. Further analysis is carried out by varying the range estimation error in terms of mean value and standard deviation for evaluating the random base-station configurations, which also plays an important role in the accuracy of estimating the location of the target.

3GPP-Inspired HetNet Model Using Poisson Cluster Process: Sum-Product Functionals and Downlink Coverage

The growing complexity of heterogeneous cellular networks (HetNets) has necessitated a variety of user and base station (BS) configurations to be considered for realistic performance evaluation and system design. This is directly reflected in the HetNet simulation models proposed by standardization bodies, such as the 3rd Generation Partnership Project (3GPP). Complementary to these simulation models, stochastic geometry-based approach, modeling the locations of the users, and the $K$ tiers of BSs as independent and homogeneous Poisson point processes (PPPs), has gained prominence in the past few years. Despite its success in revealing useful insights, this PPP-based $K$ -tier HetNet model is not rich enough to capture spatial coupling between user and BS locations that exists in real-world HetNet deployments and is included in 3GPP simulation models. In this paper, we demonstrate that modeling a fraction of users and arbitrary number of BS tiers alternatively with a Poisson cluster process (PCP) captures the aforementioned coupling, thus bridging the gap between the 3GPP simulation models and the PPP-based analytic model for HetNets. We further show that the downlink coverage probability of a typical user under maximum signal-to-interference-ratio ( $ \mathtt {SIR}$ ) association can be expressed in terms of the sum-product functionals over PPP, PCP, and its associated offspring point process, which are all characterized as a part of our analysis. We also show that the proposed model converges to the PPP-based HetNet model as the cluster size of the PCPs tends to infinity. Finally, we specialize our analysis based on general PCPs for Thomas and Matern cluster processes. Special instances of the proposed model closely resemble the different configurations for BS and user locations considered in 3GPP simulations.