Downlink Performance Analysis for a Generalized Shotgun Cellular System

Based on random network (RN) topologies generated from Poisson point processes (PPP), this paper investigates the performance of macrodiversity coordinated multipoint transmission (MD-CoMP) in dense cellular networks. First, the signal-to-interference-plus-noise ratio (SINR) outage probability is analyzed for a typical mobile station (MS) and for the global network. Next, a user-centric adaptive clustering method is described, which is designed to maximize each MS's normalized outage capacity (goodput). Simulation are carried out and show that MD-CoMP could significantly improve both the RN and regular hexagonal network (HN) coverage performance by increasing the tenth percentile of the SINR by 12 dB if each MS uses a CoMP cluster of size four. It is also shown that MD-CoMP is more beneficial for the RN since 78 MSs in the RN would choose CoMP to optimize their normalized goodput, whereas this number is 58 in the HN. Moreover, 58 MSs in the RN have their normalized goodput doubled compared with that with no CoMP, whereas this number is 36 in the HN. The impact of predefined clustering schemes is also evaluated, to show the importance of using a fully adaptive clustering to overcome cluster-edge issues, where the MSs' performance is poor due to the limited choices of BSs.

The aim of this paper is to present a non‐linear statistical model to fit and forecast the signal‐to‐interference plus noise ratio (SINR) in two‐tier heterogeneous cellular networks which consist of macrocells and femtocells. Since in these networks the number and locations of femtocell base stations (FBS) are variable, SINR forecasting can be useful in some areas such as power control and handover management. So far, linear autoregressive (AR) models have commonly been used in forecasting the received signal strength (rss) in macrocellular networks. However, AR modelling results in high mean square error (MSE) when data are non‐linear. This paper focuses on SINR which takes into account signal strength, interference and noise effects. Moreover, macro‐femto cellular network is considered. The F ‐test results show that the SINR data are non‐linear, leading to use non‐linear models instead of AR model. A non‐linear logistic smooth threshold AR (LSTAR) model is utilised to model and forecast the SINR data. Kolmogorov–Smirnov (K‐S) test demonstrates that LSTAR provides good fitness to the SINR samples. The results indicate that LSTAR model achieves much better performance in modelling and forecasting of SINR data than the AR model.

We provide new results on the signal-to-interference-plus-noise ratio (SINR) statistics considering a Poisson point process (PPP)-based heterogeneous interference field. In particular, closed-form expressions for the density functions of the reciprocal of the aggregate interference and signal-to-interference ratio (SIR) are developed. We prove that the effect of PPP-based interference on useful transmission is mathematically equivalent to the severe impact from a one-sided Gaussian fading channel. As an application example, the proposed approach is used to design and analyze the average SINR performance of a typical user in heterogeneous cellular networks (HetNets).

This paper aims to devise a power control solution for femtocell networks that can be implemented distributively and, more importantly, is optimal in Pareto sense. For this, a complete characterization of the Pareto-optimal boundary of the signal-to-interference-plus-noise ratio (SINR) feasible region is first derived. The complicated interdependency between the macrocell and femtocell networks, whose access priorities and design objectives are inherently distinct, is also revealed. Our result confirms that the Pareto-optimal SINRs of the femtocell network can only be achieved conditionally upon the guaranteed performance of macrocell users. Through a suitable parametrization, we show that all SINR points on the aforementioned boundary can be realized. A unique operating SINR point is chosen among those infinite possible solutions, based upon the specific utility of femtocell users as well as the minimum SINR requirements of the macrocell network. Distributed transmit power adaptation is then performed to attain such optimal design target. We prove that the developed algorithm converges to the global optimum, wherein the performance of femtocell users is optimized while macrocell users being robustly protected with their minimum required SINRs maintained at all times. The merits of our approach are illustrated by numerical results.

This article performs a unified analysis of three coordinated multipoint (CoMP) transmission strategies in the downlink of mmWave cellular networks, including the fixed-number base station (BS) cooperation (FNC), the fixed-region BS cooperation (FRC), and the interference-aware BS cooperation (IAC). We first develop a comprehensive framework for CoMP operation in cellular networks, and investigate the network performance under a Poisson point process (PPP) model together with mmWave spectrum. To show what fraction of users in the network achieve target reliability for a given signal to interference-plus-noise ratio (SINR)/signal-to-interference ratio (SIR), we derive the SINR/SIR meta distributions, and further obtain the coverage probability as well as mean local delay for the three cooperation strategies. A pivotal intermediate step to compute the performance metrics is the derivation of joint distributions of distances between a typical user and cooperative BSs. Our analysis demonstrates that parameters of blockage have a significant influence on the network performance for the three CoMP schemes. We find that the FRC scheme makes more users achieve the given link reliability for the scenario with a low density of BSs, while the IAC scheme provides better performance for the network with a high density of BSs. Moreover, the optimal CoMP scheme can be approximately selected by considering the nearest distance from the serving BS to user and the radius of the approximate line-of-sight (LoS) region in the cellular networks.

Modern cellular communication networks are already being perturbed by large and steadily increasing mobile subscribers in high demand for better service quality. To constantly and reliably deploy and optimally manage such mobile cellular networks, the radio signal attenuation loss between the path lengths of a base transmitter and the mobile station receiver must be appropriately estimated. Although many log-distance-based linear models for path loss prediction in wireless cellular networks exist, radio frequency planning requires advanced non-linear models for more accurate predictive path loss estimation, particularly for complex microcellular environments. The precision of the conventional models on path loss prediction has been reported in several works, generally ranging from 8–12 dB in terms of Root Mean Square Error (RMSE), which is too high compared to the acceptable error limit between 0 and 6 dB. Toward this end, the need for near-precise machine learning-based path loss prediction models becomes imperative. This work develops a distinctive multi-layer perception (MLP) neural network-based path loss model with well-structured implementation network architecture, empowered with the grid search-based hyperparameter tuning method. The proposed model is designed for optimal path loss approximation between mobile station and base station. The hyperparameters examined include the neuron number, learning rate and hidden layers number. In detail, the developed MLP model prediction accuracy level using different learning and training algorithms with the tuned best values of the hyperparameters have been applied for extensive path loss experimental datasets. The experimental path loss data is acquired via a field drive test conducted over an operational 4G LTE network in an urban microcellular environment. The results were assessed using several first-order statistical performance indicators. The results show that prediction errors of the proposed MLP model compared favourably with measured data and were better than those obtained using conventional log-distance-based path loss models.

In dense deployment area of femtocell networks, interference becomes major problem normally decreasing signal to interference plus noise ratio (SINR) of connection between Femto User Equipment (FUE) and Femto Base Station (FBS). Thus, FUE must select appropriate FBS to get high SINR value in order for achieving high data rates. In this paper, we investigate cell selection process in Femtocell networks and problem related to interference. We propose cell selection method using bacterial foraging optimization algorithm (BFOA) to find the most appropriate FBS and resource blocks (RBs) for FUE. Simulation results show that proposed method has capability to converge in finding the best solution, i.e. FBS and RBs that will provide high link capacity for FUE.

In a conventional cellular network, a terminal receives signals not only from the base station of that cell, but also from other cell base stations. This inter-cell interference has more impact on the cell-edge users, in multi cell environment. The inter-cell interference degrades the performance of wireless systems. Using Base Station Cooperation, the ability of a mobile station to receive signals from multiple base stations can be utilized as an opportunity to improve the spectral efficiency and to get higher data rates for cell edge users. In multi cell environment using base station cooperation overall interference can be minimized marginally, whereas the interference within the cooperation region is largely reduced. This leads to a question whether it is worth doing cooperation all the time. However increase in terms of throughput may not always be enough to increase the throughput of each of the user .Hence for such a scenario the distinct cooperation scheme is used. The distinct cooperation is a joint transmission scheme in which the selection criterion is based on user’s signal to interference plus noise ratio (SINR) is proposed and the capacity achieved through cooperation is shared equally among the cell-edge users. Here we will analyze the normal operation, full cooperation and distinct cooperation scheme in the downlink environment for cell edge users in cellular network and we will compare and see which method improves the user capacity and data rate.KeywordsCooperative transmissionfull cooperationDistinct cooperationsignal to interference plus noise ratio (SINR)

There are many scenarios that have been proposed for fifth generation (5G) networks. Some of them, if implemented, will bring fundamental changes at the architectural and node level. One example of such proposed technologies is device-to-device (D2D) communications which will change the nature of conventional cellular network design. D2D permits direct communication between two or more user devices without intervention of the base station (i.e. eNB). D2D can ensure network performance improvement over the traditional cellular network, because it can offload the mobile data traffic from the other devices. However, applying D2D features in a cellular network will bring about more complex interference problems, since D2D communication uses the same band as its underlying cellular communication network. The aim of this research is to investigate interference-related problems caused by D2D communications, affecting the underlying cellular networks, during downlink and uplink transmissions. The paper examines the use of power control methods to mitigate interference. A comparison is offered between fixed power level (FC) with or without power control, and adaptive power controls using two methods (AC1 and AC2), on a base station or on each of the D2D devices, based on the measured signal to interference plus noise ratio (SINR). The simulation results show that both power control methods contribute to improvement of network performance. AC1 and AC2 can improve SINR by about 1 dB and 0.5 dB compared to FC in a downlink transmission, and by 0.5 dB in an uplink transmission.

This study focuses on the performance of device-to-device (D2D) communications in underlay cellular networks by analyzing key metrics such as successful transmission probability, coverage probability, and throughput.Under the homogeneous Poisson point process (PPP) spatial distribution of full-duplex (FD)-D2D users in cellular networks, stochastic geometry tools are used to derive approximate expressions for D2D users' coverage probability and throughput.In comparison to the conventional half-duplex (HD) communication mode, when the self-interference cancellation factor reaches -95 dB, there is a substantial improvement in the throughput of FD-D2D users, nearly doubling their gain.Additionally, experimental results demonstrate that the Newton iterative algorithm can be used to optimize the targeted signal-to-interference-plus-noise-ratio (SINR) threshold of users within the range of (10, 20) dB.

Existing cellular network analyses are based on the standard power law path loss model. If the base stations are modeled by a Poisson point process, this leads to a tractable analysis of coverage probability and other metrics for downlink cellular networks. Yet, it is also well-known that the standard path loss model is idealized and does not capture the distance-dependence of the path loss exponent. This paper considers a more precise and general model, the dual-slope path loss model, where the path loss exponents are different for short links and long links differentiated by a critical distance. We derive compact expressions on the coverage probability and its tight closed-form estimate under this model. The analytical results show that the SINR does not monotonically increase with network density (as under the standard path loss model). Rather, ultra-densification leads to worse or even zero coverage when the near-field path loss exponent is 2 or less.

This paper studies coverage maximization for cellular networks in which base station (BS) locations are modeled using a homogenous spatial Poisson point process, and user locations are arbitrary. A user is covered for communication if its received signal-to-interference-plus-noise-ratio (SINR) is above a given threshold value. Two coverage models are considered. In the first model, the coverage of a user is determined based on the received SINR only from the nearest BS. The nearest BS happens to be the BS maximizing the received SINR without fading. In the second model, on the other hand, the coverage of a user is determined based on the maximum SINR from all BSs in the network. The objective is to maximize the coverage probability under the constraints on transmit power density (per unit area). Using stochastic geometry, coverage probability expressions for both coverage models are obtained. Using these expressions, bounds on the coverage maximizing power per BS and BS density are obtained. These bounds truncate the search space of the optimization problem, and thereby simplify the numerical evaluation of optimum BS power and density values considerably. All results are derived for general bounded path loss models satisfying some mild conditions. Specific applications are also illustrated to provide further insights into the optimization problem of interest.

In this work, we investigate the physical layer security (PHYLS) performance of full-duplex (FD) cellular networks, where the downlink (DL) and uplink (UL) occur over the same radio-frequency (RF) resources. Here, the locations of the base stations (BSs) and mobile terminals (MTs) are drawn from stationary Poisson point processes (PPPs). Moreover, the eavesdroppers (EDs) locations are unknown to the network, and are thus modeled from an independent PPP. We characterize the signal-to-interference-plus-noise ratio (SINR) distributions at the reference BS, MT, and most malicious EDs. Accordingly, we develop explicit expressions for the secrecy rates in both UL and DL of the FD cellular network under consideration. Our finding show that the choice of FD versus HD operation, in addition to improving the spectral efficiency, can enhance the secrecy rate, particularly for ultra-dense deployments.

In this paper, we address the problem of optimally placing relay nodes in a cellular network with the aim of maximizing cell capacity. In order to accurately model interference, we use a dynamic framework, in which users arrive at random time instants and locations, download a file and leave the system. A fixed point equation is solved to account for the interactions between stations. We also propose an extension of a fluid model to relay based cellular networks. This allows us to obtain quick approximations of the Signal to Interference plus Noise Ratio (SINR) that are very close to 3GPP LTE-A guideline results in terms of SINR distribution. We then use these formulas to develop a dedicated Simulated Annealing (SA) algorithm, which adapts dynamically the temperature to energy variations and uses a combination of coarse and fine grids to accelerate the search for an optimized solution. Simulations results are provided for both in-band and out-of-band relays. They show how relays should be placed in a cell in order to increase the capacity in case of uniform and non-uniform traffic. The crucial impact of the backhaul link is analyzed for in-band relays. Insights are given on the influence of shadowing.

In the planning of cellular networks, link budget calculation is the first step to get the maximum allowable cell radius that guarantees a target signal to interference plus noise ratio (SINR) with a certain level of outage probability at the cell border. The interference margin as one of key inputs for link budget is used to compensate for co-channel interference. In this paper, a mathematical analysis for interference margin as a function of system load is proposed in orthogonal frequency division multiple access (OFDMA) cellular networks. The analysis is derived from OFDMA features based on a general expression of exponential effective SINR mapping (EESM). The proposed approach can be easily applied to the evaluation of interference from neighboring cells, and help to improve the accuracy of the link budget calculation in OFDMA systems. All the theoretical analysis given in this paper have been proved by Monte Carlo simulations.