Rigorous Indoor Wireless Communication System Simulations With Deep Learning-Based Radio Propagation Models

This paper presents five commonly used radio propagation models (RPMs) which are suitable for the prediction of path loss in macrocell environments of LTE wireless communication systems. These RPMs’ application in high altitude mountainous areas networks (HAMANETs) environment requires further validation and studies. Through using the measured path loss in the HAMANETs at 2.6 GHz to calculate the predicted value of the five RPMs and the measured value’s mean error (ME), root mean square error, and error standard deviation (ESTD), we verified the predicted value of the SPM model that is closer to the actual measurement. On this basis, the empirical propagation model in HAMANETs environment is corrected. When correcting, a method to calculate base station’s effective antenna height and propagation distance is provided by using the altitude above sea level data. This method can reduce the error that the mountainous areas are simplified to the flat-terrain in the existed propagation models. A linear least square method is used to calculate the optimal propagation model. Finally, the ME is the smallest, and the ESTD is less than 8 dB, which indicate that the corrected propagation model is more suitable for the actual environmental path loss’s prediction. The results show that the path loss factor of the test area is about 65 dB, including the influence of the high altitude, mountains, vegetation, and air humidity in HAMANETs environment. The study results can provide useful advice to the evaluation and verification of personal wireless communications in the HAMANETs. Furthermore, using the correction method proposed in this paper can correct propagation models suitable for the different propagation environments to improve the accuracy and efficiency of wireless network optimization.

Infrared light for indoor wireless communications has received considerable attention recently. Unfortunately infrared are more susceptible to shadowing or noise source and have stringent alignment requirements. However, a reliable communication can be made possible by the design of transceiver, which in turn depends on designer’s knowledge on the propagation properties at infrared frequency and characterized infrared channel by measurements. The objective of this work, is to setup an indoor wireless infrared communication system, based on the Line of Sight (LOS) transmission link using a laser diode as the transmitter device and a photodiode as the receiver device. The main purpose of this setup is to determine the best channel characterization for an optical wireless communication by varying the parameters such as receiver bandwidth and transmission distance. This work is divided into two parts. The first part is to design and stimulate a transimpedance amplifier receiver with bandwidth adjustment capabilities using Multisim. The stimulation results shows that by varying the designed transimpedance amplifier receiver bandwidth, produces a cutoff frequency range between 10MHz to 100MHz while the gain remains at 15dB. Optsim is used to determine the eyediagram, bit error rate and the Q factor of the optical wireless system when the transmission distance is varied. The stimulated results shows that as the distance increase, the bit error rate decreased. The second part of this work is to setup the experimental system. The experimental measurement shows that the maximum transmission distance is 4m. As the distance increased, the transmitted signal becomes distorted due to ambient noise. The measured gain at 0m is -4.8dB, compared to the stimulated gain has a difference of 19.8dB.

The era of wireless communications began at the turn of the 20th century, when Guglielmo Marconi used electromagnetic waves to transmit telegraph signals from ships to stations onshore <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> . To understand how radio signals propagate is critical for wireless communication system design. With the development of wireless communications, much effort has been made to characterize radio propagation in different frequency bands and physical environments. Radio propagation and wireless channel modeling are essential for communication system simulation, channel emulator design, wireless system planning and optimization, and the development of regulations and standards in wireless communications <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref> , <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref> .

Vehicle-to-vehicle and vehicle-to-infrastructure wireless communications are currently under development to improve traffic efficiency and safety. The time-critical nature of road safety applications imposes the need to accurately dimension the operation and performance of wireless vehicular communication systems. Given that radio propagation modeling has been shown to importantly affect the performance of traditional mobile and wireless communication systems, this work investigates its impact on the dimensioning of traffic safety wireless vehicular communications by separately analyzing the contributions of pathloss, shadowing and fast fading.

With the support of GIS spatial analysis technology, based on an in-depth study of the wireless propagation environment of a city, combined with the analysis of project requirements, it proposes to use the SPM model to correct the propagation model parameters, using SPM. The wireless propagation model, and research and analysis of the SPM wireless propagation model correction algorithm, further corrected the parameters of a city's SPM wireless propagation model. On this basis, the propagation loss of several classic propagation models in different environments is compared, and the SPM propagation model suitable for the signal frequency band and propagation environment of this study is selected. The correction of the SPM propagation model is based on the designed correction principle and correction process, that is, the weighted least square method is used to fit and analyze the measured level data to obtain an SPM prediction improvement model with local characteristics, and according to the designed verification link. Evaluation of the correction results shows that the accuracy requirements are met. Based on the corrected SPM prediction model, link loss calculations were performed on the 13 test base stations studied in the experiment, and the effective coverage radius of each base station community was obtained. In combination with GIS technology, model parameters and workers of each base station participated in the electronic map loading of the area Go to the network planning software to get the wireless signal coverage prediction map of each base station. Finally, according to the technical requirements of the TD-LTE system network planning and network optimization engineering, the objectiveness and rationality of the site selection and number of base stations in the area were verified, and specific problems regarding poor coverage and overlapping coverage in the area were proposed.

Due to the attractive features of millimeter band, its uses are greatly expanding in the indoor wireless communication systems. As the distance between the transmitter and receiver is much shorter in indoor environments than that of the outdoor environments, the radio wave paths of the millimeter band frequencies are highly influenced by the building materials as well as by the human movements. Ray tracing is widely used method to characterize the radio wave propagation for the planning and establishment of the indoor wireless network. Precise object modeling for the real environment and computational burden are the two classical problems of the propagation model. Because, large number of rays that travels in a complex and convoluted indoor environment must be traced. Therefore, an accurate and efficient ray tracing method is proposed here, which is based on the surface separation, object address distribution, and surface skipping techniques. The proposed approach considers the effects of human body movement to provide a realistic estimation of the wave propagation. Hence, an approximated human body model is used to simulate the activities of humans, whereas three-dimensional (3-D) cube or cuboids are used for the remaining objects of the simulation environment. To prove the superiority, complexity analysis and detailed comparisons between the proposed and existing methods are presented in this paper. The results obtained will be of great interest for the proposed ray tracing method that involves human motion within the simple and complex indoor environments.

This paper deals with the radio propagation models predominantly used for the 4th Generation (4G) of cellular networks generally known as Long Term Evolution (LTE). It is necessary to study the radio wave propagation models at the development level of any wireless communication network or system. A comparative analysis is made among various radio propagation prediction models to assess the appropriate prediction model which can be helpful for LTE networks in a particular environment. In the analysis part; the mean, standard deviation and root mean square value are computed. In the evaluation Free space model predicts the minimum path loss and SUI model predicts the more path loss for the given values of frequency, base station antenna heights, and Mobile equipment antenna heights and transmitted power. Ericsson, winner II, Cost-231 and ECC models are showing better results when compared with the practical data obtained in the NCR region Delhi (INDIA). Among these models Ericsson model is showing least RMSE and standard deviation. From the analysis carried out in this paper, it is observed that the Ericsson path loss model is the best model for NCR region Delhi (INDIA). To acquire more accurate results in the existed Ericsson model some modifications are given using statistical measures.

White LED offers advantageous properties such as high brightness, reliability, lower power consumption and long lifetime. White LEDs are expected to serve in the next generation of lamps. An indoor visible-light wireless communication system using white LED lightings has been proposed from our laboratory. In the proposed system, these devices are used not only for illuminating rooms but also for a wireless optical communication system. Generally, plural lights are installed in our room. So, their optical path difference must be considered. We discuss about the influence of intersymbol interference and the difference between visible-light wireless communication and other optical wireless communication. Based on numerical analyses, we show that the system will expect as indoor communication of next generation.

With the rapid growth of indoor wireless communication systems, the need to accurately model radio wave propagation inside the building environments has increased. Many site-specific methods have been proposed for modeling indoor radio channels. Among these methods, the ray tracing algorithm and the finite-difference time domain (FDTD) method are the most popular ones. The ray tracing approach as a high frequency technique is efficient for calculating the received field at a small number of receiver locations. Application of FDTD method as a full wave technique for indoor propagation modeling is time consuming and requires large amounts of memory. The parabolic equation method (PEM) is a fast full-wave technique which allows accurate modeling of the propagation environment and its electrical parameters. This paraxial version of the wave equation can be solved by marching techniques which need far less computation resources than a full elliptic equation. The PEM has been extensively used as an efficient algorithm for outdoor propagation modeling. In this paper we propose an unprecedented application of PEM for indoor propagation problems. Depending on the required speed and accuracy of computations, two and three-dimensional versions of the PEM can be used for indoor problems. Without loss of generality, we restrict ourselves to the two-dimensional problems and use two-dimensional approximation of the parabolic equation for fast and accurate radio wave propagation modeling in indoor environments. The parabolic equation has been derived for lossless media where the refractive index is very close to unity. To the authors' best knowledge the paraxial version of the wave equation has not yet been derived for propagation in general lossy dielectric media. In this paper, we first derive the general form of the parabolic wave equation for lossy dielectric media where it can be used for modeling the radio wave propagation through walls. The special form of the parabolic equation for modeling wave propagation in free space can be derived from this general form. We then apply PEM to model propagation of radio waves through a row of windows, reinforced concrete walls and typical corridors inside buildings. As windows are one of the most prevailing architectural elements in buildings, the phenomenon of plane wave transmission through them is of interest. In this paper PEM is used to model the radio wave propagation through windows. The numerical simulation results are presented for both normal and oblique incidence and compared with some reported results. The transmission and reflection characteristics of inhomogeneous walls have been studied by many numerical and analytical methods such as the finite-element method (FEM) and FDTD. In this paper, we use PEM to characterize reflection and transmission properties of reinforced concrete walls under plane wave incidence. The effect of several parameters namely wall thickness, bar diameter and spacing on the transmission coefficients of reinforced concrete walls will be analyzed. Corridors are also popular elements of buildings, so that the analysis of radio wave propagation in corridors has involved many researchers. The PEM is an effective method for modeling wave propagation in these environments. The effect of obstacles such as cupboards and cabinets inside a corridor can be modeled by PEM. This method is also able to model the effects of variations of the corridor direction on the wave propagation. The numerical simulation results will be presented and compared with the available data in the literature.

In this paper, two models for diffuse indoor cellular optical wireless communication (OWC) systems with and without a holographic light shaping diffuser (LSD) are presented. For both models, the power distribution, the impulse response of the channels and root mean square (RMS) delay are described and analyzed. We perform a computer simulation to compare the channel characteristics of the typical indoor cellular OWC systems with that employing the holographic LSD. The results show that the system with the holographic LSD provides a more uniform power distribution and a less RMS delay spread for the same divergence angles.

This paper concerns about the radio propagation models used for the upcoming 4 th Generation (4G) of cellular networks known as Long Term Evolution (LTE). The radio wave propagation model or path loss model plays a very significant role in planning of any wireless communication systems. In this paper, a comparison is made between different proposed radio propagation models that would be used for LTE, like Stanford University Interim (SUI) model, Okumura model, Hata COST 231 model, COST Walfisch-Ikegami & Ericsson 9999 model. The comparison is made using different terrains e.g. urban, suburban and rural area.SUI model shows the lowest path lost in all the terrains while COST 231 Hata model illustrates highest path loss in urban area and COST Walfisch-Ikegami model has highest path loss for suburban and rural environments.

In modern wireless communication systems, radio propagation modeling has always been a fundamental task in system design and performance optimization. These models are used in cellular networks and other radio systems to estimate the pathloss or the received signal strength (RSS) at the receiver or characterize the environment traversed by the signal. An accurate and agile estimation of pathloss is imperative for achieving desired optimization objectives. The state-of-the- art empirical propagation models are based on measurements in a specific environment and limited in their ability to capture idiosyncrasies of various propagation environments. To cope with this problem, ray-tracing based solutions are used in commercial planning tools, but they tend to be extremely time consuming and expensive. In this paper, we propose a Machine Learning (ML) based approach to complement the empirical or ray tracing-based models, for radio wave propagation modeling and RSS estimation. The proposed ML-based model leverages a pre-identified set of smart predictors, including transmitter parameters and the physical and geometric characteristics of the propagation environment, for estimating the RSS. These smart predictors are readily available at the network-side and need no further standardization. We have quantitatively compared the performance of several machine learning algorithms in their ability to capture the channel characteristics, even with sparse availability of training data. Our results show that Deep Neural Networks outperforms other ML techniques and provides a 25% increase in prediction accuracy as compared to state-of-the-art empirical models and a 12x decrease in prediction time as compared to ray tracing.

The commercial interest in proximity services is increasing. Application examples include location- based information and advertisements, logistics, social networking, file sharing, etc. In this paper, we consider network-based positioning based on times series of proximity reports from a mobile device, either only a proximity indicator, or a vector of RSS from observed nodes. Such positioning corresponds to a latent and nonlinear observation model. To address these problems, we combine two powerful tools, namely particle filtering and Gaussian process regression (GPR) for radio signal propagation modeling. The latter also provides some insights into the spatial correlation of the radio propagation in the considered area. Radio propagation modeling and positioning performance are evaluated in a typical office area with Bluetooth-Low-Energy (BLE) beacons deployed for proximity detection and reports. Results show that the positioning accuracy can be improved by using GPR.

Climate change poses several environmental threats like floods to urban environment; thus, effective and reliable communication of emergency information is needed during massive breakdown of network infrastructure. This paper presents a mobile adhoc network (MANETs) based effective information such as calls, image, and videos communication system that is compatible with current 3GPP and 5G communication network. Here in maintaining connectivity the information is communicated between different MANET nodes in a multi-hop manner. However, designing radio propagation is challenging considering higher local emergency request congestion at different terrain with varying speed of users. The current radio propagation model is designed without considering the effect of line-of-sight between communicating device and are not adaptive to different environment considering urban disaster management environment. This paper develops an adaptive radio propagation (ARP) model namely expressway, city and semiurban. Then, in reducing congestion and improving network performance efficiency the work introduced an adaptive medium access control (AMAC) protocol. The MAC incorporates a dynamic network controller (DNC) to optimize the contention window size in dynamic manner according to current traffic demands. The AMAC protocol achieves much improved throughput with lesser packet loss in comparison with existing MAC (EMAC) model considering different radio propagation model introduced in this work.

The authors review the coverage prediction techniques in use for indoor wireless communications systems. The production of computer-generated coverage maps, allowing an interactive design for a particular indoor site using an engineering workstation, is the goal of coverage and propagation prediction. The authors examine the approaches and techniques known to be available for the production of these coverage maps, for both radio and optical indoor wireless communication systems. >