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A Comprehensive Survey of Path Loss Types in Different Wireless Communication Environments
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Pathloss is a key element that causes signal deterioration in the channel as the signal power reduces inversely with propagation distance, this deterioration experienced by the channel is majorly as a result of reflection, absorption, and scattering of the signal. This study however takes into consideration the radio path loss for precise base station (BS), frequency, and power adjustment prediction evaluated over a frequency of 2.3 GHz. With a distance range between 0.1 and 1.5 km for collection of data on the measured received signal strength (MRSS), five empirical models and a modified model were used to validate the measured data to determine their suitability for pathloss prediction at Federal University of Technology, Owerri (FUTO), Imo state, Nigeria. The results shows that the root mean square error (RMSE) for the Okumura-Hata, COST 231-Hata, Ericsson model, Lee, Stanford University Interim (SUI), ECC-33, and modified models are 14.33, 9.73, 25.79, 48.4, 33.76, and 8.31 dB respectively. Additionally, the Ericsson model provided 0.498 dB, the COST 231-Hata recorded 0.733 dB, and the modified model provided 0.453 dB for mean absolute percentage error (MAPE). Therefore, the improved model produces the best results, consequently, be deployed to approximately predict path loss for mobile radio coverage in Owerri, Nigeria. Keywords: Communication Frequency Model Modified Pathloss This is an open access article under the CC BY-SA license.
Modern wireless systems for mobile communication use electromagnetic waves to transmit information over the air, enabling seamless connectivity for a wide range of devices. However, one of the key challenges in wireless communication paths is loss in the strength of propagated signals. Path loss refers to the reduction in signal strength as it propagates through the wireless channel. Path loss models are mathematical representations that capture the attenuation of signal power due to various factors such as distance, frequency, obstacles, and environmental conditions. Understanding and modeling path loss is crucial for designing and optimizing wireless communication systems, as it directly impacts the coverage area, link quality, and overall performance of the network. By accurately modeling path loss, engineers can also optimize various aspects of a wireless communication system, such as antenna placement; transmit power control, and interference mitigation, ultimately improving the broad-spectrum performance and reliability of the network. This paper investigates the concept of path loss in wireless communication networks and provides a comprehensive overview of its various models and their use in designing and implementation of networks. Furthermore, it reviews existing path loss models, and explains their advantages and disadvantages. Finally, it discusses the current trends future research directions related to path loss and its models. The findings in this study can help them better design and implement robust wireless communication networks with improved signal quality and capacity.
One of the most fundamental tasks in Radio network planning is Radio propagation prediction. This is done to foresee the coverage of the proposed system whilst considering the practical limitations that characterize the propagation environment. As a result, many prediction models have been developed and deployed over the years. In this paper, two of such models; Okumura-Hata, and Free Space, are comparatively studied at three different locations in Ughelli, a suburban terrain of Delta state in South-South, Nigeria with the sole aim of comparing their accuracy in Path loss prediction. A netmonitor software installed in a smart phone, and a Garmin Nuvi Global Positioning System (GPS) device were used to measure the Received Signal Strength (RSS) and Distances between Base Transceiver Stations (BTS), and Mobile Station (MS) respectively. The analysis of the result showed that Okumura-Hata model is more accurate in pathloss prediction.
Wavelet transform has become a popular tool for signal denoising due to its ability to analyze signals effectively in both time and frequency domains. This is important because the information that is not visible in the time domain can be seen in the frequency domain. However, there are many wavelet families and thresholding techniques (such as haar, Daubechies, symlets, coiflets, meyer Gaussian, morlet, etc) thatare available for the analysis of signals, and choosing the best out of them all is usually time-consuming, thus making it a difficult task for researchers. In this article, we proposed and applied a stepwise expository-based approach to identify the wavelet family and thresholding technique using real-time signal power data acquired from Long-Term Evolution (LTE). We found out from the results that Rigrsure thresholding with the Daubenchies family outperforms others when engaged in practical signal processing. The stepwise expository-based approach will be a relevant guide to effective signal processing over cellular networks, globally. For validation, different datasets were used for the analysis and Rigrsure outperforms the other thresholding techniques.
Indoor path loss models characterize the attenuation of signals between a transmitting and receiving antenna for a certain frequency and type of environment. Their use ranges from network coverage planning to joint communication and sensing applications such as localization and crowd counting. The need for this proposed geodesic path model comes forth from attempts at path loss-based localization on ships, for which the traditional models do not yield satisfactory path loss predictions. In this work, we present a novel pathfinding-based path loss model, requiring only a simple binary floor map and transmitter locations as input. The approximated propagation path is determined using geodesics, which are constrained shortest distances within path-connected spaces. However, finding geodesic paths from one distinct path-connected space to another is done through a systematic process of choosing space connector points and concatenating parts of the geodesic path. We developed an accompanying tool and present its algorithm which automatically extracts model parameters such as the number of wall crossings on the direct path as well as on the geodesic path, path distance, and direction changes on the corners along the propagation path. Moreover, we validate our model against path loss measurements conducted in two distinct indoor environments using DASH-7 sensor networks operating at 868 MHz. The results are then compared to traditional floor-map-based models. Mean absolute errors as low as 4.79 dB and a standard deviation of the model error of 3.63 dB is achieved in a ship environment, almost half the values of the next best traditional model. Improvements in an office environment are more modest with a mean absolute error of 6.16 dB and a standard deviation of 4.55 dB.
The study of path loss propagation is of high importance in telecommunication, for optimizing the efficiency of wireless communication networks. In this paper, four path loss propagation models; free space path loss (FSPL) model, Okumura model, Okumura-Hata model, and COST 231-Hata model were compared. The models were compared using measurement data from Choba, Port Harcourt, Nigeria. The data is gotten from a 4G walk test using two mobile applications. The first mobile application Network, Signal Info (version 5.68.07), was used to acquire the received signal strength in and the distance between the BTS antenna and the mobile antenna. While the second mobile application, G-NetTrack Lite (version 14.8), was used to map out the track path followed during the test. Choba, the study area, is a coastal suburban area with map coordinates 4.8941° N, 6.9263° E. The measured distance range was from 0.09 km to 0.45 km, and a path loss range of 69dB to 81dB. While the BTS and mobile antenna heights were 32 m and 1m respectively, with a carrier frequency of 800MHz. BTS transmission power of 23 dBm was assumed, based on 3GPP eNodeB recommendations. A graph comparison of the studied models showed that Okumura-Hata model and COST 231-Hata model had the closest predictions to the measured path loss. The need for better path loss models for 4G and 5G propagations was observed
The study of radio signal propagation path loss (PL) is important for planning, designing and evaluating the performance of radio communication networks. However, the state-of-the-art in PL modelling for fixed wireless networks in rural environments is still ill-equipped for making accurate predictions. This paper explores the application of the log distance PL model to heterogeneous fixed wireless networks in harsh rural propagation conditions. This model is then extended and optimized to improve its accuracy. In particular, the dataset is classified according to many criteria, radio links are split into many intervals according to their distances, antenna heights and elevations are integrated into its formula and long-term extreme seasonal variations are considered. Our study uses a wide set of measurements from the fixed wireless networks of a wireless internet service provider in rural regions of Canada. The proposed modifications improve the accuracy by 7 to 15 dB in terms of the root mean squared error.
Many factors can produce route loss, including free space loss, diffraction, reflection, and absorption. Due to variances in the structures of cities, local topographical profiles, and weather, prediction of route loss may change from every model of propagation. This study shows observed and simulated route loss values in common urban and rural settings at the frequency of operation 2.1525 GHz. The findings of this study revealed that in metropolitan environments, higher distances had an impact on path loss estimation. After 18 meters from the measurement survey, 23 dB loss was found at the start of the measurement in an urban area. The goal of simulations and measurements is to estimate the mean signal intensity at a receiver situated at a certain distance from the transmitter, as well as the signal strength variability in a particular environment. As a result of this work, the obtained results will be beneficial for the planning and installation of any base station similar to the environments of thoughtful locations in order to make available instructions for wireless communication system cell planning, because route loss is an important consideration in the design of any radio communications system.
Accurate prediction of path losses is a key factor in Digital Terrestrial Television (DTTV) to ensure Quality of Service (QoS). This study investigates the path losses of three Digital Terrestrial Television Base Stations (DTTBS) in Lagos, Kaduna and Katsina cities of Nigeria. The Received Signal Strength (RSS) of the DTTBS was measured at intervals along selected routes around the stations using a digital signal strength meter. So also, the transmitter-receiver distances of data points with their corresponding geographic coordinates and heights were measured using a hand held GPS receiver. Also measured concurrently were some of the location's-based surface meteorological parameters such as temperature, atmospheric pressure and humidity, using a compact wireless weather station. In addition, the corresponding surface radio refractivity values along the routes were computed using the meteorological parameters recorded. Data were collected during dry and wet season months' covering a period of three years. Path losses were calculated using Okumura-Hata model. Results for all the routes and seasons revealed that path loss increases with increase in trans-receiver distances, however path losses were higher during wet compared to dry season's month. Path losses estimated were highest in Kaduna followed by Ikorodu-Lagos and least in Katsina. Average high positive correlation coefficients of 0.76, 0.75 and 0.74 were obtained between path losses and line of sight for Lagos (Coastal zone), Kaduna (Sudan Savannah) and Katsina (Sahel Savannah) respectively. In the same order, negative correlation coefficients of-0.72,-0.79 and-0.63 were obtained between path losses and RSS. In addition, Modified Okumura Hata Model(s) (MOHPL) that incorporates the effect of the specified tropospheric parameters were proposed. Results also revealed that path losses obtained by Okumura-Hata model increase with increase in LOS separation distance from the base station following a consistent exponential rise while the Modified Okumura-Hata Model (MOHPL) followed similar trend with few exceptions of crests and troughs depicting the influence of the incorporated location's-based tropospheric parameters. Another finding is that Okumura Hata model under estimated the path losses associated with digital terrestrial television channel over the study locations. In order to ensure high reliability of power budgets and link's design, the proposed models are recommended for use over the study locations. The overall findings of this work will be useful for the accurate prediction of path losses and the design of power budgets and links over digital terrestrial television and similar wireless channels on the UHF band.
The necessity and importance of path-loss determination for the purpose of mobile network planning and optimization requires that an optimal model should be developed for each specific environment. This will ensure proper planning leading to satisfactory service delivery to each environment at all times. In this study, 3G(2100MHz) mobile propagation in a mountainous area is investigated in order to determine a suitable model for optimizing path-loss prediction in urban, suburban and rural environments. Five models (free space, COST-231, Hata, Egli and ECC-33) were analyzed and compared with field measurement data. Their Mean Absolute Percentage Error (MAPE) and closeness (Root Mean Square Error) to the measured data were determined and compared. ECC-33 over-predicts path-loss for all the environments. Free space prediction was found to be impracticable. The RMSE of each of Egli, Hata and COST-231 were used to modify the models, predict new path-loss values and compare with the measured path-loss. The new RMSE values showed that the optimized models improved path-loss predictability by 76.42%, 25.50% and 73.67% for the rural, suburban and urban areas of the mountainous environment respectively.
This article involves the site specific determination of an outdoor path loss model and Signal penetration level in some selected modern residential and office apartments in Ogbomosho, Oyo State. Measurements of signal strength and its associated location parameters referenced globally were carried out. Propagation path loss characteristics of Ogbomosho were investigated using three different locations with distinctively different yet modern building materials. Consequently, received signal strength (RSS) was measured at a distance d in meters, from appropriate base stations for various environments investigated. The data were analyzed to determine the propagation path loss exponent, signal penetration level and path loss characteristics. From calculations, the average building penetration losses were, 5.93dBm, 6.40dBm and 6.1dBm outside the hollow blocks B1, solid blocks B2 and hollow blocks mixed with pre cast asbestos B3, buildings respectively with a corresponding path loss exponent values of, 3.77, 3.80 and 3.63. Models were developed and validated, and used to predict the received power inside specific buildings. Moreover, the propagation models developed for the different building types can be used to predict the respective signal level within the building types, once the transmitter – receiver distance is known. The readings obtained from the developed models were compared with both the measured values and values computed using some existing models with satisfactory results obtained.
Path loss propagation is a vital concern when designing and planning networks in mobile communication systems. Propagation models such as the empirical, deterministic and theoretical models, which possess complex, inconsistent, time-consuming and non-adaptable features, have proven to be inefficient in designing of wireless systems, thereby resulting in the need for a more reliable model. Artificial Intelligence methods seem to overcome the drawbacks of the propagation models for predicting path loss. In this paper, the ANFIS approach to path loss prediction in the GSM and WCDMA bands is presented for selected urban areas in Nigeria. Furthermore, the effects of the number of Membership Functions (MFs) are investigated. The prediction results indicated that the ANFIS model outperformed the Hata, Cost-231, Egli and ECC-33 models in both Kano and Abuja urban areas. In addition, an increase in the number of MFs conceded an improved RMSE result for the generalized bell-shaped MF. The general performance and outcome of this research work show the efficiency and usefulness of the ANFIS model in improving prediction accuracy over propagation models
Propagation is an essential factor ensuring good coverage of wireless communications systems. Propagation models are used to predict losses in the path between transmitter and receiver nodes. They are usually defined for general conditions. Therefore, their results are not always adapted to the behavior of real signals in a specific environment. The main goal of this work is to propose a new model adjusting the loss coefficients based on empirical data, which can be applied in an indoor university campus environment. The Oneslope, Log-distance and ITU models are described to provide a mathematical base. An extensive measurement campaign is performed based on a strict methodology considering different cases in typical indoor scenarios. New loss parameter values are defined to adjust the mathematical model to the behavior of real signals in the campus environment. The experimental results show that the model proposed offers an attenuation average error of 2.5% with respect to the losses measured. In addition, comparison of the proposed model with existing solutions shows that it decreases the average error significantly
for all scenarios under evaluation.
The paths loss propagation model is an important tool in wireless network planning, allowing network planner to optimize the cell towers distribution and meet expected service level requirements. However, each type of path loss propagation model is designed to predict path loss in a particular environment that may be inaccurate in other different environment. In this research different propagation models (Hata Model, ICC-33 Model, Ericson Model and Coast-231 Model) have been analyzed and compared based on the measured data. The measured data represent signal strength of two cell towers placed in two different environments which obtained by a drive test of them. First one in AL-Habebea represents an urban environment (high-density region) and the second in AL-Hindea district represents a rural environment (low-density region) with operating frequency 0.8 GHz. The results of performing the analysis and comparison conclude that Hata model and Ericsson model shows small deviation from real measurements in urban environment and Hata model generally gives better prediction in the rural environment.
Smartphones are more prevalent than computers in the digital age, particularly in poor and minority communities. Is it the effect to reduce or perpetuate socioeconomic disparities? This article reviews two decades of research investigating whether mobile phones contribute to enhancing the status of disadvantaged populations. Conclusions on the nature and extent of the mobile effect vary across areas of inquiry, including digital inequality, social networks, and coordination and mobility. Advantages accrue in particular areas, such as strengthening core ties, promoting particular Internet activities, and enhancing daily coordination and safety. Device limitations and structural inequalities overwhelm the mobile effect in many arenas, though new conditions emerge with changes in mobile technology and digital habits. Future research will benefit from closer attention to how mobile affordances, user motivation and habituation, popular mobile uses, and the particular conditions of disadvantage shape outcomes for marginalized populations.
A modified indoor path loss prediction model is presented, namely Effective Wall Loss Model (EWLM). The modified model is compared to other indoor path loss prediction models using simulation data and real‐time measurements. Different operating frequencies and antenna polarizations are considered to verify the observations. In the simulation part, EWLM shows the best performance among other models as it outperforms two times the dual slope model which is the second‐best performance. Similar observations were recorded from the experimental results. Linear attenuation and one slope models have similar behaviour, the two models parameters show dependency on operating frequency and antenna polarization. •A modified Effective Wall Loss Model (EWLM) for indoor environment. •Real time measurements and simulations for various indoor path loss models. •Several frequency spectrum band were considered for evaluation purposes.
Telecommunication system should generate the expected effect (signal), maintain the integrity of the effect in the course of propagation, with the capacity to improve the effect of the message .This ensures signal effective communication. However, the effects of the environmental factors through which signal are propagated, has some degradable influence on the radiating signal. These factors which are mainly buildings and trees do reflect, diffract, attenuate, absorb and even scatter the propagation signal in the medium. The impact of this anomaly is that it cost the network providers a very huge amount of money to install and maintain more network devices to abate this problem. Also, some network subscribers who experience this hardship in the network, do abandon their service provider for alternative networks. This research studies, analyzes and proffers solution on how to overcome the hindrances / obstacles that undermine the level of signal strength received within Owerri metropolis.
The goal of this paper is to investigate the path loss prediction models in wireless mobile networks taken into consideration different propagation environments. For the cell design of mobile communication systems, path-loss is very important issue and have been studied for long time. For the new generation of mobile networks, new prediction models with extended frequencies are needed. Therefore, we need to know which model is suitable for different application and different environments. The main idea of this paper is to analyze different path loss prediction models in different environments. Different path loss models are demonstrated, such as: free space, extended COST-231 Hata model, empirical Hata model, Walfisch-Ikegami propagation model, Stanford University Interim (SUI) Model and Ericson (9999) model. It is shown in this paper that SUI, Ericsson and Empirical Hata are overall the best choice for the new generation of mobile networks regardless of the distance and the type of environment. However, SUI outperforms Ericsson and Empirical Hata for 3.5 GHz for both urban and suburban environments. On the other hand, for higher frequencies (i.e. 28 GHz ), which is needed for the new generation of mobile networks like 5G, it is shown that Ericsson model gives better results for path loss in urban compared with SUI which gives better results in suburban environment. This conclusion is also confirmed by introducing the average path loss as well.
The Internet of Things (IoT) provides communication service for future smart manufacturing, which is capable of independently exchanging and responding to information to manage industrial production processes. For the purpose of connecting machines, devices, sensors, and people with each other in a factory, reliable and scalable communication networks used in the cellular IoT are of great importance. This paper aims at channel parameter measurements of indoor Long Term Evolution systems in order to achieve good coverage and service reliability (SR) for the IoT. For the purpose of determining the path loss exponent and the standard deviation of the received shadow fading signal, we use software defined radio techniques to build a small cell experimental platform which contains an evolved node B and user equipment. Received power measurements were performed on this platform. Finally, based on the experimental results, the modified path loss model and the calculated fade margin (FM) for 90% SR are exploited to predict the coverage range of the small cell base station deployed in the factory. The measured path loss channel models are compared with International Telecommunication Union (ITU) path loss channel model.
Objectives: Radio propagation models are used to predict signal strength in order to characterize the radio frequency channel. This will help in providing sufficient data required for the design of appropriate receivers that can recover the transmitted signal distorted due to fading and multipath effect. Methods/Statistical analysis: Data collection was carried out through drive test using TEst Mobile System, TEMS W995 phone interfaced with TEMS investigation tool version 13.1, Gstar GPS location finder and MapInfo professional and analyzed using Root Mean Squared Error (RMSE) statistical tool and tenth degree polynomial for fitting measured data with empirical models. Findings: Considering the contending empirical propagation models, the Ericsson model showed a better fit for the measured path loss data with root mean squared errors of 5.86dB, 5.86dB and 5.85dB at 1.0m, 1.5m and 2.0m mobile antenna heights respectively in comparison with Okumura model which is currently in use. It also outperformed other investigated models which are; Hata, COST 231, and SUI models at 2100MHz. These findings will help in revamping radio frequency planning and system design of the investigated and similar terrains thereby optimizing overall system performance while minimizing dropped calls, handover/quality issues and other network inherent failings. Application/Improvements: Results showed a minimum error estimate within the acceptable range of 6dB for signal prediction. This model can be used for signal prediction and channel characterization of any wireless mobile environment with similar channel characteristics. The other propagation models that over predicted the radio channel could be further investigated in future work and possibly tuned to accommodate dense urban areas.
Path loss models are useful planning tools that allow the designers of wireless communication networks to achieve optimal levels for the base station deployment and meeting the expected service level requirements. In this study various propagation models (COST 231 Walfisch-Ikegami W-I, Ericsson and Stanford University Interim SUI) are analyzed and compared with the measurements. The measured data were taken in urban (high density region) and rural (low density region) environments at the operating frequency of 1700 MHz using the spectrum analyzer. As one of the key outputs, It was found that the calculations of SUI model fit with the measured data in urban environment.
Indoor path loss models are playing an important role in the design and planning of the 4th generation of the mobile networks. Moreover, it is an important component of system level simulators used to evaluate and test the network performance before it has been established. Many propagation models were proposed for this purpose. Most of these models are for macro and micro cellular networks. Small cell which is known as femtocell has been launched for future networks and it is wildly deployed by the mobile operators around the world. The available propagation models’ accuracy is at question when applied to femtocell design and engineering. This paper attempts to quantify the accuracy of these models by studying and comparing seven different propagation models for four different implementation scenarios at 2.6 GHz and for different separation distances.
In the field of wireless communication and network planning, accurate path loss predictive modelling plays a vital role in understanding the behavior of signal propagation in diverse environments. Traditional empirical models have been widely
used for path loss estimation, but they often lack the flexibility to adapt to complex scenarios. On the other hand, machine learning techniques have shown great potential in various domains, including wireless communication. This paper aims
to present a hybrid empirical and machine learning approach for efficient path loss predictive modelling. By combining the strengths of empirical models and machine learning algorithms, we can enhance the accuracy and adaptability of path
loss predictions. The following sections provide an overview of path loss modelling, explore traditional empirical techniques, discuss the application of machine learning approaches, and outline the methodology for the hybrid approach, along with evaluation and analysis. Finally, we conclude with a summary of findings and suggest future directions for research in this field.
A survey of indoor propagation characteristics is presented, including different models for path loss, shadowing and fast fading mechanisms, different channel parameters including signal strength, power delay, coherence bandwidth, Doppler spread and angle of arrival. The concepts of MIMO channels are also covered. The study also explores many types of deterministic channel modelling, such as Finite Difference Time Domain, Finite Integration Method, Ray tracing and the Dominant path model. Electromagnetic properties of building materials, including frequency dependence, are also investigated and several models for propagation through buildings are reviewed.
To design coverage areas for wireless communication systems and evaluate the performance of the systems, it is necessary to develop a path loss model that can be used for the systems' frequency bands. The fifth-generation mobile communication system (5G) is expected to use high frequency bands above 6 GHz. Therefore, developing a path loss model for wireless access communication systems using high frequency bands has become a pressing issue. NTT Access Network Service Systems Laboratories has developed path loss models for the 20-40 GHz bands that are suitable for use scenarios of mobile phones and wireless local area networks. This article introduces the developed models.
Radio propagation is essential for emerging technologies with appropriate design, deployment and management strategies for any wireless network. It is heavily site specific and can vary significantly depending on terrain, atmospheric effects, frequency of operation, velocity of mobile terminal, interface sources and other dynamic factor. Accurate characterization of radio channel through key parameters and a mathematical model is important for: Predicting signal coverage, achievable data rates, network planning, Quality of service, hand over performance, etc. Efficiency of present path loss models for cellular communication system suffers when they are used in the environment other than for which they have been used. Accurate path loss can be determined by measuring strength of signal through site specific field measurements.
No comparisons of computer-based propagation models with experimental data collected in an urban area at 1800 MHz
- R Selung
- I Wasliah
- E A Pratiwi
Survey on various path loss models in wireless communication
- A Ali
- S Bardhan
- S Chanda
- K Karmakar
- D B Gupta
Literature survey on various outdoor propagation model for fixed wireless network
- Jha
Comparative study of path loss models for mobile communication networks
- Austin
Analyzed of path loss in outdoor to indoor model for mobile data
- Technical
Performance evaluation of channel modeling and path loss measurements for wireless communication systems in urban and rural territories. (Dept. E. Electronics)
- Y A Zakaria
- E K I Hamad
- A S Elhamid
- K M El-Khatib
Selection of radio propagation model for long term evolution (LTE) network
- P Kumar
- B Patil
- S Ram
Path loss propagation model prediction for GSM mobile network planning in Kaduna Town
- D S Nyitamen
- M Ahmed
- T A Danladi
Modified approach to estimate the propagation path loss in urban area
- D Sharma
- P K Sharma
- R K Singh
No comparisons of computer-based propagation models with experimental data collected in an urban area at 1800 MHz
- Selung
Selection of radio propagation model for long term evolution (LTE) network
- Kumar
Path loss propagation model prediction for GSM mobile network planning in Kaduna Town
- Nyitamen
Path Loss Model for 2.4GHz Indoor Wireless Networks with Application to Drones
- Gulia
Modified approach to estimate the propagation path loss in urban area
- Sharma
Characterization of prediction and enhancement of indoor propagation model with 2.4 GHz
- Tun
Review of selected wireless system path loss prediction models and its adaptation to indoor propagation environments
- Oni