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This paper discusses mobile ad hoc networks (MANETs), which are characterized by their infrastructure-less, multihop communication capabilities. It outlines the need for these networks in scenarios where fixed infrastructures are impractical, such as military operations and emergency situations. Additionally, it covers signal propagation issues, routing protocols, power-aware routing strategies, and the role of MAC mechanisms in optimizing communication within MANETs.
International Journal of Advanced Research in Computer Science and Electronics Engineering (IJARCSEE), 2019
The demand for accelerated speed, anywhere, and any time connectivity has made wireless communication networks increasingly dense. This has resulted into intense research on how speed of data transfer, security of data, spectrum sharing, and storage of the big data realized can be improved in an efficient way. However the major challenge which has necessitated continuous research progress in the subject is the study of communication path loss and shadowing and how it can be eliminated or lessened to improve the channels involved. This paper will perform experiments on radio propagation models, ray tracing models and perform its simulations in Matlab, as well as provide a review of the various path loss models. The simulation results obtained indicated that when the receiver far away from the transmitter, the signal begins to be weaker and weaker until it is lost. However if the receiver will move away from a closer base station, and while the signal is weakening, it encounters another base station, the two base stations performs a handshake and the signal will start gaining strength.
Eswar Publications, 2023
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.
IEEE Transactions on Vehicular Technology, 2000
We investigate an ad hoc network where node locations are distributed according to a homogeneous Poisson process with intensity λ. We assume that all the nodes are equipped with an identical wireless transceiver capable of operating satisfactorily up to a certain maximal link loss. Our link model depends on the length of the link and on random log-normal fading. Each node functions as a source and a destination of data packets and may also serve as a repeater to transport the packets over multihop routes, as determined by the network router. We study two important properties of the network. The first is connectivity, viz., given the peak transmit power of a node, the probability that a node cannot communicate with a random destination node at distance D when at most t hops are allowed. We provide the exact analytical results for t = 1 and t = 2 and an iterative lower bound for t > 2. We calculate the average number of hops of the minimum-hop-count route between a source and a destination at a distance D apart. The second property relates to power consumption-an important parameter when the nodes are battery operated. We derive the cumulative distribution function of the total transmit energy required per data packet when the distance between the source and the destination node is D, and only one or at most two hops, are allowed. We graphically show the benefit of allowing two hops over just one.
2013
The mobile radio channel places strong limitations on the performance of wireless communication systems because the transmission principle in wireless communication is more complex than those of the wired networks. In this paper we discuss the radio propagation with an objective to provide an overview of various characteristics of radio channel and an understanding of the process and factors that influences these characteristics. Section I describe a typical outdoor scenario for terrestrial mobile radio channel and principle causes of information loss (multipath fading). Section II presents the various radio channel characteristics like path loss which is used to denote the local average received signal power relative to the transmit power and helps in providing the information on coverage area. Other higher order statistical characteristics such as level crossing rate (lcr) and average duration of fade (adf), which relates the time rate of change of the received signal to the signa...
2011
Abstract— Simple two-ray model and FRIIS free-space model have been widely used in the literatures as the propagation models for the performance analysis of Mobile Ad hoc Network (MANET). These models do not represent real world scenarios where the environmental clutter varies widely for a given distance between two mobile nodes. In this paper, a more practical model called shadowing model has been adopted. The performances of ad hoc network have been investigated under this shadowing model. Analytical analysis of shadowing effects has also been presented in this paper. Three solutions have also been proposed in this paper to minimize the shadowing effects. Simulation results show that these three solutions minimize the shadowing effects.
In free space propagation, the propagation path between a transmitter and a receiver is direct to one another. Having no obstructions present in free space, there are minimal to no attenuation in signals. Still, there exists a free-space path loss. This is defined as the loss of the radio wave signal or its signal while it travels in free space. Determining the path loss is crucial for designing communication systems so that it can work at its best despite the issues that can be encountered. Additionally, path loss has been used in radio communications and wireless survey tools in order to identify the signal strength of antennas. With the increase in importance for wireless devices such as survey tools and software, it has become helpful to understand the concept of radio path loss as a whole. This paper focuses on simulating the free space propagation path loss to have a clear understanding of its function and the factors that affect it. The software used for this is MATLAB so that graphs can be obtained to have a direct and simple visual of the path loss.
Journal of Sensors, 2015
This study highlights the importance of the physical layer and its impact on network performance in Mobile Ad Hoc Networks (MANETs). This was demonstrated by simulating various MANET scenarios using Network Simulator-2 (NS-2) with enhanced capability by adding propagation loss models (e.g., modified Two-Ray Ground model, ITU Line of Sight and Nonline of Sight (ITU-LoS and NLoS) model into street canyons and combined path loss and shadowing model (C-Shadowing)). The simulation results were then compared with the original Two-Ray Ground (TRG) model already available into NS-2. The scenario primarily simulated was that of a mobile environment using Random Way Point (RWP) mobility model with a variable number of obstacles in the simulation field (such as buildings, etc., causing variable attenuation) in order to analyze the extent of communication losses in various propagation loss models. Performance of the Ad Hoc On-demand Distance Vector (AODV) routing protocol was also analyzed in an ad hoc environment with 20 nodes.
This paper gives an overview of the propagation models in wireless communication systems. Wireless communication system uses several physical media, ranging from sound to radio to light. These characteristics are affected by the physical environment between the transmitter and receiver. Wireless communication system suffers from various unwanted effects of fading which may be caused due to multipath propagation, path loss, shadowing, Doppler spread and cochannel interference. There are various signal propagation ranges in wireless communication channels.
IEEE International Conference on Industrial Informatics (INDIN), 2013
Wireless Sensor Networks are an emerging technology which has been recently adopted in many applications. Due to its wireless nature, the analysis of the radio propagation models plays an important role for performance evaluation in both theoretical and practical aspects. In this regards, path loss exponent is one of the most important parameter which has been considered widely in wireless communications analysis. There are several theoretical evaluations of path loss exponent for wireless sensor networks available in the literature. However there is a lack of experimental evaluation of both path loss exponent and the effect of shadowing. In this paper, three environments (free space, in building and industrial), where wireless sensor nodes are widely deployed, have been chosen in order to evaluate the experimental analysis. Path loss and path loss exponent are measured by means of Received Signal Strength Indicator (RSSI) and based on them, the standard deviation of shadowing effect is also calculated. All the measured parameters are compared with the theoretical analysis available in the literatures.
IEEE Transactions on Antennas and Propagation, 2021
Simple and accurate expressions for path gain are derived from electromagnetic fundamentals in a wide variety of common environments, including Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) indoor, urban canyons, urban/rural macro, outdoor-indoor and suburban streets with vegetation. Penetration into a scattering region, sometimes aided by guiding, is the "universal" phenomenon shared by the diverse morphologies. Root Mean Square (RMS) errors against extensive measurements are under 5 dB, better than 3GPP models by 1-12 dB RMS, depending on environment. In urban canyons the models have 4.7 dB RMS error, as compared to 7.9 dB from linear fit to data and 13.9/17.2 dB from LOS/NLOS 3GPP models. The theoretical path gains depend on distance as a power law with exponents from a small set {1.5, 2, 2.5, 4}, specific to each morphology. This provides a theoretical justification for widely used power law empirical models. Only coarse environmental data is needed as parameters: street width, building height, vegetation depth, wall material and antenna heights.
2004
Publisher Summary Communication is maintained by the transmission of data packets over a common wireless channel. The absence of any fixed infrastructure such as an array of base stations, make ad hoc networks radically different from other wireless local area networks (LANs). All nodes in an ad hoc network are required to relay packets on behalf of other nodes. Hence, a mobile ad hoc network is sometimes called a multihop wireless network. The physical layer must tackle the path loss, fading, and multi-user interference to maintain stable communication links between peers. This chapter highlights the main aspects of designing the physical transmission system, which are dependent on the characteristics of the radio propagation channel such as path loss, interference (co-channel), and fading. Directional transmission can reduce the amount of interference, reduce packet error, and directional antennas have a higher gain due to their directivity. Despite these advantages, the usage of ...
In this section, we are going to explain about wireless propagation channel. The communication between transmitter and receiver is affected by different components which have been placed through the environment of wireless propagation area. The simplest case is path loss on free space which there is direct line of sight between sender and receiver. The signal strength varies with distance of receiver from sender. We are also deals about different models of wireless propagation such as: d −n power law, Shadowing model, Rayleigh and Ricean model which come due to effect of reflection, diffraction and scattering of electromagnetic wave and also moment of mobile station.
2020
The trend of exchanging information data will continuously increase due to the rapid development of mobile communication networks. The new fifth-generation (5G) technology is designed to support the ever increasing demand for internet traffic volume over wide coverage ranges. This paper focuses on the studies of empirical path loss prediction models for network planning of 5G mobile communication systems. The relationship between path loss and other wireless propagation parameters such as transmitter-receiver antennas separation distance, antenna heights, operating frequency are presented to improve the performance optimisation of wireless networks. The data provided in this paper was analysed in MATLAB computer program to predict signal path loss; estimate radio coverage; avoid interferences; and determine received power level. The results based on the studied model showed that the propagation path loss decreases in accordance with the increase in base station tower antenna height....
Computational intelligence, 2008
In this paper, we will address the issues of modeling and simulating wireless ad hoc network and illustrate the impact of physical propagation model on ad hoc network routing protocol. The dynamic wireless channel is modeled with log-distance path loss model and log-normal shadow model. Further we will implement Rayleigh fading model to represent fading due to Doppler's effect caused by relative movement between the nodes. We will show that the performance of typical routing protocol such as OLSR significantly depends on the wireless channel through simulation in two different environments: open_environment characterized by open area and city_environment characterized by urban environment. The simulation results will show that the network degrades and the average delay and the routing packet overhead significantly increases in a higher attenuating environment such as the city_environment.
2008 8th International Conference on ITS Telecommunications, 2008
This paper shows results of narrowband path loss measurements in a typical urban and suburban mobile-to-mobile radio environment at 900 MHz band. The measurements were made with two omni-directional antennas with a transmitter and a receiver antenna height of 1.5 meters. The results of measurements provide practical values for path loss exponent and standard deviation of shadowing in a non-line-of-sight
International Journal on Cybernetics & Informatics , 2020
The paper deals with the study based on the comparative analysis of radio propagation models for mobile cellular wireless communication of global system for mobile at frequencies 0.9 GHz and 1.8 GHz, respectively. The path loss propagation models arevital tool for planning the wireless network as well as designed to predict path loss in a meticulous environment. Various propagation models: Free-space model, CCIR (ITU-R) model, Hata model, Ericson model, and Stanford University Interim (SUI) model have been studied and examined through analytically from the base station (BS) to mobile station (MS) and vice versa followed by respective simulation performance evaluation by using Matlab simulator. The observed data is collected at the operating frequency of 0.9 GHz from various environments (high density region and low density region) using the spectrum analyzer and path loss comparison is shown for different model.
The performance of any communication system is eventually determined by the medium which the message signal passes through. This medium may be an optical fiber, a hard disk drive of a computer or a wireless link, is referred to as communication channel. There exists a large variety of channels, which may be divided into two groups. If a solid connection exists between transmitter and receiver, the channel is called a wired channel. If this solid connection is missing, this connection is called a wireless channel. Wireless channels differ from wired channels, due to their unreliable behavior compared to wired channels. In wireless channels the state of the channel may change within a very short time span. This random and severe behavior of wireless channels turns communication over such channels into a difficult task. There are several different classifications regarding the wireless channels. Wireless channels may be distinguished by the propagation environment encountered. Many different propagation environments have been identified, such as urban, suburban, indoor, underwater or orbital propagation environments, which differ in various ways. The wireless channel puts fundamental limitations on the performance of wireless communication systems. The transmission path between the receiver and the transmitter can be altered from simple line-of-sight to one that is drastically obstructed by buildings, foliage and mountains. Even the speed of the mobile impacts how rapidly the signal level fades. Modeling the wireless channel has historically been one of the most difficult parts of the communication system design and is typically done in a statistical manner, based on measurements made specifically for a designated communication system or spectrum allocation.
2012
Wireless technologies have had an enormous impact on networking in recent years. It can create new business opportunities and allow users to communicate and share data in a new fashion. Wireless network decrease installation cost, reduce the deployment time of a network and overcome physical barrier problems inherent in wiring. In this article, we give a presentation of wireless propagation in atmosphere. We discuss in depth the characteristics of propagation. To complement the analysis, we give an account of experiments performed in Matlab-based.
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