Besides the above research studies, some schemes based on the deterministic and proba-bilistic framework have also been developed. Lim et al.  used the trun- cated singular value decomposition to calculate the sig- nal-distance map (SDM) based on the online measurements between the APs. Although the dynamic SDM makes it possible to capture the challenging dynamic indoor environment, the requirements of the high AP density and the modification of commercial AP’s software make the scheme impractical. Hossain et al.  proposed a robust localization algorithm that could make use of multiple wireless techniques. Schwaighofer et al.  first adopted the Gaussian pro- cess (GP) as a non-parametric tool to realize the approximation of the radio map of cellular network. Fer- ris et al.  introduced the GP into the WLAN-based indoor localization. Compared with other regression models, the GP takes into account the noise of the observation and provides the ability to approximate nonlinear signal propagation model. Madigan et al.  adopted a Bayesian hierarchical approach to realize indoor localization, which eliminated the need of know- ing the locations of the training points. Huang et al.  proposed a similar Bayesian algorithm and intro- duced the stochastic properties of measurement errors and the reliability of the measurement data into the fac- tor graph framework so as to improve the accuracy. Wymeersch et al.  also proposed a Bayesian localiza- tion algorithm and took the cooperation of the nodes into consideration to improve the accuracy. Feng et al.  employed the compressive sensing theory to analyze the localization problem. The localization problem is modeled as a sparse question and can be solved by the L1 minimization. While these methods cut down the measurement effort and partially adapt to the dynamic environment, they still require effort in terms of placing sniffers, modifying commercial AP’s software, obtaining the knowledge of AP placement, and of complex computation.
Abstract—WirelessRadio Access Point (RAP) For Radio Over Fiber (ROF) System is becoming an increasingly important technology for the indoorwireless market. The dynamic range requirements and optimum choice of laser are identified for this application. A novel architecture based on the radio over fiber application is proposed for indoor application, which gives important benefits in terms of design, installation and operation of the systems used. To meet increasing of user bandwidth and wireless demands, the Wireless design based on ROF technology has been proposed as a promising cost effective solution. In this network, a central station (CS) is connected to numerous RAP using an optical fiber to indoor connection. The aim of this project is to predict the service range for RAP for downlink transmission. The indoor RF front end consists of a photodiode, bandpass filter (BPF), power amplifier (PA) and an antenna which operating at 2.4GHz band. BPF is needed to remove out the frequency from nonlinear effect of fiber and pass through the signal at the operating frequency. The RF front end components are modelled using S-Parameter measured data from factory. Indoor picocells are used power lower than 1 Watt (30 dBm) and service range of more than 100 meters.
In 1886, the researcher, Heinrich Roudolf Hertz observed the transmission of electromagnetic waves. As the consequence of his observation, the long-debated Maxwell’s predictions of wave propagation were realized. After that, Guglielmo Marconi made the first milestone on the road of wireless communication by radio wave communication which could provide continuous contact with ships sailing the English Channel . And then, the wireless communication system has been being developed from two-way radio communications and broadcasting systems, the first generation of wireless mobile communication, the second generation (2G) digital cellular system and the third generation (3G) of wireless communication providing multimedia services and then until today 4G wireless systems with an all-IP network that integrates current available several services.
The proliferation of wireless communication and mobile computing has driven the demand of indoor location-based services (LBSs). Due to the low-cost advantage, a common approach to localization in wireless sensor networks (WSNs) is active RSS-based localization, wherein a radio device is attached to the target to be localized [1–5]. The target’s location is estimated by using RSS measurements between its radio device and other nodes in the network whose locations are known. However, in some applications such as battleﬁeld surveillance, emergency rescue, and security safeguard, it is impractical to equip the target with a wireless device. Under these situations that conventional localization systems cannot be used, RSS-based DFL systems can infer the target’s location by measuring the target’s eﬀect on the RSS of the network’s links. Therefore, RSS-based DFL without the need of carrying any device has recently become an attractive technology for determining an uncooperative target’s position [6, 7] Moreover, DFL techniques can also be used to reinforce existing device-dependent localization techniques to improve localization accuracy. In addition, compared with the existing device-free techniques such as infrared detector, video monitor and UWB radar detector, RSS-based DFL brings several advantages over other technologies by being able to work in obstructed environments, see through smoke, darkness, and walls, while avoiding the privacy concerns raised by video cameras.
This work presents the experimental results regarding the performance of a WLAN network in NLoS scenario using an ad-hoc link deployed on the emerging 24.1-24.2 GHz unlicensed band shown in figure 6. The propagation loss in a tunnel with a cross dimension larger than the wavelength of the spectrum in free space was predicted by  using the ray optical model as shown in (5). This model was adapted in this work in matlab environment to investigate the potential of the 100MHz bandwidth in 24GHz band for high data rates and improved system capacity in such environment shown in figure 6. Comparison of the empirical results and simulation models was also carried out.
The Wireless Sensor Network (WSN) is built of "nodes" where from a few to several hundreds or even thousands, where each node is connected to one or several sensors. Each such sensor network node has typically several parts: a radio transceiver with an internal antenna or connection to an external antenna, a microcontroller, an electronic circuit for interfacing with the sensors and an energy source, usually a battery or an embedded form of energy harvesting. A sensor node might vary in size from that of a shoebox down to the size of a grain of dust. The cost of sensor nodes is similarly variable, ranging from a few to hundreds of dollars, depending on the complexity of the individual sensor nodes. Size and cost constraints on sensor nodes result in corresponding constraints on resources such as energy, memory, computational speed and communications bandwidth. The topology of the WSNs can vary from a simple star network to an advanced multi-hop wireless mesh network. The propagation technique between the hops of the network can be routing or flooding.
A wireless mesh network is a communication network made up of radio nodes organized in a mesh topology as shown in Figure 1.1. Every router can communicate each other in multiple paths. This method is used as backup network in case one of the routers is down and the network is still communicated. Similar with mesh, multihop is part of mesh wirelessnetwork whereby every router connected to another router in single path as shown in Figure 1.2.
information, or ask it to maneuver in in a certain style however, most refineries lack a radionetwork infrastructure. Therefore, Wireless access points should be strategically placed throughout an atmosphere to reduce the amount of models needed to attain full dental coverage plans required for communication. Second, for an automatic system to become autonomous, it has to come with an accurate knowledge of its location. Since an oil refinery frequently is composed of tall structures made from steel, Gps navigation might not continually be available, Wireless based localization becomes essential. It complements localization techniques using other sensors built- in an automatic system. The job presented within this paper helps make the following contributions. We've carried out thorough studies of Wireless signal propagation qualities both in indoor and outside conditions, which form the foundation for Wireless AP deployment and communication. We've implemented an AP positioning formula to attain single coverage. For much better reliability and localization, we've implemented a k-coverage AP positioning formula.
efficient method for installing telecommunication cabling is presented but with a focus on the relationship of the skill of the cabling work and the installation quality. With respect to human exposure, concerns about the poten- tial health impact of electromagnetic field (EMF) radiation on the human body have arisen  and exposure val- ues have been characterized, e.g., in office environments [24, 25]. In , it was shown that in indoor environ- ments, exposure values are relevant. In , a metric is proposed to assess the environmental impact (e.g., expo- sure) of outdoor networks, but coverage is not accounted for and no (automatic) network planning is performed. In , an algorithm was presented to limit or minimize exposure in indoor environments, but it only accounted for coverage and the electric-field strength throughout the building. When the network planner imposes multi- ple requirements (high coverage, low installation cost, and low exposure), more complex optimization algorithms are required. In , the network planning problem is solved in radio-frequency identification (RFID) systems by using an altered version of a particle swarm opti- mization (PSO) algorithm. Genetic algorithms (GAs) have been used in [9, 29] for planning wireless communication networks. In , coverage and exposure are jointly opti- mized for indoor networks. In , a green optimization metric is used, but it is aimed at outdoor cellular base stations. In , energy-efficient wireless access networks are designed. However, none of these takes into account the network installation cost, the provided coverage, and an advanced exposure minimization at a same time for indoorwireless networks.
In WSNs, these radio transceivers transmit low-power signals, which make radiated signals more prone to noise, interference, and multi-path distortion. Also, they rely on antennas with non-ideal radiation patterns, which lead to anisotropic behaviour. To see to the proper monitoring of the wireless system, Wireless Sensor Network (WSN) can be deployed to the monitoring environments to sense, analyze and transmit/retransmit the data from remote distances wirelessly. It is necessary to evaluate the quality of the transmitted signals such that error detection, correction and control can be effected simultaneously in order to obtain an error free result. Therefore, this work provides the frame work for the characterization of an indoor environment. The sensor nodes used in the work are deployed at angles to obtain an all round measurements of signal strength in the form of Received Signal Strength Indicator (RSSI). The measurements were done for several months and the result obtained were analysed. The measurement environment was characterised and the pathloss model of the environment was developed.
An RF-based indoor localization design targeted for wireless sensor networks (WSNs) is presented. The energy-eﬃciency of mobile location nodes is maximized by a localization medium access control (LocMAC) protocol. For location estimation, a location resolver algorithm is introduced. It enables localization with very scarce energy and processing resources, and the utilization of simple and low-cost radio transceiver HardWare (HW) without received signal strength indicator (RSSI) support. For achieving high energy-eﬃciency and minimizing resource usage, LocMAC is tightly cross-layer designed with the location resolver algorithm. The presented solution is fully calibration-free and can cope with coarse grained and unreliable ranging measurements. We analyze LocMAC power consumption and show that it outperforms current state-of-the-art WSN medium access control (MAC) protocols in location node energy-eﬃciency. The feasibility of the proposed localization scheme is validated by experimental measurements using real resource constrained WSN node prototypes. The prototype network reaches accuracies ranging from 1 m to 7 m.With one anchor node per a typical oﬃce room, the current room of the localized node is determined with 89.7% precision.
The gateway node is designed to improve the operability of existing building automation systems and external networks. Remote users can access the system information via the Internet and mobile networks. This feature allows users to leave the real-time control and monitoring of the task process. The gateway node supports three function interface, ZigBee can access the wireless sensor network, also can through the indoor local wireless LAN or ASDL access to the Internet, or you can communicate through the GPRS terminal and mobile phone network. The gateway integrates the secure data program and detects and processes the information through the nodes. The state data of all access devices is integrated into the gateway node. In this way, all the states of each device in the system are continuously stored and updated in real time. Remote users can control and detect the status of all devices in the building.
Indoor robot global path planning needs to complete the motion between the starting point and the target point according to robot position command transmitted by the wirelessnetwork. Behavior dynamics and rolling windows in global path planning methods have limitations in their applications because the path may not be optimal, there could be a pseudo attractor or blind search in an environment with a large state space, there could be an environment where offline learning is not applicable to real-time changes, or there could be a need to set the probability of selecting the robot action. To solve these problems, we propose a behavior dynamics and rolling windows approach to a path planning which is based on online reinforcement learning. It applies Q learning to optimize the behavior dynamics model parameters to improve the performance, behavior dynamics guides the learning process of Q learning and improves learning efficiency, and each round of intensive learning action selection knowledge is gradually corrected as the Q table is updated. The learning process is optimized. The simulation results show that this method has achieved remarkable improvement in path planning. And, in the actual experiment, the robot obtains the target location information by wirelessnetwork, and plans an optimized and smooth global path online.
A Wireless Local Area Network (LAN) is a Radio frequency (RF) data communications system. WLANs transmit and receive data Over the Air (OTA) and thus collectively combine data connectivity with ease of mobility. Wireless LANs today provide wireless access to vital network resources such as large, multi- location enterprises, small and medium size enterprises as well as Hospitals, Hotel, Airports and homes. Wireless LANs are being widely recognized as a viable, cost-effective general-purpose solution in providing high-speed real-time access to information.An Intrusion Detection System (IDS) is a program that analyzes what happens or has happened during an execution and tries to find indications that the computer has been misused. IDSs can be classified as the tools and methods that monitor computer systems and network traffic to identify. Snort is an open source network intrusion detection system (NIDS) created by Martin Roesch. Snort is a packet sniffer that monitors network traffic in real time, scrutinizing each packet closely to detect a dangerous payload or suspicious anomalies. In my Research work I will define that how snort file used in WLAN system and which types of problems facing in this system.
This work presents directional radio channel measurements in the W-band using a commercial versatile channel sounder based on a vector network analyzer (VNA), capable of measuring scattering parameters from 75 to 500 GHz with frequency converters. The commercial setup has been modified by increasing the distance for one of the converters using precision coaxial cables and avoiding the use of amplifiers. Firstly, initial distance-dependent single-input single- output (SISO) measurements of indoorradio channels are presented to assess the validity of the setup in the 75 – 110 GHz frequency band with highly directive horn antennas. Then, single-input multiple-output (SIMO) radio channels were measured at 94 GHz using one directional and one omnidirectional antenna mounted on two positioners. Initial channel characterization is presented comprising root mean square (rms) delay spread, rms angular spread, K-factor, and path loss in an indoor environment at 94 GHz.
architectures by enabling the wireless connections between BSs, which is similar to the Hybrid Wireless Mesh Networks. Some BSs may connect to the wired backbone/core networks and function as gateways. Since BSs can be deployed without necessarily connecting to wire backbone or core networks, it is more flexible and less costly in planning the locations of BS.
Independent of the actual energy source that is used for powering the accessnetwork achieving the highest possible energy efficiency is very important. This applies to conventional, grid-powered network elements in larger cities as well as (and often even more so) to, for example, solar-powered base stations in developing countries withoutreliable grid-based energy. Effective energy management is thus a key requirement for successful and profitableoperation of mobile communication networks.
While this paper addresses some concerns over the viability of network MIMO in practice, several others remain, especially in the context of a larger-scale outdoor cellular deployment. Foremost among these are the band- width and latency requirements on the backhaul network connecting the access points to each other (or to a central processor), to facilitate the exchange of user data, channel state information, control signaling, and so forth. It would also be desirable to distribute the computation required to implement network MIMO among many nodes, so that the solution scales well with the size of the network. Finally, in a low-SNR environment, estimating the channels to/from faraway access points without excessive pilot overhead might require data-aided channel estimation algorithms. Further work is needed in all these areas to make network MIMO truly practical.
Wirelessnetwork is often referred to as unbounded media in which the network transmission is unrestricted. In wirelessnetwork the signals are transmitted through the atmosphere as electromagnetic waves. Wireless technology is a truly revolutionary paradigm shift, enabling communications between devices and people from any location. It also underpins exciting applications such as sensor network, automated highways, smart phones etc. Now a day’s wireless networks have been as essential part of communication. Society moves towards information centricity, the need to have information accessible at any time and any where takes on a new dimensions. Growth in commercial wireless networks occurred primarily in the late 1980’s and continues in 2000.
adaptive distributed application services, is a fundamental challenge for autonomic system research. Policy Based Management (PBM) has emerged as an attractive approach for flexibly and dynamically controlling systems, services and network behaviour. In particular, over the last few years it has attracted increasing attention from researchers, industry and standards bodies (e.g. IETF, DMTF and TMForum). However, PBM suffer in two important respects. Firstly, as the managed system scales in complexity, it becomes increasingly complicated to determine the impact of policy changes on system behaviour. This problem arises due to the difficulty in linking policy models, which are usually expressed in specific policy languages, to suitable models of both elemental and emergent composite system behaviour. Secondly, current PBM systems are weak in resolving business- and user-level policies into enforceable system-level policies in a generic and automated way. Such interpretation and resolution usually requires expert mediation by a policy author with considerable domain knowledge. This approach becomes unsustainable as responsibility for the management of resources is increasingly delegated and decentralised, reflecting current organisational trends. The problem is further exacerbated as organisations become integrated with other (partner) organizations in e-commerce value chains, virtual organisations, Internet communities or collaborative projects between organisations. This results in significant increases in both the quantity and heterogeneity of the resources that must be managed by the human administrator.