Aleksandar M. Neskovic

Positioning in WLAN environment by use of artificial neural networks and space partitioning

Short range wireless technologies such as wireless local area network (WLAN), Bluetooth, radio frequency identification, ultrasound and Infrared Data Association can be used to supply position information in indoor environments where their infrastructure is deployed. Due to the ubiquitous presence of WLAN networks, positioning techniques in these environments are the scope of intense research. In this paper, the position determination by the use of artificial neural networks (ANNs) is explored. The single ANN multilayer feedforward structure and a novel positioning technique based on cascade-connected ANNs and space partitioning are presented. The proposed techniques are thoroughly investigated on a real WLAN network. Also, an in-depth comparison with other well-known techniques is shown. Positioning with a single ANN has shown good results. Moreover, when utilising space partitioning with the cascade-connected ANNs, the median error is further reduced for as much as 28%.

Improving the efficiency of measurement procedures for assessing human exposure in the vicinity of mobile phone (GSM/DCS/UMTS) base stations

Standards stipulate 6-min time interval of averaging for measurements of radio-frequency electromagnetic fields to assess human exposure to non-ionising radiation. Having in mind the base stations of public land mobile systems, the time interval defined in such a way noticeably limits the number of measuring points in practical applications. In this paper, based on the results of measurements in the vicinity of a multisystem base station (Global System for Mobile Communications [GSM], Digital Communication System [DCS] and Universal Mobile Telecommunications System [UMTS]), it was shown that the measurement process can be significantly accelerated by using shorter time intervals of averaging--15 s, 30 s and 1 min. It was found that measurement results differed from the 6-min root-mean-square mean by 10.5 %, 15.9 and 19 %, respectively, while the uncertainty of the measurements was increased by 3.0 %, 3.8 and 4.4 %, respectively. Shorter time-averaging intervals would reduce the total duration of the exposure assessment survey, while not compromising too much on measurement quality.

Comparative analysis of RSSI, SNR and Noise level parameters applicability for WLAN positioning purposes

In this paper, the extensive experimental analysis of RSSI, SNR and Noise level parameters usefulness for WLAN positioning purposes was conducted. Four positioning models, based on artificial neural networks, with RSSI, SNR, Noise level and both RSSI and SNR as networks inputs, were created, trained and verified. The obtained results have shown that, contrary to the common knowledge, SNR parameter is equally suitable for WLAN positioning purposes as RSSI parameter. In addition, the obtained results pointed out that the space distribution of the noise level parameter contains less location dependant information than RSSI or SNR.

Application of artificial neural networks in classification of digital modulations for Software Defined Radio

This paper presents one feature based method for automatic classification and recognition of 7 digital modulations for Software Defined Radio. After reviewing some spectral based features, new statistical based ones are proposed. The classification is conducted with artificial neural networks (ANN). Three architectures are investigated: Multilayer Perceptron (MLP) with one and two hidden layers and Probabilistic Neural Network (PNN). Simulation results for SNR levels of 0, 5, 8, 10dB are shown. The simulation as well as comparison of these three architectures reveals that MLP with two hidden layers exhibits best classification results with 95% success rate at 5dB SNR level, while all of them correctly classify in over 98% at 10dB SNR.

Positioning in Indoor Mobile Systems

At present times people travel far greater distances on daily bases than our not so distanced ancestors had travelled in their lifetimes. Technological revolution had brought human race in an excited state and steered it towards globalization. Nevertheless, the process of globalization is not all about new and faster means of transportation or about people covering superior distances. Immense amount of information, ubiquitous and easily accessible, formulate the essence of this process. Consequently, ways through which the information flows are getting too saturated for free usage so, for example, frequency spectrum had become a vital natural resource with a price tagged on its lease. However, the price of not having the information is usually much higher. By employing various wireless technologies we are trying to make the most efficient use of frequency spectrum. These new technologies have brought along the inherent habit of users to be able to exchange information regardless of their whereabouts. Higher uncertainty of the user’s position has produced increase in the amount of information contained in its position. As a result, services built on the location awareness capabilities of the mobile devices and/or networks, usually referred to as Location Based Services (LBS, also referred to as LoCation Services – LCS), have been created. Example of services using the mobile location can be: location of emergency calls, mobile yellow pages, tracking and monitoring, location sensitive billing, commercials, etc. With the development of these services, more efforts are being pushed into producing the maximum of location-dependent information from a wireless technology. Simply, greater the amount of information available – more accurate the location estimate is. Whereas in outdoor environment the satellite-based positioning techniques, such as the Global Positioning System (GPS), have considerable advantages in terms of accuracy, the problem of position determination in an indoor environment is much farther from having a unique solution. Cellular-based, Computer vision, IrDA (Infrared Data Association), ultrasound, satellite-based (Indoor GPS) and RF (Radio Frequency) systems can be used to

Short-term fading simulator based on artificial neural networks

In this paper, a novel technique for simulation of the short-term fading is presented and analyzed. A proposed solution is based on a trained artificial neural network (in further text ANN) and an oscillator for regulating the simulation process. In order to obtain adequate input data for training, cross-validation and testing, extensive measurements of electric field level were carried out in indoor environment. Statistical analysis of gained results has shown good performances of the proposed technique, and thereby the possibility for applying it in the real life situations.

Correlated EEG Signals Simulation Based on Artificial Neural Networks

In recent years, simulation of the human electroencephalogram (EEG) data found its important role in medical domain and neuropsychology. In this paper, a novel approach to simulation of two cross-correlated EEG signals is proposed. The proposed method is based on the principles of artificial neural networks (ANN). Contrary to the existing EEG data simulators, the ANN-based approach was leveraged solely on the experimentally acquired EEG data. More precisely, measured EEG data were utilized to optimize the simulator which consisted of two ANN models (each model responsible for generation of one EEG sequence). In order to acquire the EEG recordings, the measurement campaign was carried out on a healthy awake adult having no cognitive, physical or mental load. For the evaluation of the proposed approach, comprehensive quantitative and qualitative statistical analysis was performed considering probability distribution, correlation properties and spectral characteristics of generated EEG processes. The obtained results clearly indicated the satisfactory agreement with the measurement data.

Optimization of routing protocols and metrics for multi-channel multi-interface wireless mesh networks

One of the main goals of this paper is to improve the existing routing metrics in such a way to track fast changes that occur in the link state. Three new metrics are proposed by introducing a parameter based on the received signal level into three known metrics. The results have shown that proposed metrics significantly outperform original metrics. Moreover, a new link layer protocol, Quality of Service Hybrid Multi Channel Protocol (QoS-HMCP), that takes into account the need for QoS support in multi-channel multi-interface Wireless Mesh Networks (MCMI - WMNs) is proposed in this paper. The results have shown that implementation of QoS-HMCP protocol in MCMI-WMN results in a very small delay for voice and video traffic, while low-priority traffic categories were still able to access the media.

Artificial neural network based simulation of short-term fading in mobile propagation channel

A novel method for correlated short-term fading simulation is presented and analyzed in this paper. Proposed solution is based on artificial neural networks. In order to obtain an adequate training data set, extensive measurements of the electric field strength were carried out in an indoor environment. Due to its modular architecture, the proposed simulator could be used to generate potentially any number of correlated fading processes (or a single fading process). For verification purposes, the proposed method was compared against the existing simulation methods (of both single and two correlated fading processes). The quantitative and qualitative analysis showed that the proposed method was in better agreement with the measurements comparing to the existing methods.

Estimation of maximal number of HTTP users in a TETRA cell

This paper provides results regarding the maximal number of TETRA packet data service users which can be served by one TETRA cell. The analyzed scenario assumes that users are using web based applications and generate HTTP/IP packet data traffic. The paper considers single-slot packet-data TETRA system mode. A range of simulations and measurements were performed to evaluate the average packet delay and packet failure probability corresponding to HTTP traffic on the packet data channel in a TETRA cell. Based on the simulation and measurement results a recommendation on the maximum number of users was derived.