Improvement of Fading Channel Modeling Performance for Wireless Channel

Fading channel modeling is generally defined as the variation of the attenuation of a signal with various variables. Time, geographical position, and radio frequency which is included. Fading is often modeled as a random process. Thus, a fading channel is a communication channel that experiences fading. In this paper, the proposed system presents a new design and simulate a wireless channel using Rayleigh channels. Rayleigh channels using two approaches (flat and frequency-selective fading channels) in order to calculate some path space loss efforts and analysis the performance of different wireless fading channel modeling. The results show that the bite error rate (BER) performance is dramatically improved in the value of signal to noise ratio (SNR) is equal to 45dB. Finally, the experimental results show that the proposed method enhances the performance of fading channel modeling by reducing the error of BER when the SNR is reduced also. Moreover, the more accurate model is Rayleigh model which can be considered for developing fading channel model

Reconfigurable OFDM Tx/Rx for multi-purpose physical layers over fast Heterogenous Systems

Los objetivos principales en este proyecto son los análisis matemáticos y prácticos de diferentes generadores de variables Rayleigh, estimadores de canal y estrategias para su implementación de una manera reconfigurable a través de Simulink y FPGA. La diferentes técnicas para generar variables Rayleigh usadas en este proyecto son las siguientes: la suma de sinusoides, la técnica de Smith y el método de Bealieu-Young. El primero se base en la suma de exponenciales complejas mientras los otros dos se basan en la IDFT. De todos estos métodos vemos que el método de Bealieu-Young tiene la mínima complejidad para la misma precisión que los otros métodos. En consecuencia ha sido el escogido para ser implementado en la FPGA Cuando hablamos de estimadores de canal se han considerado dos enfoques diferentes. El primero consiste en introducir los pilotos de manera uniforme a lo largo de la trama, mientras el otro introduce los pilotos al principio de la trama. A la hora de estimar la trama dos estrategias han sido analizadas: el estimador de canal promedio y el estimador de canal por interpolación lineal. La técnica de promediado se puede considerar como un filtro paso bajo. En este caso el estimador por promediado es capaz de eliminar la frecuencias altas que son introducidas por el ruido. Por el contrario el estimador por interpolación lineal, ofrece los mejores resultados cuando el ruido es bajo. En ambos casos hemos calculado la potencia de error en el proceso de estimación. Los resultados prácticos y teóricos obtenidos a través de Matlab y Simulink concuerdan a la perfección. En un escenario co-simulado la FPGA trabaja con Matlab. Los resultados nos dicen que el sistema se ve limitado por el cable que conecta ambos sistemas. Por lo que es crucial para aprovechar al máximo la potencia de la FPGA que el sistema si integre por completo dentro de la FPGA y si no es posible usar conexiones de alta velocidad. English: The main goals of this project are the study from a mathematical and practical point of views of different correlated Rayleigh fading generator, linear channel generator estimators, and strategies for implementing them in a reconfigurable way by means of Simulink and FPGA. Thus it is not necessary to remap again the FPGA for different configurations of the channel estimation. The techniques of correlated Rayleigh fading that has been analysed under this project are the next: the sum of sines, the Smith technique and Bealieu-Young method. The first one consists on a sum of exponentials whereas the others two algorithms are based on decompositions based on IDFT. From all these methods we show that the Bealieu-Young channel generation requires a lower complexity for the same accuracy. Consequently, this method of channel estimation is the technique that has been implemented into the FPGA. Regarding to the channel estimation process two different approaches has been considered. The first one consists on spreading the pilots uniformly along the frames, whereas the other one places the pilots at the beginning of the frames. Next, in order to estimate the channel two strategies have been analysed: the averaging channel estimator and the linear interpolation technique. The averaging strategy can be considered as a low pas filter. So, it offers the best results when there channel is flat and the noise is high. In this case, the averaging filter is able to remove the high frequencies that introduce the noise signal. On the contrary, the linear interpolator gives the best performance when the noise level is small. Moreover, it allows a degree of mobility, which limits the distance between the pilots. In both cases we have computed the theoretical error power of the channel estimators. The practical results from Matlab and Simulink perfectly match with the theoretical ones. In a co-simulation environment the FPGA works with Matlab. The results show that the speed of the simulation is limited by the wire that connects the FPGA and Matlab. So, it is crucial for a hardware accelerator to try to integrate the full system into the FPGA and if it is not possible to use high-speed links between the FPGA and Matlab

Multiple-input multiple-output system simulation for spinning vehicles

This paper investigates the performance of a multiple-input multiple-output (MIMO) wireless communication system, when the transmitter is located on a spinning vehicle. In particular, a 2x2 MIMO system is used, with Alamouti coding at the transmitter. Both Rayleigh and Rician statistical models are considered in this paper and are combined with a deterministic spinning model to simulate the channel. The spinning of the transmitting vehicle, relative to the stationary receive antennas causes additional signal fading, and complicates the decoding and channel estimation. The simulated bit error rate is the primary performance metric used. A 4x2 asymmetric Alamouti coding scheme is proposed to increase the performance of the space-time code in this configuration. The 2x2 Alamouti channel code is shown to perform better than the Maximal Ratio Receiver Combining (MRRC) and single receiver (2x1) system in some circumstances and performs similarly to the MRRC in the broadside case. The unsymmetric 4x2 Alamouti code is shown to improve the performance of the 2x2 Alamouti code in the broadside case --Abstract, page iii

Detection of OFDM Signals Using Pilot Tones and Applications to Spectrum Sensing for Cognitive Radio Systems

Nowadays there are an increasing number of wireless devices which support wireless networking and the need for higher data rate communication is increasing rabidly. As more and more systems go wireless, approaching technologies will face spectral crowding and existence of wireless devices will be an important issue. Because of the limited bandwidth availability, accepting the request for higher capacity and data rates is a challenging task, demanding advanced technologies that can offers new methods of using the available radio spectrum. Cognitive radio introduces a key solution to the spectral increasing issue by presenting the opportunistic usage of spectrum that is not heavily occupied by licensed users. It is a latest idea in wireless communications systems which objective to have more adaptive and aware communication devices which can make better use of available natural resources. Cognitive radio appears to be an attractive solution to the spectral congestion problem by introducing the notion of opportunistic spectrum use. Cognitive radios can operate as a secondary systems on top of existence system which are called primary (or licensed) systems. In this case, secondary (cognitive) users need to detect the unused spectrum in order to be able to access it. Because of its many advantages, orthogonal frequency division multiplexing (OFDM) has been successfully used in numerous wireless standards and technologies. It\u27s shown that OFDM will play an important role in realizing the cognitive radio concept as well by providing a proven, scalable, and adaptive technology for air interface. Researches show that OFDM technique is considered as a candidate for cognitive radio systems. The objective of this dissertation is to explore detecting of OFDM modulated signals using pilot tones information. Specifically we applying Time-Domain Symbol Cross-Correlation (TDSC) method in the confect of actual 4G wireless standards such as WIMAX and LTE. This detection is only based upon the knowledge of pilot structures without knowledge of received signal so that, it can be performed on every portion of the received signal. The approach induces Cross-Correlation between pilots subcarriers and exploits the deterministic and periodic characteristics of pilot mapping in the time frequency domain

A Self-organizing Hybrid Sensor System With Distributed Data Fusion For Intruder Tracking And Surveillance

A wireless sensor network is a network of distributed nodes each equipped with its own sensors, computational resources and transceivers. These sensors are designed to be able to sense specific phenomenon over a large geographic area and communicate this information to the user. Most sensor networks are designed to be stand-alone systems that can operate without user intervention for long periods of time. While the use of wireless sensor networks have been demonstrated in various military and commercial applications, their full potential has not been realized primarily due to the lack of efficient methods to self organize and cover the entire area of interest. Techniques currently available focus solely on homogeneous wireless sensor networks either in terms of static networks or mobile networks and suffers from device specific inadequacies such as lack of coverage, power and fault tolerance. Failing nodes result in coverage loss and breakage in communication connectivity and hence there is a pressing need for a fault tolerant system to allow replacing of the failed nodes. In this dissertation, a unique hybrid sensor network is demonstrated that includes a host of mobile sensor platforms. It is shown that the coverage area of the static sensor network can be improved by self-organizing the mobile sensor platforms to allow interaction with the static sensor nodes and thereby increase the coverage area. The performance of the hybrid sensor network is analyzed for a set of N mobile sensors to determine and optimize parameters such as the position of the mobile nodes for maximum coverage of the sensing area without loss of signal between the mobile sensors, static nodes and the central control station. A novel approach to tracking dynamic targets is also presented. Unlike other tracking methods that are based on computationally complex methods, the strategy adopted in this work is based on a computationally simple but effective technique of received signal strength indicator measurements. The algorithms developed in this dissertation are based on a number of reasonable assumptions that are easily verified in a densely distributed sensor network and require simple computations that efficiently tracks the target in the sensor field. False alarm rate, probability of detection and latency are computed and compared with other published techniques. The performance analysis of the tracking system is done on an experimental testbed and also through simulation and the improvement in accuracy over other methods is demonstrated

"Análisis de Desempeño de un Sistema MIMO-OFDM con Predicción de Canal"

Las comunicaciones inalámbricas en que el canal de transmisión inalámbrico se define por efectos de dispersión por movimiento y obstáculos físicos entre transmisor y receptor, son un claro ejemplo de los retos que se enfrentan para lograr una comunicación efectiva mediante un ambiente ruidoso. La demanda de múltiples servicios de telecomunicaciones, como transmisión de voz, video y datos, ha hecho que la capacidad de transmisión y recepción de los sistemas de comunicaciones aumente para lograr grandes tasas de transmisión de datos con baja cantidad de errores recibidos, que hagan la comunicación confiable y utilizando el mínimo de recursos como espectro radioeléctrico y energía (potencia). Los sistemas de cuarta generación (4G) han llegado en los últimos años, con diversas tecnologías, para cumplir con los requerimientos impuestos; en estos sistemas se utilizan técnicas como el uso de múltiples antenas (Multiple Input – Multiple Output, MIMO), modulación (Orthogonal Frequency Division Multiplexing, OFDM), codificación, estimación y predicción de canal para adaptar el sistema a las condiciones de este, y así lograr el objetivo de obtener una transmisión confiable. En este trabajo se evalúan diferentes técnicas lineales y no lineales de predicción del canal inalámbrico, cuyas muestras con distribución Rayleigh han sido generadas y aplicadas sobre un sistema MIMO-OFDM. El sistema MIMO-OFDM se desarrolló con una descripción a nivel de sistemas usando el lenguaje de SystemC para obtener medidas de desempeño del mismo sobre el canal de comunicaciones, al cual se adapta utilizando la relación señal a ruido del canal estimado y predicho. La adaptación al canal o enlace de comunicaciones (Link Adaptation) se obtuvo en relación a esquemas de modulación para aumentar o disminuir la tasa de transmisión y de errores de bit (BER – Bit Error Rate) de acuerdo con las condiciones de ruido del canal. El análisis de desempeño del sistema y las técnicas de predicción de canal fue determinado por métricas de cantidad de errores, precisión de la predicción realizada, tasa de transmisión, latencia, complejidad computacional y utilización de memoria. A partir de allí se hicieron comparaciones de desempeño entre técnicas lineales y no lineales que permitieron establecer la viabilidad de la implementación de estas en un sistema de comunicaciones real. La investigación fue llevada a cabo usando una descripción del sistema a nivel de capa física cuya evaluación en banda base da la posibilidad de validar el comportamiento del mismo con respecto al procesamiento de señales generadas en forma de trama de datos binaria con distribución uniforme. Los resultados obtenidos muestran que los algoritmos de predicción de canal generan un aumento de aproximadamente el 7% mínimo en la latencia del sistema MIMO-OFDM y además existe una relación entre el funcionamiento y la complejidad computacional de los algoritmos estudiados.Abstract. Wireless communications, where the channel is defined by spread effects and physical obstacles between transmitter and receiver, are a clear example of the challenges faced in order to have an effective communication in noisy environments. Demand for multiple communication systems, such as voice, video and data, have made transmission and reception capabilities of nowadays communication systems to increase in order to accomplish high transmission and low reception error rates that makes wireless communications more reliable with the use of minimum radio spectrum and power. Fourth generation (4G) systems have come in the recent years with diverse technologies, to fit requirements imposed; in this systems multiple techniques such as multiple antennas at transmitter and receiver, modulation, coding channel estimation and prediction are used to adjust the system to channel conditions. In this work different techniques are evaluated for linear and non-linear prediction of n time spaces of the wireless channel, whose samples have been generated and applied to a MIMO-OFDM system. The MIMO-OFDM system has been developed on a system – level description with SystemC in order to enable performance measures of the communication system adaptation over a noisy wireless channel using Signal to Noise ratio (SNR) measured of the estimated and/or predicted channel. Link adaptation was made around different modulation schemes to increase or decrease transmission data rates and Bit Error Rate (BER) according to channel noise conditions. Performance analysis for the system and its channel prediction techniques was determined by metrics of number of errors, prediction error, transmission rate, latency, computational complexity and memory usage. Comparison between linear and non-linear prediction techniques in order to establish the viability of implementation of such techniques in real communication systems was also performed as one of the main goals for this work. Research on this topic was performed using a system level description of the physical layer of the MIMO-OFDM system whose evaluation in base band gives the possibility to validate system behaviour in relation to signal processing of randomly generated bit frames with a uniform distribution. Results show that channel prediction algorithms increase latency of the MIMO-OFDM system in about 7%, and also that there is a relationship between performance and computational complexity for the studied algorithms.Maestrí

A channel model and coding for vehicle to vehicle communication based on a developed V-SCME

Over the recent years, VANET communication has attracted a lot of attention due to its potential in facilitating the implementation of 'Intelligent Transport System'. Vehicular applications need to be completely tested before deploying them in the real world. In this context, VANET simulations would be preferred in order to evaluate and validate the proposed model, these simulations are considered inexpensive compared to the real world (hardware) tests. The development of a more realistic simulation environment for VANET is critical in ensuring high performance. Any environment required for simulating VANET, needs to be more realistic and include a precise representation of vehicle movements, as well as passing signals among different vehicles. In order to achieve efficient results that reflect the reality, a high computational power during the simulation is needed which consumes a lot of time. The existing simulation tools could not simulate the exact physical conditions of the real world, so results can be viewed as unsatisfactory when compared with real world experiments. This thesis describes two approaches to improve such vehicle to vehicle communication. The first one is based on the development of an already existing approach, the Spatial Channel Model Extended (SCME) for cellular communication which is a verified, validated and well-established communication channel model. The new developed model, is called Vehicular - Spatial Channel Model Extended (V-SCME) and can be utilised for Vehicle to Vehicle communication. V-SCME is a statistical channel model which was specifically developed and configured to satisfy the requirements of the highly dynamic network topology such as vehicle to vehicle communication. V-SCME provides a precise channel coefficients library for vehicle to vehicle communication for use by the research community, so as to reduce the overall simulation time. The second approach is to apply V-BLAST (MIMO) coding which can be implemented with vehicle to vehicle communication and improve its performance over the V-SCME. The V- SCME channel model with V-BLAST coding system was used to improve vehicle to vehicle physical layer performance, which is a novel contribution. Based on analysis and simulations, it was found that the developed channel model V-SCME is a good solution to satisfy the requirements of vehicle to vehicle communication, where it has considered a lot of parameters in order to obtain more realistic results compared with the real world tests. In addition, V-BLAST (MIMO) coding with the V-SCME has shown an improvement in the bit error rate. The obtained results were intensively compared with other types of MIMO coding

Statistical simulation models for rayleigh and rician fading

Abstract — New simulation models are proposed for Rayleigh and Rician fading channels. First, the statistical properties of Clarke’s fading model with a finite number of sinusoids are analyzed. An improved Clarke’s model is then proposed for the simulation of Rayleigh fading channels. Based on this improved Rayleigh fading model, a novel simulation model is proposed for Rician fading channels. The new Rician fading model employs a zero-mean stochastic sinusoid as the specular (line-of-sight) component, in contrast to all existing Rician fading simulators that utilize a non-zero mean deterministic specular component. The statistical properties of the proposed Rician fading model are analyzed in detail. It is shown that the probability density function of the Rician fading phase is not only independent of time but also uniformly distributed over [−π, π). This property is different from that of existing Rician fading models. The statistical properties of the new simulators are confirmed by extensive simulation results, finding good agreement with theoretical analysis in all cases. An explicit formula for the level crossing rate is derived for general Rician fading when the specular component has non-zero Doppler frequency. I