Propagation modelling and measurements in a populated indoor environment at 5.2 GHz

There are a number of significant radiowave propagation phenomena present in the populated indoor environment, including multipath fading and human body effects. The latter can be divided into shadowing and scattering caused by pedestrian movement, and antenna-body interaction with bodyworn or hand portable terminals [1]. Human occupants within indoor environments are not always stationary and their movement will lead to temporal channel variations that can strongly affect the quality of indoor wireless communication systems. Hence, populated environments remain a major challenge for wireless local area networks (WLAN) and other indoor communication systems. Therefore, it is important to develop an understanding of the potential and limitations of indoor radiowave propagation at key frequencies of interest, such as the 5.2 GHz band employed by commercial wireless LAN standards such as IEEE 802.11a and HiperLAN 2. Although several indoor wireless models have been proposed in the literature, these temporal variations have not yet been thoroughly investigated. Therefore, we have made an important contribution to the area by conducting a systematic study of the problem, including a propagation measurement campaign and statistical channel characterization of human body effects on line-of-sight indoor propagation at 5.2 GHz. Measurements were performed in the everyday environment of a 7.2 m wide University hallway to determine the statistical characteristics of the 5.2 GHz channel for a fixed, transverse line-of-sight (LOS) link perturbed by pedestrian movement. Data were acquired at hours of relatively high pedestrian activity, between 12.00 and 14.00. The location was chosen as a typical indoor wireless system environment that had sufficient channel variability to permit a valid statistical analysis. The paper compares the first and second order statistics of the empirical signals with the Gaussian-derived distributions commonly used in wireless communications. The analysis shows that, as the number of pedestrians within the measurement location increases, the Ricean K-factor that best fits the Cumulative Distribution Function (CDF) of the empirical data tends to decrease proportionally, ranging from K=7 with 1 pedestrian to K=0 with 4 pedestrians. These results are consistent with previous results obtained for controlled measurement scenarios using a fixed link at 5.2 GHz in [2], where the K factor reduced as the number of pedestrians within a controlled measurement area increased. Level crossing rate results were Rice distributed, considering a maximum Doppler frequency of 8.67 Hz. While average fade duration results were significantly higher than theoretically computed Rice and Rayleigh, due to the fades caused by pedestrians. A novel statistical model that accurately describes the 5.2 GHz channel in the considered indoor environment is proposed. For the first time, the received envelope CDF is explicitly described in terms of a quantitative measurement of pedestrian traffic within the indoor environment. The model provides an insight into the prediction of human body shadowing effects for indoor channels at 5.2 GHz

Propagation Modelling and Measurements in a Populated Indoor Environment at 5.2GHz

Human occupants within indoor environments are not always stationary and their movement will lead to temporal channel variations that strongly affect the quality of indoor wireless communication systems. This paper describes a statistical channel characterization, based on experimental measurements, of human body effects on line-of-sight indoor narrowband propagation at 5.2 GHz. The analysis shows that, as the number of pedestrians within the measurement location increases, the Ricean K-factor that best fits the empirical data tends to decrease proportionally, ranging from K=7 with 1 pedestrian to K=0 with 4 pedestrians. Level crossing rate results were Rice distributed, while average fade duration results were significantly higher than theoretically computed Rice and Rayleigh, due to the fades caused by pedestrians. A novel CDF that accurately characterizes the 5.2 GHz channel in the considered indoor environment is proposed. For the first time, the received envelope CDF is explicitly described in terms of a quantitative measurement of pedestrian traffic within the indoor environment

Design and theoretical analysis of advanced power based positioning in RF system

Accurate locating and tracking of people and resources has become a fundamental requirement for many applications. The global navigation satellite systems (GNSS) is widely used. But its accuracy suffers from signal obstruction by buildings, multipath fading, and disruption due to jamming and spoof. Hence, it is required to supplement GPS with inertial sensors and indoor localization schemes that make use of WiFi APs or beacon nodes. In the GPS-challenging or fault scenario, radio-frequency (RF) infrastructure based localization schemes can be a fallback solution for robust navigation. For the indoor/outdoor transition scenario, we propose hypothesis test based fusion method to integrate multi-modal localization sensors. In the first paper, a ubiquitous tracking using motion and location sensor (UTMLS) is proposed. As a fallback approach, power-based schemes are cost-effective when compared with the existing ToA or AoA schemes. However, traditional power-based positioning methods suffer from low accuracy and are vulnerable to environmental fading. Also, the expected accuracy of power-based localization is not well understood but is needed to derive the hypothesis test for the fusion scheme. Hence, in paper 2-5, we focus on developing more accurate power-based localization schemes. The second paper improves the power-based range estimation accuracy by estimating the LoS component. The ranging error model in fading channel is derived. The third paper introduces the LoS-based positioning method with corresponding theoretical limits and error models. In the fourth and fifth paper, a novel antenna radiation-pattern-aware power-based positioning (ARPAP) system and power contour circle fitting (PCCF) algorithm are proposed to address antenna directivity effect on power-based localization. Overall, a complete LoS signal power based positioning system has been developed that can be included in the fusion scheme --Abstract, page iv

Applications of Stochastic Ordering to Wireless Communications

Stochastic orders are binary relations defined on probability distributions which capture intuitive notions like being larger or being more variable. This paper introduces stochastic ordering of instantaneous SNRs of fading channels as a tool to compare the performance of communication systems over different channels. Stochastic orders unify existing performance metrics such as ergodic capacity, and metrics based on error rate functions for commonly used modulation schemes through their relation with convex, and completely monotonic (c.m.) functions. Toward this goal, performance metrics such as instantaneous error rates of M-QAM and M-PSK modulations are shown to be c.m. functions of the instantaneous SNR, while metrics such as the instantaneous capacity are seen to have a completely monotonic derivative (c.m.d.). It is shown that the commonly used parametric fading distributions for modeling line of sight (LoS), exhibit a monotonicity in the LoS parameter with respect to the stochastic Laplace transform order. Using stochastic orders, average performance of systems involving multiple random variables are compared over different channels, even when closed form expressions for such averages are not tractable. These include diversity combining schemes, relay networks, and signal detection over fading channels with non-Gaussian additive noise, which are investigated herein. Simulations are also provided to corroborate our results.Comment: 25 pages, 10 figures, Submitted to the IEEE transactions on wireless communication

A Bayesian Variable Selection Approach Yields Improved Detection of Brain Activation From Complex-Valued fMRI

Voxel functional magnetic resonance imaging (fMRI) time courses are complex-valued signals giving rise to magnitude and phase data. Nevertheless, most studies use only the magnitude signals and thus discard half of the data that could potentially contain important information. Methods that make use of complex-valued fMRI (CV-fMRI) data have been shown to lead to superior power in detecting active voxels when compared to magnitude-only methods, particularly for small signal-to-noise ratios (SNRs). We present a new Bayesian variable selection approach for detecting brain activation at the voxel level from CV-fMRI data. We develop models with complex-valued spike-and-slab priors on the activation parameters that are able to combine the magnitude and phase information. We present a complex-valued EM variable selection algorithm that leads to fast detection at the voxel level in CV-fMRI slices and also consider full posterior inference via Markov chain Monte Carlo (MCMC). Model performance is illustrated through extensive simulation studies, including the analysis of physically based simulated CV-fMRI slices. Finally, we use the complex-valued Bayesian approach to detect active voxels in human CV-fMRI from a healthy individual who performed unilateral finger tapping in a designed experiment. The proposed approach leads to improved detection of activation in the expected motor-related brain regions and produces fewer false positive results than other methods for CV-fMRI. Supplementary materials for this article are available online

An efficient approximation to the correlated Nakagami-m sums and its application in equal gain diversity receivers

There are several cases in wireless communications theory where the statistics of the sum of independent or correlated Nakagami-m random variables (RVs) is necessary to be known. However, a closed-form solution to the distribution of this sum does not exist when the number of constituent RVs exceeds two, even for the special case of Rayleigh fading. In this paper, we present an efficient closed-form approximation for the distribution of the sum of arbitrary correlated Nakagami-m envelopes with identical and integer fading parameters. The distribution becomes exact for maximal correlation, while the tightness of the proposed approximation is validated statistically by using the Chi-square and the Kolmogorov-Smirnov goodness-of-fit tests. As an application, the approximation is used to study the performance of equal-gain combining (EGC) systems operating over arbitrary correlated Nakagami-m fading channels, by utilizing the available analytical results for the error-rate performance of an equivalent maximal-ratio combining (MRC) system

Characterisation and Modelling of Indoor and Short-Range MIMO Communications

Over the last decade, we have witnessed the rapid evolution of Multiple-Input Multiple-Output (MIMO) systems which promise to break the frontiers of conventional architectures and deliver high throughput by employing more than one element at the transmitter (Tx) and receiver (Rx) in order to exploit the spatial domain. This is achieved by transmitting simultaneous data streams from different elements which impinge on the Rx with ideally unique spatial signatures as a result of the propagation paths’ interactions with the surrounding environment. This thesis is oriented to the statistical characterisation and modelling of MIMO systems and particularly of indoor and short-range channels which lend themselves a plethora of modern applications, such as wireless local networks (WLANs), peer-to-peer and vehicular communications. The contributions of the thesis are detailed below. Firstly, an indoor channel model is proposed which decorrelates the full spatial correlation matrix of a 5.2 GHzmeasuredMIMO channel and thereafter assigns the Nakagami-m distribution on the resulting uncorrelated eigenmodes. The choice of the flexible Nakagami-m density was found to better fit the measured data compared to the commonly used Rayleigh and Ricean distributions. In fact, the proposed scheme captures the spatial variations of the measured channel reasonably well and systematically outperforms two known analytical models in terms of information theory and link-level performance. The second contribution introduces an array processing scheme, namely the three-dimensional (3D) frequency domain Space Alternating Generalised Expectation Maximisation (FD-SAGE) algorithm for jointly extracting the dominant paths’ parameters. The scheme exhibits a satisfactory robustness in a synthetic environment even for closely separated sources and is applicable to any array geometry as long as its manifold is known. The algorithm is further applied to the same set of raw data so that different global spatial parameters of interest are determined; these are the multipath clustering, azimuth spreads and inter-dependency of the spatial domains. The third contribution covers the case of short-range communications which have nowadays emerged as a hot topic in the area of wireless networks. The main focus is on dual-branch MIMO Ricean systems for which a design methodology to achieve maximum capacities in the presence of Line-of-Sight (LoS) components is proposed. Moreover, a statistical eigenanalysis of these configurations is performed and novel closed-formulae for the marginal eigenvalue and condition number statistics are derived. These formulae are further used to develop an adaptive detector (AD) whose aim is to reduce the feasibility cost and complexity of Maximum Likelihood (ML)-based MIMO receivers. Finally, a tractable novel upper bound on the ergodic capacity of the above mentioned MIMO systems is presented which relies on a fundamental power constraint. The bound is sufficiently tight and applicable for arbitrary rank of the mean channel matrix, Signal-to-Noise ratio (SNR) and takes the effects of spatial correlation at both ends into account. More importantly, it includes previously reported capacity bounds as special cases

Aproximações estatísticas para somas de variáveis aleatórias correlacionadas dos tipos Rayleigh e exponencial com aplicação a esquemas de combinação de diversidade

Orientador: José Cândido Silveira Santos FilhoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Somas de variáveis aleatórias são amplamente aplicadas em sistemas de comunicação sem fio. Exemplos incluem equalização linear, detecção de sinais, fenômenos de interferência e esquemas de combinação de diversidade. No entanto, a formulação exata para as funções estatísticas dessas somas, como a função densidade de probabilidade e a função distribuição acumulada, requer em geral um tratamento matemático complicado, o que tem motivado a busca por soluções aproximadas mais simples. Apesar de haver várias propostas de aproximação disponíveis na literatura, muitas das quais obtidas usando-se a tradicional técnica de casamento de momentos, elas não oferecem um bom ajuste em regime de alta relação sinal-ruído. Sabe-se, porém, que essa é uma região primordial para a análise de desempenho de sistemas de comunicação em termos de métricas importantes como taxa de erro de bit e probabilidade de interrupção. Mais recentemente, com o intuito de contornar essa limitação, foi proposta uma nova técnica promissora conhecida como casamento de assíntotas, capaz de fornecer aproximações para estatísticas de somas de variáveis aleatórias positivas com um ótimo ajuste em regime de alta relação sinal-ruído. Ainda assim, essa técnica foi inicialmente implementada apenas para o caso de somas de variáveis independentes, não sendo até então aplicável para somas de variáveis correlacionadas. Neste trabalho, uma nova análise assintótica é proposta, a partir da qual é possível generalizar o uso do casamento de assíntotas para o caso correlacionado. A análise proposta é ilustrada para somas de variáveis Rayleigh e somas de variáveis exponenciais com correlação e parâmetros de desvanecimento arbitrários. Além disso, deduzem-se expressões assintóticas em forma fechada com o intuito de obter novas aproximações simples e precisas em regime de alta relação sinal-ruído. Como exemplos de aplicação, esquemas práticos de combinação de diversidade são abordados, quais sejam, combinação por ganho igual e combinação por razão máxima. Por fim, resultados numéricos mostram o excelente desempenho das aproximações propostas em comparação com as aproximações obtidas via casamento de momentosAbstract: Sums of random variables are widely applied to wireless communications systems. Examples include linear equalization, signal detection, interference phenomena, and diversity-combining schemes. However, the exact formulation for the statistical functions of these sums, such as the probability density function and the cumulative distribution function, requires in general a complicated mathematical treatment, which has motivated the search for simple approximate solutions. Although there are several approximate proposals available in the literature, many of which obtained through the traditional moment-matching technique, they do not offer a good fit under the regime of high signal-to-noise ratio. It is well-known that this regime is a paramount region for the performance analysis of communications systems in terms of important metrics such as bit error rate and outage probability. More recently, in order to circumvent this limitation, a new promising technique known as asymptotic matching was proposed, capable of providing approximations for statistics of the sum of random variables with an excellent fit under the regime of high signal-to-noise ratio. Even so, this technique was initially proposed for the sum of mutually independent variables only, and thus it has not been applicable to sums of correlated variables. In this work, a novel asymptotic analysis is proposed, from which it is possible to generalize the application of asymptotic matching to the correlated case. The proposed analysis is illustrated for sums of Rayleigh and sums of exponential variables with arbitrary correlation and arbitrary fading parameters. Furthermore, closed-form asymptotic expressions are derived in order to obtain new simple and precise approximations under the regime of high signal-to-noise ratio. As application examples, practical diversity-combining schemes are addressed, namely, equal-gain combining and maximal-ratio combining. Finally, numerical results show the excellent performance of the proposed approximations in comparison to the approximations obtained via moment matchingMestradoTelecomunicações e TelemáticaMestre em Engenharia ElétricaCAPE