The impact of shadowing and the severity of fading on the first and second order statistics of the capacity of OSTBC MIMO Nakagami-lognormal channels

This article presents a thorough statistical analysis of the capacity of orthogonal space-time block coded (OSTBC) multiple-input multiple-output (MIMO) Nakagami- lognormal (NLN) channels. The NLN channel model allows to study the joint effects of fast fading and shadowing on the statistical properties of the channel capacity. We have derived exact analytical expressions for the probability density function (PDF), cumulative distribution function (CDF), level-crossing rate (LCR), and average duration of fades (ADF) of the capacity of MIMO NLN channels. It is observed that an increase in the MIMO dimension or a decrease in the severity of fading results in an increase in the mean channel capacity, while the variance of the channel capacity decreases. On the other hand, an increase in the shadowing standard deviation increases the spread of the channel capacity, however the shadowing effect has no influence on the mean channel capacity. We have also presented approximation results for the statistical properties of the channel capacity, obtained using the Gauss-Hermite integration method. It is observed that approximation results not only reduce the complexity, but also have a very good fitting with the exact results. The presented results are very useful and general because they provide the flexibility to study the impact of shadowing on the channel capacity under different fading conditions. Moreover, the effects of severity of fading on the channel capacity can also be studied. The correctness of theoretical results is confirmed by simulations

The impact of shadowing and the severity of fading on the first and second order statistics of the capacity of OSTBC MIMO Nakagami-lognormal channels

Published version of an article in Wireless Personal Communications (2011), 1-16. Also available from the publisher at http://dx.doi.org/10.1007/s11277-011-0275-xThis article presents a thorough statistical analysis of the capacity of orthogonal space-time block coded (OSTBC) multiple-input multiple-output (MIMO) Nakagami- lognormal (NLN) channels. The NLN channel model allows to study the joint effects of fast fading and shadowing on the statistical properties of the channel capacity. We have derived exact analytical expressions for the probability density function (PDF), cumulative distribution function (CDF), level-crossing rate (LCR), and average duration of fades (ADF) of the capacity of MIMO NLN channels. It is observed that an increase in the MIMO dimension or a decrease in the severity of fading results in an increase in the mean channel capacity, while the variance of the channel capacity decreases. On the other hand, an increase in the shadowing standard deviation increases the spread of the channel capacity, however the shadowing effect has no influence on the mean channel capacity. We have also presented approximation results for the statistical properties of the channel capacity, obtained using the Gauss-Hermite integration method. It is observed that approximation results not only reduce the complexity, but also have a very good fitting with the exact results. The presented results are very useful and general because they provide the flexibility to study the impact of shadowing on the channel capacity under different fading conditions. Moreover, the effects of severity of fading on the channel capacity can also be studied. The correctness of theoretical results is confirmed by simulations

Statistical analysis of the capacity of mobile radio channels

Doktorgradsavhandling i informasjons- og kommunikasjonsteknologi, Universitetet i Agder, Grimstad, 201

Analysis of Gaussian Quadratic Forms with Application to Statistical Channel Modeling

Finalmente, en el contexto de modelado de canal, la metodología de análisis de variables propuesta permite obtener dos nuevas generalizaciones del conocido modelo de desvanecimiento kappa-mu shadowed. Estas dos nuevas distribuciones, nombradas Beckmann fluctuante y kappa-mu shadowed correlado, incluyen como casos particulares a la gran mayoría de distribuciones de desvanecimientos usadas en la literatura, abarcando desde los modelos clásicos de Rayleigh y Rice hasta otros más generales y complejos como el Beckmann y el kappa-mu. Para ambas distribuciones, se presenta su caracterización estadística de primer orden, i.e., función generadora de momentos (MGF), PDF y CDF; así como los estadísticos de segundo orden del modelo Beckmann fluctuante. Fecha de lectura de Tesis Doctoral: 24 Enero 2020En esta tesis se presenta una nueva aproximación a la distribución de de formas cuadráticas gaussianas (FCGs) no centrales tanto en variables reales como complejas. Para ello, se propone un nuevo método de análisis de variables aleatorias que, en lugar de centrarse en el estudio de la variable en cuestión, se basa en la caracterización estadística de una secuencia de variables aleatorias auxiliares convenientemente definida. Como consecuencia, las expresiones obtenidas, con independencia del grado de precisión adquirido, siempre representan una distribución válida, siendo ésta su principal ventaja. Aplicando este método, se obtienen simples expresiones recursivas para la función densidad de probabilidad (PDF) y la función de distribución (CDF) de las FCGs reales definidas positivas. En el caso de las formas complejas, esta nueva forma de análisis conduce a aproximaciones para los estadísticos de primer orden en términos de funciones elementales (exponenciales y potencias), siendo más convenientes para cálculos posteriores que otras soluciones disponibles en la literatura. La tratabilidad matemática se ejemplifica mediante el análisis de sistemas de combinación por razón máxima (MRC) sobre canales Rice correlados, proporcionando aproximaciones cerradas para la probabilidad de outage y la probabilidad de error de bit

Komunikace na milimetrových vlnách v 5G a dalších sítích: Nové systémové modely a analýza výkonnosti

The dissertation investigates different network models, focusing on three important features for next generation cellular networks with respect to millimeter waves (mmWave) communications: the impact of fading and co-channel interference (CCI), energy efficiency, and spectrum efficiency. To address the first aim, the dissertation contains a study of a non-orthogonal multiple access (NOMA) technique in a multi-hop relay network which uses relays that harvest energy from power beacons (PB). This part derives the exact throughput expressions for NOMA and provides a performance analysis of three different NOMA schemes to determine the optimal parameters for the proposed system’s throughput. A self-learning clustering protocol (SLCP) in which a node learns its neighbor’s information is also proposed for determining the node density and the residual energy used to cluster head (CH) selection and improve energy efficiency, thereby prolonging sensor network lifetime and gaining higher throughput. Second, NOMA provides many opportunities for massive connectivity at lower latencies, but it may also cause co-channel interference by reusing frequencies. CCI and fading play a major role in deciding the quality of the received signal. The dissertation takes into account the presence of η and µ fading channels in a network using NOMA. The closed-form expressions of outage probability (OP) and throughput were derived with perfect successive interference cancellation (SIC) and imperfect SIC. The dissertation also addresses the integration of NOMA into a satellite communications network and evaluates its system performance under the effects of imperfect channel state information (CSI) and CCI. Finally, the dissertation presents a new model for a NOMA-based hybrid satellite-terrestrial relay network (HSTRN) using mmWave communications. The satellite deploys the NOMA scheme, whereas the ground relays are equipped with multiple antennas and employ the amplify and forward (AF) protocol. The rain attenuation coefficient is considered as the fading factor of the mmWave band to choose the best relay, and the widely applied hybrid shadowed-Rician and Nakagami-m channels characterize the transmission environment of HSTRN. The closed-form formulas for OP and ergodic capacity (EC) were derived to evaluate the system performance of the proposed model and then verified with Monte Carlo simulations.Dizertační práce zkoumala různé modely sítí a zaměřila se na tři důležité vlastnosti pro buňkové sítě příští generace s ohledem na mmW komunikace, kterými jsou: vliv útlumu a mezikanálového rušení (CCI), energetická účinnost a účinnost spektra. Co se týče prvního cíle, dizertace obsahuje studii techniky neortogonálního vícenásobného přístupu (NOMA) v bezdrátové multiskokové relay síti využívající získávání energie, kde relay uzly sbírají energii z energetických majáků (PB). Tato část přináší přesné výrazy propustnosti pro NOMA a analýzu výkonnosti se třemi různými schématy NOMA s cílem určit optimální parametry pro propustnost navrženého systému. Dále byl navržen samoučící se shlukovací protokol (SLCP), ve kterém se uzel učí informace o sousedech, aby určil hustotu uzlů a zbytkovou energii použitou k výběru hlavy shluku CH pro zlepšení energetické účinnosti, čímž může prodloužit životnost sensorové sítě a zvýšit propustnost. Za druhé, přístup NOMA poskytl mnoho příležitostí pro masivní připojení s nižší latencí, NOMA však může způsobovat mezikanálové rušení v důsledku opětovného využívání kmitočtů. CCI a útlum hrají klíčovou roli při rozhodování o kvalitě přijímaného signálu. V této dizertace je brána v úvahu přítomnost η a µ útlumových kanálů v síti užívající NOMA. Odvozeny jsou výrazy v uzavřené formě pro pravděpodobnost výpadku (OP) a propustnost s dokonalým postupným rušením rušení (SIC) a nedokonalým SIC. Dále se dizertace zabývá integrací přístupu NOMA do satelitní komunikační sítě a vyhodnocuje výkonnost systému při dopadech nedokonalé informace o stavu kanálu (CSI) a CCI. Závěrem disertační práce představuje nový model pro hybridní družicově-terestriální přenosovou síť (HSTRN) založenou na NOMA vícenásobném přístupu využívající mmWave komunikaci. Satelit využívá NOMA schéma, zatímco pozemní relay uzly jsou vybaveny více anténami a aplikují protokol zesilování a předávání (AF). Je zaveden srážkový koeficient, který je uvažován jako útlumový faktor mmWave pásma při výběru nejlepšího relay uzlu. Samotné přenosové prostředí HSTRN je charakterizováno pomocí hybridních Rician a Nakagami-m kanálů. Vztahy pro vyhodnocení výkonnosti systému navrženého modelu vyjadřující ergodickou kapacitu (EC) a pravděpodobnost ztrát (OP) byly odvozeny v uzavřené formě a následně ověřeny pomocí simulační numerické metody Monte Carlo.440 - Katedra telekomunikační technikyvyhově

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

Spectrum sensing and occupancy prediction for cognitive machine-to-machine wireless networks

A thesis submitted to the University of Bedfordshire, in partial fulfil ment of the requirements for the degree of Doctor of Philosophy (PhD)The rapid growth of the Internet of Things (IoT) introduces an additional challenge to the existing spectrum under-utilisation problem as large scale deployments of thousands devices are expected to require wireless connectivity. Dynamic Spectrum Access (DSA) has been proposed as a means of improving the spectrum utilisation of wireless systems. Based on the Cognitive Radio (CR) paradigm, DSA enables unlicensed spectrum users to sense their spectral environment and adapt their operational parameters to opportunistically access any temporally unoccupied bands without causing interference to the primary spectrum users. In the same context, CR inspired Machine-to-Machine (M2M) communications have recently been proposed as a potential solution to the spectrum utilisation problem, which has been driven by the ever increasing number of interconnected devices. M2M communications introduce new challenges for CR in terms of operational environments and design requirements. With spectrum sensing being the key function for CR, this thesis investigates the performance of spectrum sensing and proposes novel sensing approaches and models to address the sensing problem for cognitive M2M deployments. In this thesis, the behaviour of Energy Detection (ED) spectrum sensing for cognitive M2M nodes is modelled using the two-wave with dffi use power fading model. This channel model can describe a variety of realistic fading conditions including worse than Rayleigh scenarios that are expected to occur within the operational environments of cognitive M2M communication systems. The results suggest that ED based spectrum sensing fails to meet the sensing requirements over worse than Rayleigh conditions and consequently requires the signal-to-noise ratio (SNR) to be increased by up to 137%. However, by employing appropriate diversity and node cooperation techniques, the sensing performance can be improved by up to 11.5dB in terms of the required SNR. These results are particularly useful in analysing the eff ects of severe fading in cognitive M2M systems and thus they can be used to design effi cient CR transceivers and to quantify the trade-o s between detection performance and energy e fficiency. A novel predictive spectrum sensing scheme that exploits historical data of past sensing events to predict channel occupancy is proposed and analysed. This approach allows CR terminals to sense only the channels that are predicted to be unoccupied rather than the whole band of interest. Based on this approach, a spectrum occupancy predictor is developed and experimentally validated. The proposed scheme achieves a prediction accuracy of up to 93% which in turn can lead to up to 84% reduction of the spectrum sensing cost. Furthermore, a novel probabilistic model for describing the channel availability in both the vertical and horizontal polarisations is developed. The proposed model is validated based on a measurement campaign for operational scenarios where CR terminals may change their polarisation during their operation. A Gaussian approximation is used to model the empirical channel availability data with more than 95% confi dence bounds. The proposed model can be used as a means of improving spectrum sensing performance by using statistical knowledge on the primary users occupancy pattern

Journal of Telecommunications and Information Technology

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