Analysis of DVB-H network coverage with the application of transmit diversity

This paper investigates the effects of the Cyclic Delay Diversity (CDD) transmit diversity scheme on DVB-H networks. Transmit diversity improves reception and Quality of Service (QoS) in areas of poor coverage such as sparsely populated or obscured locations. The technique not only povides robust reception in mobile environments thus improving QoS, but it also reduces network costs in terms of the transmit power, number of infrastructure elements, antenna height and the frequency reuse factor over indoor and outdoor environments. In this paper, the benefit and effectiveness of CDD transmit diversity is tackled through simulation results for comparison in several scenarios of coverage in DVB-H networks. The channel model used in the simulations is based on COST207 and a basic radio planning technique is used to illustrate the main principles developed in this paper. The work reported in this paper was supported by the European Commission IST project—PLUTO (Physical Layer DVB Transmission Optimization)

Rainfall attenuation prediction model for dynamic rain fade mitigation technique considering millimeter wave communication link.

Doctoral Degree. University of KwaZulu-Natal, Durban.To deliver modern day broadband services to both fixed and mobile devices, ultra-high speed wireless networks are required. Innovative services such as the Internet-of-Things (IoT) can be facilitated by the deployment of next generation telecommunication networks such as 5G technologies. The deployment of 5G technologies is envisioned as a catalyst in the alleviation of spectrum congestion experienced by current technologies. With their improved network speed, capacity and reduced communication latency, 5G technologies are expected to enhance telecommunication networks for next generation services. These technologies, in addition to using current Long Term Evolution (LTE) frequency range (600 MHz to 6 GHz), will also utilize millimetre wave bands in the range 24-86 GHz. However, these high frequencies are susceptible to signal loss under rain storms. At such high frequencies, the size of the rain drop is comparable to the wavelength of the operating signal frequency, resulting in energy loss in the form of absorption and scattering by water droplets. This study investigates the effect of intense rain storms on link performance to accurately determine and apply dynamic rain fade mitigation techniques such as the use of a combination of modulation schemes to maintain link connectivity during a rain event. The backpropagation neural network (BPNN) model is employed in this study to predict the state of the link for decision making in employment of dynamic rain fade mitigation. This prediction model was tested on all rainfall regimes including intense rain storms and initial results are encouraging. Further on, the prediction model has been tested on a rainfall event rainfall data collected over Butare (2.6078° S, 29.7368° E), Rwanda, and the results demonstrate the portability of the proposed prediction model to other regions. The evolution of R0.01 (rain rate exceeded for 0.01% of the time in an average year) parameter due to intense rain storms over the region of study is examined and detailed analysis shows that this parameter is double the proposed ITU-R value of 60 mm/h. Moreover, an investigation on the largest rain drop size present in each rain storm is carried out for different storm magnitudes. The study goes further to examine the frequency of occurrence of rain storms using the Markov chain approach. Results of this approach show that rain spikes with maximum rain rates from 150 mm/h and above (intense storms) are experienced in the region of study with probability of occurrence of 11.42%. Additionally, rain spike service times for various rain storm magnitudes are analyzed using the queueing theory technique. From this approach, a model is developed for estimation of rain cell diameter that can be useful for site diversity as a dynamic rain fade mitigation strategy. Finally, the study further investigates second-order rain fade statistics at different attenuation thresholds

Impact of Link Parameters and Channel Correlation on the Performance of FSO Systems With the Differential Signaling Technique

We investigate the effects of link parameters and the channel correlation coefficient on the detection threshold, Q-factor, and bit-error-rate (BER) of a free-space optical system employing a differential signaling scheme. In systems employing differential signaling schemes, the mean value of the signal is used as the detection threshold level, provided that differential links are identical or highly correlated. However, in reality, the underlying links are not essentially identical and have a low level of correlation. To show the significance of the link parameters as well as the correlation coefficient, we derive analytical relations describing the effect of weak turbulence and we determine the improvement of Q-factor with the channel correlation. Further, for the same signal-to-noise ratio, we demonstrate that a link with a higher extinction ratio offers improved performance. We also propose a closed-form expression of the system BER. We present experimental results showing improved Q-factor for the correlated channel case compared to the uncorrelated channel

Differential Signalling in Free-Space Optical Communication Systems

In this paper, we review the differential signalling technique and investigate its implementation of in free-space optical (FSO) communication systems. The paper is an extended version of our previous works, where the effects of background noise, weak turbulence and pointing errors (PEs) were investigated separately. Here, for the first time, we present a thorough description of the differential signalling scheme including for combined effects. At first, we present an extension of the analysis of differential signalling to the case of moderate to strong atmospheric turbulence. Next, we investigate a more general case where both channel turbulence and PEs are taken into consideration. We provide closed-form expressions for the optimal detection threshold and the average bit-error-rate, and present a set of numerical results to illustrate the performance improvement offered by the proposed differential signalling under various turbulence and PEs conditions

FREE SPACE OPTICS LINKS AFFECTED BY OPTICAL TURBULENCE: CHANNEL MODELING, MEASUREMENTS AND CODING TECHNIQUES FOR ERROR MITIGATION

FSO is an optical wireless line-of-sight communication system able to offer good broadband performance, electromagnetic interference immunity, high security, license-free operation, low power consumption, ease of relocation, and straightforward installation. It represents a modern technology, significantly functional when it is impossible, expensive or complex to use physical connections or radio links. Unfortunately, since the transmission medium in a terrestrial FSO link is the air, these communications are strongly dependent on various atmospheric phenomena (e.g., rain, snow, optical turbulence and, especially, fog) that can cause losses and fading. Therefore, in worst-case conditions, it could be necessary to increase the optical transmission power, although, at the same time, it is needed to comply to safety regulations. The effects of the already mentioned impairments are: scattering (i.e., Rayleigh and Mie) losses, absorption and scintillation. The first two can be described by proper attenuation coefficients and increase if the atmospheric conditions get worst. As regards scintillation, it is a random phenomenon, appreciable even under clear sky. Because of scintillation, in FSO links, the irradiance fluctuates and could drop below a threshold under which the receiver is not able to detect the useful signal. In this case, communications suffer from erasure errors, which cause link outages. This phenomenon becomes relevant at high distance, but it can also be observed in 500m-long FSO links. Moreover, the optical turbulence intensity can change of an order of magnitude during the day: it reaches its maximum around midday (when the temperature is the highest) and, conversely, it is lower during the night. In order to reduce or eliminate these impairments, different methods (both hardware and software) were studied and reported in literature. Hardware solutions focus on aperture averaging effects to reduce irradiance fluctuations, in particular by using a bigger detector or multi-detector systems. On the other hand, software techniques mostly focus on transmission codes. Rateless codes are an innovative solution, suitable for channels affected by erasure or burst errors. They add a redundant coding (also settable on the fly) to the source data, allowing the receiver to successfully recover the whole payload that, otherwise, would be corrupted or partially lost. To test rateless codes, recovery capabilities in FSO channels, detailed information about the occurring signal fading are needed: in particular, its depth, temporal duration and statistics. For this reason, I have implemented a time-correlated channel model able to generate an irradiance time-series at the receiver side, at wide range of turbulence conditions (from weak to strong). The time-series represents a prediction of temporal irradiance fluctuations caused by scintillation. In this way, I was able to test the recovery capabilities of several types of rateless codes. I have performed measurement campaigns in order to characterize Free Space Optics links affected by the optical turbulence. In particular, I have used three different setups placed in the Laboratory of Optics of the University of Palermo and in the Optical Communication Laboratory of the Northumbria University. Thanks to an in-depth post-processing of the collected data, I was able to extract useful information about the FSO link quality and the turbulence strength, thus proving the effectiveness of the Gamma-Gamma model under several turbulence conditions. In Chapter 1, I will introduce the theory of optical wireless communications and, in particular, of Free Space Optics communications. In detail, I will describe the advantages and the impairments that characterize this kind of communication and discuss about its applications. In Chapter 2, the adopted channel models are presented. In particular, these models are able to predict irradiance fluctuations at the detector in Free Space Optics links and were designed for terrestrial and space-to-ground communications at different link specifications, turbulence conditions and temporal covariance. Firstly, a brief description of the employed irradiance distribution and of the irradiance covariance functions is presented. The details of the above mentioned channel model implementation and the performance are then described. Finally, in order to detail the channel model features, several examples of irradiance fluctuation predictions are depicted. In Chapter 3, the details of a measurement campaign, focused on the analysis of optical turbulence effects in a FSO link, will be treated. Three different measurement setups composed of different typologies of laser sources, detectors and turbulent channels will be described. Data post-processing will be discussed. Moreover, a performance evaluation of the terrestrial channel model described in Chapter 2 will be discussed. In Chapter 4, rateless codes will be presented. These codes introduce a redundancy by means of repair symbols, associated to the source data, and, in case of losses, they are able to recover the source data without any need for retransmission. They can also manage large amounts of data and offer very interesting features for erasure channels and multicast/broadcast applications. Three different classes of rateless codes will be described and, in particular: Luby Transform, Raptor and RaptorQ codes. Moreover, the performance of the rateless codes in Free Space Optics links will be investigated. The implemented simulators are based on the channel models presented in Chapter 2 and focus on the study of rateless codes recovery capabilities when erasure errors due to fadings occur. The results on the performance of three rateless codes typologies, in two different FSO links, will be illustrated. All the research work was supported by the European Space Agency (grant no. 5401001020). Experimental activities were performed in collaboration with the Optical Communications Research Group of the Northumbria University and within the COST IC1101 European Action

Game-Theoretic and Machine-Learning Techniques for Cyber-Physical Security and Resilience in Smart Grid

The smart grid is the next-generation electrical infrastructure utilizing Information and Communication Technologies (ICTs), whose architecture is evolving from a utility-centric structure to a distributed Cyber-Physical System (CPS) integrated with a large-scale of renewable energy resources. However, meeting reliability objectives in the smart grid becomes increasingly challenging owing to the high penetration of renewable resources and changing weather conditions. Moreover, the cyber-physical attack targeted at the smart grid has become a major threat because millions of electronic devices interconnected via communication networks expose unprecedented vulnerabilities, thereby increasing the potential attack surface. This dissertation is aimed at developing novel game-theoretic and machine-learning techniques for addressing the reliability and security issues residing at multiple layers of the smart grid, including power distribution system reliability forecasting, risk assessment of cyber-physical attacks targeted at the grid, and cyber attack detection in the Advanced Metering Infrastructure (AMI) and renewable resources. This dissertation first comprehensively investigates the combined effect of various weather parameters on the reliability performance of the smart grid, and proposes a multilayer perceptron (MLP)-based framework to forecast the daily number of power interruptions in the distribution system using time series of common weather data. Regarding evaluating the risk of cyber-physical attacks faced by the smart grid, a stochastic budget allocation game is proposed to analyze the strategic interactions between a malicious attacker and the grid defender. A reinforcement learning algorithm is developed to enable the two players to reach a game equilibrium, where the optimal budget allocation strategies of the two players, in terms of attacking/protecting the critical elements of the grid, can be obtained. In addition, the risk of the cyber-physical attack can be derived based on the successful attack probability to various grid elements. Furthermore, this dissertation develops a multimodal data-driven framework for the cyber attack detection in the power distribution system integrated with renewable resources. This approach introduces the spare feature learning into an ensemble classifier for improving the detection efficiency, and implements the spatiotemporal correlation analysis for differentiating the attacked renewable energy measurements from fault scenarios. Numerical results based on the IEEE 34-bus system show that the proposed framework achieves the most accurate detection of cyber attacks reported in the literature. To address the electricity theft in the AMI, a Distributed Intelligent Framework for Electricity Theft Detection (DIFETD) is proposed, which is equipped with Benford’s analysis for initial diagnostics on large smart meter data. A Stackelberg game between utility and multiple electricity thieves is then formulated to model the electricity theft actions. Finally, a Likelihood Ratio Test (LRT) is utilized to detect potentially fraudulent meters

Severely Fading MIMO Channels

In most wireless communications research, the channel models considered experience less severe fading than the classic Rayleigh fading case. In this thesis, however, we investigate MIMO channels where the fading is more severe. In these environments, we show that the coefficient of variation of the channel amplitudes is a good predictor of the link mutual information, for a variety of models. We propose a novel channel model for severely fading channels based on the complex multivariate t distribution. For this model, we are able to compute exact results for the ergodic mutual information and approximations to the outage probabilities for the mutual information. Applications of this work include wireless sensors, RF tagging, land-mobile, indoor-mobile, ground-penetrating radar, and ionospheric radio links. Finally, we point out that the methodology can also be extended to evaluate the mutual information of a cellular MIMO link and the performance of various MIMO receivers in a cellular scenario. In these cellular applications, the channel itself is not severely fading but the multivariate t distribution can be applied to model the effects of intercellular interference