On the cognitive interference channel with causal unidirectional destination cooperation

In previous works, the cognitive interference channel with unidirectional destination cooperation has been studied. In this model, the cognitive receiver acts as a relay of the primary user's message, and its operation is assumed to be strictly causal. In this letter, we study the same channel model with a causal rather than a strictly causal relay, i.e., the relay's transmit symbol depends not only on its past but also on its current received symbol. We propose an outer bound for the discrete memoryless channel, which is later used to compute an outer bound for the Gaussian channel. We also propose an achievable scheme based on instantaneous amplify-and-forward relaying that meets the outer bound in the very strong interference regime

Estimation of void fraction for homogenous regime of two-phase flows in unstable operational conditions using gamma-ray and neural networks

 Almost all the multi-phase flow meters (MPFMs) using gamma-ray attenuation, are calibrated for liquid and gas phases with constant density and pressure. When operational conditions such as temperature and pressure change in pipelines, the radiation-based multi-phase flowmeters would measure the flow rate with error. Therefore, performance of MPFMs would be improved by eliminating any dependency on the fluid properties such as density. In this work, a method based on dual modality densitometry combined with Artificial Neural Network (ANN) is proposed in order to estimate the void fraction in homogenous regime of gas-liquid two-phase flows in unstable operational conditions (changeable temperature and pressure) in oil industry. An experimental setup was implemented to generate the optimum required input data for training the network. ANNs were trained on the registered counts of the transmission and scattering detectors in various liquid phase densities and void fractions. Void fractions were predicted by ANNs with mean relative error of less than 0.78% in density variations range of 0.735 up to 0.98 g/cm

Computational Optimization in Engineering - Paradigms and Applications

The purpose of optimization is to maximize the quality of lives, productivity in time, as well as interests. Therefore, optimization is an ongoing challenge for selecting the best possible among many other inferior designs. For a hundred years in the past, as optimization has been essential to human life, several techniques have been developed and utilized. Such a development has been one of the long-lasting challenges in engineering and science, and it is now clear that the optimization goals in many of real-life problems are unlikely to be achieved without resource for computational techniques. The history of such a development in the optimization techniques starts from the early 1950s and is still in progress. Since then, the efforts behind this development dedicated by many distinguished scientists, mathematicians, and engineers have brought us today a level of quality of lives. This book concerns with the computational optimization in engineering and techniques to resolve the underlying problems in real life. The current book contains studies from scientists and researchers around the world from North America to Europe and from Asia to Australia

A transmit strategy for self-organising cellular network with hot-spots.

Self-Organising Network (SON) is a dynamic entity with capability of learning and functionality of self-optimisation, which has been desired for various optimisation tasks. If self-optimisation function includes several objectives, Multi-Objective- Optimisation (MOO) methods needs to be carried out; hence a self-optimisation algorithm for such task is ambitious. In this thesis, we introduce an algorithm of self-optimisation multi-objective task using concept of Similarity Measure (SM). The introduced algorithm is applied to concurrent capacity and coverage optimisation in SON use-cases with standard data and is compared with self-optimisation methods in literature for optimisation tasks. Furthermore, a unified framework for performance evaluation in SON is introduced using a Markovian approach. An ergodic Markov model is used to estimate residue Uncertainty ENtropy (UEN) for performance evaluation of underlying SON with a procedural self-optimisation function. A comparison of theoretical results on performance evaluation using Markovian approach is also presented in this study. In addition, a comparison of results is presented in a system level simulation of wireless cellular network for a scenario in SON with hot-spot. The network parameters of antenna and power are used in optimisation with two objectives of users’ throughput and cell fairness as target Key Performance Indicators (KPIs). Finally, in this thesis, we show that the enhancement in measured KPIs, using the introduced self-optimisation algorithm, is Pareto- Koopmans (P-K) efficient in which an efficient transmit strategy is achieved. This efficiency can provide more options to the decision-maker with less conflict problem. Methodology, theoretical approach, analytical evaluation, simulation results and future studies are presented in this thesis

The total colorant sensitivity of a color matching recipe: An approach to colorant weighting and tinctorial strength errors

The repeatability of the recipe color can be affected by several different types of inevitable inaccuracies in the coloration process. Two of the major causes of poor target-color reproducibility are the (random) weighing and (proportional) strength errors. This article describes alternative definitions of colorant strength sensitivity and total colorant sensitivity of a dyeing recipe. The influences of the maximal colorant weighing and strength errors are taken into account in order to bring the magnitudes of the two treated types of sensitivity into a mutually realistic balance between each other. The quantifications of precision and accuracy of a color matching recipe are also developed and combined into a single-number measure of recipe quality. The listed quantities are expected to be useful in selecting the most reliable one(s) among the different formulations for the same standard color. The methods are presented for calculating numerical estimates of the newly introduced quantities. The precision and accuracy of the coloration process are investigated in laboratory experiments involving repeated dyeings

A Target-Following Regime using Similarity Measure for Coverage and Capacity Optimization in Self-Organizing Cellular Networks with Hot-Spot

The Self-Organizing Network (SON) has been seen as one of the promising areas to save OPerational EXpenditure (OPEX) and to bring real efficiency to the wireless networks. Though the studies in literature concern with local interaction and distributed structure for SON, study on its coherent pattern has not yet been well-conducted. We consider a target-following regime and propose a novel approach of goal attainment using Similarity Measure (SM) for Coverage & Capacity Optimization (CCO) use-case in SON. The methodology is based on a self-optimization algorithm, which optimizes the multiple objective functions of UE throughput and fairness using performance measure, which is carried out using SM between target and measured KPIs. After certain epochs, the optimum results are used in adjustment and updating modules of goal attainment. To investigate the proposed approach, a simulation in downlink LTE has also been set up. In a scenario including a congested cell with hot-spot, the joint antenna parameters of tilt/azimuth using a 3D beam pattern is considered. The final CDF results show a noticeable migration of hot-spot UEs to higher throughputs, while no one worse off