Opportunistic transmission scheduling for next generation wireless communication systems with multimedia services

The explosive growth of the Internet and the continued dramatic increase for all wireless services are fueling the demand for increased capacity, data rates, and support of different quality of service (QoS) requirements for different classes of services. Since in the current and future wireless communication infrastructures, the performances of the various services are strongly correlated, as the resources are shared among them, dynamic resource allocation methods should be employed. With the demand for high data rate and support of multiple QoS, the transmission scheduling plays a key role in the efficient resource allocation process in wireless systems. The fundamental problem of scheduling the users\u27 transmissions and allocating the available resources in a realistic CDMA wireless system that supports multi-rate multimedia services, with efficiency and fairness, is investigated and analyzed in this dissertation. Our proposed approach adopts the use of dynamically assigned data rates that match the channel capacity in order to improve the system throughput and overcome the problems associated with the location-dependent and time-dependent errors and channel conditions, the variable system capacity and the transmission power limitation. We first introduce and describe two new scheduling algorithms, namely the Channel Adaptive Rate Scheduling (CARS) and Fair Channel Adaptive Rate Scheduling (FCARS). CARS exploits the channel variations to reach high throughput, by adjusting the transmission rates according to the varying channel conditions and by performing an iterative procedure to determine the power index that a user can accept by its current channel condition and transmission power. Based on the assignment of CARS and to overcome potential unfair service allocation, FCARS implements a compensation algorithm, in which the lagging users can receive compensation service when the corresponding channel conditions improve, in order to achieve asymptotic throughput fairness, while still maintaining all the constraints imposed by the system. Furthermore the problem of opportunistic fair scheduling in the uplink transmission of CDMA systems, with the objective of maximizing the uplink system throughput, while satisfying the users\u27 QoS requirements and maintaining the long-term fairness among the various users despite their different varying channel conditions, is rigorously formulated, and a throughput optimal fair scheduling policy is obtained. The corresponding problem is expressed as a weighted throughput maximization problem, under certain power and QoS constraints, where the weights are the control parameters that reflect the fairness constraints. With the introduction of the power index capacity it is shown that this optimization problem can be converted into a binary knapsack problem, where all the corresponding constraints are replaced by the users\u27 power index capacities at some certain system power index. It is then argued that the optimal solution can be obtained as a global search within a certain range, while a stochastic approximation method is presented in order to effectively identify the required control parameters. Finally, since some real-time services may demand certain amount of service within specific short span of time in order to avoid service delays, the problem of designing policies that can achieve high throughput while at the same time maintain short term fairness, is also considered and investigated. To this end a new Credit-based Short-term Fairness Scheduling (CSFS) algorithm, which achieves to provide short-term fairness to the delay-sensitive users while still schedules opportunistically the non-delay-sensitive users to obtain high system throughput, is proposed and evaluated

Change detection in SAR images based on the salient map guidance and an accelerated genetic algorithm

This paper proposes a change detection algorithm in synthetic aperture radar (SAR) images based on the salient image guidance and an accelerated genetic algorithm (S-aGA). The difference image is first generated by logarithm ratio operator based on the bi-temporal SAR images acquired in the same region. Then a saliency detection model is applied in the difference image to extract the salient regions containing the changed class pixels. The salient regions are further divided by fuzzy c-means (FCM) clustering algorithm into three categories: changed class (set of pixels with high gray values), unchanged class (set of pixels with low gray values) and undetermined class (set of pixels with middle gray value, which are difficult to classify). Finally, the proposed accelerated GA is applied to explore the reduced search space formed by the undetermined-class pixels according to an objective function considering neighborhood information. In S-aGA, an efficient mutation operator is designed by using the neighborhood information of undetermined-class pixels as the heuristic information to determine the mutation probability of each undetermined-class pixel adaptively, which accelerates the convergence of the GA significantly. The experimental results on two data sets demonstrate the efficiency of the proposed S-aGA. On the whole, S-aGA outperforms five other existing methods including the simple GA in terms of detection accuracy. In addition, S-aGA could obtain satisfying solution within limited generations, converging much faster than the simple GA

Correlation between the Quantifiable Parameters of Whole Solitary Pulmonary Nodules Perfusion Imaging Derived with Dynamic CT and Nodules Size

Background and objective The solitary pulmonary nodules (SPNs) is one of the most common findings on chest radiographs. The blood flow patterns of the biggest single SPNs level has been studied. This assessment may be only a limited sample of the entire region of interest (ROI) and is unrepresentative of the SPNs as a volume. Ideally, SPNs volume perfusion should be measured. The aim of this study is to evaluate the correlation between the quantifiableparameters of SPNs volume perfusion imaging derived with 16-slice spiral CT and 64-slice spiral CT and nodules size. Methods Sixty-five patients with SPNs (diameter≤3 cm; 42 malignant; 12 active inflammatory; 11 benign) underwent multi-location dynamic contrast material-enhanced serial CT scanning mode with stable table were performed; The mean values of valid sections were calculated, as the quantifiable parameters of volume SPNs perfusion imaging derived with16-slice spiral CT and 64-slice spiral CT. The correlation between the quantifiable parameters of SPNs volume perfusion imaging derived with 16-slice spiral CT and 64-slice spiral CT and nodules size were assessed by means of linear regression analysis. Results No significant correlations were found between the nodules size and each of the peak height (PHSPN) (32.15 Hu±14.55 Hu)，ratio of peak height of the SPN to that of the aorta (SPN-to-A ratio(13.20±6.18)%, perfusion(PSPN) (29.79±19.12) mLmin-1100 g-1 and mean transit time (12.95±6.53) s (r =0.081, P =0.419; r =0.089, P =0.487; r =0.167, P =0.077; r =0.023, P =0.880). Conclusion No significant correlations were found between the quantifiable parameters of SPNs volume perfusion imaging derived with 16-slice spiral CT and 64-slice spiral CT and nodules size

Correlation between the quantifiable parameters of blood flow pattern derived with dynamic CT in maliagnant solitary pulmonary nodules and tumor size

Background and Objective The solitary pulmonary nodules (SPNs ) is one of the most common findings on chest radiographs. It becomes possible to provide more accurately quantitative information about blood flow patterns of solitary pulmonary nodules (SPNs ) with multi-slice spiral computed tomography (MSCT). The aim of this study is to evaluate the correlation between the quantifiable parameters of blood flow pattern derived with dynamic CT in maliagnant solitary pulmonary nodules and tumor size. Methods 68 patients with maliagnant solitary pulmonary nodules (SPNs ) (diameter <=4 cm)underwent multi-location dynamic contrast material-enhanced (nonionic contrast material was administrated via the antecubital vein at a rate of 4mL/s by an autoinjector, 4*5mm or 4*2.5mm scanning mode with stable table were performed.) serial CT. Precontrast and postcontrast attenuation on every scan was recorded. Perfusion (PSPN), peak height (PHSPN)ratio of peak height of the SPN to that of the aorta (SPN-to-A ratio)and mean transit time(MTT) were calculated. The correlation between the quantifiable parameters of blood flow pattern derived with dynamic CT in maliagnant solitary pulmonary nodules and tumor size were assessed by means of linear regression analysis. Results No significant correlations were found between the tumor size and each of the peak height (PHSPN) ratio of peak height of the SPN to that of the aorta (SPN-to-A ratio) perfusion(PSPN)and mean transit time (r=0.18, P=0.14; r=0.20,P=0.09; r=0.01, P=0.95; r=0.01, P=0.93). Conclusion No significant correlation is found between the tumor size and each of the quantifiable parameters of blood flow pattern derived with dynamic CT in maliagnant solitary pulmonary nodules

Comprehensive Evaluation of Coal-Fired Power Units Using Grey Relational Analysis and a Hybrid Entropy-Based Weighting Method

In recent years, coal-fired power plants contribute the biggest part of power generation in China. Challenges of energy conservation and emission reduction of the coal-fired power plant encountering with a rapid growth due to the rising proportion of renewable energy generation in total power generation. Energy saving power generation dispatch (ESPGD) based on power units sorting technology is a promising approach to meet the challenge. Therefore, it is crucial to establish a reasonable and feasible multi-index comprehensive evaluation (MICE) framework for assessing the performance of coal-fired power units accessed by the power grid. In this paper, a hierarchical multiple criteria evaluation system was established. Except for the typical economic and environmental indices, the evaluation system considering operational flexibility and power quality indices either. A hybrid comprehensive evaluation model was proposed to assess the unit operational performance. The model is an integration of grey relational analysis (GRA) with analytic hierarchy process (AHP) and a novel entropy-based method (abbreviate as BECC) which integrates bootstrap method and correlation coefficient (CC) into entropy principle to get the objective weight of indices. Then a case study on seven typical 600 megawatts coal-fired power units was carried out to illustrate the proposed evaluation model, and a weight sensitivity analysis was developed in addition. The results of the case study shows that unit 4 has the power generating priority over the rest ones, and unit 2 ranks last, with the lowest grey relational degree. The weight sensitivity analysis shows that the environmental factor has the biggest sensitivity coefficient. And the validation analysis of the developed BECC weight method shows that it is feasible for the MICE model, and it is stable with an ignorable uncertainty caused by the stochastic factor in the bootstrapping process. The elaborate analysis of the result reveals that it is feasible to rank power units with the proposed evaluation model. Furthermore, it is beneficial to synthesize the updated multiple criteria in optimizing the power generating priority of coal-fired power units

An Integrated Multi-Criteria Decision Making Model and AHP Weighting Uncertainty Analysis for Sustainability Assessment of Coal-Fired Power Units

The transformation of the power generation industry from coal-based to more sustainable energy sources is an irreversible trend. In China, the coal-fired power plant, as the main electric power supply facility at present, needs to know its own sustainability level to face the future competition. A hybrid multi-criteria decision making (MCDM) model is proposed in this paper to assess the sustainability levels of the existing Chinese coal-fired power units. The areal grey relational analysis (AGRA) method is involved in the hybrid model, and a combined weighting method is used to determine the priorities of the criteria. The combining weight fuses the fuzzy rough set (FRS) and entropy objective weighting method together with the analytic hierarchy process (AHP) subjective weighting method by game theory. Moreover, an AHP weighting uncertainty analysis using Monte Carlo (MC) simulation is introduced to measure the uncertainty of the results, and a 95 percent confidence interval (CI) is defined as the uncertainty measurement of the alternatives. A case study about eight coal-fired power units is carried out with a criteria system, which contains five aspects in an operational perspective, such as the flexibility, economic, environmental, reliability and technical criterion. The sustainability assessment is performed at the unit level, and the results give a priority rank of the eight alternatives; additionally, the uncertainty analysis supplies the extra information from a statistical perspective. This work expands a novel hybrid MCDM method to the sustainability assessment of the power generation systems, and it may be a benefit to the energy enterprises in assessing the sustainability at the unit level and enhance its ability in future sustainable development

Low-Carbon Optimization Design for Low-Temperature Granary Roof Insulation in Different Ecological Grain Storage Zones in China

The optimization design of buildings is very important to the energy consumption, carbon emissions, and sustainable development of buildings. The low-temperature granary has a low grain storage temperature and high energy consumption indexes. The design scheme of the roof insulation for a low-temperature granary should be determined in actual building design processes by considering the costs, carbon emissions, and outdoor climate, comprehensively. In this paper, a new low-carbon optimization design method is proposed for the roof insulation in the low-temperature granary. The low-carbon optimization design method can respond to the cost issue, emission reduction issue, and outdoor climate issue, simultaneously. Moreover, the low-temperature granary roof insulation of different ecological grain storage zones in China is optimized in terms of carbon reduction by using the proposed low-carbon optimization design method. The application results of the optimization design method in different ecological grain storage zones in China indicate that the outdoor climate has significant impacts on the economic performance and carbon reduction effect of roof insulation. The cost considerations related to carbon emissions can apparently increase the economic efficiency of roof insulation. The optimal economic thicknesses of expanded polystyrene (EPS) in the cities of Urumqi, Harbin, Zhengzhou, Changsha, Guiyang, and Haikou are 0.025 m, 0.037 m, 0.085 m, 0.097 m, 0.072 m, and 0.148 m, respectively. The different outdoor climates of the seven ecological grain storage areas in China have important influences on the comprehensive economic performances of low-temperature granary roof insulation. The design of the low-temperature granary roof insulation in Haikou city has the best economic performance among the seven ecological grain storage zones in China

An Improved System for Utilizing Low-Temperature Waste Heat of Flue Gas from Coal-Fired Power Plants

In this paper, an improved system to efficiently utilize the low-temperature waste heat from the flue gas of coal-fired power plants is proposed based on heat cascade theory. The essence of the proposed system is that the waste heat of exhausted flue gas is not only used to preheat air for assisting coal combustion as usual but also to heat up feedwater and for low-pressure steam extraction. Air preheating is performed by both the exhaust flue gas in the boiler island and the low-pressure steam extraction in the turbine island; thereby part of the flue gas heat originally exchanged in the air preheater can be saved and introduced to heat the feedwater and the high-temperature condensed water. Consequently, part of the high-pressure steam is saved for further expansion in the steam turbine, which results in additional net power output. Based on the design data of a typical 1000 MW ultra-supercritical coal-fired power plant in China, an in-depth analysis of the energy-saving characteristics of the improved waste heat utilization system (WHUS) and the conventional WHUS is conducted. When the improved WHUS is adopted in a typical 1000 MW unit, net power output increases by 19.51 MW, exergy efficiency improves to 45.46%, and net annual revenue reaches USD 4.741 million while for the conventional WHUS, these performance parameters are 5.83 MW, 44.80% and USD 1.244 million, respectively. The research described in this paper provides a feasible energy-saving option for coal-fired power plants