Despite the large bandwidth available for all users in high-speed wireless networks, resources allocation and user scheduling remain essential to combat interference, increase throughput and reduce complexity. As the number of users increases, the computational complexity tends to increase significantly. The trade-off between the complexity reduction and capacity improvement is the challenge. Hence a unique ant-colony optimisation method is implemented with successive interference cancellation to reduce complexity and provide higher capacity to more users. The incurred complexity is at least 50% less than other schemes. The average mean square error achieved is around 4 dB smaller than that of the existing scheme.
Abstract-The study of earth terrain in Antarctica is important as this region has a direct impact on global environment and weather condition. There have been many research works in developing remote sensing technologies, as it can be used as an earth observation technique to monitor the polar region [11,15]. In previous studies, remote sensing forward model has been developed to study and understand scattering mechanisms and sensitivity of physical parameters of snow and sea ice. This paper is an extended work from previous studies [16][17][18][19], where an improved theoretical model to study polar region was developed. Multiple-surface scattering, based on an existing integral equation model (IEM) that calculates surface scattering and additional second-order surface-volume scattering, were added in the model from prior research works [7] for improvement in the backscattering calculation. We present herein the application of this model on a snow layer above ground which is modeled as a volume of ice particles that are closely packed and bounded by irregular boundaries above a homogenous half space. The effect of including multiple surface scattering and additional surface-volume scattering up to second order in the backscattering coefficient calculation of snow layer is studied for co-polarized and cross-polarized returns. Comparisons with satellite data are also done for validation. Results show improvement in the total backscattering coefficient for cross-polarized return in the studied range, suggesting that multiple-surface scattering and surface-volume scattering up to second order are important scattering mechanisms in the snow layer and should not be ignored in polar research.
Driving vehicles in all-weather conditions is challenging as the lane markers tend to be unclear to the drivers for detecting the lanes. Moreover, the vehicles will move slower hence increasing the road traffic congestion which causes difficulties in detecting the lane markers especially for advanced driving assistance systems (ADAS). Therefore, this paper conducts a thorough review on vision-based lane marking detection algorithms developed for all-weather conditions. The review methodology consists of two major areas, which are a review on the general system models employed in the lane marking detection algorithms and a review on the types of weather conditions considered for the algorithms. Throughout the review process, it is observed that the lane marking detection algorithms in literature have mostly considered weather conditions such as fog, rain, haze and snow. A new contour-angle method has also been proposed for lane marker detection. Most of the research work focus on lane detection, but the classification of the types of lane markers remains a significant research gap that is worth to be addressed for ADAS and intelligent transport systems.
Remote sensing has been used in Antarctic studies as an earth observation technique to study the polar region. A remote sensing forward model is an important tool in polar research to study and understand scattering mechanisms and sensitivity of physical parameters of snow and sea ice. In this paper, a reliable theoretical model to study sea ice is developed. The theoretical model in a prior work was improved by including multiple-surface scattering, based on an existing integral equation model and additional second-order surface-volume scattering. This model is applied to a desalinated ice layer above thick saline ice and analyzed using different frequencies, bottom surface roughness and sea-ice layer thickness. Improvement in calculation of the backscattering coefficient of the sea-ice layer is investigated for both co-polarized and cross-polarized returns. The effect on each scattering mechanism is also investigated, to understand in more detail the effect of surface multiple scattering and second-order surface-volume scattering. Comparisons are also made with field measurement results, to validate the theoretical model. Results show improvement in the total backscattering coefficient for cross-polarized return in the studied range, suggesting that multiple-surface scattering and surface-volume scattering up to second order are important scattering mechanisms in the sea-ice layer and should not be ignored in polar research.
Antarctica remains the continent with least access to human due to its harsh weather condition and remoteness from human civilization. However, the major heat sink effect and its critical role in balancing world climate have made Antarctica an important continent to monitor and understand constantly. Due to its remoteness and wide area coverage, remote sensing technology is suitable to be utilized for such purposes. As the majority parts of Antarctica are covered by ice and snow, it is necessary to model the ice and snow media for microwave scattering analysis to interpret the satellite SAR images and deduce physical parameters from the data. In this paper, a theoretical model is developed to model the sea ice and ice shelf areas in Antarctica by treating them as layers of random discrete medium with scatterers embedded in the host medium. The Dense Medium Phase and Amplitude Correction Theory (DMPACT) which takes into account the close spacing effect among the scatterers is applied to the sea ice and snow medium [1]. The air-snow interface and snow-sea ice interface are modeled using the Integral Equation Method (IEM) with the consideration of surface multiple scattering effect [2]. This scattering problem of an electrically dense medium such as sea ice and ice shelf is solved using the Radiative Transfer Theory. Ground truth measurement trips were conducted in the years of 2002-2004 at Ross Island, Antarctica with the logistic assistance of Antarctica New Zealand to measure the physical parameters of the sea ice, ice shelf and sea water, which were then used in the theoretical model calculation. RadarSat images of the study sites were also acquired for the comparison with the theoretical results. The results indicate that the matches between the theoretical predictions and the satellite data over the measurement period are promising. In the theoretical analysis, a study of the physical parameters affecting the backscattering returns and the major scattering mechanisms involved is carried out and the analysis is presented. This project is funded by the Academy of Sciences Malaysia, under the Malaysian Antarctica Research Program (MARP).
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