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.
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