Residue Number System Fade Mitigation Technique with Error Detection and Correction on a Satellite Communication Link
Stephen Akobre,
Mohammed Ibrahim Daabo,
Abdul-Mumin Salifu
Issue:
Volume 9, Issue 2, December 2021
Pages:
23-32
Received:
28 July 2021
Accepted:
12 August 2021
Published:
24 August 2021
Abstract: Rain fade is the loss of signal power at the receiver of a telecommunication system mainly due to absorption and scattering caused by rain in the transmission medium, especially at frequencies above 10 GHz. In order to combat the loss of the signal power at the receiver, there is the need to employ rain fade mitigation techniques. Consequently, researchers have been studying how rain affects the signal in different geographical locations as well as proposing some mitigation techniques. Power control is one of the mitigation techniques that have been proposed. But this technique has some associated challenges. Increasing the power will lead to an increase in cost of transmission which will eventually be passed on to the consumer thereby making satellite services expensive. It requires high power in uplink and downlink which increases the burden either on user terminal or satellite payload. Also, because of health concerns there is a limit to the amount of power that can be radiated to the ground and this is governed by international agreements. Another power management drawback in using this technique is that, uplink power control is not efficient in directing the added power to only the ground station experiencing path attenuation, because the additional power is distributed to all locations within the satellite antenna coverage area. In this paper, we address the power control challenges, by leveraging on the inherent properties of Residue Number System (RNS) and Redundant Residue Number System (RRNS) to propose an RNS architecture using the moduli set {22n+1-1, 22n -1, 22n, 24n+1 -1, 22n +1} that can mitigate rain fade in the satellite link as well as detect and correct multiple errors. In digital communication systems, the bit energy, eb, is the most important parameter in determining the communications link performance. Numerical analysis shows that the proposed scheme performs better than the traditional method as indicated in the high energy per bit value obtained in the proposed system in comparison with the traditional method, all other things being equal.
Abstract: Rain fade is the loss of signal power at the receiver of a telecommunication system mainly due to absorption and scattering caused by rain in the transmission medium, especially at frequencies above 10 GHz. In order to combat the loss of the signal power at the receiver, there is the need to employ rain fade mitigation techniques. Consequently, res...
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Image Processing Techniques and Neuro-computing Algorithms in Computer Vision
Ibrahim Goni,
Asabe Sandra Ahmadu,
Yusuf Musa Malgwi
Issue:
Volume 9, Issue 2, December 2021
Pages:
33-38
Received:
30 July 2021
Accepted:
16 August 2021
Published:
12 October 2021
Abstract: Computer vision is a multidisciplinary field that cannot be separated with image processing techniques and Neuro-Computing specifically Deep Learning (DL) algorithms, in recent time DL techniques enable computer vision to understand the content of an image, moreover, it is working hand in hand with image processing techniques because image preprocessing are essential components in digital image analysis. Therefore, the remarkable advancement recorded by computer vision today such as in remote sensing, security, medical imaging and robotics etc. The aim of this research work was to explored the technical and theoretical contributions of image processing techniques and DL algorithms to computer vision. A systematic method of literature review was adapted. Basic image processing techniques such as standardization, denoising, filtering, and segmentation are clearly explored, concept of DL algorithms are briefly discussed, recent reviewed articles (from 2018 to date) are obtained from top journals in computer vision thus; IEEE, Elsevier and ISPR and tabulated as a major source of information for this work. We have shown some of the software’s used for the implementation of deep learning researches in computer vision. Finally we concludes and give recommendations based on our findings.
Abstract: Computer vision is a multidisciplinary field that cannot be separated with image processing techniques and Neuro-Computing specifically Deep Learning (DL) algorithms, in recent time DL techniques enable computer vision to understand the content of an image, moreover, it is working hand in hand with image processing techniques because image preproce...
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