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Distributed Resource Allocation for Two-Tier Heterogeneous Cellular Networks
--O Oguejiofor, A Abe, A N Aniedu and G N Okechukwu
Heterogeneous cellular Network (HetNet) is a promising technology for 5th generation (5G) mobile networks that can potentially improve spatial resource reuse and extend coverage, therefore allowing it to achieve significantly higher data rates than single-tier networks. However, the performance of HetNet is limited by co-channel (inter-UE, inter-cell) interference. Hence, resource allocation is carefully done in this paper to ensure that the loss in achievable data rate due to interference does not diminish the gain in the achievable data rate due to higher spatial reuse. The resources considered are the spatial resource (unit-beamformer) and the power resource. Distributed spatial resource allocation problem is formulated as a quadratic optimization problem with non-convex quadratic constraints and solved by exploiting Karush-Kuhn-Tucker (KKT) conditions. The proposed hybrid power resource allocation scheme involves a three-step process, starting with two power optimization procedures. These two power optimization procedures are formulated as convex optimization problems and solved by exploiting KKT conditions and CVX
(a Matlab software for discipline convex programming), respectively, while the third step involves utilizing results from the aforementioned power optimization procedures to compute average powers allocated to UEs. The simulation results of the proposed method, when compared with other existing methods showed significant improvement.
© 2018 IUP. All Rights Reserved.
An Entropy-Based Binarization Method
to Separate Foreground from Background in Document Image Processing
--Parthajit Roy and Swati Adhikari
Character recognition is a branch of pattern recognition, where texts or characters are realized from images. Binarization is an important step of character recognition, where foregrounds or texts or characters are separated from backgrounds. The paper proposes a novel entropy-based fuzzy clustering method for text binarization of a gray-level document image. The proposed method considers the spatial information of the gray pixels and the original gray level values for its computations. In order to separate text or document pixels and background pixels in a more realistic way, the proposed method incorporates fuzzy logic-based decision system. The performance of the method has been tested with several images consisting of different Indian languages and the results are evaluated with respect to two existing standard binarization methods.
© 2018 IUP. All Rights Reserved.
Evolution of Non-Conventional
MOS Device Structures: A Review
--Navneet Kaur, Munish Rattan and Sandeep Singh Gill
High packing density and low power dissipation in a chip are the needs of very large-scale integrated circuits. As technology is shrinking, conducting channels are becoming shorter to add more devices onto the fixed area, but simultaneously certain factors arise which degrade the device performance. To overcome the limitations of short channel MOS transistors, several designs for the device architecture like Double Gate (DG) and Triple Gate (TG) MOS structures have been explored. The paper reviews the performance advantages of each advanced structure and relative dependence on various process parameters. Also, the developed analytical models for calculating drain current, surface potential, transcapacitances, etc., of these structures have been assessed.
© 2018 IUP. All Rights Reserved.
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