Near-Optimal Contraction of Voronoi Regions for Pruning of Blind Decoding Results

2015 ◽  
Vol 63 (6) ◽  
pp. 1963-1974
Author(s):  
Dongwoon Bai ◽  
Jungwon Lee ◽  
Sungsoo Kim ◽  
Hanju Kim ◽  
Inyup Kang
Keyword(s):  
2009 ◽  
Vol 34 (1) ◽  
pp. 116-126 ◽  
Author(s):  
Cristobal Luque ◽  
Jose M. Valls ◽  
Pedro Isasi

2012 ◽  
Vol 588-589 ◽  
pp. 802-805
Author(s):  
Ban Teng Liu ◽  
Xi Lin Hu ◽  
Zheng Yu Xu ◽  
Yao Lin Liu ◽  
You Rong Chen

This paper propose a two-tiered network in which lower-power users communicate with one another through repeaters, which amplify signals and retransmit them, have limited capacity, and may interfere with one another if their transmitter frequencies are close and they share the same private-line tone. Motivated by cellular networks, this paper gives a naive solution where the number of repeaters and their positions can be obtained analytically. In a circular area with radius 40 miles, 12 repeaters can accommodate 1,000 simultaneous users. This paper further propose an iterative refinement algorithm consisting of three fundamental modules that draw the Voronoi diagram, determine the centers of the circumscribed circles of the Voronoi regions, and escape the local optimum by using external optimization. The algorithm obtains a solution with 11 repeaters, which we prove to be the absolute minimum. For 10,000 users, it uses 104 repeaters, better than the naive solution's 108.


Algorithms ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 41
Author(s):  
Jie Chen ◽  
Gang Yang ◽  
Meng Yang

In our daily lives, many plane patterns can actually be regarded as a compact distribution of a number of elements with certain shapes, like the classic pattern mosaic. In order to synthesize this kind of pattern, the basic problem is, with given graphics elements with certain shapes, to distribute a large number of these elements within a plane region in a possibly random and compact way. It is not easy to achieve this because it not only involves complicated adjacency calculations, but also is closely related to the shape of the elements. This paper attempts to propose an approach that can effectively and quickly synthesize compact distributions of elements of a variety of shapes. The primary idea is that with the seed points and distribution region given as premise, the generation of the Centroidal Voronoi Tesselation (CVT) of this region by iterative relaxation and the CVT will partition the distribution area into small regions of Voronoi, with each region representing the space of an element, to achieve a compact distribution of all the elements. In the generation process of Voronoi diagram, we adopt various distance metrics to control the shape of the generated Voronoi regions, and finally achieve the compact element distributions of different shapes. Additionally, approaches are introduced to control the sizes and directions of the Voronoi regions to generate element distributions with size and direction variations during the Voronoi diagram generation process to enrich the effect of compact element distributions. Moreover, to increase the synthesis efficiency, the time-consuming Voronoi diagram generation process was converted into a graphical rendering process, thus increasing the speed of the synthesis process. This paper is an exploration of elements compact distribution and also carries application value in the fields like mosaic pattern synthesis.


Author(s):  
Farid Sharifi ◽  
Youmin Zhang ◽  
Brandon W. Gordon

This paper investigates the problem of covering an environment using a group of quadrotor Unmanned Aerial Vehicles (UAVs) based on locational optimization techniques to assign Voronoi regions to vehicles. In comparison with the standard coverage control problems for single integrator agents, we design a planar position controller for UAVs to spread out over an environment to provide coverage. The stability of entire system is guaranteed using LaSalle’s invariance principle, and numerical simulation is provided to show the effectiveness of the proposed method.


2014 ◽  
Vol 36 (2) ◽  
pp. A792-A827 ◽  
Author(s):  
Lisa J. Larsson ◽  
Rustum Choksi ◽  
Jean-Christophe Nave

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