The relay technology is an essential piece of LTE-Advanced in its pursuit of cost effective capacity enhancement and coverage extension. Simple RF repeaters have been widely used in cellular technologies to offer coverage extension. However, they cannot distinguish desired signals from interference and noise and are unable to operate with sophisticated mechanisms, such as power control, beam-forming, and adaptive modulating/coding. As a result, simple RF repeaters do not provide capacity enhancement nor do they reach the capacity potential of extended coverage areas. The use of more sophisticated relay in cellular technologies is relatively new. With its great benefits in QoS differentiation, capacity enhancement, and coverage extension, the development of LTE relay technology faces challenges in providing backward compatibility, minimizing complexity, providing sufficient QoS differentiation, reducing over the air overhead, and ensuring security. This paper addresses these challenges with solutions in the aspect of relay architecture and upper layer designs.

We analyze the properties of straight homogeneous generalized cylinders (SHGCs) and constant cross section generalized cylinders (CGCs), and derive the types of symmetries that the limb boundaries and cross sections of these objects produce on the image plane. The constraints on the 3D shape of the objects are formulated based on the symmetries and from the geometry of the projection models. Finally, the methods that recover the 3D shape from the image of their contours are discussed and recovered surfaces are shown for sample objects.>

Inference of 3-D shape from 2-D contours in a single image is an important problem in machine vision. The authors survey classes of techniques proposed in the past and provide a critical analysis. They show that two kinds of symmetries in figures, which are known as parallel and skew symmetries, give significant information about surface shape for a variety of objects. They derive the constraints imposed by these symmetries and show how to use them to infer 3-D shape. They also discuss the zero Gaussian curvature (ZGC) surfaces in depth and show results on the recovery of surface orientation for various ZGC surfaces.>

The authors describe a technique for inference of 3-D shape from 2-D contours that utilizes not only the shapes of individual surfaces but also the interactions between them. The analysis applies to objects made of zero-Gaussian curvature surfaces viewed under orthographic projection.>

The authors analyze the properties of constant cross section generalized cylinders (CGCs), and derive the types of symmetries that the limb boundaries and cross sections of these objects produce on the image plane. The constraints on the 3-D shape of the objects are formulated based on the symmetries and from the geometry of the projection models. The methods that recover the 3-D shape from the image of their contours are discussed and recovered surfaces are shown for sample objects.>

The authors analyze the properties of straight homogeneous generalized cones (SHGCs) and derive the types of symmetries, that the limb boundaries and cross sections of these objects produce on the image plane. The constraints on the 3-D shape of the objects are formulated based on the symmetries and from the geometry of the projection models. Finally the methods that recover the 3-D shape from the image of their contours are discussed and recovered surfaces are shown for sample objects.>

A technique based on analysis of symmetries in an image is proposed for inferring the 3-D shapes of surfaces of objects in it. This technique is analyzed and applied to zero-Gaussian-curvature surfaces. The method consists of deriving a number of constraints based on a few simple assumptions. The combination of constraints to give unique (or few) solutions is discussed. Experimental results on selected scenes are given and are shown to conform well with human perception.>

The Laplacian of Gaussian (LoG) operator is one of the most popular operators used in edge detection. This operator, however, has some problems: zero-crossings do not always correspond to edges, and edges with an asymmetric profile introduce a symmetric bias between edge and zero-crossing locations. The authors offer solutions to these two problems. First, for one-dimensional signals, such as slices from images, they propose a simple test to detect true edges, and, for the problem of bias, they propose different techniques: the first one combines the results of the convolution of two LoG operators of different deviations, whereas the others sample the convolution with a single LoG filter at two points besides the zero-crossing. In addition to localization, these methods allow them to further characterize the shape of the edge. The authors present an implementation of these techniques for edges in 2-D images.>

Inference of 3-D shape from 2-D contours in a single image is an important problem in machine vision. We survey classes of techniques proposed in the past and provide a critical analysis. We propose two kinds of symmetries in figures, which we call parallel and mirror symmetries, give significant information about surface shape for a variety of objects. We show the constraints imposed by these symmetries and how to use them to infer 3-D shape. Our method is applicable to any zero-gaussian curvature surface, and also to a variety of doubly curved surfaces. One of our mathematical results is that for a cone, the surface shape can be constructed uniquely under very simple assumptions. We also show some preliminary results on extraction of symmetries from real images.