Transmission Experiment of Bandwidth Compressed Carrier Aggregation in a Realistic Fading Channel

In this paper, an experimental testbed is designed to evaluate the performance of a bandwidth compressed multicarrier technique termed spectrally efficient frequency division multiplexing (SEFDM) in a carrier aggregation (CA) scenario1. Unlike orthogonal frequency division multiplexing (OFDM), SEFDM is a non-orthogonal waveform which, relative to OFDM, packs more sub-carriers in a given bandwidth, thereby improving spectral efficiency. CA is a long term evolution-advanced (LTE-Advanced) featured technique that offers a higher throughput by aggregating multiple legacy radio bands. Considering the scarcity of radio spectrum, SEFDM signals can be utilized to enhance CA performance. The combination of the two techniques results in a larger number of aggregated component carriers (CCs) and therefore increased data rate in a given bandwidth with no additional spectral allocation. It is experimentally shown that CA-SEFDM can aggregate up to 7 CCs in a limited bandwidth while CA-OFDM can only put 5 CCs in the same bandwidth. In this work, LTE-like framed CA-SEFDM signals are generated and delivered through a realistic LTE channel. A complete experimental setup is described together with error performance and effective spectral efficiency comparisons. Experimental results show that the measured BER performance for CA-SEFDM is very close to CA-OFDM and the effective spectral efficiency of CA-SEFDM can be substantially higher than that of CA-OFDM

Exact Algorithms for the Maximum Planar Subgraph Problem: New Models and Experiments

Given a graph G, the NP-hard Maximum Planar Subgraph problem asks for a planar subgraph of G with the maximum number of edges. The only known non-trivial exact algorithm utilizes Kuratowski\u27s famous planarity criterion and can be formulated as an integer linear program (ILP) or a pseudo-boolean satisfiability problem (PBS). We examine three alternative characterizations of planarity regarding their applicability to model maximum planar subgraphs. For each, we consider both ILP and PBS variants, investigate diverse formulation aspects, and evaluate their practical performance

Mathematics and Digital Signal Processing

Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems

Faster and better nested dissection orders for Customizable Contraction Hierarchies

Graph partitioning has many applications. We consider the acceleration of shortest path queries in road networks using Customizable Contraction Hierarchies (CCH). It is based on computing a nested dissection order by recursively dividing the road network into parts. Recently, with FlowCutter and Inertial Flow, two flow-based graph bipartitioning algorithms have been proposed for road networks. While FlowCutter achieves high-quality results and thus fast query times, it is rather slow. Inertial Flow is particularly fast due to the use of geographical information while still achieving decent query times. We combine the techniques of both algorithms to achieve more than six times faster preprocessing times than FlowCutter and even faster queries on the Europe road network. We show that, using 16 cores of a shared-memory machine, this preprocessing needs four minutes

Fast Dynamic Arrays

We present a highly optimized implementation of tiered vectors, a data structure for maintaining a sequence of n elements supporting access in time O(1) and insertion and deletion in time O(n^e) for e > 0 while using o(n) extra space. We consider several different implementation optimizations in C++ and compare their performance to that of vector and set from the standard library on sequences with up to 10^8 elements. Our fastest implementation uses much less space than set while providing speedups of 40x for access operations compared to set and speedups of 10.000x compared to vector for insertion and deletion operations while being competitive with both data structures for all other operations

Advances in raw material industries for sustainable development goals

"""Advances in Raw Material Industries for Sustainable Development Goals"" presents the results of joint scientific research conducted in the context of the Russian-German Raw Materials Forum. Today Russia and Germany are exploring various forms of cooperation in the field of mining, geology, mineralogy, mechanical engineering and energy. Russia and Germany are equally interested in expanding cooperation and modernizing the economy in terms of sustainable development. The main theme of this article collection is connected with existing business ventures and ideas from both Russia and Germany. In this book the authors regard complex processes in mining industry from various points of view, including: - modern technologies in prospecting, exploration and development of mineral resources - progressive methods of natural and industrial mineral raw materials processing - energy technologies and digital technologies for sustainable development - cutting-edge technologies and innovations in the oil and gas industry. Working with young researchers, supporting their individual professional development and creating conditions for their mobility and scientific cooperation are essential parts of Russian-German Raw Materials Forum founded in Dresden 13 years ago. This collection represents both willingness of young researchers to be involved in large-scale international projects like Russian-German Raw Material Forum and the results of their long and thorough work in the promising areas of cooperation between Russia and Germany.