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Collaboration and competition spatial complex networks in regional science

Journal of Ambient Intelligence and Humanized Computing 2024年第3期15卷 1995-2008页

作者： Salcedo-Sanz, S. Cornejo-Bueno, S. Casillas-Pérez, D. Camacho-Gómez, C. Cuadra, L. Chidean, M.I. Caamaño, A.J. Department of Signal Processing and Communications Universidad de Alcalá Alcalá de Henares Madrid Spain Department of Signal Processing and Communications Universidad Rey Juan Carlos Fuenlabrada Spain Department of Information Systems Universidad Politécnica de Madrid Madrid Spain

This paper discusses different spatial complex networks construction models useful in Regional Science, and different associated issues and problems. First, we define two different models of spatial networks: Collaboration (SCN) and Competition (SCtN) network, both based on distances among nodes. We then discuss several problems related to Regional Science in these types of spatial networks, showing alternative cases and possible computational solutions. Evolutionary algorithms are proposed to solve these problems both in SCN and SCtN. The experimental part of the paper is comprehensive, and it discuses several approaches for spatial network modelling and construction by means of different computational experiments and simulations, including the evolution of SCN and SCtN in Regional Science problems. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.

关键词： Complex networks

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Saliency-Driven Hierarchical Learned Image Coding for Machines 48

Saliency-Driven Hierarchical Learned Image Coding for Machin...

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48th IEEE International Conference on Acoustics, Speech and signal processing, ICASSP 2023

作者： Fischer, Kristian Brand, Fabian Blum, Christian Kaup, Andre Multimedia Communications and Signal Processing Germany

ISBN: (纸本)9781728163277

We propose to employ a saliency-driven hierarchical neural image compression network for a machine-to-machine communication scenario following the compress-then-analyze paradigm. By that, different areas of the image are coded at different qualities depending on whether salient objects are located in the corresponding area. Areas without saliency are transmitted in latent spaces of lower spatial resolution in order to reduce the bitrate. The saliency information is explicitly derived from the detections of an object detection network. Furthermore, we propose to add saliency information to the training process in order to further specialize the different latent spaces. All in all, our hierarchical model with all proposed optimizations achieves 77.1 % bitrate savings over the latest video coding standard VVC on the Cityscapes dataset and with Mask R-CNN as analysis network at the decoder side. Thereby, it also outperforms traditional, non-hierarchical compression networks. © 2023 IEEE.

关键词： Image compression

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A Novel Cross-Component Context Model for End-to-End Wavelet Image Coding 48

A Novel Cross-Component Context Model for End-to-End Wavelet...

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48th IEEE International Conference on Acoustics, Speech and signal processing, ICASSP 2023

作者： Meyer, Anna Kaup, Andre Multimedia Communications and Signal Processing Erlangen Germany

ISBN: (纸本)9781728163277

In contrast to traditional compression techniques performing linear transforms, the latent space of popular compressive autoencoders is obtained from a learned nonlinear mapping and hard to interpret. In this paper, we explore a promising alternative approach for neural compression, with an autoencoder whose latent space represents a nonlinear wavelet decomposition. Previous work has shown that neural wavelet image coding can outperform HEVC. However, the approach codes color components independently, thereby ignoring inter-component dependencies. Hence, we propose a novel crosscomponent context model (CCM). With CCM, the entropy model for the chroma latent space can be conditioned on previously coded components exploiting correlations in the learned wavelet space. The proposed CCM outperforms the baseline model with average Bjontegaard delta rate savings of 2.6 % and 1.6 % for the Kodak and Tecnick image sets. Also, our method is competitive with VVC and learning-based methods. © 2023 IEEE.

关键词： Image compression

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Deep Probabilistic Model for Lossless Scalable Point Cloud Attribute Compression 48

Deep Probabilistic Model for Lossless Scalable Point Cloud A...

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48th IEEE International Conference on Acoustics, Speech and signal processing, ICASSP 2023

作者： Nguyen, Dat Thanh Nambiar, Kamal Gopikrishnan Kaup, André Multimedia Communications and Signal Processing Erlangen Germany

ISBN: (纸本)9781728163277

In recent years, several point cloud geometry compression methods that utilize advanced deep learning techniques have been proposed, but there are limited works on attribute compression, especially lossless compression. In this work, we build an end-to-end multiscale point cloud attribute coding method (MNeT) that progressively projects the attributes onto multiscale latent spaces. The multiscale architecture provides an accurate context for the attribute probability modeling and thus minimizes the coding bitrate with a single network prediction. Besides, our method allows scalable coding that lower quality versions can be easily extracted from the losslessly compressed bitstream. We validate our method on a set of point clouds from MVUB and MPEG and show that our method outperforms recently proposed methods and on par with the latest G-PCC version 14. Besides, our coding time is substantially faster than G-PCC. © 2023 IEEE.

关键词： Deep Learning G-PCC MNeT Point Cloud Sparse Convolution

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Modeling Time-Varying Latency in 5G Non-Terrestrial Networks 21

Modeling Time-Varying Latency in 5G Non-Terrestrial Networks

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21st IEEE India Council International Conference, INDICON 2024

作者： Tadavarty, Sriram Chavali, Nanda Kishore Signal Processing and Communications MathWorks Hyderabad India

ISBN: (纸本)9798350391282

In the view of worldwide internet coverage, the Third-Generation Partnership Project (3GPP) started the study of satellite or aerial access to the existing cellular technologies. The network that uses the flying objects (satellites or high-altitude platform systems) for any access are referred to as non-terrestrial network (NTN). In comparison with terrestrial networks, NTN networks impose a couple of challenges, namely, the time-varying latency and the time-varying Doppler. The time the signal travels from the source to the destination is called latency. The time-varying latency leads to an increase in timers in the protocol stack. This latency must be known to analyze its impact on physical layer processing like synchronization, aggregation, and hybrid automatic repeat request acknowledgment. This paper discusses the computation methodology for modeling the latency for NTN terminal as source and destination. The latency is analyzed as a function of the elevation angle for different satellite orbits. © 2024 IEEE.

关键词： Queueing networks

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In-band full-duplex MIMO PLC systems for relaying networks

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Digital communications and Networks 2025年第1期11卷 145-159页

作者： Francisco J.Canete Gautham Prasad Lutz Lampe Communications and Signal Processing Lab Telecommunication Research Institute(TELMA)ETS Ingenieria TelecomunicacionUniversidad de MalagaSpain Ofinno RestonVAUSA Department of Electrical and Computer Engineering The University of British ColumbiaCanada

In Power Line communications(PLC),there are regulatory masks that restrict the transmit power spectral density for electromagnetic compatibility reasons,which creates coverage issues despite the not too long ***,PLC networks often employ repeaters/relays,especially in smart grid neighborhood area *** in broadband indoor PLC systems that offer a notable data rate,relaying may pave the way to new applications like being the backbone for wireless technologies in a cost-effective manner to support the Internet-of-things *** this paper,we study Multiple-Input Multiple-Output(MIMO)PLC systems that incorporate inband full-duplex functionality in relaying *** present several MIMO configurations that allow end-to-end half-duplex or full-duplex operations and analyze the achievable performance with state-of-the-art PLC *** reach this analysis,we get channel realizations from random network layouts for indoor and outdoor *** adopt realistic MIMO channel and noise models and consider transmission techniques according to PLC *** concepts discussed in this work can be useful in the design of future PLC relay-aided networks for different applications that look for a coverage extension and/or throughput:smart grids with enhanced communications in outdoor scenarios,and“last meter”systems for high-speed connections everywhere in indoor ones.

关键词： PLC MIMO Relaying networks OFDM Spatial correlation Performance analysis

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Multiresolution Point Cloud Compression for Real-Time Visualization and Streaming of Large 3D Datasets 58

Multiresolution Point Cloud Compression for Real-Time Visual...

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58th Asilomar Conference on signals, Systems and Computers, ACSSC 2024

作者： Nguyen, Dat Thanh Zieger, Daniel Gambietz, Markus Koelewijn, Anne D. Stamminger, Marc Kaup, André Multimedia Communications and Signal Processing Erlangen Germany Visual Computing Erlangen Germany Erlangen Germany

ISBN: (纸本)9798350354058

In recent years, the integration of point cloud data has been observed across diverse domains such as immersive media, autonomous driving, and healthcare. However, processing and visualizing 3D point cloud data requires more computational power and processing time than typical 2D images or videos. In this paper, we present a multiresolution point cloud visualization approach that enables the encoding and reconstruction of human body point clouds at multiple quality/bitrate levels for streaming or real-time visualization applications. Specifically, we partition the 3D model into cells and build an octree structure to store the point cloud at multiple levels of detail. The hierarchical structure is encoded efficiently for fast loading times. We optimize the resolution selection for each visible node based on the camera viewpoint and the geometric error perceived by the user. We validate the proposed method using a widely known point cloud dataset from the Moving Picture Experts Group. The experiments demonstrate that the method can dynamically adapt the resolution of point clouds and provide faster rendering times compared to well-known point cloud visualization software. © 2024 IEEE.

关键词： Rendering (computer graphics)

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RGB-Guided Resolution Enhancement of IR Images 30

RGB-Guided Resolution Enhancement of IR Images

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30th International Conference on Systems, signals and Image processing, IWSSIP 2023

作者： Trammer, Marcel Genser, Nils Seiler, Jurgen Ai & Signal Processing Lab Sielaff GmbH & Co. Kg Herrieden Germany Multimedia Communications and Signal Processing Erlangen Germany

ISBN: (纸本)9798350337297

This paper introduces a novel method for RGB-Guided Resolution Enhancement of infrared (IR) images called Guided IR Resolution Enhancement (GIRRE). In the area of single image super resolution (SISR) there exists a wide variety of algorithms like interpolation methods or neural networks to improve the spatial resolution of images. In contrast to SISR, even more information can be gathered on the recorded scene when using multiple cameras. In our setup, we are dealing with multi image super resolution, especially with stereo super resolution. We consider a color camera and an IR camera. Current IR sensors have a very low resolution compared to color sensors so that recent color sensors take up 100 times more pixels than IR sensors. To this end, GIRRE increases the spatial resolution of the low-resolution IR image. After that, the upscaled image is filtered with the aid of the high-resolution color image. We show that our method achieves an average PSNR gain of 1.2dB and at best up to 1.8 dB compared to state-of-the-art methods, which is visually noticeable. © 2023 IEEE.

关键词： Image enhancement

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Kuhn-Munkres-Based Sub-optimum Resource Allocation Algorithm for Ultra-Dense Networks 11

Kuhn-Munkres-Based Sub-optimum Resource Allocation Algorithm...

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11th International Symposium on Telecommunication, IST 2024

作者： Moghaddam, Shahriar Shirvani Ashoor, Ebrahim Lavizan Department of Communications Faculty of Electrical Engineering Tehran*** Iran Lavizan Digital Communications Signal Processing Research Lab Tehran*** Iran

ISBN: (纸本)9798350356250

This paper proposes a sub-optimum Kuhn-Munkres-based algorithm for resource allocation in ultra-dense networks, which aims to maximize the number of connected users and throughput. In the proposed method, users are first assigned to access points supporting higher data rates considering the interference of all access points. Then, only the interference of the selected access points is considered and users connected to these access points that meet the minimum throughput threshold level are found. In the second step, considering the interference of the access points assigned in the first step and the remaining access points selected in the second step, new users are connected to the remaining selected access points. Simulations in MATLAB and numerical analyses for an area of 250 meters by 250 meters including 250 access points and different numbers of 10 to 250 randomly distributed users, show more connected users, the total sum-rate (throughput), and the average throughput per user while the processing time is far lower than the two other simulated ones, Genetic and particle swarm optimization algorithms. Also, where the number of users and access points are the same and equal to 250, the proposed algorithm compared to the two other optimization algorithms increases the number of connected users by 14% and 54%, the average throughput per user by 55% and 30%, and the total throughput by 77% and 163%. Due to the lower order of complexity of the proposed algorithm compared to the two others, it experiences a lower processing time of 99.97 and 99.96 percent, respectively. © 2024 IEEE.

关键词： Genetic algorithms

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Variational signal Separation for Automotive Radar Interference Mitigation

IEEE Transactions on Radar Systems

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IEEE Transactions on Radar Systems 2024年 2卷 1007-1026页

作者： Toth, Mate Leitinger, Erik Witrisal, Klaus Graz University of Technology Institute of Communication Networks and Satellite Communications Graz Austria Graz University of Technology Laboratory of Signal Processing and Speech Communication Graz Austria

Algorithms for mutual interference mitigation and object parameter estimation are a key enabler for automotive applications of frequency-modulated continuous wave (FMCW) radar. In this paper, we introduce a signal separation method to detect and estimate radar object parameters while jointly estimating and successively canceling the interference signal. The underlying signal model poses a challenge, since both the coherent radar echo and the non-coherent interference influenced by individual multipath propagation channels must be considered. Under certain assumptions, the model is described as a superposition of multipath channels weighted by parametric interference chirp envelopes. Inspired by sparse Bayesian learning (SBL), we employ an augmented probabilistic model that uses a hierarchical Gamma-Gaussian prior model for each multipath channel. Based on this, an iterative inference algorithm is derived using the variational expectation-maximization (EM) methodology. The algorithm is statistically evaluated in terms of object parameter estimation accuracy and robustness, indicating that it is fundamentally capable of achieving the Cramer-Rao lower bound (CRLB) with respect to the accuracy of object estimates and it closely follows the radar performance achieved when no interference is present. © 2023 IEEE.

关键词： Radar interference

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