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IEEE Global Communications Conference (GLOBECOM)

作者： Beygi, Sajjad Strom, Erik G. Mitra, Urbashi USC Sch Elect Engn Los Angeles CA 90089 USA Chalmers Univ Technol Dept Signals & Syst Gothenburg Sweden

ISBN: (纸本)9781479935123

In this paper, we consider the estimation of a signal that has both group-and element-wise sparsity (joint sparsity);motivated by channel estimation in vehicle-to-vehicle channels. A general approach for the design of separable regularizing functions is proposed to adaptively induce sparsity in the estimation. A joint sparse signal estimation problem is formulated via these regularizers and its optimal solution is computed based on proximity operations. Our optimization results are quite general and they can be applied in the context of hierarchical sparsity models as well. The proposed recovery algorithm is a nested iterative method based on the alternating direction method of multipliers (ADMM). Due to regularizer separability, key operations can be performed in parallel. V2V channels are estimated by exploiting the joint sparsity (group/element-wise) exhibited in the delay-Doppler domain. Simulation results reveal that the proposed method can achieve as much as a 1 0 dB gain over previously examined methods.

关键词： channel estimation iterative methods mobile radio optimisation signal processing ADMM V2V channel estimation alternating direction method of multipliers delay-Doppler domain element-wise sparsity hierarchical sparsity models nested iterative method recovery algorithm separable regularizing functions sparse signal estimation problem structured sparse approximation vehicle-to-vehicle channels Approximation methods Channel estimation Estimation Joints Optimization Signal processing Vectors

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Resource pre-reservation algorithm for intelligent optical networks

Resource pre-reservation algorithm for intelligent optical n...

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International Symposium on Communications and Information Technologies (ISCIT2005)

作者： Li, H Lu, YM Ji, YF Beijing Univ Posts & Telecommun Sch Telecommun Engn Beijing 100088 Peoples R China

ISBN: (纸本)0780395387

Intelligent optical networks support real-time automatic connection configuration and recovery, which give rise to another new set of problems, such as the unsureness of resource reservation and the uncertainty of connection recovery. In view of those facts, we examine current optical network protection and restoration schemes, and propose a connection survivable resource reservation algorithm based on fault simulation. By automatic simulating one link failure or multi share risk link group failures combination, this algorithm can allocate enough backup resources, which make the networks can survive any 1 similar to 3 node or link failures.

关键词： network planning recovery algorithm resource allocation network optimization intelligent optical networks

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Context-Aware Expert for Software Architecture recovery (CAESAR): An automated approach for recovering software architectures

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JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES 2023年第8期35卷

作者： Ibrahim, Khaled Hassan, Hesham Wassif, Khaled T. Makady, Soha Cairo Univ Fac Comp & Artificial Intelligence 5 Dr Ahmed Zewail St Giza 12613 Orman Egypt

Software architecture recovery approaches help to reconstruct the architecture of complex software systems. However, the manual effort and expertise required to use such techniques are high, as the user demands detailed knowledge about software architecture recovery process and preparing additional software artifacts to use as input for such approaches. Such practices lack consideration for the context standards of the recovered software. Additionally, proper module detection rules that are aware of the modeled system's context should be studied to enhance the cluster quality of the detected modules. We introduce a novel approach to software architecture recovery by implementing an automated knowledge-based rules solution that considers the context of the developed software while identifying and clustering that system's software modules. Such solution is aided by a novel code distance model that is utilized to enhance the cohesiveness of the recovered software modules, improving the recovered software architecture quality, and enhancing readability through providing visualizations at different abstraction levels for the recovered architecture. The proposed method has been evaluated on two software systems with varying sizes and from different contexts and involved experienced participants. The results demonstrate significant improvements in cohesion and coupling of the produced clusters compared to alternative architecture recovery approaches. (C) 2023 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Software architecture recovery algorithm Reverse engineering Module Clustering AUTOSAR FACE Software visualization

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Construction of Wideband Radio Environment Map Based on Compressed Sensing 14

Construction of Wideband Radio Environment Map Based on Comp...

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14th IEEE International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Yang, Ensong Yu, Hui Mo, Xiaohao Gao, Ao Shanghai Jiao Tong Univ Dept Elect Engn Shanghai Peoples R China

ISBN: (纸本)9781665450850

The ever-growing demand for wireless communication has led to an increasingly complex radio environment, which has caused the construction of wideband radio environment map (WREM) as an effective means to manage and utilize spectrum resources. In this paper, we investigate the low-complexity method for building a high-accuracy WREM. By jointly exploiting the sparsity in spatial and frequency domains, we transform the WREM construction problem into a compressed sensing (CS) problem to reduce the construction complexity and resource consumption. Then we propose a spatial sampling points (SSP) optimization algorithm based on reducing columns correlation to improve the recovery accuracy. Inspired by the quasi-block sparse structure of the vector to be recovered, we propose a quasi-block sparse block matching pursuit (QBSBMP) algorithm to recover the locations and power spectral density (PSD) of all transmitting sources. Simulation results show that the proposed scheme significantly reduces the amount of sampled data and achieves the high-precision of constructing WREM.

关键词： WREM compressed sensing sampling optimization recovery algorithm

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On the Reconstruction of Multiple Sinusoidal Signals from Compressed Measurements 30

On the Reconstruction of Multiple Sinusoidal Signals from Co...

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30th European Signal Processing Conference (EUSIPCO)

作者： Perez, Dailys Arronde Zangl, Hubert Univ Klagenfurt Inst Smart Syst Technol Sensors & Actuators Klagenfurt Austria AAU SAL USE Lab Silicon Austria Labs Klagenfurt Austria

ISBN: (纸本)9789082797091

The introduction of compressive sensing in wireless smart transducers can substantially reduce the high impact of sampling rate on their overall power consumption. Such systems are often dealing with signals that can be expressed as a sum of multiple sinusoids, having a frequency-sparse representation. Although the reconstruction of frequency-sparse signals has been widely studied and solutions based on greedy and relaxation methods exist, their performance is degraded in presence of spectral leakage, which affects the sparse representation of the signal and consequently, its estimation accuracy. In this paper, a two-stage optimization approach, named Opti2, is presented for the reconstruction of frequency-sparse signals that can be expressed as a sum of multiple real-valued sinusoidal waveforms. The estimation provided by basis pursuit denoising (BPDN) sparse optimization is computed in the first stage and used as initial guess for the second stage, where a non-linear least squares (NLLS) problem is formulated to improve the estimation of the signal parameters from undersampled data. Simulation results demonstrate that the proposed approach outperforms existing methods in terms of accuracy, showing its robustness to noise and compression rate.

关键词： compressive sampling frequency-sparse signals multiple sinusoids recovery algorithm optimization spectral leakage

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A Hybrid Approach to Failed Disk recovery Using RAID-6 Codes: algorithms and Performance Evaluation

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ACM TRANSACTIONS ON STORAGE 2011年第3期7卷 11-11页

作者： Xiang, Liping Xu, Yinlong Lui, John C. S. Chang, Qian Pan, Yubiao Li, Runhui Univ Sci & Technol China Sch Comp Sci & Technol Hefei Peoples R China Chinese Univ Hong Kong Dept Comp Sci & Engn Hong Kong Hong Kong Peoples R China

The current parallel storage systems use thousands of inexpensive disks to meet the storage requirement of applications. Data redundancy and/or coding are used to enhance data availability, for instance, Row-diagonal parity (RDP) and EVENODD codes, which are widely used in RAID-6 storage systems, provide data availability with up to two disk failures. To reduce the probability of data unavailability, whenever a single disk fails, disk recovery will be carried out. We find that the conventional recovery schemes of RDP and EVENODD codes for a single failed disk only use one parity disk. However, there are two parity disks in the system, and both can be used for single disk failure recovery. In this article, we propose a hybrid recovery approach that uses both parities for single disk failure recovery, and we design efficient recovery schemes for RDP code (RDOR-RDP) and EVENODD code (RDOR-EVENODD). Our recovery scheme has the following attractive properties: (1) "read optimality" in the sense that our scheme issues the smallest number of disk reads to recover a single failed disk and it reduces approximately 1/4 of disk reads compared with conventional schemes;(2) "load balancing property" in that all surviving disks will be subjected to the same (or almost the same) amount of additional workload in rebuilding the failed disk. We carry out performance evaluation to quantify the merits of RDOR-RDP and RDOR-EVENODD on some widely used disks with DiskSim. The offline experimental results show that RDOR-RDP and RDOR-EVENODD outperform the conventional recovery schemes of RDP and EVENODD codes in terms of total recovery time and recovery workload on individual surviving disk. However, the improvements are less than the theoretical value (approximately 25%), as RDOR-RDP and RDOR-EVENODD change the disk access pattern from purely sequential to a more random one compared with their conventional schemes.

关键词： algorithms Reliability Theory Disk failure EVENODD code RAID recovery RDP code recovery algorithm

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Optimal recovery of Single Disk Failure in RDP Code Storage Systems 10

Optimal Recovery of Single Disk Failure in RDP Code Storage ...

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SIGMETRICS 2010

作者： Liping Xiang Yinlong Xu John C.S. Lui Qian Chang University of Science and Technology of China Hefei China The Chinese University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9781450300384

Modern storage systems use thousands of inexpensive disks to meet the storage requirement of applications. To enhance the data availability, some form of redundancy is used. For example, conventional RAID-5 systems provide data availability for single disk failure only, while recent advanced coding techniques such as row-diagonal parity (RDP) can provide data availability with up to two disk failures. To reduce the probability of data unavailability, whenever a single disk fails, disk recovery (or rebuild) will be carried out. We show that conventional recovery scheme of RDP code for a single disk failure is inefficient and suboptimal. In this paper, we propose an optimal and efficient disk recovery scheme, Row-Diagonal Optimal recovery (RDOR), for single disk failure of RDP code that has the following properties: (1) it is read optimal in the sense that it issues the smallest number of disk reads to recover the failed disk;(2) it has the load balancing property that all surviving disks will be subjected to the same amount of additional workload in rebuilding the failed disk. We carefully explore the design state space and theoretically show the optimality of RDOR. We carry out performance evaluation to quantify the merits of RDOR on some widely used disks.

关键词： RAID recovery RDP code disk failure recovery algorithm

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Compressive spectrum sensing for 5G cognitive radio networks - LASSO approach

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HELIYON 2022年第6期8卷 e09621页

作者： Koteeshwari, R. S. Malarkodi, B. Natl Inst Technol Dept Elect & Commun Engn Trichy 620015 India EGS Pillay Engn Coll Dept Elect & Commun Engn Nagapattinam 611002 India

In recent years, the importance of Artificial Intelligence is inevitable for effective performance in communication area. The progressing in standards from beyond 5G networks are compatible gadgets for incorporate wireless communication. Cognitive radio (CR) is a sensible and advanced scientific communication that can effectively handle the radio spectrum applications. Spectrum sensing (SR) is the primary role in CR. In SR, various Wide Band techniques suited for 5G were investigated in this paper. (Least Absolute Shrinkage and Selection Operator) LASSO is the suitable choice for communication in compressive sensing and recovery in wideband 5G networks. The obtained results were correlated with recent report. Further, the relative merit and demerits are discussed significantly.

关键词： 5G networks Compressed sensing recovery algorithm LASSO

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A High-Resolution Joint Angle-Doppler Estimation Sub-Nyquist Radar Approach Based on Matrix Completion

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INFORMATION 2019年第4期10卷 124页

作者： Wang, Quanhui Sun, Ying Lingnan Normal Univ Sch Informat Engn Zhanjiang 524000 Peoples R China Huawei Technol Co Ltd Shenzhen 518000 Peoples R China

In order to reduce power consumption and save storage capacity, we propose a high-resolution sub-Nyquist radar approach based on matrix completion (MC), termed as single-channel sub-Nyquist-MC radars. While providing the high-resolution joint angle-Doppler estimation, this proposed radar approach minimizes the number of samples in all three dimensions, that is, the range dimension, the pulse dimension (also named temporal dimension), and the spatial dimension. In range dimension, we use a single-channel analog-to-information converter (AIC) to reduce the number of range samples to one;in both spatial and temporal dimensions, we employ a bank of random switch units to regulate the AICs, which greatly reduce the number of spatial-temporal samples. According to the proposed sampling scheme, the samples in digital processing center forwarded by M receive nodes and N pulses are only a subset of the full matrix of size M times N. Under certain conditions and with the knowledge of the sampling scheme, the full matrix can be perfectly recovered by using MC techniques. Based on the recovered full matrix, this paper addresses the problem of the high-resolution joint angle-Doppler estimation by employing compressed sensing (CS) techniques. The properties and performance of the proposed approach are demonstrated via simulations.

关键词： compressed sensing radar sub-Nyquist sampling matrix completion array signal processing recovery algorithm

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Cyclic Spectrum Estimation Under Compressive Sensing by the Strip Spectral Correlation algorithm

Cyclic Spectrum Estimation Under Compressive Sensing by the ...

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International Wireless Communications and Mobile Computing Conference

作者： Yulong Gao Song Wang Yanping Chen Yuming Wei Communication Research Center Harbin Institute of Technology Harbin China School of Computer and Information Engineering Harbin University of Commerce Harbin China

Cyclic spectrum is a basic tool to study the cyclo-stationary of signal. It has the advantages of high resolution, anti-interference ability and low channel environment sensitivity. These properties are beneficial to process digital modulated signals. There are two time-smoothed algorithms: the FFT Accumulation Method (FAM) and the Strip Spectral Correlation algorithm (SSCA). SSCA is suitable for fast estimation and engineering realizable, while FAM has shortcoming of complex computation. But both methods need high sampling rate that requires high performance analog-to-digital converter. To improve the efficiency of cyclic spectrum estimation, we propose CS-SSCA algorithm in the framework of Compressive Sensing (CS). The cyclic spectrum can be recovered via compressed samples by SSCA. The theoretical analysis and simulation results prove that the improved algorithm displays better performance than CS-FAM under the same conditions.

关键词： Compressive Sensing Cyclic spectrum density recovery algorithm

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