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DSEP Fulcrum: Dynamic Sparsity and Expansion Packets for Fulcrum Network Coding

IEEE ACCESS 2020年 8卷 78293-78314页

作者： Vu Nguyen Tasdemir, Elif Nguyen, Giang T. Lucani, Daniel E. Fitzek, Frank H. P. Reisslein, Martin Tech Univ Dresden 5G Lab Germany Deutsch Telekom Chair D-01062 Dresden Germany Aarhus Univ Dept Engn DK-8200 Aarhus Denmark Tech Univ Dresden Ctr Tactile Internet Human In The Loop CeTI D-01062 Dresden Germany Arizona State Univ Sch Elect Comp & Energy Engn Tempe AZ 85287 USA

Fulcrum coding combines a high-field outer Random Linear Network Coding (RLNC) that generates outer coding expansion packets with a small-field inner RLNC that combines the source packets and the outer coding expansion packets. This two-layer Fulcrum coding allows flexible decoding in receivers with heterogeneous computational capabilities. Fulcrum coding has so far only been studied for conventional dense RLNC, which randomly selects all coding coefficients, and only for a statically fixed number of outer expansion packets. However, the probability that the coding coefficient row of a newly received packet is linearly independent of prior received coding coefficient rows (a prerequisite for successful decoding) is highly dynamic. We propose to exploit the dynamics of this probability to reduce the computational complexity of Fulcrum coding. In particular, we vary the density of non-zero coding coefficients, i.e., equivalently, the sparsity of coding coefficients, and the number of outer expansion packets to keep the complexity low while maintaining a reasonably high decoding probability. We introduce the general principles of dynamic sparsity and expansion packets (DSEP) for Fulcrum coding as well as two specific example DSEP policies. Our evaluations indicate that DSEP Fulcrum can increase the encoding throughput tenfold and increase the decoding throughput 1.4 to 4.3 fold while achieving decoding probabilities that are typically less than 1 & x0025;lower than the conventional Fulcrum decoding probabilities. We also find that DSEP achieves somewhat higher encoding and decoding throughputs than the CodornicesRq (Release 2.1) implementation of RaptorQ block coding for small blocks (generations) of source packets, while RaptorQ is substantially faster for large generation sizes. Furthermore, we develop and evaluate an elementary DSEP recoding mechanism that achieves a recoding throughput more than double the decoding throughput.

关键词： Decoding Throughput Receivers Block codes Network coding computational complexity computational complexity heterogeneous devices random linear network coding (RLNC) RaptorQ recoding sparsity throughput

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Three-Dimensional Coprime Array for Massive MIMO: Array Configuration Design and 2D DOA Estimation

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WIRELESS COMMUNICATIONS & MOBILE COMPUTING 2020年第1期2020卷

作者： Gong, Pan Ahmed, Tanveer Li, Jianfeng Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 211106 Peoples R China

In massive multiple-input multiple-output (MIMO) systems, it is critical to obtain the accurate direction of arrival (DOA) estimation. Conventional three-dimensional array mainly focuses on the uniform array. Due to the dense arrangement of the sensors, the array aperture is limited and severe mutual coupling effects arise. In this paper, a coprime cubic array (CCA) configuration design is presented, which is composed of two uniform cubic subarrays and can extend the interelement spacing with a selection of three pairs of coprime integers. Compared with uniform cubic array (UCA), CCA achieves the larger array aperture and less MC effects. And the analytical expression of Cramer-Rao Bound (CRB) for CCA is derived which verifies that the proposed CCA geometry outperforms the conventional UCA in two-dimensional (2D) DOA estimation performance in massive MIMO systems. Meanwhile, we propose a computationally efficient 2D DOA estimation algorithm with high accuracy for CCA. Specifically, we utilize array mapping to extract two uniform arrays from the nonuniform array by exploiting the relation derived from the signal subspace and the two directional matrices. Then, we operate a reduced dimension process on the uniform arrays and convert the 2D spectrum peak searching (SPS) problem into one-dimensional (1D) one, which significantly reduces the computational complexity. In addition, we employ the polynomial root finding technique with a lower complexity instead of 1D SPS to further relieve the computational complexity. Simultaneously, with coprime property, the phase ambiguity problem is solved, which results from the large interelement spacing. Numerical simulation results demonstrate that the proposed algorithm is very computationally efficient without degradation of DOA estimation performance.

关键词： computational complexity

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Joint AGC and receiver design for large-scale MU-MIMO systems with low-resolution signals in C-RANs

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IET COMMUNICATIONS 2020年第21期14卷 3791-3801页

作者： Cunha, Thiago E. B. de Lamare, Rodrigo C. Ferreira, Tadeu N. Landau, Lukas T. N. Pontificia Univ Catolica Rio de Janeiro Ctr Telecommun Studies CETUC BR-22451900 Rio de Janeiro Brazil Univ York Dept Elect Engn York YO10 5DD N Yorkshire England Fluminense Fed Univ UFF Sch Engn BR-24210240 Niteroi RJ Brazil

Large-scale multi-user multiple-input multiple-output (MU-MIMO) systems and cloud radio access networks (C-RANs) are promising technologies for the fifth generation (5G) of wireless networks. In this context, the use of low-resolution analogue-to-digital converters (ADCs) is key for energy efficiency and for complying with constrained fronthaul links. Processing signals with a few bits implies performance loss and, therefore, techniques that can compensate for quantisation distortion are fundamental. In wireless systems, an automatic gain control (AGC) precedes the ADCs to adjust the input signal level in order to reduce the impact of quantisation. In this work, the authors propose the joint optimisation of the AGC, which works in the remote radio heads (RRHs), and a low-resolution aware (LRA) linear receive filter based on the minimum mean square error (MMSE), which works in the cloud unit (CU), for large-scale MU-MIMO systems with coarsely quantised signals. They develop linear and successive interference cancellation receivers based on the proposed joint AGC and LRA MMSE (AGC-LRA-MMSE) approach. An analysis of the achievable sum rates along with a computational complexity study is also carried out. Simulations show that the proposed AGC-LRA-MMSE design obtains substantial gains in bit error rates and achievable information rates over existing techniques.

关键词： MIMO communication computational complexity least mean squares methods radio access networks automatic gain control radio receivers interference suppression optimisation error statistics quantisation (signal) multi-access systems telecommunication computing cloud computing 5G mobile communication filtering theory low-resolution aware linear large-scale MU-MIMO systems coarsely quantised signals successive interference cancellation receivers joint AGC LRA MMSE approach AGC-LRA-MMSE design obtains substantial gains receiver design low-resolution signals C-RAN large-scale multiuser multiple-input cloud radio access networks wireless networks low-resolution analogue-to-digital converters constrained fronthaul links processing signals quantisation distortion wireless systems input signal level joint optimisation remote radio heads

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Robust transceiver design based on switched preprocessing for K-pair MIMO interference channels

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IET COMMUNICATIONS 2020年第2期14卷 300-312页

作者： Han, Hui Cai, Yunlong Zhao, Ming-Min Shi, Qingjiang CEMEE State Key Lab Complex Electromagnet Environm Effe Luoyang 471003 Peoples R China Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310027 Peoples R China Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310027 Peoples R China Tongji Univ Sch Software Engn Shanghai 200092 Peoples R China

In this work, the authors propose a transceiver design strategy based on switched preprocessing (SP) for interference management in K-pair MIMO interference channels. Each transmitter performs SP by using a small number of permutation matrices to allocate the entries of its precoder output vector on different transmit antennas. Each arrangement of permutation matrices among the K transmitters gives rise to a set of K parallel point-to-point transceivers, referred to as MIMO latent transceiver set (MLTS). Based on the given channel state information (CSI), the optimum MLTS among the available ones is chosen by minimising the squared Euclidean distance between the pre-estimated noiseless received vector and the true transmit symbol vector. In addition, they consider two CSI error models, i.e. the stochastic error model and the norm-bounded error model, and for each type they propose robust algorithms for the design of the MLTS associated to the different choices of permutation matrices, which are based on minimising various types of mean square error criteria. A detailed study of computational complexity for the proposed SP-based MIMO transceiver design algorithms is carried out. Simulation results verify the effectiveness of the new SP-based designs for MIMO interference channels.

关键词： MIMO communication matrix algebra channel coding mean square error methods radio transceivers wireless channels radiofrequency interference precoding telecommunication network management vectors transmitting antennas minimisation stochastic processes communication complexity MIMO interference channels interference management permutation matrices precoder output vector transmit antennas k parallel point-to-point transceivers MLTS channel state information CSI error models stochastic error model norm-bounded error model mean square error criteria symbol vector transmission squared Euclidean distance pre-estimated noiseless received vector computational complexity SP-based MIMO latent transceiver set design strategy

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Cooperating in video games? Impossible! Undecidability of Team Multiplayer Games

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THEORETICAL COMPUTER SCIENCE 2020年 839卷 30-40页

作者： Coulombe, Michael J. Lynch, Jayson MIT Comp Sci & Artificial Intelligence Lab 32 Vassar St Cambridge MA 02139 USA

We show the undecidability of whether a team has a forced win in a number of well known video games including: Team Fortress 2, Super Smash Brothers: Brawl, and Mario Kart. To do so, we give a simplification of the Team Computation Game from Hearn and Demaine's "Games, Puzzles, and Computation" [7], and use that to give an undecidable abstract game on graphs. This graph game framework better captures the geometry and common constraints in many games and is thus a powerful tool for showing their computational complexity. (C) 2020 Published by Elsevier B.V.

关键词： Undecidability Games computational complexity Imperfect information

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Robust incentive Stackelberg strategy for Markov jump linear stochastic systems via static output feedback

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IET CONTROL THEORY AND APPLICATIONS 2020年第9期14卷 1246-1254页

作者： Mukaidani, Hiroaki Saravanakumar, Ramasamy Xu, Hua Hiroshima Univ Grad Sch Adv Sci & Engn 1-4-1 Kagamiyama Higashihiroshima 7398527 Japan Univ Tsukuba Grad Sch Business Sci Bunkyo Ku 3-29-1 Otsuka Tokyo 1120012 Japan

In this study, a robust static output feedback (SOF) incentive Stackelberg game for a Markov jump linear stochastic system governed by Ito differential equations with multiple leaders and multiple followers is investigated. The existence conditions for the SOF incentive Stackelberg strategies are derived in terms of the solvability of a set of higher-order cross-coupled stochastic algebraic Lyapunov type equations (CCSALTEs). A classical Lagrange multiplier technique is employed to solve the CCSALTEs;therefore, the solution of the bilinear matrix inequality, which is a common NP-hard problem when designing SOF strategies, is not required. A heuristic algorithm is developed based on the CCSALTEs. In particular, it is shown that a robust convergence is guaranteed by combining the Krasnoselskii-Mann iterative algorithm with a new convergence condition. The performance of the proposed algorithm is discussed and a simple practical example is provided to demonstrate the effectiveness of the proposed algorithm and the SOF incentive Stackelberg strategies.

关键词： computational complexity differential equations linear systems linear matrix inequalities feedback Lyapunov methods stochastic systems iterative methods game theory robust control CCSALTEs SOF incentive Stackelberg strategies robust incentive Stackelberg strategy Markov jump linear stochastic system robust static output feedback incentive Stackelberg game Ito differential equations higher-order cross-coupled stochastic algebraic Lyapunov type equations classical Lagrange multiplier technique SOF strategies bilinear matrix inequality NP-hard problem Krasnoselskii-Mann iterative algorithm Krasnoselskii-Mann iterative algorithm

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Toward Optimal Prediction Error Expansion-Based Reversible Image Watermarking

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2020年第8期30卷 2377-2390页

作者： Roy, Aniket Chakraborty, Rajat Subhra IIT Kharagpur Dept Comp Sci & Engn Kharagpur 721302 W Bengal India

Reversible image watermarking is a technique that allows the cover image to remain unmodified after watermark extraction. Prediction error expansion-based schemes are currently the most efficient and widely used class of reversible image watermarking techniques. In this paper, first, we prove that the bounded capacity distortion minimization problem for prediction error expansion-based reversible watermarking schemes is NP-hard, and the corresponding decision version of the problem is NP-complete. Then, we prove that the dual problem of bounded distortion capacity maximization problem for prediction error expansion-based reversible watermarking schemes is NP-hard, and the corresponding decision problem is NP-complete. Furthermore, taking advantage of the integer linear programming formulations of the optimization problems, we find the optimal performance metric values for a given image, using concepts from the optimal linear prediction theory. Our technique allows the calculation of these performance metric limit without assuming any particular prediction scheme. The experimental results for several common benchmark images are consistent with the calculated performance limits validate our approach.

关键词： Watermarking Distortion Histograms Measurement Optimization Image coding Estimation computational complexity integer linear programming prediction error expansion reversible image watermarking Wiener filtering

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Reduced-Order Observer Design for Boolean Control Networks

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2020年第1期65卷 434-441页

作者： Zhang, Zhihua Leifeld, Thomas Zhang, Ping Tech Univ Kaiserslautern Inst Automat Control D-67653 Kaiserslautern Germany

In this paper, we propose an approach to design reduced-order state observer for Boolean control networks by applying the semi-tensor product. At first, an approach is given to find reducible state variables. After that, we introduce an approach for reduced-order observer design based on the reducible state variables. Then, it is shown that similar to the Luenberger-like observer, the state estimate provided by the reduced-order observer also converges to real state at time not later than the minimal reconstructibility index. Additionally, the reduced-order observer requires lower computational effort, which facilitates an online implementation.

关键词： Observers Biological system modeling Biological systems Integrated circuit modeling Temperature measurement computational complexity Boolean control networks reduced-order observer state observer

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Reliability evaluation of bulk power systems using the uniform design technique

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第3期14卷 400-407页

作者： Xie, Kaigui Huang, Yingcheng Hu, Bo Tai, Heng-Ming Wang, Leibao Liao, Qinglong Chongqing Univ State Key Lab Power Transmiss Equipment & Syst Se Chongqing 400044 Peoples R China Univ Tulsa Dept Elect & Comp Engn Tulsa OK 74104 USA State Grid Chongqing Elect Power Co Elect Power Res Inst Chongqing 401123 Peoples R China

Reliability evaluation of bulk power systems (BPSs) has inherent computational complexity due to the numerous system states and the time-consuming system state analysis, including power flow calculation, load curtailment, recognition of split power systems and network reconfiguration. In this study, a novel uniform-design based method is proposed to improve the computational efficiency of power system reliability evaluation. The main idea is that the uniform-design technique is used to generate the system states in reliability evaluation, which makes the sampled states more uniform and representative in the overall state space compared to the enumerated system states in an analytical method or the random-generated system states in Monte Carlo simulation. As a result, the sample size and the computational time can be significantly reduced. In addition, the confidence intervals of the reliability indices, such as LOLP, FLOL and EENS, are given. And the estimation errors of reliability indices are discussed. The proposed method is tested on several BPSs, including the IEEE-RTS79, IEEE-RTS96 and a real BPS in China. All the case studies indicate that the proposed technique can significantly improve the computational efficiency of BPS reliability evaluation.

关键词： power system planning Monte Carlo methods computational complexity load flow power system reliability power transmission reliability power generation reliability bulk power systems uniform design technique inherent computational complexity numerous system states time-consuming system state analysis power flow calculation split power systems uniform-design based method computational efficiency power system reliability evaluation uniform-design technique sampled states state space enumerated system states computational time reliability indices BPS reliability evaluation

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On Performance of Sparse Fast Fourier Transform Algorithms Using the Flat Window Filter

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IEEE ACCESS 2020年 8卷 79134-79146页

作者： Li, Bin Jiang, Zhikang Chen, Jie Shanghai Univ Sch Mech & Elect Engn & Automat Shanghai 200072 Peoples R China

The problem of computing the Sparse Fast Fourier Transform(sFFT) of a-sparse signal of sizeS has received significant attention for a long time. The first stage of sFFT is hashing the frequency coefficients into buckets named frequency bucketization. The process of frequency bucketization is achieved through the use of filters: Dirichlet kernel filter, aliasing filter, flat filter, etc. The frequency bucketization through these filters can decrease runtime and sampling complexity in low dimensions. It is a hot topic about sFFT algorithms using the flat filter because of its convenience and efficiency since its emergence and wide application. The next stage of sFFT is the spectrum reconstruction by identifying frequencies that are isolated in their buckets. Up to now, there are more than thirty different sFFT algorithms using the sFFT idea as mentioned above by their unique methods. An important question now is how to analyze and evaluate the performance of these sFFT algorithms in theory and practice. In this paper, it is mainly discussed about sFFT algorithms using the flat filter. In the first part, the paper introduces the techniques in detail, including two types of frameworks, five different methods to reconstruct spectrum and corresponding algorithms. We get the conclusion of the performance of these five algorithms, including runtime complexity, sampling complexity and robustness in theory. In the second part, we make three categories of experiments for computing the signals of different SNR, different , and different by a standard testing platform and record the run time, percentage of the signal sampled, and error both in the exactly sparse case and general sparse case. The result of experiments is consistent with the inferences obtained in theory. It can help us to optimize these algorithms and use them correctly in the right areas.

关键词： Signal processing algorithms Microsoft Windows Runtime Discrete Fourier transforms complexity theory Kernel Frequency-domain analysis Sparse fast Fourier transform (sFFT) flat window filter sub-linear algorithms computational complexity

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