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2023 International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2023

作者： Van Den Brink, Arvid B. Meteer, Oǧuz Bekooij, Marco J.G. University of Twente Department of Computer Architectures for Embedded Systems Enschede Netherlands Nxp Semiconductors Department of Embedded Software and Signal Processing Eindhoven Netherlands

ISBN: (纸本)9798350322972

The belief propagation algorithm is one of the preferred algorithms for a polar code based decoder that can potentially achieve the lowest latency. Although belief propagation polar code algorithms have the ability for a highly parallelized implementation, they require more iterations to achieve a comparable frame error rate and bit error rate compared to the successive cancellation polar code algorithm. The iterative nature of the belief propagation algorithms also results in a higher computational complexity, i.e. O(N(2log2N-1)) compared to the computational complexity O(Nlog2N) of the successive cancellation decoder algorithm. In this paper we propose several software implementations of belief propagation polar code decoders using the computational complexity reduced belief propagation algorithm and the enhanced loop-weakened belief propagation algorithm, to increase the number of decoded codes per second. Compared to a baseline belief propagation implementation, our proposed radix-2 and radix-4 implementations increase the throughput by approximately 15.4% and 22.04% respectively. This gain is the result of a reduction of arithmetic operations, i.e., additions, compares, and multiplications, which is obtained without a loss in error-correcting performance. © 2023 IEEE.

关键词： Belief propagation

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Weakly Supervised Semantic Segmentation for Range-Doppler Maps 18

Weakly Supervised Semantic Segmentation for Range-Doppler Ma...

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18th European Radar Conference, EuRAD 2021

作者： Fatseas, Konstantinos Bekooij, Marco J.G. University of Twente Department of Computer Architectures for Embedded Systems Netherlands NXP Semiconductors Department of Embedded Software and Signal Processing Netherlands

ISBN: (纸本)9782874870651

Deep convolutional neural networks (DCNNs) have been successfully applied for object detection and semantic segmentation of radar range-Doppler (RD) maps. However, training a DCNN requires many annotated examples that are costly and difficult to create. In this work we present a method that reduces significantly the manual effort involved in the annotation of RD maps to train a DCNN for segmentation. A 40 times reduction in manual labelling effort is achieved because the annotation of each RD map includes only the class of the objects instead of drawing a polygon around the corresponding cells. The localization of the objects is performed by tracing back from the output to the input of a classification neural network. Experimental results show that our approach achieves robust localization performance in complex real-world urban scenarios as observed with a low-cost automotive radar. Furthermore, we show that our approach performs similarly to DCNNs that are trained with a publicly available dataset in which localization information is provided. © 2022 European Microwave Association (EuMA).

关键词： Convolutional neural networks

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Software Implementation and Performance of a Computational Complexity Reduced Belief Propagation Polar Code Decoder

Software Implementation and Performance of a Computational C...

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Electrical, computer, Communications and Mechatronics Engineering (ICECCME), International Conference on

作者： Arvid B. Van Den Brink Oğuz Meteer Marco J.G. Bekooij Department of Computer Architectures for Embedded Systems University of Twente Enschede The Netherlands Department of Embedded Software and Signal Processing NXP Semiconductors Eindhoven The Netherlands

The belief propagation algorithm is one of the preferred algorithms for a polar code based decoder that can potentially achieve the lowest latency. Although belief propagation polar code algorithms have the ability for a highly parallelized implementation, they require more iterations to achieve a comparable frame error rate and bit error rate compared to the successive cancellation polar code algorithm. The iterative nature of the belief propagation algorithms also results in a higher computational complexity, i.e. O(N(2log 2 N-1)) compared to the computational complexity O(Nlog 2 N) of the successive cancellation decoder algorithm. In this paper we propose several software implementations of belief propagation polar code decoders using the computational complexity reduced belief propagation algorithm and the enhanced loop-weakened belief propagation algorithm, to increase the number of decoded codes per second. Compared to a baseline belief propagation implementation, our proposed radix-2 and radix-4 implementations increase the throughput by approximately 15.4% and 22.04% respectively. This gain is the result of a reduction of arithmetic operations, i.e., additions, compares, and multiplications, which is obtained without a loss in error-correcting performance.

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Energy-Efficient Radix-4 Belief Propagation Polar Code Decoding Using an Efficient Sign-Magnitude Adder and Clock Gating

Energy-Efficient Radix-4 Belief Propagation Polar Code Decod...

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Euromicro Symposium on Digital System Design

作者： Oğuz Meteer Arvid Van Den Brink Marco J.G. Bekooij Department of Computer Architectures for Embedded Systems University of Twente Enschede The Netherlands Department of Embedded Software and Signal Processing NXP Semiconductors Eindhoven The Netherlands

ISBN: (数字)9781665474047

ISBN: (纸本)9781665474054

Polar encoding is the first information coding method that has been proven to achieve channel capacity for binary-input discrete memoryless channels. Since its introduction, much research has been done on improving decoding performance, execution time and energy efficiency. Classic belief propagation uses radix-2 decoding, but a recent study proposed radix-4 decoding which reduces memory usage by 50%. However a drawback is its higher computational complexity, negatively impacting energy usage and throughput. In this paper we present an energy-efficient radix-4 belief propagation polar decoder architecture that uses a new sign-magnitude adder that does not require conversion to two's complement and back. On top of that we also propose using clock gating of input values by checking if all $R$ inputs of the decoder are zero. These two key contributions lead to a more energy -efficient design that is smaller and has higher maximum clock speed and throughput. Post-layout simulation results show that compared to the previously proposed 1024-bit radix-4 belief propagation polar code decoder, our decoder uses between 30.22 % and 32.80 % less power and is 5.2 % smaller at the same clock speed. Also, our design can achieve a 15.7% higher clock speed at which it is still up to 10.76% more power efficient and 4.8% smaller.

关键词： Simulation Switches Energy efficiency Encoding Decoding Polar codes Adders

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Neural Network Based Multiple Object Tracking for Automotive FMCW Radar

Neural Network Based Multiple Object Tracking for Automotive...

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IEEE International Conference on Radar

作者： Konstantinos Fatseas Marco J.G. Bekooij Department of Computer Architectures for Embedded Systems University of Twente Enschede The Netherlands

ISBN: (数字)9781728126609

ISBN: (纸本)9781728137858

Tracking multiple objects from radar data poses several difficulties. In recent work, it has been shown that an algorithm consisting of a thresholding, clustering and multiple object tracking step using the Kalman filter can track multiple objects. Afterwards, features can be extracted from the range-Doppler map to classify the tracked objects. However, this method needs many heuristics on each stage and in the process, information which could be useful in subsequent steps is *** overcome these issues, in this paper we introduce a neural network based multiple object tracker. This removes the need for a separate thresholding, clustering, feature extraction and classification step because it combines those into one step which uses a neural network based on the You Only Look Once (YOLO) object detection system to classify and localize objects. The output of the neural network is fed into a Kalman filter based tracker to manage the *** show that a convolutional neural network trained as an object detector can be successfully applied in the radar domain and we show the advantages of our neural network based multiple object tracker over the clustering based method for specific scenarios. These scenarios include tracking objects that cross each other and tracking objects while the radar is non-stationary.

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Self-Awareness for Autonomous systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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Sampling Jitter mitigation in latency-critical state-estimation applications using particle filters

Sampling Jitter mitigation in latency-critical state-estimat...

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SICE International Symposium on Control systems (ISCS)

作者： Viktorio S. El Hakim Marco J.G. Bekooij Department of Embedded Software and Signal Processing NXP Semiconductors Eindhoven The Netherlands Department of Computer Architectures for Embedded Systems University of Twente Enschede The Netherlands

ISBN: (纸本)9781509056149

State estimation algorithms, such as the Kalman filter, are applied for conditioning and sensor fusion in digital control loops. It is desirable that these algorithms can be executed on embedded multiprocessor systems. However this results in large worst-case execution times with a consequence that a large sampling period must selected, which degrades the estimation and control performance. In this paper, we propose a free-running state-estimation approach in which the next sample is taken as soon as the current iteration completes. The approach utilizes the particle filter algorithm to mitigate the effects of sampling jitter, introduced by the variation in the execution times of tasks. As a result of the reduced interval between subsequent sampling moments the estimation accuracy is improved. The delay introduced by the estimator in a control loop is reduced by enabling execution of the prediction step in parallel with other control tasks. We compare simulation results obtained for our approach with a Kalman filter based approach, by estimating the state of a DC motor. These results show that our approach minimizes the estimation error, as a result of sampling jitter, by up to a factor of 10. Additionally we show that the approach does not require precise knowledge of the distribution of the execution times of the tasks.

关键词： Jitter Schedules Delays State estimation Signal processing algorithms

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Instruction set extensions for the advanced encryption standard on a multithreaded software defined radio platform

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International Journal of High Performance systems Architecture 2010年第3-4期2卷 203-214页

作者： Jenkins, Christipher Schulte, Michael Glossner, John Madison Embedded Systems and Architectures Laboratory Electrical and Computer Engineering Department University of Wisconsin-Madison 1415 Engineering Drive Madison WI 53706-1691 United States Sandbridge Technologies 120 White Plains Road Tarrytown NY 10591 United States

Software-defined radio (SDR) is an emerging technology that facilitates having multiple wireless communication protocols on one device. Previous work has shown that current wireless communication protocols can run on this class of device while consuming significant processing power. Next generation wireless networks require speeds in excess of 50 Mbps. Some of the fastest software implementations of the advanced encryption standard (AES) only achieve 20 Mbps on our reference platform. In order to have secure software-defined radio, the security processing gap must be addressed. This paper presents instruction set architecture (ISA) extensions for the sandblaster digital signal processor (DSP). The sandblaster DSP is a multithreaded processor for SDR that issues multiple operations each cycle and supports vector operations. Our proposed ISA extensions and hardware designs provide significant performance improvements for AES cryptography and should also work well with other types of embedded processors. Copyright © 2010 Inderscience Enterprises Ltd.

关键词： Software radio

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Reciprocal and reciprocal square root units with operand modification and multiplication

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Journal of VLSI Signal Processing systems for Signal, Image, and Video Technology 2006年第3期42卷 257-272页

作者： Wires, Kent E. Schulte, Michael J. Agere Systems Lehigh Valley Central Campus 1110 American Parkway NE Allentown PA 18109 Department of Electrical and Computer Engineering University of Wisconsin-Madison 1415 Engineering Drive Madison WI 53706 Agere Systems Allentown PA University of Wisconsin Madison Madison Embedded Systems and Architectures Group IEEE IEEE Computer Society

Reciprocals and reciprocal square roots are used in several digital signal processing, multimedia, and scientific computing applications. This paper presents high-speed methods for computing reciprocals and reciprocal square roots. These methods use a table lookup, operand modification, and multiplication to obtain an initial approximation. This is followed by a modified Newton-Raphson iteration, which improves the accuracy of the initial approximation. The initial approximation and Newton-Raphson iteration employ specialized hardware to reduce the delay, area, and power dissipation. The application of these methods is illustrated through the design of reciprocal and reciprocal square root units for operands in the IEEE single precision format. These designs are pipelined to produce a new result every clock cycle. © 2006 Springer Science + Business Media, Inc.

关键词： Digital signal processing

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A low-power multithreaded processor for software defined radio

A low-power multithreaded processor for software defined rad...

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作者： Schulte, Michael Glossner, John Jinturkar, Sanjay Moudgill, Mayan Mamidi, Suman Vassiliadis, Stamatis University of Wisconsin Dept. of ECE 1415 Engineering Drive Madison WI 53706 United States Sandbridge Technologies 1 North Lexington Ave. White Plains NY 10512 United States Delft University of Technology Electrical Engineering Mathematics and Computer Science Department Delft Netherlands University of Wisconsin Madison Madison Embedded Systems and Architectures Group IEEE IEEE Computer Society Sandbridge Technologies Sandbridge Systems Software and Communications Software Groups Department of Electrical and Computer Engineering University OfWisconsin Madison Netherlands ACM

embedded digital signal processors for software defined radio have stringent design constraints including high computational bandwidth, low power consumption, and low interrupt latency. Furthermore, due to rapidly evolving communication standards with increasing code complexity, these processors must be compiler-friendly, so that code for them can quickly be developed in a high-level language. In this paper, we present the design of the Sandblaster Processor, a low-power multithreaded digital signal processor for software defined radio. The processor uses a unique combination of token triggered threading, powerful compound instructions, and SIMD vector operations to provide real-time baseband processing capabilities with very low power consumption. We describe the processor's architecture and microarchitecture, along with various techniques for achieving high performance and low power dissipation. We also describe the processor's programming environment and the SB3010 platform, a complete system-on-chip solution for software defined radio. Using a super-computer class vectorizing compiler, the SB3010 achieves real-time performance in software on a variety of communication protocols including 802.11b, GPS, AM/FM radio, Bluetooth, GPRS, and WCDMA. In addition to providing a programmable platform for SDR, the processor also provides efficient support for a wide variety of digital signal processing and multimedia applications. © 2006 Springer Science + Business Media, LLC.

关键词： Program processors

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