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2nd International Japan-Egypt Conference on Electronics, Communications and Computers (JEC-ECC)

作者： Al-Nahhal, Ibrahim Emran, Ahmed kasen, Hossam Abd El-Rahman, Adel. B. Egypt Japan Univ Sci & fechnol Dept Elect & Commun Engn Alexandria 21934 Egypt

ISBN: (纸本)9781479931590

k-best sphere decoding algorithm (kBA) is used to approach near-maximum-likelihood (ML) performance for multiple-input-multiple-output (MIMO) detection with lower complexity than maximum-likelihood (ML) method. In kBA, the value of survivor paths k, can be fixed values only in all tree levels. These fixed values of k's give a certain performances at a certain complexities. In this paper, a new fractional k-best algorithm (FkBA) is proposed which gives a performance and complexity between these discreet performances and complexities for ordinary kBA, acts as if the values of k's are fractions (not integers). This can be achieved by increasing the number of survivor paths into k + Delta in some tree levels and stays k paths in other tree levels. The value of Delta in a specific tree level is resulted from the number of branches have distance metrics lower than or equal the value of average distance metric for all branches in the same tree level. The simulation results show that the performance and complexity of FkBA are approximately in the middle of performances and complexities of two successive values of k (k and k + 1) for different MIMO models of 16 - QAM over Rayleigh fading MIMO Channels for all values of SNR.

关键词： Multiple-Input Multiple-Output (MIMO) Sphere Decoder k-best algorithm

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Intervention decision-making in MAV/UAV cooperative engagement based on human factors engineering

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Journal of Systems Engineering and Electronics 2018年第3期29卷 530-538页

作者： ZHONG Yun YAO Peiyang WAN Lujun YANG Juan Information and Navigation College Air Force Engineering UniversityXi'an 710077China Air Traffic Control and Navigation College Air Force Engineering UniversityXi'an 710051China Unit 93010 of the PLA Shenyang 110015China

Aiming at the intervention decision-making problem in manned/unmanned aerial vehicle（MAV/UAV） cooperative engagement, this paper carries out a research on allocation strategy of emergency discretion based on human factors engineering（HFE）.Firstly, based on the brief review of research status of HFE, it gives structural description to emergency in the process of cooperative engagement and analyzes intervention of commanders. After that,constraint conditions of intervention decision-making of commanders based on HFE（IDMCBHFE） are given, and the mathematical model, which takes the overall efficiency value of handling emergencies as the objective function, is established. Then, through combining k-best and variable neighborhood search（VNS） algorithm, a k-best optimization variable neighborhood search mixed algorithm（kBOVNSMA） is designed to solve the model. Finally,through three groups of simulation experiments, effectiveness and superiority of the proposed algorithm are verified.

关键词： manned/unmanned aerial vehicle(MAV/UAV) intervention decision-making human factors engineering structural description k-best algorithm variable neighborhood search algorithm

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Computing all efficient solutions of the biobjective minimum spanning tree problem

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COMPUTERS & OPERATIONS RESEARCH 2008年第1期35卷 198-211页

作者： Steiner, Sarah Radzik, Tomasz Kings Coll London Dept Comp Sci London WC2R 2LS England

A common way of computing all efficient (Pareto optimal) solutions for a biobjective combinatorial optimisation problem is to compute first the extreme efficient solutions and then the remaining, non-extreme solutions. The second phase, the computation of non-extreme solutions, can be based on a "k-best" algorithm for the single-objective version of the problem or on the branch-and-bound method. A k-best algorithm computes the k-best solutions in order of their objective values. We compare the performance of these two approaches applied to the biobjective minimum spanning tree problem. Our extensive computational experiments indicate the overwhelming superiority of the k-best approach. We propose heuristic enhancements to this approach which further improve its performance. (C) 2006 Elsevier Ltd. All rights reserved.

关键词： multiple objective programming combinatorial optimisation minimum spanning tree k-best algorithm

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VLSI Implementation of a Fully-Pipelined k-best MIMO Detector with Successive Interference Cancellation

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2019年第10期38卷 4739-4761页

作者： Bello, Ibrahim A. Halak, Basel El-Hajjar, Mohammed Zwolinski, Mark Univ Oxford Dept Engn Sci Parks Rd Oxford OX1 3PJ England Univ Southampton Elect & Comp Sci Southampton SO17 1BJ Hants England

Multiple-input multiple-output (MIMO) technology is envisaged to play an important role in future wireless communications. To this end, novel algorithms and architectures are required to implement high-throughput MIMO communications at low power consumption. In this paper, we present the hardware implementation of a modified k-best algorithm combining conventional k-best detection and low-complexity successive interference cancellation at different levels of the tree search. The detector is implemented using a fully-pipelined architecture, which detects one symbol vector per clock cycle. To reduce the power consumption of the entire receiver unit, costly symbol-rate operations such as multiplication are eliminated both within and outside the detector without any impact on the performance. The hardware implementation of the modified k-best algorithm achieves area and power reductions of 16% and 38%, respectively, compared with the conventional k-best algorithm implementation, while incurring a signal-to-noise ratio penalty of 0.3 dB at the target bit error rate. Post-synthesis analysis shows that the detector achieves a throughput of 3.29 Gbps at a clock frequency of 137 MHz with a power consumption of 357 mW using a 65-nm CMOS process, which compares favourably with the state-of-the-art implementations in the literature.

关键词： VLSI MIMO k-best algorithm Wireless communications

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Research on low-complexity breadth-first detection for multiple-symbol differential unitary space-time modulation systems

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IET COMMUNICATIONS 2011年第13期5卷 1868-1878页

作者： Jin, N. Jin, X. P. Ying, Y. G. Wang, S. Lou, X. Z. China Jiliang Univ Dept Informat Engn Hangzhou 310018 Peoples R China

The breadth-first searching algorithms, typically represented by k-best algorithm, are widely studied for multiple-symbol differential detection in multiple-input multiple-output systems due to the advantages of fixed complexity and latency which are very attractive for hardware implementation. However, it needs a large k value to achieve near maximum likelihood performance, which results in large complexity. In this study, a dynamic k-best detection with reduced average k value is proposed. It reduces the complexity on path expanding, path updating and comparing and swapping (C&S) operations by 24.24, 25 and 43.46%, respectively, with less performance degradation. After that, two low-complexity sorting architectures, Batcher's merge sort and k cycles sort, are presented and applied to the proposed dynamic k-best detection. The complexity analysis and simulation results show that, compared with the traditional Bubble sorting dynamic k-best detection, the k cycles sorting and the Batcher's merge sorting dynamic k-best detections can further save C&S operations by 59.5 and 11.2%, respectively, while performance cost capable of being ignored. Moreover, the k cycles sorting dynamic k-best detection achieves best trade-off on throughput and required memory, and the architecture of the Batcher's merge sorting dynamic k-best detection is more beneficial to parallel processing and multiple-processor structure.

关键词： complexity analysis hardware implementation breadth-first searching algorithm multiple processor structure reduced average k value multiple symbol differential detection sorting maximum likelihood estimation Modulation and coding methods parallel processing Combinatorial mathematics Signal detection differential detection near maximum likelihood performance multiple input multiple output system low complexity sorting architecture k cycle sorting dynamic k-best algorithm Radio links and equipment low complexity breadth-first detection communication complexity batcher merge bubble sorting dynamic k-best detection multiple symbol differential unitary space time modulation system MIMO communication Other topics in statistics

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A Synchro-Set-Aided Breadth-First Sphere Decoder for Polar-Coded MIMO Systems

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2022年 70卷 6200-6215页

作者： Zhou, Huayi Deng, Xiangyun Cai, Yiqian Shen, Yifei Yang, Minhua Gross, Warren J. You, Xiaohu Zhang, Chuan Southeast Univ LEADS Natl Mobile Commun Res Lab Nanjing 211189 Peoples R China Southeast Univ Frontiers Sci Ctr Mobile Informat Commun & Secur Nanjing 211189 Peoples R China Southeast Univ Purple Mt Labs Nanjing 211189 Peoples R China McGill Univ Dept Elect & Comp Engn Montreal PQ H3A 0G4 Canada

The joint optimization of multiple-input-multiple-output (MIMO) detection and polar decoding has become a research hotspot for future communication systems. The error-correction performance of the separate detection and decoding (SDD) is far from the Shannon capacity, which cannot meet the requirements of communication scenarios such as ultra-reliable and low latency communications (URLLC). The existing joint detection and decoding (JDD) using breadth-first sphere decoding (BFSD) improves the reliability over SDD but still has a huge performance loss on low-rate codes. In this paper, JDD using synchro-set-aided BFSD (SA-BFSD) is proposed to greatly improve the error-correction performance for polar-coded MIMO systems. We first propose a method to generate the symbol synchro sets through the concept of frozen symbols, then refine the symbol synchro sets based on the characteristics analysis of the channel matrix. We optimize the enumerating order of the symbols and reduce the enumerating levels. The frame error rate (FER) and the bit error rate of the proposed algorithms are significantly improved especially for the low-rate codes. The proposed SA-BFSD JDD achieves an up to 7.8 dB performance gain over BFSD at FER =10(-3). The hardware architecture of the polar JDD scheme is first implemented with SMIC 40-nm CMOS technology for MIMO systems. The reliability and latency of SA-BFSD are much better than those of the existing works, which could meet the requirements of URLLC.

关键词： Codes Bit error rate Symbols Signal processing algorithms Ultra reliable low latency communication Performance gain Hardware Joint detection and decoding k-best algorithm polar codes sphere decoding URLLC

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Efficient Ordering Schemes for High-Throughput MIMO Detectors

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JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY 2011年第1期64卷 61-74页

作者： Wu, Xuebin Dai, Yongmei Wang, Ying Yan, Zhiyuan Lehigh Univ Dept Elect & Comp Engn Bethlehem PA 18015 USA Qualcomm Flar Technol Bridgewater NJ 08807 USA

The order of the channel matrix columns is an important factor that affects the computational complexity, memory requirement, and detection error rate of multi-input multi-output (MIMO) detectors. Novel efficient ordering schemes proposed in our previous work lead to advantages in the computational complexity and memory requirement of various maximum likelihood (ML) MIMO detectors. In this paper, we apply these ordering schemes to the k-best detector-a near-ML MIMO detector suitable for high-throughput hardware implementations-and show that our novel ordering schemes improve the performance of the k-best detector, especially when k is small. With a given detection error rate, our ordering schemes either lead to signal-to-noise ratio (SNR) gains, or allow even smaller k. Two of these ordering schemes, which can be easily embedded into the QR decomposition, are implemented in hardware. We adopt Givens based ordering schemes, due to their numerical stability when fixed point representations are used. Our hardware implementation results show that our novel ordering schemes incur negligible overheads and are particularly suitable for high-throughput implementations.

关键词： MIMO Ordering schemes k-best algorithm VLSI implementation Wireless communications Preprocessing

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An efficient procedure for finding best compromise solutions to the multi-objective assignment problem

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COMPUTERS & OPERATIONS RESEARCH 2014年 49卷 97-106页

作者： Belhoul, Lyes Galand, Lucie Vanderpooten, Daniel Univ Paris 09 PSL LAMSADE F-75775 Paris 16 France

In this paper, we consider the problem of determining a best compromise solution for the multi-objective assignment problem. Such a solution minimizes a scalarizing function, such as the weighted Tchebychev norm or reference point achievement functions. To solve this problem, we resort to a ranking (or k-best) algorithm which enumerates feasible solutions according to an appropriate weighted sum until a condition, ensuring that an optimal solution has been found, is met The ranking algorithm is based on a branch and bound scheme. We study how to implement efficiently this procedure by considering different algorithmic variants within the procedure: choice of the weighted sum, branching and bounding schemes. We present an experimental analysis that enables us to point out the best variants, and we provide experimental results showing the remarkable efficiency of the procedure, even for large size instances. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Multi-objective assignment problem Compromise solutions Branch and bound k-best algorithm

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COMPRESSED SENSING k-best DETECTION FOR SPARSE MULTI-USER COMMUNICATIONS 22

COMPRESSED SENSING K-BEST DETECTION FOR SPARSE MULTI-USER CO...

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22nd European Signal Processing Conference (EUSIPCO)

作者： knoop, B. Monsees, F. Bockelmann, C. Peters-Drolshagen, D. Paul, St. Dekorsy, A. Univ Bremen Inst Electrodynam & Microelect ITEM D-28359 Bremen Germany Univ Bremen Dept Commun Engn D-28359 Bremen Germany

ISBN: (纸本)9780992862619

Machine-type communications are quite often of very low data rate and of sporadic nature and therefore not well-suited for nowadays high data rate cellular communication systems. Since signaling overhead must be reasonable in relation to message size, research towards joint activity and data estimation was initiated. When the detection of sporadic multi-user signals is modeled as a sparse vector recovery problem, signaling concerning node activity can be avoided as it was demonstrated in previous works. In this paper we show how well-known k-best detection can be modified to approximately solve this finite alphabet Compressed Sensing problem. We also demonstrate that this approach is robust against parameter variations and even works in cases where fewer measurements than unknown sources are available.

关键词： k-best algorithm multi-user detection sparse signal processing Compressed Sensing

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Efficient k-best Detection Technique for MIMO-OFDM-based Mobile Multimedia Systems

Efficient K-Best Detection Technique for MIMO-OFDM-based Mob...

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4th International Conference on Computer Sciences and Convergence Information Technology

作者： Baek, Myung-Sun Park, So-Ra Song, Hyoung-kyu Lee, Yong-Tae Elect & Telecommun Res Inst Taejon South Korea UT Commun Res Inst Seoul South Korea

ISBN: (纸本)9781424452446

MIMO-OFDM schemes with SDM have been studied for high speed multimedia systems. However, since accurate received MIMO signal detection is very hard, MIMO-OFDM systems have not reached the available capacities. For high detection performance and low complexity, we propose efficient k-best detection technique. The proposed technique increases the detection performance by using OSIC scheme for initial detection. And to reduce the complexity, the computations for k- best algorithm are limited by OSIC scheme. The proposed technique can detect the transmit signal more accurately and offer lower complexity than conventional ZF-k- best algorithm.

关键词： MIMO-OFDM k-best algorithm ZF linear detection OSIC

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