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A Novel Low complexity Scheme for Multiuser Massive MIMO Systems

IEICE TRANSACTIONS ON COMMUNICATIONS 2022年第1期E105B卷 85-96页

作者： Htun, Aye Mon Maw, Maung Sann Sasase, Iwao Mathiopoulos, P. Takis Keio Univ Dept Informat & Comp Sci Yokohama Kanagawa 2238522 Japan Natl & Kapodistrian Univ Athens Dept Informat & Telecommun Athens 15784 Greece

In this paper, we propose a novel user selection scheme based on jointly combining channel gain (CG) and signal to interference plus noise ratio (SINR) to improve the sum-rate as well as to reduce the computation complexity of multi-user massive multi-input multi-output (MU-massive MIMO) downlink transmission through a block diagonalization (BD) precoding technique. By jointly considering CG and SINR based user sets, sum-rate performance improvement can be achieved by selecting higher gain users with better SINR conditions as well as by eliminating the users who cause low sum-rate in the system. Through this approach, the number of possible outcomes for the user selection scheme can be reduced by counting the common users for every pair of user combinations in the selection process since the common users of CG-based and SINR-based sets possess both higher channel gains and better SINR conditions. The common users set offers not only sum-rate performance improvements but also computation complexity reduction in the proposed scheme. It is shown by means of computer simulation experiments that the proposed scheme can increase the sum-rate with lower computation complexity for various numbers of users as compared to conventional schemes requiring the same or less computational complexity.

关键词： MU-massive MIMO user selection transmit antenna selection computation complexity SINR SVD block diagonalization

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Real-time implementation of active shunt compensator with adaptive SRLMMN control technique for power quality improvement in the distribution system

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第8期14卷 1598-1606页

作者： Badoni, Manoj Singh, Alka Singh, Bhim Saxena, Hemant Thapar Inst Engn & Technol Dept Elect & Instrumentat Engn Patiala Punjab India Delhi Technol Univ Dept Elect Engn Delhi India Indian Inst Technol Dept Elect Engn Delhi India

In this work, the development of sign regressor least mean mixed norm (SRLMMN) control technique for a distribution static compensator (D-STATCOM) is presented. This control technique extracts fundamental weight components from the non-sinusoidal load currents and generates reference grid currents. D-STATCOM is developed for harmonics eradication, reactive power injection and load balancing and its performance is investigated in several operating modes. The performance of SRLMMN control is compared with recursive least square (RLS) and variable step least mean square (VSLMS) control techniques in terms of convergence, steady-state error, harmonics elimination, sample time and computation complexity. The major advantages of SRLMMN control technique, are fast convergence, less steady-state error, low total harmonic distortion (THD) and offers less computation complexity when compared with RLS and VSLMS. A laboratory-scale prototype of compensator is realised using a voltage source converter with the controller implemented in the dSPACE-MicroLabBox. Both MATLAB simulation and experimental results are included to demonstrate the performance of shunt compensator under steady-state and dynamic loadings. The developed SRLMMN control technique mitigates power quality problems and effectively suppresses THD observed in the grid current with reference to IEEE Standard 519-2014.

关键词： least mean squares methods power grids static VAr compensators power supply quality reactive power IEEE standards harmonic distortion active shunt compensator adaptive SRLMMN control technique power quality improvement distribution system sign regressor mixed norm control technique distribution static compensator D-STATCOM fundamental weight components nonsinusoidal load currents reference grid currents harmonics eradication reactive power injection load balancing steady-state error harmonics elimination sample time computation complexity low total harmonic distortion dynamic loadings developed SRLMMN control technique power quality problems

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A decimated minimum variance beamformer applied to ultrasound imaging

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ULTRASONICS 2015年 59卷 119-127页

作者： Sakhaei, Sayed Mahmoud Babol Univ Technol Dept Elect & Comp Engn Babol Sar Iran

Minimum variance beamforming has performed significant improvement in the resolution of the ultrasound images. However, its computational complexity is a serious problem. This paper introduces a new implementation of the minimum variance beamformer for ultrasound imaging with a focused transmit beam. In this method, a decimated aperture data instead of full of it, is used as the beamformer input, on which the minimum variance beamforming is applied, with the covariance matrix estimated using the full aperture data. In this way, the method can give a linear complexity while it can show a performance comparable to that of the full array implementation of the minimum variance beamforming, as the simulation and experimental results confirm this. Therefore, this adaptive beamforming method can be viewed as an approximate implementation of the minimum variance beamforming with a linear computational complexity. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Adaptive beamforming Minimum variance Decimation computation complexity

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Hardware-software co-design architecture for Joint Photo Expert Graphic XR encoder

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IET IMAGE PROCESSING 2012年第9期6卷 1284-1292页

作者： Tseng, C. -F. Lai, Y. -T. Natl Cheng Kung Univ Dept Elect Engn Tainan 701 Taiwan

In recent years, because of to the fast growing of internet and digital multi-media, new image compression algorithms are needed to reduce the transferring bandwidth and the decay of image quality. Joint Photo Expert Graphic (JPEG) extended range (XR) is a new standard for still image compression. Compared to previous standards, it provides better image quality and plentiful pixel format. However, the better image quality often comes with the higher computation complexity. In this study, the authors propose a hardware-software co-design architecture for JPEG XR encoder. For photo overlap transform (POT), and photo core transform (PCT), the complicated parts of JPEG XR, the authors propose new algorithms which eliminate data dependency in the basic filters of POT and PCT so that operations can be executed in parallel. The processing rate of the new algorithms is much faster. The authors also demonstrate a basic filter with multiple functions, which can be time-shared by POT and PCT;the hardware cost can be therefore reduced. Moreover, a memory saving scheme is proposed. Therefore the proposed architecture is suitable for stand-alone application-specific integrated circuit (ASIC). In our co-design, POT and PCT are implemented in hardware and then mapped to field programmable gate array (FPGA), whereas the other procedures of JPEG XR such as quantisation are executed by ARM926-EJ processor. The overall performance of our hardware architecture is 50 fps for 4:4:4 HDTV format at 166 MHz.

关键词： frequency 166 MHz image quality ASIC Filtering methods in signal processing photo core transform ARM926-EJ processor data compression hardware-software codesign digital multimedia image compression algorithm JPEG XR encoder field programmable gate arrays Hardware-software codesign Internet Electronic engineering computing FPGA joint photo expert graphic XR encoder Computer vision and image processing techniques computer architecture Image and video coding still image compression application specific integrated circuits image coding hardware architecture photo overlap transform data dependency Integral transforms POT quantisation (signal) Logic circuits Computer architecture computation complexity quantisation JPEG extended range stand-alone application-specific integrated circuit PCT Logic and switching circuits memory saving scheme HDTV format filtering theory filter bandwidth transfer hardware-software co-design architecture field programmable gate array Digital circuit design, modelling and testing transforms

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Fast algorithm for large-scale subspace clustering by LRR

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IET IMAGE PROCESSING 2020年第8期14卷 1475-1480页

作者： Xie, Deyan Nie, Feiping Gao, Quanxue Xiao, Song Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Northwestern Polytech Univ Ctr Opt IMagery Anal & Learning Xian 710069 Peoples R China

Low-rank representation (LRR) and its variants have been proved to be powerful tools for handling subspace clustering problems. Most of these methods involve a sub-problem of computing the singular value decomposition of an n x n matrix, which leads to a computation complexity of O(n(3)). Obviously, when n is large, it will be time consuming. To address this problem, the authors introduce a fast solution, which reformulates the large-scale problem to an equal form with smaller size. Thus, the proposed method remarkably reduces the computation complexity by solving a small-scale problem. Theoretical analysis proves the efficiency of the proposed model. Furthermore, we extend LRR to a general model by using Schatten p-norm instead of nuclear norm and present a fast algorithm to solve large-scale problem. Experiments on MNIST and Caltech101 databse illustrate the equivalence of the proposed algorithm and the original LRR solver. Experimental results show that the proposed algorithm is remarkably faster than traditional LRR algorithm, especially in the case of large sample number.

关键词： matrix algebra singular value decomposition pattern clustering computational complexity large-scale problem computation complexity small-scale problem original LRR solver traditional LRR algorithm large-scale subspace clustering low-rank representation subspace clustering problems singular value decomposition MNIST Caltech101 databse

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Distributed sparse diffusion estimation with reduced communication cost

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IET SIGNAL PROCESSING 2018年第8期12卷 1043-1052页

作者： Shiri, Hamid Tinati, Mohammad Ali Codreanu, Marian Azarnia, Ghanbar Univ Tabriz Dept Elect & Comp Engn Tabriz 51666 Iran Univ Oulu Ctr Wireless Commun Oulu 90014 Finland

The issue considered in the current study is the problem of adaptive distributed estimation based on diffusion strategy which can exploit sparsity in improving estimation error and reducing communications. It has been shown that distributed estimation leads to a good performance in terms of the error value, convergence rate, and robustness against node and link failures in wireless sensor networks. However, the main focus of many works in the field of distributed estimation research is on convergence speed and estimation error, neglecting the fact that communications among the nodes require a lot of transmissions. In this work, the focus is on a solution based on sparse diffusion least mean squares (LMS) algorithm, and a new version of sparse diffusion LMS algorithm is proposed which takes both communications and error cost into account. Also, the computation complexity and communication cost for every node of the network, as well as performance analysis of the proposed strategy, is provided. The performance of the proposed method in comparison with the existing methods is illustrated by means of simulations in terms of computational and communicational cost, and flexibility to signal changes.

关键词： computational complexity adaptive estimation wireless sensor networks least mean squares methods network theory (graphs) convergence rate wireless sensor networks distributed estimation research convergence speed estimation error sparse diffusion least mean squares algorithm sparse diffusion LMS algorithm computation complexity computational cost communicational cost distributed sparse diffusion estimation reduced communication cost adaptive distributed estimation diffusion strategy

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Binary flower pollination algorithm based user scheduling for multiuser MIMO systems

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2022年第4期30卷 1317-1336页

作者： Mohanty, Jyoti Pattanayak, Prabina Nandi, Arnab Baishnab, Krishna Lal Talukdar, Fazal Ahmed Natl Inst Technol Silchar Dept Elect & Commun Engn Silchar Assam India Siksha O Anusandhan Deemed Univ Bhubaneswar Odisha India

In this article, a multiuser (MU) multiinput multioutput (MIMO) system is considered, which is essential to support a huge number of subscribers without consuming extra bandwidth or power. Dirty paper coding (DPC) for MU MIMO channel achieves the peak sum-rate for the MU multiple antenna system at the cost of high computational complexity. Both user and antenna scheduling with a population based meta-heuristic algorithm, i.e. binary flower pollination algorithm (binary FPA) has been demonstrated in this article to achieve system sum-rate comparable to DPC with very less computational complexity and time complexity. Moreover, binary FPA shows a significant improvement in system throughput/sum-rate performance as compared to other population based meta-heuristic algorithms like binary bat algorithm (binary BA) and binary genetic algorithm (binary GA). Furthermore, the proposed binary FPA algorithm successfully achieves higher system sum-rate as compared to random search scheme and different existing suboptimal scheduling algorithms from literature as well. The binary FPA has also better convergence rate and searching ability than both binary BA and binary GA techniques. The percentage deviation achieved by the proposed binary FPA algorithm is quite less than that of binary BA, binary GA, random search method, and existing suboptimal scheduling algorithms from the literature. The efficiency of binary FPA in all these fronts is verified using exhaustive simulation studies.

关键词： Binary flower pollination algorithm multiuser MIMO antenna user scheduling dirty paper coding computation complexity time complexity

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Semantic labelling of SAR images with conditional random fields on region adjacency graph

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IET RADAR SONAR AND NAVIGATION 2011年第8期5卷 835-841页

作者： Yang, W. Chen, L. Dai, D. Xia, G. -S. Wuhan Univ Sch Elect Informat Wuhan 430079 Peoples R China TELECOM ParisTech CNRS LTCI F-75013 Paris France

Scene segmentation and semantic labelling are important for analysing and understanding synthetic aperture radar (SAR) images. In this study, the authors propose an effective and efficient labelling method for SAR images with conditional random fields on a region adjacency graph (CRF-RAG). More precisely, for an SAR image, a region adjacency graph (RAG) representation is firstly built on an initially over-segmentation of the image. Subsequently, a conditional random field (CRF) model is established over the RAG instead of over pixels. To train and infer the CRF-RAG model, a fast max-margin training strategy and the graph cut optimisation method are finally employed. As the CRF model is based on RAG, the computation complexity of the model can be reduced significantly. Compared to the Markov random field (MRF) model on RAG, the proposed CRF-RAG model is more efficient to incorporate different measures of SAR images, such as scattering intensity, texture and image context, into a unified model. Experiments on the TerraSAR-X imagery achieve promising results with modest computation cost, which validates the generality and flexibility of the proposed method.

关键词： scattering intensity semantic labelling Optimisation techniques radar imaging synthetic aperture radar images image segmentation TerraSAR-X imagery Optical, image and video signal processing optimisation image context image representation Radar equipment, systems and applications Combinatorial mathematics image over-segmentation MRF model SAR images graph cut optimisation method RAG representation computation cost image texture synthetic aperture radar max-margin training strategy computation complexity CRF-RAG model random processes conditional random fields region adjacency graph representation CRF model labelling method computational complexity Markov random field model graph theory conditional random field model scene segmentation Markov processes

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Field Programmable Gate Array Based Parallel Strapdown Algorithm Design for Strapdown Inertial Navigation Systems

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SENSORS 2011年第8期11卷 7993-8017页

作者： Li, Zong-Tao Wu, Tie-Jun Lin, Can-Long Ma, Long-Hua Zhejiang Univ Inst Nav Guidance & Control Hangzhou 310027 Peoples R China Zhejiang Univ Dept Control Sci & Engn Hangzhou 310027 Peoples R China

A new generalized optimum strapdown algorithm with coning and sculling compensation is presented, in which the position, velocity and attitude updating operations are carried out based on the single-speed structure in which all computations are executed at a single updating rate that is sufficiently high to accurately account for high frequency angular rate and acceleration rectification effects. Different from existing algorithms, the updating rates of the coning and sculling compensations are unrelated with the number of the gyro incremental angle samples and the number of the accelerometer incremental velocity samples. When the output sampling rate of inertial sensors remains constant, this algorithm allows increasing the updating rate of the coning and sculling compensation, yet with more numbers of gyro incremental angle and accelerometer incremental velocity in order to improve the accuracy of system. Then, in order to implement the new strapdown algorithm in a single FPGA chip, the parallelization of the algorithm is designed and its computational complexity is analyzed. The performance of the proposed parallel strapdown algorithm is tested on the Xilinx ISE 12.3 software platform and the FPGA device XC6VLX550T hardware platform on the basis of some fighter data. It is shown that this parallel strapdown algorithm on the FPGA platform can greatly decrease the execution time of algorithm to meet the real-time and high precision requirements of system on the high dynamic environment, relative to the existing implemented on the DSP platform.

关键词： strapdown algorithm coning and sculling compensation parallelization design computation complexity FPGA

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A Method to Reduce the Algorithm complexity of the Single-Photodiode-per-Polarization Coherent Receiver

IEEE PHOTONICS JOURNAL

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IEEE PHOTONICS JOURNAL 2020年第1期12卷 1-10页

作者： Zhou, Keji Cui, Sheng Tu, Yicong Liu, Deming Huazhong Univ Sci & Technol Wuhan Natl Lab Optoelect Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Opt & Elect Informat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Natl Engn Lab Next Generat Internet Access Syst Wuhan 430074 Peoples R China

Single-photodiode-per-polarization coherent receivers (SCRs) can preserve all of the merits of the conventional digital coherent receivers (DCRs) such as supporting chromatic dispersion (CD) compensation and polarization multiplexing, whilst have much lower optical complexity. But the overall algorithm complexity of the SCRs is relatively higher because an extra dedicated field reconstruction algorithm (FRA) is required in addition to the standard algorithms used in DCRs. The heavy computation burden introduced by the FRA poses a major obstacle to reduce the DSP chip size and power consumption. In this paper we propose a method to reduce the overall algorithm complexity of the SCR by utilizing several techniques, including utilizing a strong local oscillator (LO) to mitigate the signal-signal beat interference (SSBI), a pseudo-single-side-band signal to recovery the signal field and a new FRA to reuse the operations in the CD compensation algorithm to realize field reconstruction. Other than reducing the overall algorithm complexity, the new method also make the SCR more robust to laser frequency offset compared with the existing heterodyne detection based FRA. Numerical simulations and experiments are presented to demonstrate the merits of new method with respect to the existing ones.

关键词： Chromatic dispersion compensation computation complexity field reconstruction algorithm heterodyne detection real-time DSP system simplified coherent receivers

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