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International Conference on Innovative Computing (ICIC)

作者： Muhammad Bilal Khan Muhammad Tauseef Mushtaq Shafaq Khan Muhammad Asjad Jehad Ali Junaid Bilal The University of Lahore Lahore Pakistan University of Management and Technology Lahore Pakistan COMSATS University Islamabad Sahiwal Pakistan AJOU University South Korea

ISBN: (纸本)9781728146836

In this work, we propose modified Recursive Least Square (rls) algorithm which helps to mitigate interference and to enhance the signal strength for wireless communication. In our proposed algorithm, we modify rls in a way that it's forgetting factor depends on the prior error and apply it to the beamforming with multiple antennas. This results in minimized error between desired signal and received signal. This reduction of error provides significant improvement in beamforming and interference cancellation. Further, it speeds up the convergence time of the rls algorithm and improves the efficiency of beamforming. The comparison has been made between the simple and modified rls and the accuracy of beamforming, null placing and error reduction have been checked. The performance results simulated in Matlab shows that the modified rls has increased the performance by approximately 400 percent.

关键词： MIMO Beamforming Cellular networks Adaptive filter Mean square error Least mean square error Weiner filter rls algorithms Beamforming Mean square error multiple input multiple output systems Restless Legs Syndrome adaptive filters Cellular networks Interference cancellation Signal Intensity

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Air Quality Monitoring Network Localization Algorithm Based on RSSI Ranging

Air Quality Monitoring Network Localization Algorithm Based ...

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2016年第七届机电一体化与制造业国际学术会议

作者： CHANG Bo ZHANG Xin-rong XV Bao-guo Faculty of Electronic Information Engineering Huaiyin Institute of Techenology Faculty of Automation Huaiyin Institute of Technology School of Internet of Things Engineering Jiangnan University

To keep abreast of the situation of environmental air quality,improve the quality of life,based on the actual needs of the air quality safety monitoring,a location method of the air quality monitoring network is proposed based on ranging correction and recursive LS *** method mainly includes the RSSI ranging,the measurement distance correction,the monitoring node localization and so *** system can realize the automatic monitoring and localization of environmental air *** with the conventional LS location algorithm,the mean value Ei of positioning error is 0.2433 and 0.2910,and the average running time is 0.2475 s and 0.2946 s respectively,which shows that the proposed localization algorithm has higher accuracy and lower computational complexity.

关键词： air quality monitoring wireless sensor network(WSN) RSSI ranging rls algorithms positioning

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Adaptive tracking of system oscillatory modes using an extended rls algorithm

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ELECTRIC POWER SYSTEMS RESEARCH 2014年 114卷 28-38页

作者： Moreno, I. Messina, A. R. Ctr Res & Adv Studies Cinvestav Dept Elect Engn Guadalajara Jalisco Mexico

The study of low-frequency electromechanical modes in power systems has experienced much progress in the past few years. In this research, a nonstationary recursive least-squares (rls) algorithm with variable forgetting factor is combined with a Kalman filter to simultaneously estimate low-frequency electromechanical modes from measured ambient power system data. Extensions and generalizations to current adaptive filtering algorithms to account for nonstationarity are implemented and tested and the correspondence between the Kalman and rls variables is examined. Applications of the proposed nonstationary rls algorithm to track the evolving dynamics of critical power system electromechanical modes in both, simulated and measured data, are presented. Comparison with other rls and least-mean squares algorithms demonstrate the accuracy of the proposed framework in tracking changes in modal parameters over time. The issues of computational efficiency and memory requirements are discussed in detail. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Kalman filtering Power phasor measurement rls algorithms WAMS

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Fire Disaster Monitoring Network Localization algorithm Based on RSSI Ranging technology

Fire Disaster Monitoring Network Localization algorithm Base...

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2015 4th International Conference on Mechatronics,Materials,Chemistry and Computer Engineering(ICMMCCE 2015)

作者： CHANG Bo ZHANG Xin-rong XV Bao-guo Faculty of Electronic Information Engineering Huai Yin Institute of Techenology Faculty of Automation Engineering Huai Yin Institute of Technology School of Internet of Things Engineering Jiang Nan University

In order to understand the environment and the situation of fire disaster and improve the efficiency of putting out the fire and emergency rescue, aiming at the actual demand of monitoring node location of fire disaster, a new recursive LS(rls) localization method for monitoring fire environment based on wireless sensor networks is proposed, which method is based on dynamic path loss index ranging algorithm. The path loss exponent is obtained periodically, then comparing the relative error coefficients of each reference node;finally the coordinates of the monitoring nodes are estimated using the rls localization algorithm based on the forgetting regulator. The system can realize the fire automatic monitoring and location, real-time collecting and processing these data such as the temperature, humidity and smoke concentration etc. The simulation results show that the method can meet the requirements of the location of the fire environment monitoring system. Compared with the conventional LS algorithm, the proposed localization algorithm has higher accuracy and lower computational complexity.

关键词： fire disaster monitoring wireless sensor network(WSN) RSSI ranging rls algorithms Localization

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A Simple Restart Scheme for Improving Convergence Rates of rls Filters in Tracking Time-varying Delay Systems

A Simple Restart Scheme for Improving Convergence Rates of R...

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SICE Annual Conference

作者： Matsuzaki, Hidenori Hikawa Kohbou Saitama Japan

ISBN: (纸本)9784907764432

The recursive-least-squares (rls) filters are known to be generally unsuitable for tracking time-varying systems. This paper proposes a scheme for improving the tracking performance of rls filters by restarting them when estimation errors exceed a pre-specified value. This scheme is quite simple in essence and can be implemented with minimal amount of additional computation. Moreover it does not affect the steady-state performance of rls filters. Several numerical examples show that the proposed scheme can be effective in tracking time-varying delay systems.

关键词： adaptive filter rls algorithms CIC filter tracking performance time-varying systems

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ADAPTIVE ITERATIVE DECISION MULTI-FEEDBACK DETECTION FOR MULTI-USER MIMO SYSTEMS

ADAPTIVE ITERATIVE DECISION MULTI-FEEDBACK DETECTION FOR MUL...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Li, Peng Liu, Jingjing de Lamare, Rodrigo C. Univ York Dept Elect Commun Res Grp York YO10 5DD N Yorkshire England

ISBN: (纸本)9781467300469

An adaptive iterative decision multi-feedback detection algorithm with constellation constraints is proposed for multiuser multi-antenna systems. An enhanced detection and interference cancellation is performed by introducing multiple constellation points as decision candidates. A complexity reduction strategy is developed to avoid redundant processing with reliable decisions along with an adaptive recursive least squares algorithm for time-varying channels. An iterative detection and decoding scheme is also considered with the proposed detection algorithm. Simulations show that the proposed technique has a complexity as low as the conventional decision feedback detector while it obtains a performance close to the maximum likelihood detector.

关键词： MIMO systems decision feedback receivers rls algorithms multi-user detection iterative processing

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Adaptive reduced-rank rls algorithms based on joint iterative optimization of adaptive filters for space-time interference suppression

Adaptive reduced-rank RLS algorithms based on joint iterativ...

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33rd IEEE International Conference on Acoustics, Speech and Signal Processing

作者： de Lamare, Rodrigo C. Sampaio-Neto, Raimundo Univ York Commun Res Grp York YO10 5DD N Yorkshire England Pontificia Univ Catolica Rio de Janeiro PUC RIO CETUC Rio De Janeiro Brazil

ISBN: (纸本)9781424414833

This paper presents novel adaptive reduced-rank filtering algorithms based on joint iterative optimization of adaptive filters. The novel scheme consists of a joint iterative optimization of a bank of full-rank adaptive filters that constitute the projection matrix and an adaptive reduced-rank filter that operates at the output of the bank of filters. We describe least squares (LS) expressions for the design of the projection matrix and the reduced-rank filter and recursive least squares (rls) adaptive algorithms for its computationally efficient implementation. Simulations for a space-time interference suppression in a CDMA system application show that the proposed scheme outperforms in convergence and tracking the state-of-the-an reduced-rank schemes at about the same complexity.

关键词： adaptive filters iterative methods rls algorithms space-time processing

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A novel general methodology for studying and remedying finite precision error with application in Kalman filtering

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STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 2003年第1-2期17卷 1-19页

作者： Papaodysseus, C Alexiou, C Panagopoulos, T Roussopoulos, G Kravaritis, D Natl Tech Univ Athens Div Commun Elect & Informat Syst Dept Elect & Comp Engn GR-15773 Athens Greece

Least squares (LS) techniques, like Kalman filtering, are widely used in environmental science and engineering. In this paper, a new general approach is introduced for the study of the generation, propagation and accumulation of the quantization error in any algorithm. This methodology employs a number of fundamental propositions demonstrating the way the four operations addition, multiplication, division and subtraction, influence quantization error generation and transmission. Using these, one can obtain knowledge of the exact number of erroneous digits with which an quantities of any algorithm are computed at each step of it. This methodology offers understanding of the actual cause of the generation and propagation of finite precision error in any computational scheme. Application of this approach to all Kalman type LS algorithms shows that not all their formulas are equivalent concerning the quantization error effects. More specifically, few generate the greater amount of quantization error. Finally, a stabilization procedure, applicable to all Kalman type algorithms, is introduced that renders all these algorithms very robust.

关键词： quantization error finite precision error rls algorithms Kalman type algorithms instability Kalman type algorithms stabilization

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Mitigating error propagation in CDMA multiuser DFE

Mitigating error propagation in CDMA multiuser DFE

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35th Asilomar Conference on Signals, Systems and Computers

作者： Zhi, T Michigan Technol Univ Dept Elect & Comp Engn Houghton MI 49931 USA

ISBN: (纸本)078037147X

In this paper, robust measures via constraining the filter weight vector are applied to the decision-directed decision feedback equalization (DFE) detectors to alleviate the error propagation problem in CDMA wireless systems. These constraints are constructed from the spreading codes of the desired user to preserve its output energy. The constrained portion of the weight vector is able to curb the effect of incorrect past decisions and provide the leverage to prevent error propagation and maintain a stable transmission. The use of signal-preserving constraints also improves the multiple access interference suppression capacity. Efficient adaptive rls algorithms for nonlinear DFE filters are developed, and the achievable steady state SINR performance of both the unconstrained and constrained DFE is derived.

关键词： decision feedback equalisers code division multiple access nonlinear filters multiuser channels signal detection radiofrequency interference interference suppression adaptive filters least mean squares methods optimisation radio links error propagation CDMA wireless systems multiuser DFE filter weight vector decision feedback equalization DFE detectors spreading codes nonlinear filters multiple access interference interference suppression MAI rls algorithms constrained optimization MMSE equalization

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A robust, parallelizable, O(m), a posteriori recursive least squares algorithm for efficient adaptive filtering

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 1999年第9期47卷 2552-2558页

作者： Papaodysseus, C Natl Tech Univ Athens Dept Elect & Comp Engn Div Comp Engn Athens Greece

This correspondence presents a new recursive least squares (rls) adaptive algorithm. The proposed computational scheme uses a finite window by means of a lemma for the system matrix inversion that is, for the first time, stated and proven here. The new algorithm has excellent tracking capabilities. Moreover, its particular structure allows for stabilization by means of a quite simple method. Its stabilized version performs very well not only for a white noise input but also for nonstationary inputs as well. It is shown to follow music, speech, environmental noise, etc, with particularly good tracking properties. The new algorithm can be parallelized via a simple technique. Its parallel form is very fast when implemented with four processors.

关键词： adaptive algorithms adaptive filtering finite precision error finite memory algorithms finite window filtering Kalman-type algorithms quantization error rls algorithms stabilized algorithms

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