scholarly journals A Novel Adaptive Algorithm Addresses Potential Problems of Blind Algorithm

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Muhammad Yasin ◽  
Muhammad Junaid Hussain
Keyword(s):  
Hybrid Algorithm ◽  
Smart Antenna ◽  
Additive White Gaussian Noise ◽  
Lms Algorithm ◽  
Mean Square ◽  
Least Mean Square ◽  
Constant Modulus ◽  
Constant Modulus Algorithm ◽  
Proposed Model ◽  
Potential Problems

A hybrid algorithm called constant modulus least mean square (CMLMS) algorithm is proposed in order to address the potential problems existing with constant modulus algorithm (CMA) about its convergence. It is a two-stage adaptive filtering algorithm and based on least mean square (LMS) algorithm followed by CMA. A hybrid algorithm is theoretically developed and the same is verified through MatLab Software. Theoretical model is verified through simulation and its performance is evaluated in smart antenna in presence of a cochannel interfering signal and additive white Gaussian noise (AWGN) of zero mean. This is also tested in Rayleigh fading channel using digital modulation technique for Bit Error Rate (BER). Finally, a few computer simulations are presented in order to substantiate the theoretical findings with respect to proposed model. Corresponding results obtained with the use of only CMA and LMS algorithms are also presented for further comparison.

The Design of the Heterotypic Antenna Array of the Smart Antenna with the LMS Algorithm

2011 ◽  
Vol 216 ◽  
pp. 6-10 ◽  
Author(s):  
Jie Jin ◽  
Xi Kong ◽  
Lan Lan Zhao
Keyword(s):  
Antenna Array ◽  
Linear Array ◽  
Smart Antenna ◽  
Step Length ◽  
Lms Algorithm ◽  
Mean Square ◽  
Least Mean Square ◽  
Rectangular Array ◽  
Algorithm Performance ◽  
Signal Environment

Using the Least Mean Square (LMS) algorithm, this paper simulates two smart antenna models under the same signal environment. By analyzing and comparing 8-antenna elements linear array and 2*4- antenna elements rectangular array, this paper proposes the way to design the heterotypic antenna model. This antenna array can help system to gain similar performance of signal to interference plus noise radio(SINR) with reduced size of the antenna. The paper realizes the simulation of two models with the LMS algorithm. The antenna pattern and the curve about convergence of error have been given. It also analyzes the influence of the step length factor on LMS algorithm performance, and finds out the reasonable step to ensure fast algorithm convergence and to suppress interference effectively.

scholarly journals Χρήση αυτορυθμιζόμενων ηλεκτρονικών εξισωτών σε οπτικά τηλεπικοινωνιακά συστήματα και δίκτυα με πυκνή πολυπλεξία μήκους κύματος και ρυθμό σηματοδοσίας 10 GB/S ανά οπτικό κανάλι

2010 ◽  
Author(s):  
Αθανάσιος Βγένης
Keyword(s):  
Mean Square ◽  
Least Mean Square ◽  
Constant Modulus ◽  
Constant Modulus Algorithm

Η παρούσα διατριβή εστιάζεται σε οπτικά τηλεπικοινωνιακά συστήματα με σύμφωνο δέκτη τετραδική διαμόρφωση φάσης και πολύπλεξη κατά πόλωση. Το κυριότερο πλεονέκτημα αυτών των συστημάτων σε σύγκριση με τα συμβατικά οπτικά τηλεπικοινωνιακά συστήματα με δέκτες άμεσης φώρασης είναι οι αυξημένες δυνατότητες ψηφιακής επεξεργασίας σήματος στο δέκτη που καθιστά εφικτή την εξίσωση των φαινομένων διάδοσης και την αποπολύπλεξη πόλωσης με ηλεκτρονικά μέσα. Μελετώνται διατάξεις ηλεκτρονικής επεξεργασίας σήματος. Η μελέτη διεξάγεται με χρήση προσομοίωσης με τη βοήθεια ηλεκτρονικού υπολογιστή. Προτείνεται η χρήση δύο πρωτότυπων μεθόδων αποπολύπλεξης σημάτων πολυπλεγμένων κατά πόλωση με πλεονεκτήματα ως προς την απόδοση, την αξιοπιστία και την ταχύτητα σύγκλισης σε σύγκριση με τις μεθόδους που έχουν προταθεί στη βιβλιογραφία. Στη συνέχεια μελετάται η απόδοση των ηλεκτρονικών εξισωτών ελαχίστου μέσου τετράγωνου (least-mean square) και σταθερής περιβάλλουσας (constant modulus algorithm) στην εξίσωση της χρωματικής διασποράς και της διασποράς τρόπων πόλωσης, τόσο μεμονωμένα, όσο και από κοινού. Στη μελέτη μας συμπεριλαμβάνουμε το θόρυβο φάσης και την ενδιάμεση συχνότητα, αίροντας αντίστοιχες απλοποιήσεις που συνήθως γίνονται στη βιβλιογραφία. Ακολούθως αναφερόμαστε στο πρόβλημα του εκφυλισμού του πίνακα συντελεστών των εξισωτών ελάχιστου μέσου τετραγώνου και σταθερής περιβάλλουσας παρουσία έντονης διεξασθένησης. Ο πίνακας συντελεστών στον οποίο έχει συγκλίνει ο εξισωτής ονομάζεται εκφυλισμένος όταν παράγεται η ίδια απεσταλμένη ακολουθία συμβόλων και στις δύο εξόδους του εξισωτή. Προτείνουμε τη χρήση του πολυχρηστικού εξισωτή σταθερής περιβάλλουσας (multiuser constant modulus algorithm equalizer). Η λύση που προτείνεται έχει πλεονεκτήματα αξιοπιστίας και απλότητας σε σχέση με αντίστοιχες προτάσεις στη βιβλιογραφία και αποδεικνύεται η άριστη απόδοσή της. Στη συνέχεια, γίνεται αναφορά στο φαινόμενο της ανισοσταθμίας ορθογωνιότητας που παρατηρείται στα οπτικά συστήματα με σύμφωνους δέκτες και αποτελεί ένα φαινόμενο το οποίο κατά κανόνα παραβλέπεται στις μελέτες της βιβλιογραφίας και αποδεικνύεται το ότι οι συμβατικοί ηλεκτρονικοί εξισωτές δεν μπορούν να το αντιμετωπίσουν. Τέλος, παραθέτουμε αποτελέσματα από την επεξεργασία πραγματικών πειραματικών δεδομένων για την επαλήθευση των συμπερασμάτων που προέκυψαν θεωρητικά.

scholarly journals A Simple and Robust Equalization Algorithm for Variable Modulation Systems

Electronics ◽  
2021 ◽  
Vol 10 (20) ◽  
pp. 2496
Author(s):  
Wanru Hu ◽  
Zhugang Wang ◽  
Ruru Mei ◽  
Meiyan Lin
Keyword(s):  
Adaptive Equalization ◽  
Mean Square ◽  
Least Mean Square ◽  
Constant Modulus ◽  
Phase Shift Keying ◽  
Constant Modulus Algorithm ◽  
Training Sequences ◽  
Shift Keying ◽  
The Stability ◽  
Variable Modulation

This paper proposes a simple and robust variable modulation-decision-directed least mean square (VM-DDLMS) algorithm for reducing the complexity of conventional equalization algorithms and improving the stability of variable modulation (VM) systems. Compared to conventional adaptive equalization algorithms, known information was used as training sequences to reduce the bandwidth consumption caused by inserting training sequences; compared with conventional blind equalization algorithms, the parameters and decisions of the equalizer were determinate, which was conducive to a stable equalization performance. The simulation and implementation results show that the proposed algorithm has a better bit error rate (BER) performance than that of the constant modulus algorithm (CMA) and modified constant modulus algorithm (MCMA) while maintaining the same level of consumption of hardware resources. Compared to the conventional decision-directed least mean square (DDLMS) algorithm, the proposed algorithm only needs to make quadrature phase shift keying (QPSK) symbol decisions, which reduces the computational complexity. In parallel 11th-order equalization algorithms, the operating frequency of VM-DDLMS can reach up to 333.33 MHz.

scholarly journals Performance of Beamforming for Smart Antenna using Traditional LMS Algorithm for Various Parameters

2021 ◽  
Vol 15 ◽  
pp. 8-13
Author(s):  
Vishal V. Sawant ◽  
Mahesh Chavan
Keyword(s):  
Smart Antenna ◽  
Minimum Mean Square Error ◽  
Sensor Arrays ◽  
Weight Vector ◽  
Adaptive Signal Processing ◽  
Lms Algorithm ◽  
Beam Forming ◽  
Mean Square ◽  
Least Mean Square ◽  
Two Factors

Adaptive signal processing sensor arrays, known also as smart antennas .The smart antenna adaptive algorithms achieve the best weight vector for beam forming by iterative means. The Least Mean Square (LMS) algorithm, is an adaptive algorithm .LMS incorporates an iterative procedure that makes successive corrections to the weight vector in the direction of the negative of the gradient vector which eventually leads to the minimum mean square error. Beam forming is directly determined by the two factors. The performance of the traditional LMS algorithm for different parameters is analysed in this paper. This algorithm can be applied to beam forming with the software Matlab. The result obtain can achieve faster convergence and lower steady state error. The algorithms can be simulated in MATLAB 7.10 version.

scholarly journals An Effective Adaptive Combination Strategy for Distributed Learning Network

2021 ◽  
Vol 11 (12) ◽  
pp. 5723
Author(s):  
Chundong Xu ◽  
Qinglin Li ◽  
Dongwen Ying
Keyword(s):  
Minimum Variance ◽  
Iteration Scheme ◽  
Estimation Problem ◽  
Lms Algorithm ◽  
Unbiased Estimation ◽  
Mean Square ◽  
Least Mean Square ◽  
Combination Strategy ◽  
Adaptive Combination ◽  
Diffusion Networks

In this paper, we develop a modified adaptive combination strategy for the distributed estimation problem over diffusion networks. We still consider the online adaptive combiners estimation problem from the perspective of minimum variance unbiased estimation. In contrast with the classic adaptive combination strategy which exploits orthogonal projection technology, we formulate a non-constrained mean-square deviation (MSD) cost function by introducing Lagrange multipliers. Based on the Karush–Kuhn–Tucker (KKT) conditions, we derive the fixed-point iteration scheme of adaptive combiners. Illustrative simulations validate the improved transient and steady-state performance of the diffusion least-mean-square LMS algorithm incorporated with the proposed adaptive combination strategy.

Convergence analysis of Bessel beamformer and its comparison with LMS in adaptive array system

2015 ◽  
Vol 34 (3) ◽  
pp. 952-961 ◽  
Author(s):  
M. Yasin ◽  
Pervez Akhtar
Keyword(s):  
Theoretical Model ◽  
Convergence Analysis ◽  
Digital Signal Processor ◽  
Wiener Filter ◽  
Digital Signal ◽  
Lms Algorithm ◽  
Mean Square ◽  
Least Mean Square ◽  
Content Type ◽  
Convergence Performance

Purpose – The purpose of this paper is to analyze the convergence performance of Bessel beamformer, based on the design steps of least mean square (LMS) algorithm, can be named as Bessel LMS (BLMS) algorithm. Its performance is compared in adaptive environment with LMS in terms of two important performance parameters, namely; convergence and mean square error. The proposed BLMS algorithm is implemented on digital signal processor along with antenna array to make it smart in wireless sensor networks. Design/methodology/approach – Convergence analysis is theoretically developed and verified through MatLab Software. Findings – Theoretical model is verified through simulation and its results are shown in the provided table. Originality/value – The theoretical model can obtain validation from well-known result of Wiener filter theory through principle of orthogonality.

An Improved ZA-LMS Algorithm for Sparse System Identification with Variable Sparsity

2014 ◽  
Vol 602-605 ◽  
pp. 2415-2419 ◽  
Author(s):  
Hui Luo ◽  
Yun Lin ◽  
Qing Xia
Keyword(s):  
System Identification ◽  
Impulse Response ◽  
Lms Algorithm ◽  
Mean Square ◽  
Least Mean Square ◽  
Sparse System ◽  
Sparse System Identification ◽  
Least Mean Square Algorithm ◽  
Improved Algorithm

The standard least mean square algorithm does not consider the sparsity of the impulse response,and the performs of the ZA-LMS algorithm deteriorates ,as the degree of system sparsity reduces or non-sparse . Concerning this issue ,the ZA-LMS algorithm is studied and modified in this paper to improve the performance of sparse system identification .The improved algorithm by modify the zero attraction term, which attracts the coefficients only in a certain range (the “inactive” taps), thus have a good performance when the sparsity decreases. The simulations demonstrate that the proposed algorithm significantly outperforms then the ZA-LMS with variable sparisity.

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