An Improved Unambiguous Tracking Technique for CBOC Signals

2014 ◽  
Vol 571-572 ◽  
pp. 853-857
Author(s):  
Hao Liu ◽  
Bing Bing Li ◽  
Zhao Tong ◽  
Yong Tao Hui ◽  
Xing Wang Zhong
Keyword(s):  
Correlation Function ◽  
Autocorrelation Function ◽  
Correlation Functions ◽  
Tracking Performance ◽  
Main Peak ◽  
Two Stage ◽  
Short Delay ◽  
Second Stage ◽  
Tracking Technique ◽  
Unambiguous Tracking

The autocorrelation function of Composite BOC(CBOC) signals has many side-peaks, which leads to the ambiguous problem. To solve this problem, an improved two-stage unambiguous tracking scheme is proposed in this paper. In the first stage, an unambiguous correlation function with narrow main peak is constructed by combining four out of twelve sub-correlation functions. In the second stage, by adding the rest of sub-correlation functions, the final correlation function with sharper and higher main-peak is developed based on the preparatory function from the first step. Numerical results demonstrate that compared to the original methods, the proposed scheme has a better tracking performance and can effectively suppress the short delay multipath.

A Novel Unambiguous Correlation Function with a High and Sharp Main-Peak for BOC Signal Tracking

2013 ◽  
Vol 479-480 ◽  
pp. 865-869
Author(s):  
Youngseok Lee ◽  
Seong Ro Lee ◽  
Seungsoo Yoo ◽  
Jaewoo Lee ◽  
Jeongyoon Shim ◽  
...  
Keyword(s):  
Correlation Function ◽  
Standard Deviation ◽  
Correlation Functions ◽  
Partial Correlation ◽  
Tracking Error ◽  
Tracking Performance ◽  
Main Peak ◽  
Binary Offset Carrier ◽  
Signal Tracking ◽  
Error Standard Deviation

In this paper, we propose a novel unambiguous correlation function with a high and sharp main-peak for binary offset carrier (BOC) signal tracking. First, we construct a correlation function with a low and narrow main-peak using partial correlation functions. Then, we generate an unambiguous correlation function with a high and sharp main-peak via combinations of the correlation function with the partial correlation functions. From numerical results, it is observed that the proposed unambiguous correlation function with a high and sharp main-peak offers a better tracking performance than the conventional correlation functions with a low and flat main-peak in terms of the tracking error standard deviation.

Unambiguous Tracking Technique Based on Combined Correlation Functions for Sine BOC Signals

2018 ◽  
Vol 72 (1) ◽  
pp. 140-154 ◽  
Author(s):  
Tian Li ◽  
Zuping Tang ◽  
Jiaolong Wei ◽  
Zhihui Zhou ◽  
Boyi Wang
Keyword(s):  
Correlation Function ◽  
Correlation Functions ◽  
Tracking Accuracy ◽  
Binary Offset Carrier ◽  
Tracking Technique ◽  
Positive Side ◽  
Unambiguous Tracking ◽  
Shift Keying ◽  
Local Reference ◽  
Significant Performance

A new unambiguous tracking technique based on combined correlation functions for sine Binary Offset Carrier (BOC) signals is proposed in this paper. The key to this method is to exploit two types of local reference signals: the BOC signal and a linear combination of a series of BOC signals with different delays. They are both correlated with the received signals. Then, a correlation function without any positive side peaks is obtained by multiplying the two correlation results to make tracking completely unambiguous. Theoretical analysis and simulation in the tracking stage show that the proposed method has the best code tracking accuracy among the method tracking BOC signals like Binary Phase-Shift Keying signals (BPSK-LIKE), the Pseudo correlation function based Unambiguous Delay Lock Loop (PUDLL), Symmetrical Pulse Ambiguity Removing (SPAR) technique, the method proposed by Shen Feng (SF) and the two methods proposed by Yan Tao (YT-V1 and YT-V2). In multipath environments, the proposed method has the best anti-multipath performance of all the tracking methods mentioned above. In conclusion, the proposed method can completely eliminate ambiguity and has significant performance advantages compared with the methods mentioned above.

A Side-Peak Cancellation Scheme for Unambiguous BOC Signal Tracking

2015 ◽  
Vol 764-765 ◽  
pp. 462-465
Author(s):  
Keun Hong Chae ◽  
Hua Ping Liu ◽  
Seok Ho Yoon
Keyword(s):  
Correlation Function ◽  
Correlation Functions ◽  
Numerical Results ◽  
Tracking Performance ◽  
Side Peak ◽  
Signal Tracking ◽  
Partial Correlations

In this paper, we propose a side-peak cancellation scheme for unambiguous BOC signal tracking. We obtain partial correlations using a pulse model of a BOC signal, and then, we finally obtain an unambiguous correlation function based on the partial correlations. The proposed correlation function is confirmed from numerical results to provide an improved tracking performance over the conventional correlation functions.

Pseudo-Correlation-Function-Based Unambiguous Tracking Technique for Sine-BOC Signals

2010 ◽  
Vol 46 (4) ◽  
pp. 1782-1796 ◽  
Author(s):  
Zheng Yao ◽  
Xiaowei Cui ◽  
Mingquan Lu ◽  
Zhenming Feng ◽  
Jun Yang
Keyword(s):  
Correlation Function ◽  
Tracking Technique ◽  
Unambiguous Tracking

An Enhanced Two Stage MMSE Equalizer for Coded FBMC/OQAM Systems

2019 ◽  
Vol 10 (1) ◽  
pp. 69-82 ◽  
Author(s):  
Mohammad Rizk Assaf ◽  
Abdel-Nasser Assimi
Keyword(s):  
Error Propagation ◽  
Channel Model ◽  
Error Correcting Codes ◽  
Two Stage ◽  
Probability Of Error ◽  
Second Stage ◽  
Different Types ◽  
Mmse Equalizer ◽  
And Performance ◽  
Ici Cancellation

In this article, the authors investigate the enhanced two stage MMSE (TS-MMSE) equalizer in bit-interleaved coded FBMC/OQAM system which gives a tradeoff between complexity and performance, since error correcting codes limits error propagation, so this allows the equalizer to remove not only ICI but also ISI in the second stage. The proposed equalizer has shown less design complexity compared to the other MMSE equalizers. The obtained results show that the probability of error is improved where SNR gain reaches 2 dB measured at BER compared with ICI cancellation for different types of modulation schemes and ITU Vehicular B channel model. Some simulation results are provided to illustrate the effectiveness of the proposed equalizer.

scholarly journals From correlation functions to event shapes in QCD

2021 ◽  
Vol 2021 (2) ◽  
Author(s):  
D. Chicherin ◽  
J. M. Henn ◽  
E. Sokatchev ◽  
K. Yan
Keyword(s):  
Correlation Function ◽  
Correlation Functions ◽  
Event Shape ◽  
Proof Of Concept ◽  
Yang Mills ◽  
Point Correlation ◽  
Point Correlation Function ◽  
Event Shapes ◽  
A Charge ◽  
Conserved Currents

Abstract We present a method for calculating event shapes in QCD based on correlation functions of conserved currents. The method has been previously applied to the maximally supersymmetric Yang-Mills theory, but we demonstrate that supersymmetry is not essential. As a proof of concept, we consider the simplest example of a charge-charge correlation at one loop (leading order). We compute the correlation function of four electromagnetic currents and explain in detail the steps needed to extract the event shape from it. The result is compared to the standard amplitude calculation. The explicit four-point correlation function may also be of interest for the CFT community.

Personalised attraction recommendation for enhancing topic diversity and accuracy

2021 ◽  
pp. 016555152199980
Author(s):  
Yuanyuan Lin ◽  
Chao Huang ◽  
Wei Yao ◽  
Yifei Shao
Keyword(s):  
Real World ◽  
Information Overload ◽  
Two Stage ◽  
Misclassification Cost ◽  
Second Stage ◽  
Low Visibility ◽  
Recommendation Diversity ◽  
Optimisation Model ◽  
Definition Of ◽  
Improved Methods

Attraction recommendation plays an important role in tourism, such as solving information overload problems and recommending proper attractions to users. Currently, most recommendation methods are dedicated to improving the accuracy of recommendations. However, recommendation methods only focusing on accuracy tend to recommend popular items that are often purchased by users, which results in a lack of diversity and low visibility of non-popular items. Hence, many studies have suggested the importance of recommendation diversity and proposed improved methods, but there is room for improvement. First, the definition of diversity for different items requires consideration for domain characteristics. Second, the existing algorithms for improving diversity sacrifice the accuracy of recommendations. Therefore, the article utilises the topic ‘features of attractions’ to define the calculation method of recommendation diversity. We developed a two-stage optimisation model to enhance recommendation diversity while maintaining the accuracy of recommendations. In the first stage, an optimisation model considering topic diversity is proposed to increase recommendation diversity and generate candidate attractions. In the second stage, we propose a minimisation misclassification cost optimisation model to balance recommendation diversity and accuracy. To assess the performance of the proposed method, experiments are conducted with real-world travel data. The results indicate that the proposed two-stage optimisation model can significantly improve the diversity and accuracy of recommendations.

scholarly journals Two-stage multi-tasking transform framework for large-scale many-objective optimization problems

2021 ◽  
Author(s):  
Lu Chen ◽  
Handing Wang ◽  
Wenping Ma
Keyword(s):  
Large Scale ◽  
Original Problem ◽  
Optimization Problems ◽  
Reference Points ◽  
Optimization Strategy ◽  
Two Stage ◽  
Decision Space ◽  
Second Stage ◽  
Decision Variables ◽  
Objective Space

AbstractReal-world optimization applications in complex systems always contain multiple factors to be optimized, which can be formulated as multi-objective optimization problems. These problems have been solved by many evolutionary algorithms like MOEA/D, NSGA-III, and KnEA. However, when the numbers of decision variables and objectives increase, the computation costs of those mentioned algorithms will be unaffordable. To reduce such high computation cost on large-scale many-objective optimization problems, we proposed a two-stage framework. The first stage of the proposed algorithm combines with a multi-tasking optimization strategy and a bi-directional search strategy, where the original problem is reformulated as a multi-tasking optimization problem in the decision space to enhance the convergence. To improve the diversity, in the second stage, the proposed algorithm applies multi-tasking optimization to a number of sub-problems based on reference points in the objective space. In this paper, to show the effectiveness of the proposed algorithm, we test the algorithm on the DTLZ and LSMOP problems and compare it with existing algorithms, and it outperforms other compared algorithms in most cases and shows disadvantage on both convergence and diversity.

scholarly journals A Two-Stage Mono- and Multi-Objective Method for the Optimization of General UPS Parallel Manipulators

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 543
Author(s):  
Alejandra Ríos ◽  
Eusebio E. Hernández ◽  
S. Ivvan Valdez
Keyword(s):  
Genetic Algorithm ◽  
Performance Metrics ◽  
Tracking Error ◽  
Parallel Manipulators ◽  
Optimization Method ◽  
Statistical Hypothesis ◽  
Two Stage ◽  
Multi Objective ◽  
Second Stage ◽  
Conflicting Objectives

This paper introduces a two-stage method based on bio-inspired algorithms for the design optimization of a class of general Stewart platforms. The first stage performs a mono-objective optimization in order to reach, with sufficient dexterity, a regular target workspace while minimizing the elements’ lengths. For this optimization problem, we compare three bio-inspired algorithms: the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO), and the Boltzman Univariate Marginal Distribution Algorithm (BUMDA). The second stage looks for the most suitable gains of a Proportional Integral Derivative (PID) control via the minimization of two conflicting objectives: one based on energy consumption and the tracking error of a target trajectory. To this effect, we compare two multi-objective algorithms: the Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D) and Non-dominated Sorting Genetic Algorithm-III (NSGA-III). The main contributions lie in the optimization model, the proposal of a two-stage optimization method, and the findings of the performance of different bio-inspired algorithms for each stage. Furthermore, we show optimized designs delivered by the proposed method and provide directions for the best-performing algorithms through performance metrics and statistical hypothesis tests.

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