Iterative Receiver Based on SAGE Algorithm for Crosstalk Cancellation in Upstream Vectored VDSL

ISRN Communications and Networking ◽

10.5402/2011/586574 ◽

2011 ◽

Vol 2011 ◽

pp. 1-15 ◽

Cited By ~ 7

Author(s):

S. M. Zafaruddin ◽

Shankar Prakriya ◽

Surendra Prasad

Keyword(s):

Expectation Maximization ◽

Time Complexity ◽

Rate Performance ◽

Iterative Receiver ◽

Suggested Approach ◽

Crosstalk Cancellation ◽

Single User ◽

Receiver Complexity ◽

Linear Receivers ◽

Alien Crosstalk

We propose the use of an iterative receiver based on the Space Alternating Generalized Expectation maximization (SAGE) algorithm for crosstalk cancellation in upstream vectored VDSL. In the absence of alien crosstalk, we show that when initialized with the frequency-domain equalizer (FEQ) output, the far-end crosstalk (FEXT) can be cancelled with no more real-time complexity than the existing linear receivers. In addition, the suggested approach does not require offline computation of the channel inverse and thus reduces the receiver complexity. In the presence of alien crosstalk, there is a significant gap between the rate performance of the linear receivers as compared with the single-user bound (SUB). The proposed receiver is shown to successfully bridge this gap while requiring only a little extracomplexity. Computer simulations are presented to validate the analysis and confirm the performance of the proposed receiver.

On error rate performance of multi-cell massive MIMO systems with linear receivers

Physical Communication ◽

10.1016/j.phycom.2015.10.002 ◽

2016 ◽

Vol 20 ◽

pp. 123-132 ◽

Cited By ~ 6

Author(s):

Haiquan Wang ◽

Meijun Zhou ◽

Ruiming Chen ◽

Wei Zhang

Keyword(s):

Error Rate ◽

Massive Mimo ◽

Mimo Systems ◽

Rate Performance ◽

Linear Receivers

Deep Learning-based Codebook Design for Code-Domain Non-Orthogonal Multiple Access Approaching Single-User Bit-Error Rate Performance

IEEE Transactions on Cognitive Communications and Networking ◽

10.1109/tccn.2021.3130308 ◽

2021 ◽

pp. 1-1

Author(s):

Minsig Han ◽

Ameha T. Abebe ◽

Chung G. Kang

Keyword(s):

Deep Learning ◽

Bit Error Rate ◽

Error Rate ◽

Multiple Access ◽

Rate Performance ◽

Codebook Design ◽

Code Domain ◽

Single User

Alien Crosstalk Cancellation for Multipair Digital Subscriber Line Systems

EURASIP Journal on Advances in Signal Processing ◽

10.1155/asp/2006/16828 ◽

2006 ◽

Vol 2006 (1) ◽

Cited By ~ 17

Author(s):

George Ginis ◽

Chia-Ning Peng

Keyword(s):

Digital Subscriber Line ◽

Subscriber Line ◽

Crosstalk Cancellation ◽

Alien Crosstalk

Modeling Intraindividual Variability in Three-Level Multilevel Models

Methodology ◽

10.1027/1614-2241/a000150 ◽

2018 ◽

Vol 14 (3) ◽

pp. 95-108 ◽

Cited By ~ 4

Author(s):

Steffen Nestler ◽

Katharina Geukes ◽

Mitja D. Back

Keyword(s):

Multilevel Model ◽

Multilevel Models ◽

Mixed Effects ◽

Repeated Measurements ◽

Scale Model ◽

Suggested Approach ◽

Psychological Study ◽

Level Data ◽

Ecological Momentary ◽

Momentary Assessment

Abstract. The mixed-effects location scale model is an extension of a multilevel model for longitudinal data. It allows covariates to affect both the within-subject variance and the between-subject variance (i.e., the intercept variance) beyond their influence on the means. Typically, the model is applied to two-level data (e.g., the repeated measurements of persons), although researchers are often faced with three-level data (e.g., the repeated measurements of persons within specific situations). Here, we describe an extension of the two-level mixed-effects location scale model to such three-level data. Furthermore, we show how the suggested model can be estimated with Bayesian software, and we present the results of a small simulation study that was conducted to investigate the statistical properties of the suggested approach. Finally, we illustrate the approach by presenting an example from a psychological study that employed ecological momentary assessment.

Supplemental Material for Resolving the Latent Structure of Schizophrenia Endophenotypes Using Expectation-Maximization-Based Finite Mixture Modeling

Journal of Abnormal Psychology ◽

10.1037/0021-843x.116.1.16.supp ◽

2007 ◽

Keyword(s):

Expectation Maximization ◽

Mixture Modeling ◽

Finite Mixture ◽

Latent Structure ◽

Finite Mixture Modeling

Ordered subset expectation maximization algorithm for image reconstruction applied to zero-flow or low-flow mimicking brain phantom

Journal of Cerebral Blood Flow & Metabolism ◽

10.1038/sj.jcbfm.9591524.0678 ◽

2005 ◽

Vol 25 (1_suppl) ◽

pp. S678-S678

Author(s):

Yasuhiro Akazawa ◽

Yasuhiro Katsura ◽

Ryohei Matsuura ◽

Piao Rishu ◽

Ansar M D Ashik ◽

...

Keyword(s):

Image Reconstruction ◽

Expectation Maximization ◽

Expectation Maximization Algorithm ◽

Low Flow ◽

Brain Phantom ◽

Zero Flow

An Efficient Clustering Algorithm Based on Expectation Maximization Algorithm in Wireless Sensor Network

Oct. 17-19, 2017 Dubai (UAE) ◽

10.15242/dirpub.dir1017011 ◽

2018 ◽

Keyword(s):

Wireless Sensor Network ◽

Sensor Network ◽

Expectation Maximization ◽

Clustering Algorithm ◽

Expectation Maximization Algorithm ◽

Wireless Sensor

BS-Cooperation Scheduler for a Multi-Site Single-User MIMO

IEICE Transactions on Communications ◽

10.1587/transcom.e94.b.1025 ◽

2011 ◽

Vol E94-B (4) ◽

pp. 1025-1032

Author(s):

Shoji KANEKO ◽

Masashi FUSHIKI ◽

Masayuki NAKANO ◽

Yoji KISHI

Keyword(s):

Single User

Tomlinson-Harashima Precoding with Substream Permutations Based on the Bit Rate Maximization for Single-User MIMO Systems

IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences ◽

10.1587/transfun.e98.a.1095 ◽

2015 ◽

Vol E98.A (5) ◽

pp. 1095-1104 ◽

Cited By ~ 4

Author(s):

Shigenori KINJO ◽

Shuichi OHNO

Keyword(s):

Mimo Systems ◽

Bit Rate ◽

Rate Maximization ◽

Single User

Recognition of Birds in Blurred and Illumination Images by Local Features

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse/v7i7/0128 ◽

2017 ◽

Vol 7 (7) ◽

pp. 243

Author(s):

Suresha .M ◽

. Sandeep

Keyword(s):

Computer Vision ◽

Time Complexity ◽

Feature Detection ◽

Feature Matching ◽

Fast Algorithms ◽

Local Features ◽

Experimental Demonstration ◽

Harris Corner ◽

Blurred Image ◽

Blurred Images

Local features are of great importance in computer vision. It performs feature detection and feature matching are two important tasks. In this paper concentrates on the problem of recognition of birds using local features. Investigation summarizes the local features SURF, FAST and HARRIS against blurred and illumination images. FAST and Harris corner algorithm have given less accuracy for blurred images. The SURF algorithm gives best result for blurred image because its identify strongest local features and time complexity is less and experimental demonstration shows that SURF algorithm is robust for blurred images and the FAST algorithms is suitable for images with illumination.