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Codebook

About: Codebook is a research topic. Over the lifetime, 8492 publications have been published within this topic receiving 115995 citations.


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Patent
Jes Thyssen1
24 Aug 1999

60 citations

Proceedings ArticleDOI
Arnold Wiliem1, Yongkang Wong1, Conrad Sanderson1, Peter Hobson1, Shaokang Chen1, Brian C. Lovell1 
15 Jan 2013
TL;DR: In this article, a dual-region codebook-based descriptor was combined with the Nearest Convex Hull Classifier to classify human epithelial (HEp-2) cells.
Abstract: The Anti-Nuclear Antibody (ANA) clinical pathology test is commonly used to identify the existence of various diseases. A hallmark method for identifying the presence of ANAs is the Indirect Immunofluorescence method on Human Epithelial (HEp-2) cells, due to its high sensitivity and the large range of antigens that can be detected. However, the method suffers from numerous shortcomings, such as being subjective as well as time and labour intensive. Computer Aided Diagnostic (CAD) systems have been developed to address these problems, which automatically classify a HEp-2 cell image into one of its known patterns (eg., speckled, homogeneous). Most of the existing CAD systems use handpicked features to represent a HEp-2 cell image, which may only work in limited scenarios. In this paper, we propose a cell classification system comprised of a dual-region codebook-based descriptor, combined with the Nearest Convex Hull Classifier. We evaluate the performance of several variants of the descriptor on two publicly available datasets: ICPR HEp-2 cell classification contest dataset and the new SNPHEp-2 dataset. To our knowledge, this is the first time codebook-based descriptors are applied and studied in this domain. Experiments show that the proposed system has consistent high performance and is more robust than two recent CAD systems.

60 citations

Journal ArticleDOI
TL;DR: In this paper, the authors proposed a power domain sparse code multiple access (PSMA) for 5G networks, where the same codebook can be reused in the coverage area of each base station more than one time.
Abstract: In this paper, a new approach for multiple access in the fifth generation (5G) of cellular networks called power domain sparse code multiple access (PSMA) is proposed. In PSMA, we adopt both the power domain and the code domain to transmit multiple users’ signals over a subcarrier simultaneously. In such a model, the same sparse code multiple-access (SCMA) codebook can be used by multiple users, where, for these users, the power domain non-orthogonal multiple access (PD-NOMA) technique is used to send signals non-orthogonally. Although the signal of different SCMA codebooks can be detected orthogonally, the same codebook used by multiple users produces interference over these users. With PSMA, a codebook can be reused in the coverage area of each base station more than one time, which can improve the spectral efficiency. We investigate the signal model as well as the receiver and transmitter of the PSMA method. In the receiver side, we propose a message passing algorithm-based successive interference cancellation detector to detect the signal of each user. To evaluate the performance of PSMA, we consider a heterogeneous cellular network. In this case, our design objective is to maximize the system sum rate of the network subject to some system level and QoS constraints such as transmit power constraints. We formulate the proposed resource allocation problem as an optimization problem and solve it by successive convex approximation techniques. Moreover, we compare PSMA with SCMA and PD-NOMA from the performance and computational complexity perspective. Finally, the effectiveness of the proposed approach is investigated using numerical results. We show that by a reasonable increase in complexity, PSMA can improve the spectral efficiency about 50% compared with SCMA and PD-NOMA.

59 citations

Journal ArticleDOI
TL;DR: In this paper, a radio frequency (RF) lens-embedded massive MIMO system was investigated and the system performance of limited feedback was evaluated by utilizing a technique for generating a suitable codebook for the system.
Abstract: In this paper, we investigate a radio frequency (RF) lens-embedded massive multiple-input multiple-output (MIMO) system and evaluate the system performance of limited feedback by utilizing a technique for generating a suitable codebook for the system. We fabricate an RF lens that operates on a 77-GHz (millimeter-wave) band. Experimental results show a proper value of amplitude gain and an appropriate focusing property. In addition, using a simple numerical technique—beam propagation method—we estimate the power profile of the RF lens and verify its accordance with experimental results. We also design a codebook—multivariance codebook quantization—for limited feedback by considering the characteristics of the RF lens antenna for massive MIMO systems. Numerical results confirm that the proposed system shows significant performance enhancement over a conventional massive MIMO system without an RF lens.

59 citations

Journal ArticleDOI
TL;DR: This paper introduces S-TREE (Self-Organizing Tree), a family of models that use unsupervised learning to construct hierarchical representations of data and online tree-structured vector quantizers and approaches that of GLA while taking less than 10% of computer time.

59 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023217
2022495
2021237
2020383
2019432
2018364