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NOMA codebook optimization by Batch Gradient Descent

IEEE ACCESS 2019年 7卷 117274-117281页

作者： Si, Zhongwei Wen, Shaoguo Dong, Bing Beijing Univ Posts & Telecommun Key Lab Universal Wireless Commun Minist Educ Beijing 100876 Peoples R China

The non-orthogonal multiple access (NOMA) has the potential to improve the spectrum efficiency and the user connectivity compared to the orthogonal schemes. The codebook design is crucial for the the performance of the NOMA system. In this paper, we comprehensively investigate the NOMA codebook design involving the characteristics from multiple signal domains. The minimizing of the pairwise error probability is considered as the target of the optimization. The neural network framework is explored for the optimization, and the mapping functions on the edges are considered as weights. The method of batch gradient descent is applied for optimizing the weights and correspondingly the codebook. The simulation results reveal that with the optimized codebook the error performance is significantly improved compared to the schemes in the literature.

关键词： Batch gradient descent codebook optimization neural network non-orthogonal multiple access pairwise error probability

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Low Complexity Vector Quantization Algorithm for codebook optimization

Low Complexity Vector Quantization Algorithm for Codebook Op...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Hui, Bing Chang, KyungHi Inha Univ Grad Sch IT & T Inchon South Korea

ISBN: (纸本)9781467304375;9781467304368

One of the most attractive research topics about multiple-input multiple-output (MIMO) techniques is interference mitigation with limited feedback. codebook design based on the vector quantization (VQ) algorithms with less quantization error and computational burden is the key for the codebook based precoding. Novel VQ algorithm is proposed in this paper which needs less execution time and less number of iterations to converge than conventional VQ Linde-Buzo-Gray (LBG) algorithm. The discussions and simulation results show that great benefits are achieved by the proposed algorithm.

关键词： vector quantization codebook based precoding MIMO codebook optimization LBG-M

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An Evolutionary Approach for Vector Quantization codebook optimization

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5th International Symposium on Neural Networks

作者： Azevedo, Carlos R. B. Bispo Junior, Esdras L. Ferreira, Tiago A. E. Madeiro, Francisco Alencar, Marcelo S. Univ Catolica Pernambuco Ctr Sci & Technol Pernambuco Brazil Federal Rural Univ Pernambuco Dept Stat & Informat Recife PE Brazil Federal Univ Campina Grande Dept Elect Engn Campinas Brazil

ISBN: (纸本)9783540877318

This paper proposes it hybrid evolutionary algorithm based on an accelerated version of K-means integrated with a modified genetic algorithm (GA) for vector quantization (VQ) codebook optimization. Front simulation results involving image compression based oil VQ, it is observed that the proposed method leads to better codebooks when compared with the conventional one (GA + standard K-means), in the sense that the former leads, to higher peak signal-to-noise ratio (PSNR) results for the reconstructed images. Additionally, it is observed that the proposed method requires fewer GA generations (up to 40%) to achieve the best, PSNR. results produced by the conventional method.

关键词： codebook optimization genetic algorithms accelerated K-means hybrid systems vector quantization image compression

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Base Station Selection and Per-cell codebook optimization for CoMP with Joint Processing

Base Station Selection and Per-cell Codebook Optimization fo...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications

作者： P. Baracca F. Boccardi V. Braun A. Tulino Department of Information Engineering University of Padova Italy Bell Laboratories Alcatel-Lucent

ISBN: (纸本)9781467325660

In cellular networks coordination among base stations (BSs) has been recognized as an important solution to handle inter-cell interference and increase spectral efficiency. In frequency division duplex systems one of the main issue that sensibly degrades the performance of coordinated multipoint (CoMP) transmission techniques is the imperfect channel state information (CSI) due to the limited bandwidth available for the feedback transmission. In this paper we focus on a CoMP scenario with data and CSI sharing among the BSs and we consider a feedback transmission scheme where each user equipment (UE) quantizes the different channels by using codebooks designed for a single-cell scenario. Due to the different propagation characteristics of the channels between a UE and each BS and by considering a constraint on the number of available feedback bits, we propose two practical algorithms depending on the large-scale fading to a) select the subset of BSs from whom the UE prefers to be served and b) optimize the number of feedback bits allocated to each channel. The developed techniques allow a UE to send more feedback bits to the BSs with a stronger signal and numerical results show the merits of the proposed approach.

关键词： codebook optimization CoMP Joint Processing

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Codehook optimization for the Superposition Transmission of Uplink SCMA Systems

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2018年第10期67卷 10112-10117页

作者： Lim, Seung-Chan Park, Hyuncheol Korea Adv Inst Sci & Technol Sch Elect Engn Daejeon 34141 South Korea

For an uplink sparse code multiple access (SCMA) system, a codehook-domain superposition transmission can be applied to increase the multiplexing gain by efficient utilization of the codebooks as multiple access resources. However, the destructive collision of superposed codewords can restrict the performance improvement of the system because of the increasing interlayer interferences. In this paper, we analyze the effects of the interlayer interferences on the bit error rates, and optimize the SCMA codebooks that can mitigate the interlayer interferences. Simulation results show that the optimized codebooks can provide a noticeable gain to improve the performance of uplink SCMA systems applied with superposition transmission.

关键词： Sparse code multiple access superposition transmission inter-layer interference codebook optimization

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Multiple description vector quantization with a coarse lattice

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IEEE TRANSACTIONS ON INFORMATION THEORY 2002年第3期48卷 781-788页

作者： Goyal, VK Kelner, JA Kovacevic, J Digital Fountain Inc Fremont CA 94538 USA Harvard Univ Cambridge MA 02138 USA Bell Labs Lucent Technol Murray Hill NJ 07974 USA

A multiple description (MD) lattice vector quantization technique for two descriptions was recently introduced in which fine and coarse codebooks are both lattices. The encoding begins with quantization to the nearest point in the fine lattice. This encoding is an inherent optimization for the decoder that receives both descriptions;performance can be improved! with little increase in complexity by considering all decoders in the initial encoding step. The altered encoding relies only on the symmetries of the coarse lattice. This allows us to further improve performance without a significant increase in complexity by replacing the fine lattice codebook with a nonlattice codebook that respects many of the symmetries of the coarse lattice. Examples constructed with the two-dimensional (2-D) hexagonal lattice demonstrate large improvement over time sharing between previously known quantizers.

关键词： codebook optimization high-rate source coding lattice vector quantization

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Nearly Doubling the Throughput of Multiuser MIMO Systems Using codebook Tailored Limited Feedback Protocol

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2012年第11期11卷 3921-3931页

作者： Wunder, Gerhard Schreck, Jan Jung, Peter Heinrich Hertz Inst Nachrichtentech Berlin GmbH D-10587 Berlin Germany Alcatle Lucent Bell Labs Crawford Hill NJ USA Tech Univ Berlin Lehrstuhl Informat Theorie & Theoret Informat Tec D-10587 Berlin Germany

We present and analyze a new robust feedback and transmit strategy for multiuser MIMO downlink communication systems, termed Rate Approximation (RA). RA combines the flexibility and robustness needed for reliable communications with the user terminal under a limited feedback constraint. It responds to two important observations. First, it is not so significant to approximate the channel but rather the rate, such that the optimal scheduling decision can be mimicked at the base station. Second, a fixed transmit codebook at the transmitter is often better when therefore the channel state information is more accurate. In the RA scheme the transmit and feedback codebook are separated and user rates are delivered to the base station subject to a controlled uniform error. The scheme is analyzed and proved to have better performance below a certain interference plus noise margin and better behavior than the classical Jindal formula. LTE system simulations sustain the analytic results showing performance gains of up to 50% or 70% compared to zeroforcing when using multiple antennas at the base station and multiple antennas or a single antenna at the terminals, respectively. A new feedback protocol is developed which inherently considers the transmit codebook and which is able to deal with the complexity issue at the terminal.

关键词： LTE multiuser MIMO limited feedback robustness RVQ covering simplex codebook optimization

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Optimized residual vector quantization for efficient approximate nearest neighbor search

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MULTIMEDIA SYSTEMS 2017年第2期23卷 169-181页

作者： Ai, Liefu Yu, Junqing Wu, Zebin He, Yunfeng Guan, Tao Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Peoples R China Anqing Normal Univ Sch Comp & Informat Anqing 246133 Peoples R China Huazhong Univ Sci & Technol Ctr Network & Computat Wuhan 430074 Peoples R China

In this paper, an optimized residual vector quantization-based approach is presented for improving the quality of vector quantization and approximate nearest neighbor search. The main contributions are as follows. Based on residual vector quantization (RVQ), a joint optimization process called enhanced RVQ (ERVQ) is introduced. Each stage codebook is iteratively optimized by the others aiming at minimizing the overall quantization errors. Thus, an input vector is approximated by its quantization outputs more accurately. Consequently, the precision of approximate nearest neighbor search is improved. To efficiently find nearest centroids when quantizing vectors, a non-linear vector quantization method is proposed. The vectors are embedded into 2-dimensional space where the lower bounds of Euclidean distances between the vectors and centroids are calculated. The lower bound is used to filter non-nearest centroids for the purpose of reducing computational costs. ERVQ is noticeably optimized in terms of time efficiency on quantizing vectors when combining with this method. To evaluate the accuracy that vectors are approximated by their quantization outputs, an ERVQ-based exhaustive method for approximate nearest neighbor search is implemented. Experimental results on three datasets demonstrate that our approaches outperform the state-of-the-art methods over vector quantization and approximate nearest neighbor search.

关键词： Approximate nearest neighbor search Vector quantization codebook optimization Filtration

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Multiple description coding by successive quantization

Multiple description coding by successive quantization

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Canadian Conference on Electrical and Computer Engineering

作者： Moradi, Saeed Linder, Tamas Gazor, Saeed Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada Queens Univ Dept Math & Stat Kingston ON K7L 3N6 Canada Queens Univ Dept Elect & Comp Engn Kingston ON K7L 3N6 Canada

ISBN: (纸本)9781424416424

Two structured multiple description (MD) vector quantization schemes with an iterative technique for designing the codebooks and partitions are proposed. The schemes are derived from the recent theoretical work by Chen et al. In the first scheme, the central decoder is formed by the weighted sum of the side codebooks, whereas the second scheme employs the optimum central decoder. The objective of the proposed iterative method is to minimize a Lagrangian cost function (defined as the weighted sum of the central and side distortions) to jointly design the side codebooks and find the associated partitions. The optimal parameters for minimizing the central distortion are also found. Simulations demonstrate that the proposed methods achieve performance close to that of the unstructured, full-search MD quantizer with considerably less complexity and with only a few iterations.

关键词： codebook optimization Lagrangian approach multiple description vector quantization

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Efficient Approximate Nearest Neighbor Search by Optimized Residual Vector Quantization

Efficient Approximate Nearest Neighbor Search by Optimized R...

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12th International Workshop on Content-Based Multimedia Indexing (CBMI)

作者： Ai, Liefu Yu, Junqing Guan, Tao He, Yunfeng Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Peoples R China

ISBN: (纸本)9781479939909

In this paper, an optimized residual vector quantization-based approach is presented for approximate nearest neighbor search. The main contributions are as follows. Built on residual vector quantization (RVQ), a joint optimization process called enhanced RVQ (ERVQ) is introduced. Each stage-codebook is iteratively optimized by the others aiming at minimizing the overall quantization errors. Thus, an input vector is approximated by its quantization outputs more accurately and the precision of approximate nearest neighbor search is improved. To efficiently find nearest centroids when quantizing vectors, a non-linear vector quantization method is proposed. The vectors are embedded into 2-dimensional space where the lower bounds of Euclidean distances between the vectors and centroids are calculated. The lower bound is used to filter non-nearest centroids for the purpose of reducing computational costs. ERVQ is noticeably optimized in terms of time efficiency on quantizing vectors when combining with this method. Experimental results on SIFT and GIST datasets demonstrate that our approaches outperform the state-of-the-art methods in vector quantization and approximate nearest neighbor search.

关键词： approximate nearest neighbor search vector quantization codebook optimization

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