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检索条件"主题词=prediction coding"

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PREDICTIVE QUANTIZATION OF BIT LOADING FOR MIMO TIME-CORRELATED CHANNELS WITH LIMITED FEEDBACK

PREDICTIVE QUANTIZATION OF BIT LOADING FOR MIMO TIME-CORRELA...

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Yuan-Pei Lin Chi-Chang Wu Dept. Electrical Engr. National Chiao Tung Univ. Hsinchu Taiwan

ISBN: (纸本)9781479928941

In this paper we consider variable-rate transmission for time-correlated MIMO (multi-input multi-output) channels with limited feedback. The number of bits loaded on each subchannel of the MIMO system is dynamically assigned according to the current channel condition and fed back to the transmitter. As the channel is time-correlated, so is bit loading. We propose to feedback bit loading using predictive coding, which is known to be a powerful technique for quantizing correlated signals. Assuming the channel is a first-order Gauss-Markov random process, we derive the optimal predictor for the bit loading to be coded. We show that the subchannels prediction errors are approximated Gaussian and thus can be quantized using quantizers designed for Gaussian random variables. Simulations demonstrate that the proposed predictive coding can achieve a very good approximation of the desired transmission rate with a very low feedback rate.

关键词： multiple input multiple output systems Feedback prediction coding subchannel quantizer TRANSMISSION RATE Binary digits Quantization Gauss Error of prediction Drill bits Transmitters loading LOADING

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HYBRID coding OF VISUAL CONTENT AND LOCAL IMAGE FEATURES

HYBRID CODING OF VISUAL CONTENT AND LOCAL IMAGE FEATURES

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IEEE International Conference on Image Processing

作者： Luca Baroffio Matteo Cesana Alessandro Redondi Marco Tagliasacchi Stefano Tubaro Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano

ISBN: (纸本)9781479983407

Distributed visual analysis applications, such as mobile visual search or Visual Sensor Networks (VSNs) require the transmission of visual content on a bandwidth-limited network, from a peripheral node to a processing unit. Traditionally, a "Compress-Then-Analyze" approach has been pursued, in which sensing nodes acquire and encode the pixel-level representation of the visual content, that is subsequently transmitted to a sink node in order to be processed. This approach might not represent the most effective solution, since several analysis applications leverage a compact representation of the content, thus resulting in an inefficient usage of network resources. Furthermore, coding artifacts might significantly impact the accuracy of the visual task at hand. To tackle such limitations, an orthogonal approach named "Analyze-Then-Compress" has been proposed [1]. According to such a paradigm, sensing nodes are responsible for the extraction of visual features, that are encoded and transmitted to a sink node for further processing. In spite of improved task efficiency, such paradigm implies the central processing node not being able to reconstruct a pixel-level representation of the visual content. In this paper we propose an effective compromise between the two paradigms, namely "Hybrid-Analyze-Then-Compress" (HATC) that aims at jointly encoding visual content and local image features. Furthermore, we show how a target tradeoff between image quality and task accuracy might be achieved by accurately allocating the bitrate to either visual content or local features.

关键词： Local features BRISK Image compression Predictive coding Visualization prediction coding Data compression Image compression local image feature Web resources HYBRID Bit rate images Line of nodes

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The Network MIMO Downlink with Per-Antenna Power Constraint: Linear Preequalization vs. Tomlinson-Harashima Precoding

The Network MIMO Downlink with Per-Antenna Power Constraint:...

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WSA 2013;17th International ITG Workshop on Smart Antennas

作者： Robert F. H. Fischer Sebastian Heinrichs Institut fur Nachrichtentechnik Universitat Ulm

Preequalization/precoding schemes for use in network MIMO downlink scenarios are assessed and compared. Whereas conventional linear preequalization and Tomlinson- Harashima precoding (THP) only obey a sum power constraint, in the situation at hand, a per-antenna power constraint is more meaningful. We evaluate the power statistics of classical transmission schemes, which are only designed according to a sum power constraint. Next, we review the optimization of linear preprocessing with per-antenna power constraint and extent the procedure to the optimization of THP. The incorporation of such a restriction into lattice-reduction-aided (LRA) precoding is also addressed. In all cases, the performance of the schemes is covered by means of numerical simulations for a typical network MIMO setting coordinating three base stations and three users. It is shown, that non-linear precoding schemes achieves gains in performance at even lower per-antenna requirements.

关键词： prediction coding pre-equalization BASE STATION multiple input multiple output systems Power (Psychology) Energy sources Downlink Scheme Constraint

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Enhanced Outage Performance With Adaptive Linear Precoding in Cognitive Radio Downlink

Enhanced Outage Performance With Adaptive Linear Precoding i...

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IEEE International Conference on Communications

作者： F. A. Khan C. Masouros T. Ratnarajah ECIT Queen's University of Belfast

ISBN: (纸本)9781457720529

In this paper, we investigate the outage performance of interference aided adaptive linear precoding in the downlink of a multiuser multiple-input-single-output (MISO) overlay cognitive radio (CR) network. While previous research studies on linear precoding techniques in CR network aim to limit or completely cancel the interference to the primary users while achieving maximum downlink throughput of the CR system, we here make use of adaptive linear precoding at the cognitive base station (CBS) to exploit the interference to the primary and the secondary systems. We show by analysis and simulations that the outage performance of the proposed precoding technique is significantly enhanced in comparison to the conventional techniques.

关键词： Cognitive radio Overlay Linear precoding Zero-forcing Outage capacity prediction coding Downlink interference interference Cognitive radio Traditional technology chromium Self tuning

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Energy-Efficient MIMO Precoding and Power Allocation for Device-to-Device Underlay Communication in Cellular Networks

Energy-Efficient MIMO Precoding and Power Allocation for Dev...

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IEEE Vehicular Technology Conference

作者： Bo Chen Minjian Zhao Ming Lei Lei Zhang Department of Information Science and Electronic Engineering Zhejiang University Hangzhou China 310027

ISBN: (纸本)9781479980925

Multiple-input-multiple-output (MIMO) Device-to-Device (D2D) communication underlaying cellular networks can improve user throughout and extend battery life of user equipment. This paper studies MIMO precoding and power allocation schemes for the D2D and cellular uplink communications to improve the energy efficiency of both the D2D and the cellular user (CU). Due to the co-channel interference caused by the shared resources, the precoder design and power allocation of both the D2D transmitter (DTX) and the CU become highly inter-dependent. A distributed cooperative iterative optimization algorithm (DCIOA) is introduced, where either the DTX or the CU cooperatively exchanges the interference information and iteratively updates its optimum precoder and power level. Meanwhile, a centralized stochastic search optimization algorithm using the particle swarm optimization (PSO) method is applied to provide an upper bound. Simulation results show that the performance of the DCIOA is close to that of the centralized algorithm with significant reduction of computation and slight increment of exchange overhead.

关键词： Energy-Efficient D2D Communication MIMO Particle Swarm Optimization Distributed Cooperative Iterative Optimization Energy efficiency multiple input multiple output systems power splitting Cellular networks Particle swarm optimization Copper Device-to-device communication Optimization algorithms prediction coding user facility Battery Life Communication Research Cochannel interference power level

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Two-layer Precoding for Dimensionality Reduction in Massive MIMO

Two-layer Precoding for Dimensionality Reduction in Massive ...

引用

European Signal Processing Conference

作者： Antti Arvola Antti Tolli David Gesbert Centre for Wireless Communications University of Oulu P.O. Box 4500 90014 University of Oulu Finland EURECOM Campus SophiaTech 450 Route des Chappes 06410 Biot Sophia Antipolis France

ISBN: (纸本)9781509018918

Massive MIMO (multiple-input multiple-output) is a promising technology for the upcoming 5G as it provides significant beamforming gains and interference reduction capabilities due to the large number of antennas. However, massive MIMO is computationally demanding, as the high antenna count results in high-dimensional matrix operations when conventional MIMO processing is applied. In this paper, we focus on two-stage digital beamforming, where the beamformer is split into a slow-varying statistics-based outer beamformer and an inner beamformer accounting for fast channel variations. We formulate two two-stage precoding optimization problems: weighted sumrate maximization and minimum user rate maximization for a single-cell downlink system. We also provide different heuristic methods of forming the outer precoder matrix via user channel covariance, while the inner precoder is obtained as a result for the optimization problem. Unlike most previous work, which consider the outer precoder design based on energy maximization and user group location, our aim is to design it to offer a tradeoff between energy maximization and interference reduction, and also take into account the fairness between users. We evaluate the performance of the different heuristic methods as a function of the number of statistical pre-beams and a fixed user angular spread to see the overall effect of complexity reduction on the system sum-rate and minimum user rate. We also evaluate the advantages of different methods in terms of user fairness.

关键词： MIMO Interference Covariance matrices Array signal processing Precoding Antennas Signal to noise ratio multiple input multiple output systems prediction coding signal to noise ratios ANTENNA array signal processing heuristic methods variance covariance matrix disturbance suppression dimensionality reduction Covariance matrix interference

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Robustification and Optimization of a Kalman Filter with Measurement Loss using Linear Precoding

Robustification and Optimization of a Kalman Filter with Mea...

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2009 American Control Conference (ACC 2009)

作者： Rainer Blind Stefan Uhlich Bin Yang Frank Allgower Institute for Systems Theory and Automatic Control University of Stuttgart Germany System Theory and Signal Processing University of Stuttgart Germany

ISBN: (纸本)9781424445233

This paper considers a linear precoding for a Kalman filter which receives the measurements over an erasure channel. We show how to design the precoding matrix that either robustifies the Kalman filter with respect to packet losses or reduces the estimation error. The effectiveness of the proposed method is demonstrated by two examples.

关键词： Kalman filters prediction coding Packet loss erasure channel

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Robust Precoding Methods for Multiuser MISO Wireless Energy Harvesting Systems

Robust Precoding Methods for Multiuser MISO Wireless Energy ...

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IEEE Vehicular Technology Conference

作者： Zhengyu Zhu Kyoung-Jae Lee Zhongyong Wang Zheng Chu Inkyu Lee School of Information Engineering Zhengzhou University Dep. of Electronics and Control Engineering Hanbat National University School of Electrical and Electronic Engineering Newcastle University School of Electrical Engineering Korea University

ISBN: (纸本)9781479980925

We address a new robust optimization problem in a multiuser multiple-input single-output broadcasting system with simultaneous wireless information and power transmission. Assuming that perfect channel-state information (CSI) for all channels is not available at the BS, the uncertainty of the CSI is modeled by an norm-bounded uncertainty set. To optimally design transmit beamforming weights and receive power splitting, an average total transmit power minimization problem is investigated subject to the individual harvested power constraint and the received signal-to-interference-plus-noise ratio constraint at each user. The original design problem is reformulated to a relaxed semidefinite program, and then two different approaches based on convex programming are proposed, which can be solved efficiently by the interior point algorithm. Interestingly, we show that the semidefinite relaxation (SDR) is tight. Numerical results are provided to validate the robustness of the proposed algorithms.

关键词： Robust Precoding Methods Multiuser MISO Wireless Energy Harvesting Systems CSI multiple-input single-output convex programming power transmission wireless prediction coding energy harvesting Not Available Broadcasting system Robustness Interior point algorithm ideal channel

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POKEMON: A non-linear beamforming algorithm for 1-bit massive MIMO

POKEMON: A non-linear beamforming algorithm for 1-bit massiv...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Oscar Castaneda Tom Goldstein Christoph Studer School of ECE Cornell University Ithaca NY United States of America Department of CS University of Maryland College Park United States of America

ISBN: (纸本)9781509041183

One-bit quantization at the base-station (BS) of a massive multiple-input multiple-output (MIMO) wireless system enables significant power and cost savings. While the 1-bit uplink (users communicate to BS) has gained significant attention, the downlink (BS transmits to users) is far less studied. In this paper, we propose a novel, computationally-efficient 1-bit beamforming algorithm referred to as POKEMON (short for PrOjected downlinK bEaMfOrmiNg), which-after its convolution with the MIMO channel matrix-minimizes multi-user interference (a.k.a. spatial leakage). Our algorithm builds upon the biconvex relaxation (BCR) framework, which efficiently approximates the optimal 1-bit beamforming problem that is of combinatorial nature. Our simulation results show that POKEMON significantly outperforms linear beamformers followed by 1-bit quantization in terms of error-rate performance and recent non-linear beamformers in terms of complexity.

关键词： Massive MIMO beamforming precoding quantization biconvex relaxation alternating optimization Beamforming 1-bit Quantization prediction coding multiple input multiple output systems Bahamas

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PSK Precoding in Multi-User MISO Systems

PSK Precoding in Multi-User MISO Systems

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WSA 2017;21th International ITG Workshop on Smart Antennas

作者： Andreas Noll Hela Jedda Josef Nossek

We consider the downlink scenario of multi-user multiple-input-single-output (MU-MISO) communication systems with constant envelope (CE) signals emitted from each antenna. This results in energy efficient power amplifiers (PAs). We propose a holistic CE precoding scheme based on the symbol-wise minimum squared error (SMSE) criterion. Additionally, we analyze the distortions introduced by low-resolution quantization to PSK for higher energy efficiency reasons. We present three solution algorithms and examine their performance to decide for the best pick for different quantization resolutions. Our results show that good performance can be achieved with minimal loss compared to an ideal unquantized case. Finally, we analyze and discuss the results and consider the overall complexity of the precoder as well as implementation issues.

关键词： PS-K Phase shift keying prediction coding Energy efficiency multiple-input single-output high energy efficiency Quantization cerium multi-user

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