Data Rate Reduction Research Articles

Data reduction algorithm based on curvature and topology control for radar simulation in maritime simulator

This paper presents a data reduction algorithm to increase the efficiency of radar simulation. The features of artificial and natural shoreline data are analyzed on the basis of original shoreline data, and the characteristic points of shoreline data are extracted on the whole by identifying the direction and curvature of the vector shorelines and using the topology controlling algorithm. Characteristic points of shoreline data are also extracted locally using an optimization algorithm of area loss ratio control. Therefore, all data points that represent shoreline features are extracted as the reduction result. Theoretical analysis of the results indicates that the proposed algorithm has a high data reduction rate. Moreover, the reduced data retains the shoreline's geometric features and fits well with the shoreline. Further, the accuracy analysis results show that the geometric accuracy of the algorithm is sufficiently precise for radar simulation.

Survey of ICIC techniques in LTE networks under various mobile environment parameters

LTE networks' main challenge is to efficiently use the available spectrum, and to provide satisfying quality of service for mobile users. However, using the same bandwidth among adjacent cells leads to occurrence of Inter-cell Interference especially at the cell-edge. Basic interference mitigation approaches consider bandwidth partitioning techniques between adjacent cells, such as frequency reuse of factor m schemes, to minimize cell-edge interference. Although SINR values are improved, such techniques lead to significant reduction in the maximum achievable data rate. Several improvements have been proposed to enhance the performance of frequency reuse schemes, where restrictions are made on resource blocks usage, power allocation, or both. Nevertheless, bandwidth partitioning methods still affect the maximum achievable throughput. In this proposal, we intend to perform a comprehensive survey on Inter-Cell Interference Coordination (ICIC) techniques, and we study their performance while putting into consideration various design parameters. This study is implemented throughout intensive system level simulations under several parameters such as different network loads, radio conditions, and user distributions. Simulation results show the advantages and the limitations of each technique compared to frequency reuse-1 model. Thus, we are able to identify the most suitable ICIC technique for each network scenario.

All-Analogue Real-Time Broadband Filter Bank Multicarrier Optical Communications System

This paper studies the key aspects of an optical link which transmits a broadband microwave filter bank multicarrier (FBMC) signal. The study is presented in the context of creating an all-analogue real-time multigigabit orthogonal frequency division multiplexing electro-optical transceiver for short range and high-capacity data center networks. Passive microwave filters are used to perform the pulse shaping of the bit streams, allowing an orthogonal transmission without the necessity of digital signal processing (DSP). Accordingly, a cyclic prefix that would cause a reduction in the net data rate is not required. An experiment consisting of three orthogonally spaced 2.7 Gbaud quadrature phase shift keyed subchannels demonstrates that the spectral efficiency of traditional DSP-less subcarrier multiplexed links can be potentially doubled. A sensitivity of −29.5 dBm is achieved in a 1-km link.

Energy Efficient Cooperative Communication with Grouped Relay in MB-OFDM for UWB Systems

Ultra Wide Band (UWB) technology is a fast emerging technology for short distance wireless communication. UWB plays a preeminent role in the short range wireless systems, due to the advantages of high speed, low power consumption and very high security. Methods/Statistical Analysis: With cooperative communication as a decisive member in its side this paper proposes cooperative MB-OFDM communication using effective grouped relays in multichannel with use of Dual Carrier Modulation (DCM) for UWB systems. We can attain maximum diversity by using simple Maximum Likelihood (ML) receiver without reduction of data rate as its found using almounti coding which is most used to provide diversity in cooperative communication. Findings: The Proposed method’s resulting diversity is observed using outage probability as a basic parameter and also how the outage probability varies in accordance to threshold power. Application/Improvements: The results shows an improved BER versus SNR with effect of CFO is considered and the improvement in channel capacity and data rate of various different modulation schemes is obtained by varying SNR and distance.

Joint Power and Rate Control for Device-to-Device Communications in Cellular Systems

This paper investigates device-to-device (D2D) communication nested in a cellular network, where a pair of D2D users directly exchanges their information using the uplink frequency band of the cellular network. When the D2D user treats the interference from the cellular user as noise, power control at the cellular user is optimal for maximizing the rate of the cellular user while controlling the interference to the D2D user. However, if the D2D user can perform successive interference cancelation (SIC), the cellular user needs to adjust both transmit power and rate to maximize its rate, because the decodability of the interfering signals at the D2D user depends not only on the signal power but also on the rate of the cellular user. To control the interference from the cellular user, we propose a joint transmit power and rate control scheme at the cellular user. Forcing the cellular user to transmit with a reduced data rate compared with the maximum possible rate, given its transmit power, the proposed joint power and rate control scheme efficiently enables SIC at the D2D user. To reduce the computational complexity, we also propose a near-optimal scheme that employs either power control or rate control depending on the channel conditions.

A practical in-home illumination consideration to reduce data rate fluctuation in visible light communication

Visible light communication based on LED has attracted more and more attention. As the primary function of LED luminaries is optimized for lighting and illumination, it challenges the communication properties of VLC. An investigation based on different in-home illumination conditions using commercially available whitelight LED luminaries to optimize both illumination and communication is highly desirable. In this work, we investigate joint illumination and communication systems to provide an in-home lighting and VLC system. We first focus on the performance constraints set by illumination properties and discuss lighting conditions using different kinds of commercially available luminaries, beam angles, and LED lamp arrangements, and consider reflections off different wall materials. Then we propose and experimentally demonstrate a white-light phosphor-based LED adaptive data rate VLC system. Finally, the achievable data rates of a joint illumination and VLC system are discussed based on the experimental results, and an environment with reduced VLC data rate fluctuation can be achieved.

AGP–NCS Scheme for PAPR Reduction

In this paper, a combinational method is proposed for peak-to-average power ratio reduction in orthogonal frequency division multiplexing systems using approximate gradient-project with null-subcarriers switching (AGP---NCS) scheme. The key idea of the proposed method is to generate a dynamically extended outer constellation points using AGP method with exploiting the concept of NCS process. The proposed method substantially reduces peak-to-average power without sacrificing the bit error rate. Moreover, proposed scheme requires no channel side information during transmission, therefore shows no reduction in data rate. The simulation results of proposed method show a better performance when compared with other methods.

Rate Adaptation Based on Exposure Assessment Using Rectenna Output for WLAN Station Powered with Microwave Power Transmission

This paper proposes a rate adaptation scheme (RAS) for a wireless local area network (WLAN) station powered with microwave power transmission (MPT). A WLAN station attempting to transmit data frames when exposed to microwave radiation for MPT, experiences a reduction in the physical (PHY) layer data rate because frames are lost even when the carrier sense mechanism is used. The key idea of the proposed scheme is to utilize the output of the rectenna used for receiving microwave power. Using rectenna output, a WLAN station based on the proposed scheme assesses whether the station is exposed to microwave radiation for MPT. Then, using historical data corresponding to the assessment result, the station selects an appropriate PHY data rate. The historical data are obtained from previous transmission results, e.g., historical data pertaining to the data frame loss ratio. The proposed scheme was implemented and verified through an experiment. Experimental results showed that the proposed scheme prevents the reduction in the PHY data rate, which is caused by the use of historical data stored in a single memory. Thus, the proposed scheme leads to an improvement in the WLAN throughput. key words: wireless local area network, rate adaptation, microwave power transmission, rectenna

An Adaptive Recovery Method in Compressed Sensing of Extracellular Neural Recording

A novel adaptive recovery method in the emerging compressed sensing theory is described and applied to extracellular neural recordings in order to reduce data rate in wireless neural recording systems. To strike a balance between high compression ratio and high spike reconstruction quality, a novel method that employs a group-sparsity recovery algorithm, prior information about the input neural signal, learning prior supports of spikes, and a matched wavelet technique is introduced. Our simulation results, using four different sets of real extracellular recordings from four distinct neural sources, show that our proposed method is effective, viable, and outperforms the state-of-the-art compressed sensing-based methods, in particular, when the number of the measurement is two times of the sparsity.

Recent results of medium wave infrared compressive sensing.

The application of compressive sensing (CS) for imaging has been extensively investigated and the underlying mathematical principles are well understood. The theory of CS is motivated by the sparse nature of real-world signals and images, and provides a framework in which high-resolution information can be recovered from low-resolution measurements. This, in turn, enables hardware concepts that require much fewer detectors than a conventional sensor. For infrared imagers there is a significant potential impact on the cost and footprint of the sensor. When smaller focal plane arrays (FPAs) to obtain large images are allowed, large formats FPAs are unnecessary. From a hardware standpoint, this benefit is independent of the actual level of compression and effective data rate reduction, which depend on the choice of codes and information recovery algorithm. Toward this end, we used a CS testbed for mid-wave infrared (MWIR) to experimentally show that information at high spatial resolution can be successfully recovered from measurements made with a small FPA. We describe the highly parallel and scalable CS architecture of the testbed, and its implementation using a reflective spatial light modulator and a focal plane array with variable pixel sizes. We also discuss the impact of real-world devices and the effect of sensor calibration that must be addressed in practice. Finally, we present preliminary results of image reconstruction, which demonstrate the testbed operation. These results experimentally confirm that high-resolution spatial information (for tasks such as imaging and target detection) can be successfully recovered from low-resolution measurements. We also discuss the potential system-level benefits of CS for infrared imaging, and some of the challenges that must be addressed in future infrared CS imagers designs.

RHC: a non-parametric cluster-based data reduction for efficient $$k$$ k -NN classification

Although the $$k$$k-NN classifier is a popular classification method, it suffers from the high computational cost and storage requirements it involves. This paper proposes two effective cluster-based data reduction algorithms for efficient $$k$$k-NN classification. Both have low preprocessing cost and can achieve high data reduction rates while maintaining $$k$$k-NN classification accuracy at high levels. The first proposed algorithm is called reduction through homogeneous clusters (RHC) and is based on a fast preprocessing clustering procedure that creates homogeneous clusters. The centroids of these clusters constitute the reduced training set. The second proposed algorithm is a dynamic version of RHC that retains all its properties and, in addition, it can manage datasets that cannot fit in main memory and is appropriate for dynamic environments where new training data are gradually available. Experimental results, based on fourteen datasets, illustrate that both algorithms are faster and achieve higher reduction rates than four known methods, while maintaining high classification accuracy.

Peak Power Reduction Using Improved Selective Mapping Technique for OFDM

OFDM has Major disadvantage is that it leads to high Peak to Average Power Ratio (PAPR) which is consider to be as the main implementation drawback. In this paper we are discussing about PAPR which affects the performance and efficiency of Power Amplifier (PA) and its influence by utilizing the Selective Mapping (SLM) technique in OFDM system for reduction of PAPR. the idea for improved SLM produces several independent signals based on converting the original data lock into many independent signal and then the signal has lowest PAPR that specific signal is transmitted. Also data rate trade-off exist at the receiver end when side information is detected for the recovery of data block. which leads to the reduction of data rate. Improved SLM techniques for reducing the PAPR is the most promising reduction technique in its non-uniform phase factor for PAPR reduction in multicarrier OFDM system. Furthermore the estimate expression by using Complementary Cumulative Distribution Function (CCDF) for PAPR has been discussed. Simulated results demonstrate that OFDMA signals using improved SLM technique carried significant effects in reduction of PAPR in OFDM system.

An 8-channel neural spike processing IC with unsupervised closed-loop control based on spiking probability estimation.

This paper presents a neural spike processing IC for simultaneous spike detection, alignment, and transmission on 8 recording channels with unsupervised closed-loop control. In this work, spikes are detected according to online estimated spiking probability maps, which reliably predict the possibility of spike occurrence. The closed-loop control has been made possible by estimating firing rates based on alignment results and turning on/off channels individually and automatically. The 8-channel neural spike processing IC, implemented in a 0.13 μm CMOS process, has a varied power dissipation from 36 μW to 54.4 μW per channel at a voltage supply of 1.2 V. The chip also achieves a 380× data rate reduction for the testing in vivo data, allowing easy integration with wireless data transmission modules.

M4

Visual analysis of high-volume time series data is ubiquitous in many industries, including finance, banking, and discrete manufacturing. Contemporary, RDBMS-based systems for visualization of high-volume time series data have difficulty to cope with the hard latency requirements and high ingestion rates of interactive visualizations. Existing solutions for lowering the volume of time series data disregard the semantics of visualizations and result in visualization errors. In this work, we introduce M4, an aggregation-based time series dimensionality reduction technique that provides error-free visualizations at high data reduction rates. Focusing on line charts, as the predominant form of time series visualization, we explain in detail the drawbacks of existing data reduction techniques and how our approach outperforms state of the art, by respecting the process of line rasterization. We describe how to incorporate aggregation-based dimensionality reduction at the query level in a visualization-driven query rewriting system. Our approach is generic and applicable to any visualization system that uses an RDBMS as data source. Using real world data sets from high tech manufacturing, stock markets, and sports analytics domains we demonstrate that our visualization-oriented data aggregation can reduce data volumes by up to two orders of magnitude, while preserving perfect visualizations.

Investigations on Bits on Film high speed scanning device

Whereas the recording of digital data on film for long term storage can be realized with high speed the reading of those data by scanning devices still needs significant more time. Additionally to that it is crucial to realize a fast scanning of the recorded data for verification of the integrity of the data. This is actually the bottleneck in realizing a fast archiving production chain "bits on film". We describe here a new approach for a high speed scanning system, where a new frame grabber based electronics to generate a fast data reduction of the scanned data is used. The amount of data generated by a high resolution scanner with four times oversampling rate is enormous. In order to read the "bits on film" (information data) with a line-sampling rate of 100kHz the high speed scanner has to acquire data with a data rate of about 1,6GByte/s. The challenge is to get the data amount reduced significantly already in the camera device without losing information. Therefore the region of information has to be separated and the data reduction has to be done geometrically and in bit depth. We have built up a test scanning device to verify the principal usage and functionality of this approach. We calculated that a data reduction rate of about 40 can be achieved. Although the focus of the test is on the fast data reduction we have to consider other requirements like the resolution of the optics, the lightning, the necessary oversampling rate, film transport accuracy and the structuring of the symbols on film. We experienced that the approach of reducing the amount of data from the scanned data down to the information data already in the scanning device is only possible if also other challenging specifications of the scanning system are realized there. We analyze in addition the necessary composition of the scanning device to realize a fast reading of the bits on film.

비균등 표본화 기법과 음성 부호화로의 응용

국소적으로 선형적인 특성을 보이는 음성신호와 같은 신호의 데이터율을 감소시키기 위하여 변곡점 검출에 기반한 비균등 표본화 방법을 제안한다. 국소적인 최대값과 최소값 검출에 기반하여 비균등 표본화를 수행하는 기존의 방법에 비하여 변곡점에 기반한 비균등 표본화는 신호의 기하학적인 특징을 충실히 활용한다. 결과로서, 변곡점 검출에 기반하여 비균등 표본화된 데이터를 보간법으로 처리하면 기존의 방법보다 원시신호를 정밀하게 복원할 수 있다. 컴퓨터 모의실험을 통하여 기존의 최대값/최소값 검출 방법에 비교해서 제안된 변곡점 검출 기반의 비균등 표본화가 약 9~23dB의 신호대 잡음비 개선효과가 있음을 확인하였다. 제안된 변곡점 검출 기반의 비균등 부호화의 유용성을 보이기 위하여 음성신호의 부호화에 적용하였으며, Continuously variable slope delta modulation (CVSD)방법과 성능을 비교하였다. 변곡점 표본은 1로 설정된 플래그와 함께 이진수로 전송되며, 비 변곡점은 플래그만 0으로 설정된다. 음성신호에 따라 약 0.3 ~ 9dB의 신호대 잡음비 개선효과가 있으며, 주관적인 성능지표인 Mean Opinion Score (MOS)는 약 0.5 ~ 1.3 개선되었다. For a signal such as speech showing piece-wise linear shape in a very short time period, a nonuniform sampling method based on the inflection point detection (IPD) is proposed to reduce data rate. The method exploits the geometrical characteristics of signal further than the existing local maxima/minima detection (MMD) based sampling method. As results, the reconstructed signal by the interpolation of the IPD based sampled data resembles the original speech more. Computer simulation shows that the proposed IPD based method produces about 9~23 dB improvement over the existing MMD method. To show the usefulness of the IPD technique, it is applied to speech coding, and compared to the continuously variable slope delta modulation (CVSD). The nonuniformly sampled data is binary coded with one bit flag set "1". Noninflection samples are not sent, but only flag bits set 0 are sent. The method shows 0.3 ~ 9 dB SNR and 0.5 ~ 1.3 mean opinion score (MOS) improvements over the CVSD.

Coding Efficiency of the DCT and DST in Hybrid Video Coding

Standardized hybrid video coding algorithms, e.g., HEVC, apply intra frame prediction or motion compensated prediction and subsequent integer approximated DCT or DST transform coding. The coding efficiency of the transforms depends on the statistical moments and probability distribution of the input signals. For a Gaussian distribution, the DCT always leads to a data rate reduction. However, for Laplacian distributed prediction errors, the transforms sometimes increase the data rate. This paper presents a theoretical analysis, which explains the reason for an increase of the data rate, which is due to the generation of higher statistical moments of the coefficients by the DCT or DST in the case of Laplacian distributed input signals. The data rate can increase by up to 0.10 bit per sample for blocks with low correlation. For screen content, in about 20% of the blocks, the transform increases the data rate. By skipping the transform for these blocks, HEVC achieves a 7% data rate reduction.

A 75-µW, 16-Channel Neural Spike-Sorting Processor With Unsupervised Clustering

Energy-efficient spike-sorting DSPs are necessary to allow for the real-time processing of multi-channel, wireless, implantable neural recordings. Online, unsupervised clustering forms an integral part of on-chip spike sorting. However, previous spike-sorting DSPs did not include unsupervised clustering due to the large memory required for its implementation. We demonstrate the first multi-channel spike-sorting DSP chip that includes online, unsupervised clustering. On-chip clustering has been made possible by using a two-stage implementation of an online clustering algorithm, a noise-tolerant distance metric, and selectively clocked high-V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</sub> register banks. The 16-channel spike-sorting chip, implemented in a 65-nm CMOS process, has a power dissipation of 75 μW at a supply voltage of 270 mV. The implementation of on-chip clustering provides a 240× reduction in the output data rate, which is 3× higher than the data-rate reduction obtained from previous spike-sorting DSP chips.

High-speed panoramic light-sheet microscopy reveals global endodermal cell dynamics

The ever-increasing speed and resolution of modern microscopes make the storage and post-processing of images challenging and prevent thorough statistical analyses in developmental biology. Here, instead of deploying massive storage and computing power, we exploit the spherical geometry of zebrafish embryos by computing a radial maximum intensity projection in real time with a 240-fold reduction in data rate. In our four-lens selective plane illumination microscope (SPIM) setup the development of multiple embryos is recorded in parallel and a map of all labelled cells is obtained for each embryo in <10 s. In these panoramic projections, cell segmentation and flow analysis reveal characteristic migration patterns and global tissue remodelling in the early endoderm. Merging data from many samples uncover stereotypic patterns that are fundamental to endoderm development in every embryo. We demonstrate that processing and compressing raw image data in real time is not only efficient but indispensable for image-based systems biology.

Haptic Data Compression Based on Linear Prediction

A new linear prediction-based haptic data reduction technique is presented. The prediction approach relies on the least-squares method to reduce the number of data packets. Knowledge from human haptic perception is incorporated into the architecture to assess the perceptual quality of the compressed haptic signals. Experiments prove the effectiveness of the proposed approach in data reduction rate.