nils-herrmann/clean_scirepeval huggingface dataset:
Digital halftoning as 2-D delta-sigma modulation

The error diffusion algorithm for digital halftoning is equivalent in form to a noise-shaping feedback coder, a class of delta-sigma modulator. The white noise assumption of the quantizer error is known to be false; in fact, the quantizer error is seen to be highly correlated with the input image. To account for this correlation, we use a gain model for the quantizer. This model accurately predicts the edge sharpening and noise shaping caused by all error diffusion schemes. It also permits an extension of error diffusion to oversampled imagery.
Adaptive downlink OFDMA resource allocation

Optimizing OFDMA resource allocation with respect to communication performance requires solving a nonlinear mixed-integer programming problem. As a result, many researchers have fallen back on suboptimal heuristic algorithms. In a recent paper, we demonstrate that ergodic rate maximization is possible using a dual optimization framework that results in a practically optimal solution with complexity that is on the order of the number of subcarriers times the number of users. One of the primary disadvantages of considering ergodic rates is the assumption that the channel distribution information (CDI) is perfectly known at the transmitter. Therefore, this paper proposes an adaptive algorithm based on stochastic approximation methods that do not require knowledge of the CDI. This algorithm converges to the optimal solution with probability one, while for each OFDMA symbol, the complexity is on the order of the number of subcarriers times the number of users. There are no iterations in a given OFDMA symbol time; instead, the ldquoiterationsrdquo are actually performed across time (symbols). Simulation results based roughly on a third-generation partnership project, long-term evolution (3GPP-LTE) OFDMA system corroborate our claims.
Unsupervised merger detection and mitigation in still images using frequency and color content analysis

When taking pictures, professional photographers apply photographic composition rules, e.g. avoidance of mergers. A merger occurs when equally focused foreground and background regions appear to merge as one object. This paper presents an unsupervised algorithm that: (a) detects the main subject; (b) detects background objects merging with the main subject; and (c) reduces the visibility of merging background objects. Detection of the main subject requires automated adjustment of camera settings. The rest of the algorithm does not adjust or use the camera settings. The algorithm does not make assumptions about the scene setting (indoor/outdoor) or content. The algorithm is amenable to implementation on a fixed-point processor.
Low-complexity velocity estimation in high-speed optical Doppler tomography systems

Optical Doppler Tomography (ODT) is a noninvasive 3-D optical interferometric imaging technique that measures static and dynamic structures in a sample. To obtain the dynamic structure, e.g. blood flowing in tissue, a velocity estimation algorithm detects the Doppler shift in the received interference fringe data with respect to the carrier frequency. Previous velocity estimation algorithms use conventional Fourier magnitude techniques that do not provide sufficient frequency resolution in fast ODT systems because of the high data acquisition rates and hence short time series. In this paper, we propose a nonlinear algorithm that uses the phase shift between two successive scans of interference fringe data to give a high-resolution estimate of the Doppler shift. The algorithm detects Doppler shifts of 0.1 to 3 kHz with respect to a 1 MHz carrier. In processing 5 frames/s with 100×100 pixels/frame and 32 samples/pixel, i.e. 1.6 million samples/s, the algorithm requires 26 million multiply-accumulates/s. The algorithm works well at 4 bits/sample. The low complexity and small input data size are well-suited for real-time implementation in software. We provide a mathematical analysis of the Doppler shift resolution by modeling the interference fringe data as an AM-FM signal.
Advanced sonar processing techniques for underwater acoustic multi-input multi-output communications

This paper investigates the issue of high-rate, underwater acoustic communication and the potential of multi-input multi-output (MIMO) techniques to achieve that end; further, this paper suggests that implementation of such a system would benefit from sonar array processing techniques such as multichannel combining. In order to justify this assertion, this paper first develops an algorithm for a hybrid array processing, decision feedback equalization (DFE) MIMO receiver. Subsequently, the hybrid receiver is compared against a traditional MIMO-DFE receiver of similar complexity. These simulations demonstrate that the hybrid receiver improves receiver communication performance and attains higher spatial diversity compared to a traditional MIMO-DFE receiver structure.
A methodology for the design and deployment of reliable systems on heterogeneous platforms

Heterogeneous multi-target platforms composed of processors, FPGAs, and specialized I/O are popular targets for embedded applications. Model based design approaches are increasingly used to deploy high performance concurrent applications on these platforms. In addition to programmability and performance, embedded systems need to ensure reliability and availability in safety critical environments. However, prior design approaches do not sufficiently characterize these non-functional requirements in the application or in the mapping on the multitarget platform. In this work, we present a design methodology and associated run-time environment for programmable heterogeneous multi-target platforms that enable design of reliable systems by: (a) elevating reliability concerns to the system modeling level, so that a domain expert can capture reliability requirements within a formal model of computation, (b) modeling platform elements that can be automatically composed into systems to provide a reliable architecture for deployment, and (c) segmenting (in space and time) the run-time environment such that the system captures independent end-user provided reliability criteria. We illustrate the modeling, analysis, and implementation capabilities of our methodology to design fault tolerant control applications. Using the National Instruments PXIe platform and FlexRIO components, we demonstrate a runtime environment that provides desired levels of reliability.
Complex block floating-point format with box encoding for wordlength reduction in communication systems

We propose a new complex block floating-point format to reduce implementation complexity. The new format achieves wordlength reduction by sharing an exponent across the block of samples, and uses box encoding for the shared exponent to reduce quantization error. Arithmetic operations are performed on blocks of samples at time, which can also reduce implementation complexity. For a case study of a baseband quadrature amplitude modulation (QAM) transmitter and receiver, we quantify the tradeoffs in signal quality vs. implementation complexity using the new approach to represent IQ samples. Signal quality is measured using error vector magnitude (EVM) in the receiver, and implementation complexity is measured in terms of arithmetic complexity as well as memory allocation and memory input/output rates. The primary contributions of this paper are (1) a complex block floating-point format with box encoding of the shared exponent to reduce quantization error, (2) arithmetic operations using the new complex block floatingpoint format, and (3) a QAM transceiver case study to quantify signal quality vs. implementation complexity tradeoffs using the new format and arithmetic operations.
Sum Capacity of Multiuser MIMO Broadcast Channels with Block Diagonalization

The sum capacity of a Gaussian broadcast MIMO channel can be achieved with dirty paper coding (DPC). However, algorithms that approach the DPC sum capacity do not appear viable in the forseeable future, which motivates lower complexity interference suppression techniques. Block diagonalization (BD) is a linear preceding technique for downlink multiuser MIMO systems. With perfect channel knowledge at the transmitter, BD can eliminate other users' interference at each receiver. In this paper, we study the sum capacity of BD with and without receive antenna selection. We analytically compare BD without receive antenna selection to DPC for a set of given channels. It is shown that (1) if the user channels are orthogonal to each other, then BD achieves the same sum capacity as DPC; (2) if the user channels lie in the same subspace, then the gain of DPC over BD can be upper bounded by the minimum of the number of transmit and receive antennas. These observations also hold for BD with receive antenna selection. Further, we study the ergodic sum capacity of BD with and without receive antenna selection in a Rayleigh fading channel. Simulations show that BD can achieve a significant part of the total throughput of DPC. An upper bound on the ergodic sum capacity gain of DPC over BD is proposed for easy estimation of the gap between the sum capacity of DPC and BD without receive antenna selection.
Local Utility Power Line Communications in the 3–500 kHz Band: Channel Impairments, Noise, and Standards

Future smart grid systems will intelligently monitor and control energy flows to improve the efficiency and reliability of power delivery. This monitoring and control requires low-delay, highly reliable communication between customers, local utilities, and regional utilities. A vital part of future smart grids is the two way communication links between smart meters at the customer sites and a (decentralized) command and control center operated by the local utility. To enable these two-way communication links, narrowband power line communication (PLC) systems operating in the 3-500 kHz band are attractive because they can be deployed over existing outdoor power lines. Power lines, however, have traditionally been designed for one-directional power delivery and remain hostile environments for communication signal propagation. In this article, we review signal processing approaches to model channel impairments and impulsive noise and mitigate their effects in narrowband PLC systems. We examine ways to improve the communication performance based on current and emerging standards.
Efficient diversity technique for hybrid narrowband-powerline/wireless smart grid communications

Narrowband powerline communications (NB-PLC) and unlicensed wireless communications are considered as two leading communications technologies for emerging Smart Grid applications. The diversity provided by the simultaneous transmission of the same information over powerline and wireless links can be exploited to enhance the overall system reliability. In this paper, we propose an efficient technique to combine the received signals of the NB-PLC and wireless links considering the impulsive nature of the noise and interference on both links. We derive an expression for the average bit-error-rate of the proposed technique. In addition, we present simulation results that quantify the performance gains achieved by our proposed combining technique compared to conventional techniques.
DSP & analog SOC integration in the Internet era

In the PC era, microprocessors and memory were the semiconductor components that drove the PC industry. In the Internet era, DSP and analog functions will drive the Internet access industry. System-on-a-chip (SOC) integration will be the primary technology driver along with continuing Moore's law. This paper discusses the device issues on the integration of analog baseband, small signal RF functions and power management function together with low cost, high density, deep submicron digital CMOS. The integration will require creative new analog and RF device design together with creative circuit techniques.
Predictive shape coding using generic polygon approximation

We introduce an efficient predictive binary shape coding method that consists of (1) global motion estimation, (2) local motion estimation, (3) matched segment coding, and (4) residual segment coding. Global and local motion estimation use contour pel matching and knowledge of previously reconstructed contours. After motion compensation, we code the one-dimensional reference contour indices of the matched contour positions. The final step codes the mismatched contour segments using residual coding. We use a maximum shape distortion tolerance parameter (d/sub max/), which is zero for lossless coding, for both motion estimation and residual coding. We apply the new shape coding method to MPEG-4 binary mask test sequences in QCIF and SIF formats for a wide range of d/sub max/ values. The key contribution of our method is in lossy shape coding in which the average coding gain is more than 100% over generalized differential chain coding. The proposed scheme can be applied to MPEG-4 compliant shape coding and to efficient shape representation for future MPEG-7 applications.
Minimum intersymbol interference methods for time domain equalizer design

During initialization, discrete multitone receivers train a time domain equalizer (TEQ) to shorten the channel impulse response to a preset length, /spl nu/+1. G. Arslan et al. report a minimum intersymbol interference (Min-ISI) method for TEQ design (see  2001). Min-ISI TEQs give the highest bit rates among single-FIR TEQs amenable to real-time implementation on programmable fixed-point digital signal processors (DSPs). The Min-ISI method, however, has several disadvantages: (1) sensitivity to transmission delay; (2) inability to design TEQs longer than /spl nu/+1 taps; (3) sensitivity to the fixed-point computation in the Cholesky decomposition. We develop an alternate Min-ISI cost function, from which we derive: (1) a fast search method for the optimal transmission delay; (2) extensions to design arbitrary-length Min-ISI TEQs; (3) an iterative Min-ISI method. The iterative Min-ISI method avoids Cholesky decomposition, designs arbitrary length TEQs, and achieves the bit rate performance of the original Min-ISI method.
Low complexity EM-based decoding for OFDM systems with impulsive noise

Modern OFDM systems such as cellular LTE and powerline communications experience additive impulsive noise emitted from their environment. OFDM modulation has been shown to provide resilience to impulsive noise due to its code diversity. However, typical OFDM receivers designed under the Gaussian noise assumption will lead to suboptimal performance due to the dependence in noise statistics across subcarriers resulting from the FFT operation. As a result, optimal detection of OFDM symbols becomes prohibitive due to its exponential complexity. We consider the design of a practical class of OFDM receivers that are constrained to perform independent detection on each subcarrier. In this paper, we propose an EM based low-complexity iterative decoding algorithm for OFDM systems in impulsive noise environments that preserves the independent decoding across subcarriers. We validate its performance under typical impulsive noise conditions based on noise traces collected from wireless and powerline platforms. Our proposed method achieves a gain between 2 – 7dB over the conventional OFDM receiver depending on the SNR range.
Joint Interference Cancellation and Channel Shortening in Multiuser-MIMO Systems

In this paper, a two-stage receiver structure for interference cancellation in multiuser spatially multiplexed multiple-antenna systems is presented. A space-time equalizer is used in the first stage for joint coantenna/cochannel-interference suppression and shortening of the effective channel for each transmit stream of the desired user. The channel shortening, combined with independent detection, helps reduce the complexity of the second stage Viterbi equalizer, which is used for separate intersymbol-interference equalization for each of the streams. Three objective functions are proposed for determining the coefficients of the space-time equalizer using a direct training data-based approach, which does not require estimation of the interferer's channel. Simulation results show good symbol error performance as compared to existing algorithms with asynchronous multiple-input multiple-output interferers
Low complexity user selection algorithms for multiuser MIMO systems with block diagonalization

Block diagonalization (BD) is a precoding technique that eliminates interuser interference in downlink multiuser multiple-input multiple-output (MIMO) systems. With the assumptions that all users have the same number of receive antennas and utilize all receive antennas when scheduled for transmission, the number of simultaneously supportable users with BD is limited by the ratio of the number of base station transmit antennas to the number of user receive antennas. In a downlink MIMO system with a large number of users, the base station may select a subset of users to serve in order to maximize the total throughput. The brute-force search for the optimal user set, however, is computationally prohibitive. We propose two low-complexity suboptimal user selection algorithms for multiuser MIMO systems with BD. Both algorithms aim to select a subset of users such that the total throughput is nearly maximized. The first user selection algorithm greedily maximizes the total throughput, whereas the criterion of the second algorithm is based on the channel energy. We show that both algorithms have linear complexity in the total number of users and achieve around 95% of the total throughput of the complete search method in simulations
Performance bounds of MIMO receivers in the presence of radio frequency interference

Multi-input multi-output (MIMO) receivers have generally been designed and their communication performance analyzed under the assumption of additive Gaussian noise. Wireless transceivers, however, may also be affected by radio frequency interference (RFI) that is well modeled using non-Gaussian impulsive statistics. In this paper, we derive bounds on the communication performance for a two transmit, two receive antenna MIMO system in the presence of RFI. Our contributions include derivation of (1) channel capacity in the presence of RFI, (2) probability of symbol error for uncoded transmissions, and (3) Chernoff bound on the pairwise error probability and cutoff rate as a measure of the throughput performance for coded transmissions. Comparison with the communication performance bounds for receivers designed assuming additive Gaussian noise demonstrates degradation in communication performance in the presence of RFI.
Scalable multi-core sonar beamforming with Computational Process Networks

This paper evaluates the scalability with respect to processor cores of a three-dimensional sonar beamforming kernel implemented on a multi-core workstation. Beamforming is an example of an extremely parallelizable problem. This implementation is instrumented with OpenMP to exploit multi-core computer systems. However, when executed on a 16-core machine, this kernel scales much less than expected. We implement this beamformer system within the scalable framework of Computational Process Networks to achieve additional performance and processor utilization for a larger number of cores. On our benchmark machine, the implementation with Computational Process Networks obtains a throughput speedup of more than two times over OpenMP with the default settings, and 13% improvement in throughput over OpenMP with optimized settings.
Real-time high-throughput sonar beamforming kernels using native signal processing and memory latency hiding techniques

We evaluate the use of native signal processing with loop unrolling and software prefetching to achieve high-performance digital signal processing on general-purpose processors. We apply these techniques to minimize the number of processors necessary for real-time implementation of a 3-D sonar beamformer. Because our beamforming kernels operate on high-throughput (/spl sim/100 Mb/s) input/output streams, memory latency hiding techniques are key for maximum performance. On the Sun UltraSPARC-II processor, we find speedups of 2.4 for hand loop unrolling, 1.46 for the visual instruction set over floating-point arithmetic in C, and 1.33 for software prefetching.
Using Higher Order Cyclostationarity to Identify Space-Time Block Codes

Research in cognitive radios has renewed interest in tools, such as spectrum estimation and modulation identification, to characterize the radio frequency (RF) environment. The use of multiple antennas for multiple-input multiple-output (MIMO) communications presents a new challenge in detecting and classifying signals. In this paper, we propose a cyclostationarity-based statistical test to detect space-time block codes, focusing on the two transmitter Alamouti space-time block code (STBC). Our test exploits a new characterization of the Alamouti code using fourth order cyclic frequencies. The test requires only a single receive antenna, and does not require any symbol synchronization.
Spatial domain synthetic scene statistics

Natural Scene Statistics (NSS) has been applied to natural images obtained through optical cameras for automated visual quality assessment. Since NSS does not need a reference image for comparison, NSS has been used to assess user quality-of-experience, such as for streaming wireless image and video content acquired by cameras. In this paper, we take an important first step in using NSS to automate visual quality assessment of synthetic images found in video games and animated movies. In particular, we analyze NSS for synthetic images in the spatial domain using mean-subtracted-contrast-normalized (MSCN) pixels and their gradients. The primary contributions of this paper are (1) creation of a publicly available ESPL Synthetic Image database, containing 221 color images, mostly in high definition resolution of 1920 × 1080, and (2) analysis of the statistical distributions of the MSCN coefficients (and their gradients) for synthetic images, obtained from the image intensities. We find that similar to the case for natural images, the distributions of the MSCN pixels for synthetic images can be modeled closely by Generalized Gaussian and Symmetric α-Stable distributions, with slightly different shape and scale parameters.
Optimal Downlink OFDMA Subcarrier, Rate, and Power Allocation with Linear Complexity to Maximize Ergodic Weighted-Sum Rates

In this paper, we propose a resource allocation algorithm for ergodic weighted-sum rate maximization in downlink OFDMA systems. In contrast to most previous research that focused on maximizing instantaneous rates using deterministic optimization techniques, we focus on maximizing ergodic rates using stochastic optimization techniques, which allow us to exploit the temporal dimension, in addition to the frequency and multiuser dimensions. Furthermore, in contrast to most previous algorithms that used greedy suboptimal heuristics with quadratic complexity, we use a dual optimization approach that resulted in a simple subcarrier, rate, and power allocation algorithm that has complexity O(MK) for an M-user, K-subcarrier OFDMA system. Surprisingly, our method is shown to result in duality gaps less than 10-4 in scenarios of practical interest, thereby allowing us to claim practical optimality. We present simulation results for a 3GPP-LTE system employing adaptive modulation.