nils-herrmann/clean_scirepeval huggingface dataset:
System architecture of an adaptive reconfigurable DSP computing engine

In this paper, we present the system architecture of an adaptive reconfigurable DSP computing engine for numerically intensive front-end audio/video communications. The proposed system is a massively parallel architecture that is capable of performing most low-level computationally intensive data processing including finite impulse response/infinite impulse response (FIR/IIR) filtering, subband filtering, discrete orthogonal transforms (DT), adaptive filtering, and motion estimation for the host processor in DSP applications. Since the properties of each programmed function such as parallelism and pipelinability have been fully exploited in this design, the computational speed of this computing engine can be as fast as ASIC designs that are optimized for individual specific applications. We also show that the system can be easily configured to perform multirate FIR/IIR/DT operations at negligible hardware overhead. Since the processing elements are operated at half of the input data rate, we are able to double the processing speed on-the-fly based on the same system architecture without using high-speed/full-custom circuits. The programmable/high-speed features of the proposed design make it very suitable for cost-effective video-rate DSP applications.
Robust Image and Video Transmission Over Spectrally Shaped Channels Using Multicarrier Modulation

This paper presents a new parallel transmission framework for reliable multimedia data transmission over spectrally shaped channels using multicarrier modulation. We propose to transmit source data layers of different perceptual importance in parallel, each occupying a number of subchannels. New loading algorithms are developed to efficiently allocate the available resources, e.g., transmitted power and bit rate, to the subchannels according to the source layers they transmit. Instead of making the bit error rate of all the subchannels equal as in most existing loading algorithms, the proposed algorithm assigns different error performance to the subchannels to achieve unequal error protection for different layers. The channel induced distortion in mean-square sense is minimized. We show that the proposed system can be applied nicely to both fixed length coding and variable-length coding. Asymptotic gains with respect to channel distortion are also derived. Numerical examples show that the proposed algorithm achieves significant performance improvement compared to the existing work, especially for spectrally shaped channels commonly used in in ADSL systems.
A multi-layer 2D adaptive filtering architecture based on McClellan transformation

A fully pipelined systolic array structure for multidimensional adaptive filtering is proposed. It utilizes the McClellan transformation (MT) to reduce the total number of parameters used in the 2D filter. A new multilayer triangular array, which is based on QR-decomposition recursive least squares (RLS) (QRD-RLS) as well as the projection method, are derived for the '1-D prototype filter' of MT. The hardware complexity for the new architecture is only O(N). The system latency is also reduced from O(N) to O(log2N). The QRD-RLS algorithm is suitable for real-time image processing such as video signal processing.
On the performance of orthogonal space-time block codes for spatially and temporally correlated wireless channels [mobile radio]

Monte Carlo simulations are used to determine the performance of several orthogonal space-time block codes for wireless channels that exhibit both temporal and spatial correlation. A channel model is employed that specifies the spatial distribution of the channel scatterers and is based upon recent measurements. A significant degradation in the performance of the space-time codes is observed for cases where the scatterers are located in close proximity to the mobile and fractional wavelength antenna spacing is used at the transmitter. The conditions under which the channel transmission paths may be assumed to be independent are quantified in terms of the scattering radius about the mobile and transmit antenna spacing.
Evolutionary Game Framework for Behavior Dynamics in Cooperative Spectrum Sensing

Cooperative spectrum sensing has been shown to greatly improve the sensing performance in cognitive radio networks. However, if the cognitive users belong to different service providers, they tend to contribute less in sensing in order to achieve a higher throughput. In this paper, we propose an evolutionary game framework to study the interactions between selfish users in cooperative sensing. We derive the behavior dynamics and the stationary strategy of the secondary users, and further propose a distributed learning algorithm that helps the secondary users approach the Nash equilibrium with only local payoff observation. Simulation results show that the average throughput achieved in the cooperative sensing game with more than two secondary users is higher than that when the secondary users sense the primary user individually without cooperation.
Time-Reversal Wideband Communications

With the advance of semiconductor technologies, the performance of analog-to-digital converter (ADC) has been improved a lot during the past decade in terms of both sampling rate and resolution. The cost has gone down dramatically that makes the wideband communication much affordable. Under such circumstances, a natural question to ask is: Is there a low complexity high energy-efficient solution to high throughput wideband communications? In this letter, we explore this question by studying time-reversal communications. We find that compared with that of OFDM system, the computational complexity of a time-reversal system at the transmitter side is lower since it requires similar additions but no multiplications. Furthermore, the computational complexity of a time-reversal system at the receiver side is negligible since only onetap detection is performed, which means that the overall computational complexity of time-reversal system is much lower than that of OFDM system. Moreover, we find that when the bandwidth is large enough, time-reversal system can achieve much higher achievable rate than OFDM system. Therefore, time-reversal technique is a desired solution to low complexity high throughput wideband communications when more bandwidth is available.
Local tomography in fan-beam geometry using wavelets

An algorithm is developed for wavelet based multiresolution reconstruction of a function directly from its fan beam projections. The algorithm uses the locality of wavelet and scaling functions to reconstruct a local region of interest with reduced exposure. In other words, our algorithm saves the radiation exposure in the cases where only a local region of the cross section of a body is to be reconstructed. For example, in order to reconstruct a region of 16 pixels in radius in a 256/spl times/255 image, our method can reduce the X-ray dosage down to 22% of full exposure.
On Outage Probability for Stochastic Energy Harvesting Communications in Fading Channels

An optimal transmission policy is considered for energy harvesting (EH) wireless point-to-point communications, wherein the source node is solar-powered and equipped with a finite-sized battery. The long-term outage probability is minimized by adapting the transmission power to the causal energy arrival information, battery energy amount and channel fading through a Markov decision process (MDP) framework. We reveal an interesting saturated structure of the expected outage probability for which it eventually converges to a battery empty probability in high signal-to-noise power ratio (SNR). This phenomenon that links outage probability with EH capability is derived based on a monotonic and bounded differential structure of the long-term reward and a threshold structure of the optimal policy. Furthermore, a saturation-free condition on the outage performance is presented as well. Simulations confirm the theoretical analysis and the superiority of the proposed policy.
Waveform Design With Interference Pre-cancellation Beyond Time-Reversal Systems

In wideband communication systems, the time-reversal (TR) technique can boost the signal-to-noise ratio (SNR) at the receiver with simple single-tap detection. It has been shown that conventional waveform design can significantly improve the system performance of TR systems. However, when the symbol rate is very high, the severe intersymbol interference still limits the performance at high-power region. In this work, we study a new waveform design with interference pre-cancellation by exploiting the message information to further improve the performance. In the proposed design, the causal interference is subtracted by interference compensation, and the anticausal interference can be further suppressed by conventional waveform design by virtue of the more abundant degrees of freedom. The transmitter utilizes the information of previous symbols to enhance the signal quality while the receiver structure remains simple. In the multiuser scenario, both the interuser interference and intersymbol interference can be similarly categorized by the causality, and then be tackled accordingly by the proposed waveform design with interference pre-cancellation. The resulting multiuser waveform design is a nonconvex optimization problem, for which two iterative algorithms are proposed and both are guaranteed to converge to suboptimal solutions. Simulation results validate the convergence behavior and demonstrate the remarkable performance improvement over the conventional waveform design in the previous work.
Dynamic range of finite-precision recursive QRD LS algorithm and its stability

It is observed that the cosine parameters generated by boundary cells will eventually reach quasi-steady-state if lambda is close to one. It is shown that the quasi-steady-state and ensemble values of sine and cosine parameters are the same for all boundary cells. It is independent of the statistics of the input data sequence and the position of the boundary cell which generates the sine and cosine parameters. Simulation results are presented to support this observation. The stability under quantization effect problem is discussed, and bounds tighter than previously published work are obtained.<<ETX>>
Waveforming Optimizations for Time-Reversal Cloud Radio Access Networks

Due to the unique spatial and temporal focusing effects, time-reversal (TR) communication can be utilized in the cloud radio access network (C-RAN), where it creates “tunneling effects” such that the traffic load in the front-haul links can be alleviated in both downlink and uplink. Although the basic TR waveforms are simple to use, and they cannot provide the optimal performance in some cases. Since the C-RAN is usually expected to serve massive wireless devices, the severe inter-user interference will limit the performance of the system, especially in the high signal-to-noise ratio region where the interference power dominates the noise power. In this paper, we propose to optimize both downlink and uplink transmissions in the TR-based C-RAN so as to alleviate the interference. In the downlink transmission, an optimal content-aware waveform design is proposed, so that the baseband units (BBUs) are able to combine both the channel information and the content information to suppress the interference. In the uplink transmission, an optimal receiver design algorithm is proposed, such that the BBUs can detect the symbols transmitted by the terminal devices more accurately by leveraging the channel information. We study the bit error rate performance of the proposed algorithms based on extensive measurements of the wireless channel in a real-world environment. Numerical results demonstrate the significant performance improvement over the basic TR transmission techniques and the traditional waveform design techniques.
A Time-recursive DCT And DST Parallel Lattice Structure For VLSI Implementation

In this paper, a new scheme employing the time-recursive approach to compute the discrete cosine transform (DCT) and discrete sine transform (DST) is presented. Using such approach, parallel lattice structure that can dually generate the DCT and DST simultaneously is developed. The resulting architecture is regular, module, and without global communication and can be applied to any transform size N .
Low power/high speed design of a Reed Solomon decoder

With the spread of Reed Solomon codes to portable applications, low power RS decoder design has become important. This paper discusses how the Berlekamp Massey Decoding algorithm can be modified in order to obtain a low power architecture. In addition, modifications that speed-up the syndrome and error computations are sugested. Then the VLSI design of a low power/high speed decoder is described. The power reduction when compared to the normal design is estimated.
A game theoretic framework for incentive-based peer-to-peer live-streaming social networks

Multimedia social network analysis is an emerging research area, which analyzes the behavior of users who share multimedia content and investigates the impact of human dynamics on multimedia systems. In peer-to-peer live-streaming social networks, user cooperate with each other to provide a distributed, highly scalable and robust platform for live streaming applications. However, every user wishes to use as much bandwidth as possible to receive a high-quality video, and full cooperation cannot be guaranteed. This paper proposes a game-theoretic framework to model user behavior and designs incentive-based strategies to stimulate user cooperation in peer-to-peer live streaming. We analyze the Nash equilibrium and the Pareto optimality of the game. We also take into consideration selfish users' cheating behavior and propose cheat-proof strategies. Both our analytical and simulation results show that the proposed strategies can effectively stimulate user cooperation, achieve cheat free and help provide reliable services.
When Does Cooperation Have Better Performance in Sensor Networks?

The gains of cooperative communications in wireless networks have been explored recently under the ideal assumption of negligible receiving and processing power. In sensor networks, the power spent for listening and computing can constitute a significant portion of the total consumed power, and such an overhead can reduce the gains promised by cooperation. In this paper, cooperation gains are investigated by taking into consideration such overheads in the analytical framework. The performance metric considered is the energy efficiency of the system measured by the total power required to achieve a certain quality of service requirement. The analytical and numerical results reveal very interesting threshold behavior below which direct transmission is more energy efficient, and above which cooperation provides more gains. Such a tradeoff is shown to depend on many parameters such as the relative locations of the source and destination, the values of the receive and processing powers, the application, and many other factors. Moreover, there are experimental results conducted to verify the channel model assumed in the paper
A game theoretical approach for image denoising

How to adaptively choose optimal neighborhoods is very important to pixel-domain image denoising algorithms since too many neighborhoods may cause over-smooth artifacts and too few neighborhoods may not be able to efficiently remove the noise. While the Stein's principle is shown to be able to estimate the true mean square error (MSE) for determining the optimal neighborhoods, there exists a trade-off between the accuracy of the estimate and the minimum of the true MSE. In this paper, we study the impact of this trade-off and formulate the image denoising problem as a coalition formation game. In the game, every pixel is treated as a player, who tries to seek partners to form a coalition to achieve better denoising results. By forming a coalition, every player in the coalition can obtain a gain of improving the accuracy of the Stein's estimate while incurring a cost of increasing the minimum of the true MSE. We also propose a heuristically distributed approach for coalition formation. Finally, experimental results show that the proposed game theoretical approach can achieve better performance than the nonlocal method in terms of both PSNR and visual quality.
High accuracy indoor localization: A WiFi-based approach

Indoor positioning systems (IPS) based on Wi-Fi signals are gaining popularity recently. IPS based on Received Signal Strength Indicator (RSSI) could only achieve a precision of several meters due to the strong temporal and spatial variation of indoor environment. On the other hand, IPS based on Channel State Information (CSI) drive the precision into the sub-meter regime with several access points (AP). However, the performance degrades with fewer APs mainly due to the limit of bandwidth. In this paper, we propose a Wi-Fi-based time-reversal indoor positioning system (WiFi-TRIPS) using the location-specific fingerprints generated by CSIs with a total bandwidth of 1 GHz. WiFi-TRIPS consists of an offline phase and an online phase. In the offline phase, CSIs are collected in different 10 MHz bands from each location-of-interest and the timing and frequency synchronization errors are compensated. We perform a bandwidth concatenation to combine CSIs in different bands into a single fingerprint of 1 GHz. In the online phase, we evaluate the time-reversal resonating strength using the fingerprint from an unknown location and those in the database for location estimation. Extensive experiment results demonstrate a perfect 5cm precision in an 20cm × 70cm area in a non-line-of-sight office environment with one link measurement.
Diversity Analysis of Non-Coherent Wireless Network Coding

Network coding has been widely used in the wireless uplink. To do coherent detection at the receiver, channel estimation is performed to collect the channel state information (CSI). For multi-user channels, the channel estimation overhead is sometimes formidable and may even outweigh the network coding gain. To address this issue, we study the non-coherent network coding in this work. Both the analog network coding (ANC) and digital network coding (DNC) are studied. Depending on the available CSI, we first develop the coherent and non-coherent maximum likelihood receivers. For ANC, as the non-coherent receivers have no closed form, we develop two suboptimum receivers according to the average link qualities. Next we study the error rates, and show that full diversity can always be achieved at extremely high signal-to-noise ratios (SNR) regardless of the CSI assumptions. However, the lack of perfect CSI would incur some diversity loss at modest SNRs. Besides, the performance loss of ANC is more serious due to the incapability to efficiently suppress multi-user interferences at the receivers. Extensive simulations are performed to verify our analytical results.
A complete pipelined parallel CORDIC architecture for motion estimation

In this paper, a novel fully pipelined parallel CORDIC architecture is proposed for motion estimation. Unlike other block matching structures, it estimates motion in the discrete cosine transform (DCT) domain instead of the spatial domain. As a result, it achieves high system throughput and low hardware complexity as compared to the conventional motion estimation design in MPEG standards. That makes the proposed architecture very attractive in real-time high-speed video communication. Importantly, the DCT-based nature enables us not only to efficiently combine DCT and motion estimation units into a single component but also to replace all multiply-and-add operations in plane rotation by CORDICs to gain further savings in hardware complexity. Furthermore, this multiplier-free architecture is regular, modular, and has solely local connection suitable for VLSI implementation. The goal of the paper is to provide a solution for MPEG compatible video codec design on a dedicated single chip.
Anti-forensics of median filtering

A number of forensic techniques have been developed to identify the use of digital multimedia editing operations. In response, several anti-forensic operations have been designed to fool forensic algorithms. One operation that has received considerable attention is median filtering, since it can be used for image enhancement or anti-forensic purposes. As a result, several median filtering detectors have been developed. In this paper, we propose an anti-forensic technique to disguise the use of median filtering. We do this by first proposing a model for an unaltered image's pixel difference distribution. We then modify a median filter image's pixel difference distribution using anti-forensic noise so that it no longer contains median filtering fingerprints. Through a series of experiments, we are able to show that our anti-forensic technique can fool existing median filtering detectors under realistic conditions.
Downlink power control and base station assignment

The joint power control and base station assignment for the downlink is considered in this paper. Based on the results and observations of previous work we present an algorithm that finds a feasible joint base assignment and transmission power vector in the downlink. We show that under some conditions the algorithm also minimizes the sum of downlink powers. Interestingly, there is not always a Pareto optimal power vector for the joint problem in the downlink as is the case in the uplink. This fact is demonstrated through a counterexample.
Optimal pricing for interference control in time-reversal device-to-device uplinks

The Device-to-Device (D2D) communication is a promising technique to empower local wireless communications. However, without proper management it may generate interference to the existing network and degrade the overall performance. By treating each multipath as a virtual antenna, time-reversal (TR) signal transmission in a rich-scattering environment produces a spatial-temporal resonance which efficiently suppresses the inter-user interference (IUI) while boosting the signal power at the target receiver. In this work, we design a TR-based D2D hybrid network, where both primary users (PUs) and D2D pairs share the same time-frequency resources and use TR focusing effect to combat interference. With the purpose of enhancing D2D performance while providing a performance protection to PUs, an efficient optimal pricing algorithm is proposed to dynamically control interference through TR focusing strength control.
Near-Optimal Waveform Design for Sum Rate Optimization in Time-Reversal Multiuser Downlink Systems

Utilizing channel reciprocity, the traditional time-reversal technique boosts the signal-to-noise ratio at the receiver with very low transmitter complexity. However, the large delay spread gives rise to severe inter-symbol interference (ISI) when the data rate is high, and the achievable transmission rate is further degraded in the multiuser downlink due to the inter-user interference (IUI). In this work, we study the weighted sum rate optimization problem by means of waveform design in the time-reversal multiuser downlink where the receiver processing is based on a single sample. Power allocation has a significant impact on the waveform design problem. We propose a new power allocation algorithm named Iterative SINR Waterfilling, which is able to achieve comparable sum rate performance to that of globally optimal power allocation. We further propose another approach called Iterative Power Waterfilling for multiple data streams. Iterative SINR Waterfilling provides better performance than Iterative Power Waterfilling in the scenario of high interference, while Iterative Power Waterfilling can work under multiple data streams. Simulation results show the superior performance of the proposed algorithms in comparison with other waveform designs such as zero-forcing and conventional time-reversal waveform.