nils-herrmann/clean_scirepeval huggingface dataset:
Anti-attack cooperation stimulation in self-organized ad hoc networks

In self-organized ad hoc networks, nodes usually belong to different authorities and pursue different goals. To save their valuable resources, they tend to be selfish. Meanwhile, some nodes may be malicious whose objective is to degrade the network performance. In this paper, we present an anti-attack cooperation stimulation system for self-organized ad hoc networks to stimulate cooperation among selfish nodes and to defend against attacks. In the proposed system, the damage that can be caused by attackers is bounded, and the cooperation among selfish nodes is enforced. Simulation studies also verify the effectiveness of the proposed system. Another key property of the proposed system is that it is fully distributive, and does not require any tamper-proof hardware or central management point.
Content-aware multiple access protocol for cooperative packet speech communications

A novel cooperative multiple access protocol for packet speech communications is proposed, where cooperation is achieved through the deployment of a relay node that exploits the silence periods typical of speech communications. The relay forwards speech packets for active calls using a subset of the free time slots left available by users that are silent. No new channel resources are needed for cooperation and the system encounters no bandwidth losses. Because the resources allocated to the relay are not drawn from the pool of reused resources but from those potentially used for random channel access. Thus, the use of cooperation introduces a tradeoff between the amount of help offered to active calls and the probability of a successful contention for channel access. Such cooperation tradeoff is investigated and guidelines for the choice of protocol parameters are developed. The throughput and delay performance of the proposed protocol are characterized and compared to a similar non-cooperative packet speech protocol. Results demonstrate significant gains achieved by the proposed cooperative protocol. Moreover, the speech quality under the cooperative protocol was measured using a perceptual model, and results reveal significant improvement over the non-cooperative protocol especially in the low signal-to-noise ratio regime.
Stimulating cooperation and defending against attacks in self-organized mobile ad hoc networks

In self-organized mobile ad hoc networks, nodes belong to different authorities and pursue different goals, so they tend to be selfish, that is, they try to maximize the benefits they can get from the network, but are not willing to forward packets for the benefits of other nodes. Meanwhile, some nodes may be malicious whose objective is to degrade the network's performance and waste other nodes' valuable resource. In this paper, we propose an Attack-Resilient Cooperation Stimulation (ARCS) system for self-organized mobile ad hoc networks to stimulate cooperation among selfish nodes and to defend against attacks. In the ARCS system, the damage that can be caused by malicious nodes is bounded, and the cooperation among selfish nodes is enforced. Both theoretical analysis and simulation studies have confirmed the effectiveness of the ARCS system. Another key property of the ARCS system lies in that it is completely self-organizing and fully distributed, and does not require any tamper-proof hardware or central management points.
Real-time recursive two-dimensional DCT for HDTV systems

The two-dimensional discrete cosine transform (2-D DCT) has been widely recognized as the most effective technique in image data compression. A new algorithm is proposed to compute the 2-D DCT from a frame-recursive point of view. Based on this approach, a real-time parallel lattice structure for the 2-D DCT is developed. The system is fully-pipelined with throughput rate N clock cycles for an N*N successive input data frame. The 2-D DCT architecture is modular, regular, and requires only two 1-D DCT blocks which can be extended directly from the 1-D DCT array. A parallel 2-D DCT architecture and a new scanning pattern for the HDTV system are also proposed to achieve higher performance.<<ETX>>
Cognitive femtocell market: How to price?

Cognitive femtocell has been envisioned as a promising technology for covering indoor environment and assisting heavy-loaded macrocell network. Although lots of technical issues of it have been studied, e.g., spectrum sharing, interference mitigation, etc, the economic issues that are very important for practical femtocell deployment have not been well investigated in the literatures. In this paper, we focus on the pricing issues in cognitive femtocell network, and propose a two-tier pricing game theoretic framework with a dynamic pricing model. We first model the cognitive users' network access behavior as a 2-dimensional Markov decision process and propose a modified value iteration algorithm to find the best strategy profiles for cognitive users. Based on the analysis of users' behavior, we further design an iterative gradient descent algorithm to find the Nash equilibrium pricing strategies for both macrocell and femtocell operators. Simulation results verify our theoretic analysis and show that the proposed algorithm can quickly converge to the Nash equilibrium prices.
Attack-Resistant Collaboration in Wireless Video Streaming Social Networks

Users using the same video streaming service within a wireless network share the same limited backbone bandwidth to the Internet. These users are motivated to collaborate with each other to obtain better-quality service. The decisions and actions of users influence the performance of others, hence they form a social network. In a fully-distributed wireless network, malicious attack can cause much more damage than over the Internet since the unstable wireless channel allows hostile users to mimic as a non-malicious user. Therefore, a robust attack-resistant cooperation strategy for non-malicious user is needed to combat the challenges in wireless networks. In this paper, we incorporate trust modelling into the cooperation among users to increase attack-resistance. Simulation results show our robust cooperation strategies can against $40 \%$ more attackers.
Systematic space-time trellis code design for an arbitrary number of transmit antennas

The potential for a capacity increase in multi-antenna wireless communication systems has drawn considerable attention to space-time codes. In this work, we propose a systematic code construction method that jointly considers diversity advantage and coding advantage for an arbitrary number of transmit antennas and any memoryless constellation. Due to the special structure of the channel symbol difference matrix, the code construction problem is reduced to a combinatorial optimization problem and a computationally efficient suboptimal solution is proposed. The simulations show that our design procedure results in codes that outperform the ones constructed by previously existing methods. In certain cases, as much as 2-2.5 dB coding gain can be observed.
Distributed Relay Selection and Power Control for Multiuser Cooperative Communication Networks Using Buyer/Seller Game

The performances in cooperative communications depend on careful resource allocation such as relay selection and power control, but traditional centralized resource allocation needs considerable overhead and signaling to exchange the information for channel estimations. In this paper, we propose a distributed buyer/seller game theoretic framework over multiuser cooperative communication networks to stimulate cooperation and improve the system performance. By employing a two-level game to jointly consider the benefits of source nodes as buyers and relay nodes as sellers, the proposed approach not only helps the source smartly find the relays at relatively better locations and buy optimal amount of power from them, but also helps the competing relays maximize their own utilities by asking the reasonable prices. The game is proved to converge to a unique optimal equilibrium. From the simulation results, the relays in good locations can play more important roles in increasing source node's utility, so the source would like to buy more power from these preferred relays. On the other hand, the relays have to set the proper prices to attract the source's buying because of competition from other relays and selections from the source. Moreover, the distributed game resource allocation can achieve comparable performance compared with the centralized one.
Maximum achievable diversity for MIMO-OFDM systems with arbitrary spatial correlation

In this paper, the maximum achievable diversity order is determined for MIMO-OFDM systems with arbitrary spatial correlation. We show that the maximum achievable diversity order is the rank of the spatial correlation matrix of the channel including all delay paths. We also show that any space-frequency code designed to achieve full diversity in spatially independent MIMO-OFDM systems can be used to achieve full diversity in spatially correlated scenarios. Extensive simulation results are provided to support the theoretical analysis.
Multiplicative update rules for nonnegative matrix factorization with co-occurrence constraints

Nonnegative matrix factorization (NMF) is a widely-used tool for obtaining low-rank approximations of nonnegative data such as digital images, audio signals, textual data, financial data, and more. One disadvantage of the basic NMF formulation is its inability to control the amount of dependence among the learned dictionary atoms. Enforcing dependence within predetermined groups of atoms allows objects to be represented using multiple atoms instead of only one atom. In this paper, we introduce three simple and convenient multiplicative update rules for NMF that enforce dependence among atoms. Using examples in music transcription, we demonstrate the ability of these updates to represent each musical note with multiple atoms and cluster the atoms for source separation purposes.
A low-power and low-complexity DCT/IDCT VLSI architecture based on backward Chebyshev recursion

A low-power parallel VLSI structure for DCT/IDCT is proposed. By treating the transformations as the evaluation of the Chebyshev series, and exploiting the Backward Chebyshev Recursion (BCR), we can reduce the total number of multipliers (N+1 for IDCT, 2N-2 for DCT). The property of BCR is also used to compute the DCT/IDCT through the down-sampled even and odd sequences. Since the operation frequency for the down-sampled sequences is two times slower, the speed penalty caused by the low-voltage design can be compensated at the architectural level. The total multipliers required for the low-power design is only 2N+1 for IDCT and 3N-3 for DCT. Extension to downsampling-by-4 is also achievable at a reasonable increase in hardware complexity.<<ETX>>
Dynamic distortion control for 3-D embedded wavelet video over multiuser OFDM networks

In this paper, we propose a system to transmit multiple 3D embedded wavelet video programs over downlink multiuser OFDM. We consider the fairness among users and formulate the problem as minimizing the users' maximal distortion subject to power, rate, and subcarrier constraints. By exploring frequency, time, and multiuser diversity in OFDM and flexibility of the 3D embedded wavelet video codec, the proposed algorithm can achieve fair video qualities among all users. Compared to a scheme similar to the current multiuser OFDM standard (IEEE 802.11a), the proposed scheme outperforms it by 1-5 dB on the worst received PSNR among all users and has much smaller PSNR deviation.
Forensically determining the order of signal processing operations

Currently, many forensic techniques have been developed to determine which processing operations were used to manipulate a multimedia signal. Determining the order in which these operations were applied, however, remains an open challenge. Understanding this order is important because it not only provides greater insight into a signal's processing history, but it can also be used to determine a forger's behavior patterns or provide insight into who manipulated a signal. In this paper, we propose a new forensic detection framework that can be used determine the order in which manipulations were applied to a signal. Additionally, we introduce the notion of a conditional fingerprint to describe how a manipulation's fingerprints can change under subsequent processing. We identify the conditional fingerprints of contrast enhancement followed by resizing, and use our framework to develop an algorithm to determine the order in which resizing and contrast enhancement were applied to an image.
Joint channel estimation and equalization in multicarrier modulation system using cyclic prefix

Multicarrier modulation (MCM) is a promising technique for high rate data transmission. A one-tap equalizer is an essential part of the MCM system and channel estimation is needed to obtain the coefficient of the equalizer. Lack of correct channel estimation may cause significant performance degradation. We propose to use the cyclic prefix to estimate the channel for the MCM system. We found that the cyclic prefix originally used solely to guarantee the optimality of modulation using the discrete Fourier transform (DFT) can be viewed as a source of channel information. Based on this observation, we propose a joint channel estimation and equalization algorithm using the cyclic prefix. Our simulations show that the algorithm can adaptively track the variation of a moderately time varying channel and has about 1-2 dB gain over the system using the channel estimation obtained by the conventional training schemes.
Error performances of multiple access system using analog network coding

In this work, we study the error performances of the multiple access system using analog network coding (ANC), where all the users broadcast their data to the relays and destination simultaneously in the first phase, and the relays forward the source messages that have been mixed in the air in the second phase. Depending on the type of relay power constraint, both the variable gain relaying and fixed gain relaying are considered. We show that the error rates of both schemes scale as O(log P/P2) at high signal-to-noise ratio (SNR), where P is the transmitted power. We also show that the error performance is dominated by the relay-destination channel, thus the best relay position should be close to the destination. We also demonstrate that ANC may be outperformed by the conventional amplify-and-forward scheme when the data rate is low and the user number is not large. Finally, we propose a relay selection strategy based on Min-Max criterion that can achieve full diversity when there are multiple relays.
On Spectrum Sharing in Cooperative Multiple Access Networks

The coexistence and resource sharing between a primary network utilizing cognitive relays and a secondary network are investigated. Two multiple access protocols are proposed to coordinate idle time slots sharing between the two networks in a TDMA setting. While relays in the primary network are using these free time slots to help users in the primary network forward their unsuccessfully transmitted packets, users of the secondary network use these time slots to transmit their own packets. The diversity-multiplexing sort of tradeoff imposed by this resource sharing problem and optimum resource allocation strategy are studied through the characterization of the maximum stable throughput region of both networks.
Vlsi Implementation Of Real-time Parallel Dct/dst Lattice Structures For Video Communications

The alternate use [l] of the discrete cosine transform (DCT) and the discrete sine transform (DST) can achieve higher data compression rates and less blocking effects in image processing. A parallel lattice structure that can dually generate the 1-D DCT and DST is proposed. This architecture is ideally suited for VLSI implementation because of its maldularity, regularity, and local interconnections. The VLSI implementation of the lattice module using the distributed arithmetic approach is described. This realization of the lattice module using 2pm double metal CMOS technology is capable of processing a t a data rate of 116Mb/s in rea 1time.
A Data-Bearing Approach for Pilot-Embedding Frameworks in Space-Time Coded MIMO Systems

Space-time (ST) coded MIMO systems employing coherent detectors crucially require channel state information. This paper presents a novel pilot-embedding framework for channel estimation and data detection by exploiting the null-space property and the orthogonality property of the data-bearer and pilot matrices. The ST data matrix is firstly projected onto the data bearer matrix, which is a null-space of the pilot matrix, and the resulting matrix and the pilot matrix are combined for transmitting. The data and pilot extractions are achieved independently through linear transformations by exploiting the null-space property. The unconstrained maximum-likelihood (ML) and linear minimum mean-squared error (lmmse) estimators are explored for channel estimation. Then the ML approach for data detection is developed by exploiting the orthogonality property. The mean-squared error (mse) of channel estimation, Cramer-Rao lower bound (CRLB), and the Chernoff's bound of a pair-wise error probability for ST codes are analyzed for examining the performance of the proposed scheme. The optimum power allocation scheme for data and pilot parts is also considered. Three data-bearer and pilot structures, including time-multiplexing (TM)-based, ST-block-code (STBC)-based, and code-multiplexing (CM)-based, are proposed. Simulation results show that the CM-based structure provides superior performance for nonquasi-static flat Rayleigh fading channels, while these three structures yield similar performances for quasi-static flat Rayleigh fading channels
A Technical Revolution: Social Learning and Networking [From the Guest Editors]

The past decade witnesses the emergence and popularity of online social Web sites, blogs, instant messaging systems, and media-sharing networks. The resulting trend toward social learning and networking creates a technological revolution to industries, brings new experience to users, and profoundly changes our daily lives. Increasingly, people use the Internet as a social medium to interact with each other and expand their social circles, share information and experiences, and organize communities and activities.
Risk-Distortion Analysis for Video Collusion Attacks: A Mouse-and-Cat Game

Copyright protection is a key issue for video sharing over public networks. To protect the video content from unauthorized redistribution, digital fingerprinting is commonly used. To develop an efficient collusion-resistant fingerprinting scheme, it is very important for the system designer to understand how the behavior dynamics of colluders affect the performance of collusion attack. In the literature, little effort has been made to explicitly study the relationship between risk, e.g., the probability of the colluders to be detected, and the distortion of the colluded signal. In this paper, we investigate the risk-distortion relationship for the linear video collusion attack with Gaussian fingerprint. We formulate the optimal linear collusion attack as an optimization problem of finding the optimal collusion parameters to minimize the distortion subject to a risk constraint. By varying the risk constraint and solving the corresponding optimization problem, we can derive the optimal risk-distortion curve. Moreover, based upon the observation that the detector/attacker can each improve the detection/attack performance with the knowledge of his/her opponent's strategy, we formulate the attack and detection problem as a dynamic mouse and cat game and study the optimal strategies for both the attacker and detector. We show that if the detector uses a fixed detection strategy, the attacker can estimate the detector's strategy and choose the corresponding optimal strategy to attack the fingerprinted video with a small distortion. However, if the detector is powerful, i.e., the detector can always estimate the attacker's strategy, the best strategy for the attacker is the min-max strategy. Finally, we conduct several experiments to verify the proposed risk-distortion model using real video data.
Model-based channel estimation framework for MIMO multicarrier communication systems

The multicarrier modulation (MCM) using multiple antennas is a promising technique for broadband communications over mobile wireless channels. In this work, we investigate the channel estimation problem for the MCM system with multiple transmitter and receiver antennas. The difficulty of such a problem is that the number of the channel parameters increases proportionally with the number of transmitter antennas while the observations at the receiver do not. A model-based channel estimation framework is proposed to identify the multiple channels simultaneously. Based on this framework, we further discuss the identification condition and the training sequence design by taking into account both the model error and residual noise. Finally, we show the performance of the proposed model-based channel estimation scheme using two types of models, Fourier-transform-based model and polynomial model. We also show the system performance of two space-time codes using the proposed channel estimation algorithm.
On the impact of correlation on distributed detection in wireless sensor networks with relays deployment

In this paper, a binary hypothesis distributed detection problem in correlated wireless sensor networks with cooperative relays deployment is considered. In particular, the effect of correlation between sensor nodes is modeled and analyzed in Rayleigh flat fading channels in order to explore the natural tradeoffs between the number of sensor/relay nodes and the detection error performance in the network. Specifically, two communication protocols are utilized; in protocol I, each sensor node communicates its observation directly to the fusion center while in protocol II, amplify-and-forward (AF) cooperative relays are deployed and a fewer number of sensors is used. Based on the theoretical analysis and simulations, it is revealed that employing less sensor nodes and instead deploying relay nodes results in significant performance gains under strict network power constraint It is concluded that with cooperative distributed detection and exploitation of spatial diversity, better detection error performance is achieved as well as reduction in the required number of sensor nodes.
A contract-based approach for ancillary services in V2G networks: Optimality and learning

With the foreseeable large scale deployment of electric vehicles (EVs) and the development of vehicle-to-grid (V2G) technologies, it is possible to provide ancillary services to the power grid in a cost efficient way, i.e., through the bidirectional power flow of EVs. A key issue in such kind of schemes is how to stimulate a large number of EVs to act coordinately to achieve the service request. This is challenging since EVs are self-interested and generally have different preferences toward charging and discharging based on their own constraints. In this paper, we propose a contract-based mechanism to tackle this challenge. Through the design of an optimal contract, the aggregator can provide incentives for EVs to participate in ancillary services to power grid, match the aggregated energy rate with the service request and maximize its own profits. We prove that under mild conditions, the optimal contract-based mechanism takes a very simple form, i.e., the aggregator only needs to publish an optimal unit price to EVs, which is determined based on the statistical distribution of EVs' preferences. We then consider a more practical scenario where the aggregator has no prior knowledge regarding the statistical distribution and study how should the aggregator learn the optimal unit price from its interactions with EVs. Simulation results are shown to verify the effectiveness of the proposed contract-based mechanism.