nils-herrmann/clean_scirepeval huggingface dataset:
Differential Modulations for Multinode Cooperative Communications

This paper proposes and analyzes differential modulation schemes for two cooperation protocols in multinode cooperative wireless networks; namely, multinode differential amplify-and-forward scheme (DiffAF) and multinode differential decode-and-forward scheme (DiffDF). In the DiffAF scheme, with knowledge of long-term average of received signals from all communication links, the destination efficiently combines signals from direct and all multiple-relay links to improve communication reliability. In the DiffDF scheme, by utilizing a decision threshold at each relay-destination link, the destination efficiently combines signals from the direct link and each relay link whose signal amplitude is larger than the threshold. For the DiffAF scheme, an exact bit error rate (BER) formulation based on optimum combining is provided for differential M-ary phase shift keying (DMPSK) modulation, and it serves as a performance benchmark of the proposed DiffAF scheme. In addition, BER upper bounds, BER lower bounds, and simple BER approximations are derived. Then, optimum power allocation is provided to further improve performance of the DiffAF scheme. Based on the tight BER approximation, the optimum power allocation can be simply obtained through a single dimensional search. In case of the DiffDF scheme, the performance of DMPSK modulation is analyzed. First, a BER formulation for DMPSK modulation is derived. Next, an approximate BER formulation of the DiffDF scheme is obtained, and a tractable BER lower bound is derived to provide further insights. Then, the performance of the DiffDF scheme is enhanced by jointly optimizing power allocation and decision thresholds with an aim to minimize the BER. Finally, simulation results under the two proposed cooperation protocols are given to validate their merit and support the theoretical analysis.
Scalable multimedia fingerprinting forensics with side information

Digital fingerprinting uniquely labels each distributed copy with user's ID and provides a proactive means to track the distribution of multimedia. Multi-user collusion is a powerful attack against digital fingerprinting, in which a group of attackers collectively mount attacks to remove the embedded identification information. To resist such multi-user collusion and support multimedia forensics, this paper investigates the side information based multimedia fingerprinting. We explore techniques to utilize side information of collusion attacks during colluder identification process, and show that the means of the detection statistics at the detector's side can significantly improve the traitor tracing capability. We also investigate how the fingerprint detector can probe such side information from the colluded copy, and our simulation results show that the proposed scheme helps the fingerprint detector achieve the optimum detection performance.
MIMO-OFDM systems with multi-user interference

We consider downlink transmission in a multi-user environment, where each base station transmits multiple data streams to its corresponding mobiles using multiple input multiple output (MIMO) OFDM. Using distributed schemes, we find the optimal transmit and receive weight vectors to maximize the total data rate for each user. We consider two scenarios, where in one the total power per user and in the other total power per subcarrier is fixed. In each case, we propose iterative algorithms to maximize the allocated rate per user. We discuss the convergence of our schemes and compare their performances with those of previous work.
Distributed Adaptive Networks: A Graphical Evolutionary Game-Theoretic View

Distributed adaptive filtering has been considered as an effective approach for data processing and estimation over distributed networks. Most existing distributed adaptive filtering algorithms focus on designing different information diffusion rules, regardless of the nature evolutionary characteristic of a distributed network. In this paper, we study the adaptive network from the game theoretic perspective and formulate the distributed adaptive filtering problem as a graphical evolutionary game. With the proposed formulation, the nodes in the network are regarded as players and the local combiner of estimation information from different neighbors is regarded as different strategies selection. We show that this graphical evolutionary game framework is very general and can unify the existing adaptive network algorithms. Based on this framework, as examples, we further propose two error-aware adaptive filtering algorithms. Moreover, we use graphical evolutionary game theory to analyze the information diffusion process over the adaptive networks and evolutionarily stable strategy of the system. Finally, simulation results are shown to verify the effectiveness of our analysis and proposed methods.
Joint downlink beamforming, power control, and data rate allocation for DS-CDMA mobile radio with multimedia services

Power control and rate allocation are two fundamental issues for improving the spectrum efficiency of downlink transmission for wireless multimedia communications. Downlink beamforming, on the other hand, can be used to suppress stronger interference induced by high rate users, thereby improving the system performance. We present a joint downlink beam-forming, power control and rate allocation technique suitable for DS-CDMA systems with multimedia services. To simplify the computational complexity a practical rate allocation algorithm as also proposed. Computer simulation results are given to evaluate downlink capacity of DS-CDMA systems using base station antenna and the new algorithm proposed.
Fast orthogonalization algorithm and parallel architecture for AR spectral estimation based on forward-backward linear prediction

Truncated QR methods have been shown to be comparable to SVD-based methods for the sinusoidal frequency estimation based on the forward-backward linear prediction (FBLP) model. However, without exploiting the special structure of the FBLP matrix, the QR decomposition (QRD) of the FBLP matrix has a computational complexity on the order of 2(6m-n)n/sup 2//3+O(n/sup 2/) for a 2m*n FBLP matrix. A fast algorithm to perform the QRD of the FBLP matrix by exploiting its special Toeplitz-Hankel form is proposed. The computational complexity is reduced to 10n/sup 2/+4mn+O(n). The fast algorithm can also be easily implemented by a linear systolic array, reducing the number of time steps required to 2m+5n-4.
A dynamic pricing approach for self-organized mobile ad hoc networks

In self-organized mobile ad hoc networks (MANET) where each user is its own authority, fully cooperative behaviors, such as unconditionally forwarding packets for each other, cannot be directly assumed. The pricing mechanism is one way to provide incentives for the users to act cooperatively by rewarding some payment for cooperative behaviors. In this paper, we model the pricing and routing in self-organized MANETs as multistage dynamic games. A dynamic pricing framework is proposed to maximize the sender/receiver's payoff by considering the dynamic nature of MANETs, meanwhile, keeping the forwarding incentives of the relay nodes by providing the optimal payments based on the auction rules. The simulation results illustrate that the proposed dynamic pricing schemes have significant performance gains over the existing static pricing algorithms.
Resistance analysis of scalable video fingerprinting systems under fair collusion attacks

Digital fingerprinting is an important tool in multimedia forensics to trace traitors and protect multimedia content after decryption. This paper addresses the enforcement of digital rights when distributing multimedia over heterogeneous networks and studies the scalable multimedia fingerprinting systems in which users receive copies of different quality. We investigate the traitor tracing capability of such scalable fingerprinting systems, in particular, the robustness of the embedded fingerprints against multi-user collusion attacks. Under the fairness constraints on collusion that all attackers share the same risk of being captured, we analyze the maximum number of colluders that the fingerprinting systems can withstand, and our results show that multimedia fingerprints can survive collusion attacks by a few dozen colluders.
Secure cooperative mobile ad hoc networks against injecting traffic attacks

In this paper we investigate how to defend against injecting traffic attacks in cooperative mobile ad hoc networks where nodes belong to the same authority and pursue the common goals. By injecting an overwhelming amount of traffic into the network, the attackers can easily consume good nodes' valuable network resources and reduce the network's lifetime. Since in cooperative mobile ad hoc networks nodes will usually unconditionally forward packets for other nodes, such networks are extremely vulnerable to injecting traffic attacks, especially those launched by inside attackers. In this paper, the possible types of injecting traffic attackers are studied, and a set of mechanisms are proposed to protect cooperative mobile ad hoc network against such attacks. The performance of the proposed mechanisms is analyzed. Both theoretical and experimental bounds are derived, which show that from attackers' point of view, the best strategy is not to launch injecting traffic attacks. Simulation studies have also verified the theoretical analysis.
Time-recursive computation and real-time parallel architectures: a framework

The time-recursive computation has been proven a particularly useful tool in real-time data compression, in transform domain adaptive filtering, and in spectrum analysis. Unlike the FFT-based ones, the time-recursive architectures require only local communication. Also, they are modular and regular, thus they are very appropriate for VLSI implementation and they allow a high degree of parallelism. In this two-part paper, we establish an architectural framework for parallel time-recursive computation. We consider a class of linear operators that consists of the discrete time, time invariant, compactly supported, but otherwise arbitrary kernel functions. We show that the structure of the realization of a given linear operator is dictated by the decomposition of the latter with respect to proper basis functions. An optimal way for carrying out this decomposition is demonstrated. The parametric forms of the basis functions are identified and their properties pertinent to the architecture design are studied. A library of architectural building modules capable of realizing these functions is developed. An analysis of the implementation complexity for the aforementioned modules is conducted. Based on this framework, the time-recursive architecture of a given linear operator can be derived in a systematic routine way.
Opportunistic Multiple Access for Cognitive Radio Networks

In this paper, opportunistic multiple access to the under-utilized channel resources is investigated. Exploiting source burstiness, secondary cognitive nodes utilizes primary nodes' periods of silence to access the channel and transmit their packets. Cognitive relays could also make use of these silence periods to offer spatial diversity without incurring bandwidth efficiency losses. First, we consider the cognitive cooperation protocol and propose two different relay assignment schemes. Comparison between the proposed schemes is carried out through a maximum stable throughput analysis of the network. Then, secondary nodes access to the remaining idle channel resources is investigated. Queueing theoretical analysis and numerical results reveal that despite the fact that relays occupy part of the idle resources to provide cooperation, secondary nodes surprisingly achieve higher throughput in the presence of relays. The rationale is that relays help primary nodes empty their queues at faster rates, therefore, secondary nodes observe increased access opportunities to the channel.
Outage analysis and optimal power allocation for multinode relay networks

In this letter, a novel approach for outage probability analysis of the multinode amplify-and-forward relay network is provided. It is shown that the harmonic mean of two exponential random variables can be approximated, at high signal-to-noise ratio (SNR), to be an exponential random variable. The single relay case considered before is a special case of our analysis. Based on that approximation, an outage probability bound is derived which proves to be tight at high SNR. Based on the derived outage probability bound, optimal power allocation is studied. Simulation results show a performance improvement, in terms of symbol error rate, of the optimal power allocation compared to the equal power-allocation scheme
A subspace based blind identification and equalization algorithm

A subspace based blind channel identification algorithm is proposed here. This algorithm operates directly on the data domain and therefore avoids the problems associated with other algorithms which use the statistical information contained in the received signal directly. In the noiseless case, this algorithm uses the least number of symbols that can possibly be used to identify the channel exactly. In the noisy case, simulations have shown that almost exact identification can be obtained by using a few more symbols than the theoretical minimum. This is orders of magnitude better than the other blind algorithms. Once the channel has been identified by using this procedure, any of the existing equalization techniques can be used along with it to obtain the symbols.
TRIEDS: Wireless Events Detection Through the Wall

In this paper, we propose a novel wireless indoor events detection system, TRIEDS. By leveraging the time-reversal technique to capture the changes of channel state information (CSI) in the indoor environment, TRIEDS enables low-complexity single-antenna devices that operate in the ISM band to perform through-the-wall indoor multiple events detection. The multipath phenomenon denotes that the electromagnetic signals undergo different reflecting and scattering paths in a rich-scattering environment. In TRIEDS, each indoor event is detected by matching the instantaneous CSI to a multipath profile in a training database. To validate the feasibility of TRIEDS and to evaluate the performance, we build a prototype that works on ISM band with carrier frequency being 5.4 GHz and 125 MHz bandwidth. Experiments are conducted to detect the states of the indoor wooden doors. Experimental results show that with a single receiver access point and transmitter (client), TRIEDS can achieve a detection rate higher than 96.92% and a false alarm rate smaller than 3.08% under either line-of-sight (LOS) or non-LOS transmission.
Smart deployment/movement of unmanned air vehicle to improve connectivity in MANET

Unmanned air vehicles (UAVs) can provide important communication advantages to ground-based wireless ad hoc networks. In this paper, the location and movement of UAVs are optimized such that the network connectivity can be improved. Two types of network connectivity are quantified: global message connectivity and worst-case connectivity. The problems of UAV deployment and movement are formulated for these applications. The optimization problems are NP hard and some heuristic adaptive schemes are proposed in order to yield simple solutions. From the simulation results, by deploying only a single UAV, the global message network connectivity and worst-case network connectivity can be improved by up to 109% and 60%, respectively
Securing Cooperative Ad-Hoc Networks Under Noise and Imperfect Monitoring: Strategies and Game Theoretic Analysis

In cooperative ad-hoc networks, nodes belong to the same authority and pursue the common goals, and will usually unconditionally help each other. Consequently, without necessary countermeasures, such networks are extremely vulnerable to insider attacks, especially under noise and imperfect monitoring. In this paper, we present a game theoretic analysis of securing cooperative ad-hoc networks against insider attacks in the presence of noise and imperfect monitoring. By focusing on the most basic networking function, namely routing and packet forwarding, we model the interactions between good nodes and insider attackers as secure routing and packet forwarding games. The worst case scenarios are studied where initially good nodes do not know who the attackers are while insider attackers know who are good. The optimal defense strategies have been devised in the sense that no other strategies can further increase the good nodes' payoff under attacks. Meanwhile, the optimal attacking strategies and the maximum possible damage that can be caused by attackers have been discussed. Extensive simulation studies have also been conducted to evaluate the effectiveness of the proposed strategies
Image Denoising Games

Based on the observation that every small window in a natural image has many similar windows in the same image, the nonlocal denoising methods perform denoising by weighted averaging all the pixels in a nonlocal window and have achieved very promising denoising results. However, the use of fixed parameters greatly limits the denoising performance. Therefore, an important issue in pixel-domain image denoising algorithms is how to adaptively choose optimal parameters. While the Stein's principle is shown to be able to estimate the true mean square error (MSE) for determining the optimal parameters, there exists a tradeoff between the accuracy of the estimate and the minimum of the true MSE. In this paper, we study the impact of such a tradeoff and formulate the image denoising problem as a coalition formation game. In this game, every pixel/block 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 certain gains by improving the accuracy of the Stein's estimate, while incurring some costs by increasing the minimum of the true MSE. Moreover, we show that the traditional approaches using same parameters for the whole image are special cases of the proposed game theoretic framework by choosing the utility function without a cost term. Finally, experimental results demonstrate the efficiency and effectiveness of the proposed game theoretic method.
Optimal unified IIR architectures for time-recursive discrete sinusoidal transforms

An optimal unified architecture that can efficiently compute the discrete cosine, sine, Hartley, Fourier, lapped orthogonal, and complex lapped transforms for a continuous input data stream is proposed. This structure uses only half as many multipliers as the previous best known scheme. The proposed architecture is regular, modular, and locally connected. In the realisation of the discrete cosine transform, only 2N-2 multipliers are needed. A theoretical justification is provided showing that any discrete transform whose basic functions satisfy the fundamental recurrence formula has a second-order autoregressive structure in its filter realization. It is also demonstrated that dual generation transform pairs share the same autoregressive structure.<<ETX>>
VLSI design of high-speed time-recursive 2-D DCT/IDCT processor for video applications

In this paper we present a full-custom VLSI design of high-speed 2-D DCT/IDCT processor based on the new class of time-recursive algorithms and architectures which has never been implemented to demonstrate its performance. We show that the VLSI implementation of this class of DCT/IDCT algorithms can easily meet the high-speed requirements of high-definition television (HDTV) due to its modularity, regularity, local connectivity, and scalability. Our design of the 8/spl times/8 DCT/IDCT can operate at 50 MHz (or have a 50 MSamples/s throughput) based on a very conservative estimate under 1.2 /spl mu/ CMOS technology. In comparison to the existing designs, our approach offers many advantages that can be further explored for even higher performance.
Transform Coder Classification for Digital Image Forensics

The area of non-intrusive forensic analysis has found many applications in the area of digital imaging. One unexplored area is the identification of source coding in digital images. In other words, given a digital image, can we identify which compression scheme was used, if any? This paper focuses on the aspect of transform coder classification, where we wish to determine which transform was used during compression. This scheme analyzes the histograms of coefficient subbands to determine the nature of the transform method. By obtaining the distance between the obtained histogram and the estimate of the original histogram, we can determine if the image was compressed using the transform tested. Results show that this method can successfully classify compression by transform as well as detect whether any compression has occurred at all in an image.
Coalition formation games for energy-efficient wireless network cocast

Wireless network cocast (WNC) is a cooperative communication protocol that overcomes the issues of imperfect frequency and timing synchronization while achieving spatial diversity to substantially reduce transmit power over direct transmission (DTX). Due to additional processing power in receiving and retransmitting each other information, however, not all nodes and WNC networks result in energy efficiency. To ensure energy efficient WNC networks, a TDMA-based merge process based on coalition formation games is proposed to orderly form cooperative groups. A node is merged into a cooperative group if the merge leads to power saving without causing additional power burden to individual nodes. Simulation shows that WNC networks require much less power to provide comparable quality of service of DTX networks. In addition, WNC networks achieve even power distribution, which improves the network lifetime.
Dynamic join-exit amortization and scheduling for time-efficient group key agreement

We propose a time-efficient contributory key agreement framework for secure communications in dynamic groups. The proposed scheme employs a special join-tree/exit-tree topology in the logical key tree and effectively exploits the efficiency of amortized operations. We derive the optimal parameters and design an activation algorithm for the join and exit trees. We also show that the asymptotic average time cost per user join and leave event is /spl theta/(log (log n)), where n is the group size. Our experiment results on both simulated user activities and the real MBone data have shown that the proposed scheme outperforms the existing tree-based schemes.
Indirect reciprocity game modelling for secure wireless networks

We formulate the wireless security problem as an indirect reciprocity game, and propose a security mechanism that applies the indirect reciprocity principle to suppress attacks in wireless networks. In this system, a large number of nodes cooperate to reject the network access requests from attackers during the punishment periods. If the punishment time is so long that the cost due to the loss of network services exceeds the illegal security gains of the attack, rational nodes do not have incentive to attack, and hence our system can reduce the attacking probability in the network. We develop a social norm and reputation updating process to build such an indirect reciprocity mechanism for the network. We evaluate the evolutionarily stable strategy (ESS) in the game, and provide the optimal action strategy and its corresponding stationary reputation distribution. Our system is robust against collusion attacks, and can significantly reduce the attacking rate for a wide range of attacks. Simulation results show that our system has much better security performance than the direct reciprocity mechanism, especially in the large-scale wireless network with terminal mobility. Our system can be applied to many wireless networks including cognitive radio networks to improve their security performance.