nils-herrmann/clean_scirepeval huggingface dataset:
Synchronization-Aware Distributed Space-Time Codes in Wireless Relay Networks

In this paper, we consider the design of synchronization-aware distributed space-time codes, which we denote as diagonal distributed space-time codes (DDSTC), for N relay nodes helping the source. We impose the diagonal structure of the distributed space-time code to simplify synchronization among the different relay nodes because it is very difficult to synchronize simultaneous transmissions of randomly located relay nodes. We derive an upper bound on the outage probability of the system, which shows that a diversity of order N can be achieved using the diagonal structure of the code. Then, we derive the code design criterion for the DDSTC based on minimizing the pairwise error probability (PEP) to achieve full diversity.
Multiband-OFDM MIMO coding framework for UWB communication systems

The emerging ultrawideband (UWB) system offers a great potential for the design of high speed short-range wireless communications. In order to satisfy the growing demand for higher data rates, one possible solution is to exploit both spatial and multipath diversities via the use of multiple-input multiple-output (MIMO) and proper coding techniques. In this paper, we propose a general framework to analyze the performance of multiband UWB-MIMO systems regardless of specific coding schemes. A combination of space-time-frequency (STF) coding and hopping multiband OFDM modulation is also proposed to fully exploit all of the available spatial and frequency diversities, richly inherent in UWB environments. We quantify the performance merits of the proposed scheme in case of Nakagami-m frequency-selective fading channels. Different from the conventional STF coded MIMO-OFDM system, the performance of the STF coded hopping multiband UWB does not depend on the temporal correlation of the propagation channel. We show that the maximum achievable diversity of multiband UWB-MIMO system is the product of the number of transmit and receive antennas, the number of multipath components, and the number of jointly encoded OFDM symbols. Interestingly, the diversity gain does not severely depend on the fading parameter m, and the diversity advantage obtained under Nakagami fading with arbitrary m parameter is almost the same as that obtained in Rayleigh fading channels. Finally, simulation results are presented to support the theoretical analysis.
Anti-forensics of digital image compression

As society has become increasingly reliant upon digital images to communicate visual information, a number of forensic techniques have been developed to verify the authenticity of digital images. Amongst the most successful of these are techniques that make use of an image's compression history and its associated compression fingerprints. Little consideration has been given, however, to anti-forensic techniques capable of fooling forensic algorithms. In this paper, we present a set of anti-forensic techniques designed to remove forensically significant indicators of compression from an image. We do this by first developing a generalized framework for the design of anti-forensic techniques to remove compression fingerprints from an image's transform coefficients. This framework operates by estimating the distribution of an image's transform coefficients before compression, then adding anti-forensic dither to the transform coefficients of a compressed image so that their distribution matches the estimated one. We then use this framework to develop anti-forensic techniques specifically targeted at erasing compression fingerprints left by both JPEG and wavelet-based coders. Additionally, we propose a technique to remove statistical traces of the blocking artifacts left by image compression algorithms that divide an image into segments during processing. Through a series of experiments, we demonstrate that our anti-forensic techniques are capable of removing forensically detectable traces of image compression without significantly impacting an image's visual quality. Furthermore, we show how these techniques can be used to render several forms of image tampering such as double JPEG compression, cut-and-paste image forgery, and image origin falsification undetectable through compression-history-based forensic means.
HADOF: defense against routing disruptions in mobile ad hoc networks

HADOF is a set of mechanisms to protect mobile ad hoc networks against routing disruption attacks launched by inside attackers. First, each node launches a route traffic observer to monitor the behavior of each valid route in its route cache, and to collect the packet forwarding statistics submitted by the nodes on this route. Since malicious nodes may submit false reports, each node also keeps cheating records for other nodes. If a node is detected as dishonest, this node will be excluded from future routes, and the other nodes will stop forwarding packets for it. Third, each node will try to build friendship with other nodes to speed up malicious node detection. Route diversity will be explored by each to discover multiple routes to the destination, which can increase the chance of defeating malicious nodes who aim to prevent good routes from being discovered. In addition, adaptive route rediscovery will be applied to determine when new routes should be discovered. HADOF can handle various attacks and introduces little overhead to the existing protocols. Both analysis and simulation studies have confirmed the effectiveness of HADOF.
Matrix rotation based signal design for differential unitary space-time modulation

In this paper, we consider the design of matrix rotation based (MRB) space-time signals based on the design criterion of minimizing the union bound on pairwise block error probability (PBEP). We further propose to design the signal parameters via noninteger searching to get better signals. Superiority of our improved design over the previous design are demonstrated through numerical calculations and performance simulations. With our proposed design for two transmit antennas and one or two receive antennas, we achieve the coding gain of about 1 dB over that of the previous design.
Component forensics

Visual sensor technologies have experienced tremendous growth in recent decades, and digital devices are becoming ubiquitous. Digital images taken by various imaging devices have been used in a growing number of applications, from military and reconnaissance to medical diagnosis and consumer photography. Consequently, a series of new forensic issues arise amidst such rapid advancement and widespread adoption of imaging technologies. For example, one can readily ask what kinds of hardware and software components as well as their parameters have been employed inside these devices? Given a digital image, which imaging sensor or which brand of sensor was used to acquire the image? How was the image acquired? Was it captured using a digital camera, cell phone camera, image scanner, or was it created artificially using an imageediting software? Has the image undergone any manipulation after capture? Is it authentic, or has it been tampered in any way? Does it contain any hidden information or steganographic data? Many of these forensic questions are related to tracing the origin of the digital image to its creation process. Evidence obtained from such analysis would provide useful forensic information to law enforcement, security, and intelligence agencies. Knowledge of image acquisition techniques can also help answer further forensic questions regarding the nature of additional processing that the image might have undergone after capture.
Belief-Assisted Pricing for Dynamic Spectrum Allocation in Wireless Networks with Selfish Users

In order to fully utilize the scarce spectrum resources, with the development of cognitive radio technologies, dynamic spectrum allocation becomes a promising approach to increase the efficiency of spectrum usage. In this paper, we consider the spectrum allocation in wireless networks with multiple selfish legacy spectrum holders and unlicensed users as multi-stage dynamic games. A belief-assisted dynamic pricing approach is proposed to optimize overall spectrum efficiency while keeping the participating incentives of the users based on double auction rules. Moreover, considering the budget constraints of the unlicensed users, a dynamic programming approach is further developed to optimize the spectrum allocation over time. The simulation results show that our proposed scheme not only approaches optimal outcomes with low overhead compared to general continuous double auction mechanisms, but also fully exploits the time diversity of spectrum resources when budget constraints exist
Learning and decision making with negative externality for opportunistic spectrum access

In cognitive radio networks, secondary users (SUs) are allowed to opportunistically exploit the licensed channels by sensing primary users' (PUs) activities. Once finding the spectrum holes, SUs generally need to share the available licensed channels. Therefore, one of the critical challenges for fully utilizing the spectrum resources is how the SUs obtain accurate information about the PUs' activities and make right decisions of accessing channels to avoid competition from other SUs. In this paper, we formulate SUs' learning and decision making process as a Chinese Restaurant Game by considering the scenario where SUs sense channels simultaneously and make access decisions sequentially. In the proposed game, SUs build the knowledge of the PUs' activities by their own sensing and learning the information from other SUs. They also predict their subsequent SUs' decisions to maximize their own utilities. We analyze the interactions among SUs in the proposed game and study specifically the impact of SUs' prior belief and sensing accuracy on their decisions. We also derive the theoretic results for the two-user two-channel case. Finally, we demonstrate the effectiveness and efficiency of the proposed scheme through simulations.
A parameter estimation scheme for damped sinusoidal signals based on low-rank Hankel approximation

Most of the existing algorithms for parameter estimation of damped sinusoidal signals are based only on the low-rank approximation of the prediction matrix and ignore the Hankel property of the prediction matrix. We propose a modified Kumaresan-Tufts (MKT) algorithm exploiting both rank-deficient and Hankel properties of the prediction matrix. Computer simulation results demonstrate that compared with the original Kumaresan-Tufts (1982) algorithm and the matrix pencil algorithm, the MKT algorithm has a lower noise threshold and can estimate the parameters of signal with larger damping factors.
Bandwidth efficient fingerprint multicast for video streaming

Digital fingerprinting embeds unique information in each distributed copy and can be used to protect multimedia from illegal redistribution. In video streaming applications, there are a large number of users and a huge amount of data to transmit. Thus, given a multimedia fingerprinting system with the required robustness, it is essential to distribute fingerprinted copies efficiently without revealing the embedded fingerprints. We propose a bandwidth efficient fingerprint multicast scheme that can be used with most spread spectrum embedding based multimedia fingerprinting systems, and analyze its bandwidth efficiency. We also propose a fingerprint drift compensation for the fingerprint multicast scheme to improve the quality of the reconstructed frames at the receiver's side without increasing the communication cost.
Distortion management of real-time MPEG-4 video over downlink multicode CDMA networks

In this paper, a protocol is designed to manage source rate/channel coding rate adaptation, code allocation, and power control to transmit real-time MPEG-4 FGS video over downlink multicode CDMA networks. We develop a fast adaptive scheme of distortion management to reduce the overall distortion received by all users subject, to the limited number of codes and maximal transmitted power. Compared with a modified greedy method in literature, our proposed algorithm can reduce the overall system's distortion by at least 45%.
Extrinsic Channel-Like Fingerprint Embedding for Authenticating MIMO Systems

A framework for introducing an extrinsic fingerprint signal to space-time coded transmissions at the physical layer is presented, where the fingerprint signal conveys a low capacity cryptographically secure authentication message of arbitrary length. The multi-bit digital fingerprint message conveyed by the fingerprint signal is available to all users within reception range and is used to authenticate the fingerprinted transmission. A novel approach is discussed where the fingerprint signaling mechanism mimics distortions similar to time-varying channel effects. Specifically, the fingerprint is detectable to receivers considering previous channel state information, but will be ignored by receivers equalizing according to current channel state information. Two example fingerprint signaling mechanisms and detection rules are presented based on pulse-amplitude keying and phase-shift keying approaches. The methods for obtaining the real (intrinsic) channel estimate, the extrinsic fingerprint message, and the primary transmission are analytically demonstrated using general pilot embedding schemes. The worst-case distortions caused by non-ideal equalization of a fingerprinted message are derived using the 2×2 Alamouti code. Simulation results including bit error rate (BER) and model mismatch error using a maximum-likelihood (ML) receiver are presented for both the primary and fingerprint signal, while authentication signal BERs lower than the primary signal are demonstrated.
Multipoint-to-point and point-to-multipoint space-time network coding

Traditional cooperative communications can improve communication reliability. However, the simultaneous transmissions from multiple relays are challenging in practice due to the issue of imperfect frequency and timing synchronization. In this work, we propose space-time network codes (STNCs) that overcome the issue of imperfect synchronization, reduce the large transmission delay, and still provide full spatial diversity in multipoint-to-point (M2P) and point-to-multipoint (P2M) transmissions. Relays form single linearly-coded signals from the overheard symbols and transmit them to the destination, where multiuser detection is utilized to detect the desired symbol. For a network of N client nodes, M2P and P2M STNCs result in a diversity order of N with only 2N time slots, a significant reduction from N2 time slots in traditional cooperative communications using TDMA.
Space-time network coding

Traditional cooperative communications can improve communication reliability. However, transmissions from multiple relay nodes are challenging in practice. Single transmissions in time-division multiple-access (TDMA) manner cause large transmission delay, but simultaneous transmissions from two or more nodes using frequency-division multiple access (FDMA) and code-division multiple access (CDMA) are associated with the issue of imperfect frequency and timing synchronization. In this work, a novel framework for cooperative communications is proposed to achieve full spatial diversity with low transmission delay and eliminate the issue of imperfect synchronization. This is realized by the use of space-time network codes (STNCs) associated with a novel concept of wireless network cocast. For a network of N client nodes, R relay nodes and a base node, the STNCs provide a diversity order of (R+1) for each symbol with (N+R) time slots, a reduction from 2N time slots in traditional FDMA and CDMA cooperative communications for N being usually greater than R and from N(R+1) time slots in traditional TDMA cooperative communications. The STNCs are also applied in networks, where the client nodes located in a cluster act as relays to help one another to improve their transmission performance. The performance in clustering setting is studied to show the improvement in power saving, range extension, and transmission rate.
Time-Reversal Tunneling Effects for Cloud Radio Access Network

The explosion of today's wireless traffic requires operators to deploy more access points (APs) and design efficient collaboration mechanism to alleviate the interference among them. However, the collaborative techniques cannot work efficiently due to the high latency and low bandwidth interface between the APs in traditional networks. To address this challenge, cloud radio access network (C-RAN) is proposed, where a pool of base band units (BBUs) are connected to the distributed remote radio heads (RRHs) via high bandwidth and low latency links (i.e., the front-haul) and are responsible for all the baseband processing. But the limited front-haul link capacity may prevent the C-RAN from fully utilizing the benefits made possible by the centralized baseband processing. As a result, the front-haul link capacity becomes a bottleneck. To address this challenge, in this work, we propose using the time-reversal (TR)-based communication as the air interface in C-RAN. Due to the unique spatial and temporal focusing effects of TR-based communications, multiple terminal devices (TDs) are naturally separated by their location-specific signatures. Such a property allows signals to be combined to deliver without demanding more bandwidth. Therefore, the TR-based communication in essence creates a “tunneling” effect such that the baseband signals for all the TDs can be efficiently combined and transmitted in the front-haul. We study the performance of the proposed C-RAN architecture in terms of spectral efficiency and front-haul rate, based on extensive measurements of the wireless channel in a real-world environment. It is shown that with nearly the same amount of traffic load in the front-haul, more information can be transmitted when there are more TDs. The proposed TR tunneling effect can help deliver more information in the C-RAN and alleviate the burden of the front-haul caused by network densification.
An Information Secrecy Game in Cognitive Radio Networks

Although cognitive radio technology improves efficiency of spectrum utilization, primary users usually do not gain from opening up the spectrum in the opportunistic spectrum access, and sometimes even suffer from collisions due to secondary users' imperfect spectrum sensing. However, in this paper, we show that if information secrecy is a concern, primary users could actually be better off by allowing secondary users to cooperatively share the spectrum. Specifically, we propose a new cooperation paradigm in cognitive radio networks that primary users improve secrecy with the help of trustworthy secondary users, in the presence of an intelligent and passive eavesdropper attempting to decode primary users' messages. After deriving the achievable pair of primary users' secrecy rate and secondary users' transmission rate under various circumstances, we model the interaction between primary users and secondary users as a Stackelberg game in which transmission power levels are the key to maximize data rates. Moreover, based on a 2-D representation of how achievable rates depend on power-level regions, we apply equilibrium analysis to understand the optimal strategy of primary and secondary users. Finally, simulation results are presented to verify the performance.
Mitigating channel estimation error via cooperative communications

Channel estimation error problem is among the main causes of performance degradation in wireless networks. In this paper, we investigate the impact of cooperative communications on mitigating the effect of channel estimation error. Two main performance criteria, namely, the traditional outage probability and the proposed signal-to-noise ratio (SNR) gap ratio, are utilized to characterize such impact. The SNR gap ratio measures the reduction in the SNR due to channel estimation error. Taking into consideration the channel estimation error, we show that the outage probability is reduced by utilizing cooperative transmission. We also show that cooperative transmission results in lower SNR gap ratio compared to that of the direct transmission. Thus, cooperative transmission is less susceptible to the effect of channel estimation error compared to direct transmission. Finally, we illustrate that increasing the number of cooperating relays reduces the effect of the channel estimation error more.
An evolutionary game-theoretic approach for image interpolation

In this paper, we study the image interpolation from the game theoretic perspective and formulate the image interpolation problem as an evolutionary game. In this evolutionary game, the players are the unknown high resolution pixels and the pure strategies of the players are the corresponding low resolution neighbors. By regarding the non-negative weights of the low resolution pixels as the probabilities of selecting the pure strategies, the problem of estimating the high resolution pixels becomes finding the evolutionarily stable strategies for the evolutionary game. Experimental results show that the proposed game theoretical approach can achieve better performance than the state-of-the-art image interpolation methods in terms of both PSNR and visual quality.
2-D spatial smoothing for multipath coherent signal separation

The use of two-dimensional spatial smoothing (SS) to increase channel capacity of wireless communications system is discussed, The necessary and sufficient conditions on array configuration for applying SS to multiple signal classification (MUSIC), and adaptive beamforming algorithms are defined and proved, This array must have an orientational invariance structure with an ambiguity free center array, and the number of subarrays must be larger than or equal to the size of the largest group of coherent signals. We also studied the cause of ambiguities in a multipath environment. We found the necessary and sufficient conditions for a three-sensor array manifold to be ambiguity free and identified several higher order ambiguity situations, If an array is also central symmetric, the forward/backward SS (FBSS) can be used to improve the resolution. Finally, we extended our results to the estimation of signal parameters via rotational invariance techniques (ESPRIT). All the predicted results are verified by simulations.
Generic network cost minimization: A decentralized Newton's method

In this work, we examine a generic network cost minimization problem, in which every node has a local decision vector to optimize. Each node incurs a cost associated with its decision vector while each link incurs a cost related to the decision vectors of its two end nodes. All nodes collaborate to minimize the overall network cost. The formulated network cost minimization problem has broad applications in distributed signal processing and control, in which the notion of link costs often arises. To solve this problem in a decentralized manner, we develop a distributed variant of the Newton's method. The proposed method is based on an appropriate splitting of the Hessian matrix and an approximation of its inverse, which is used to determine the Newton step. Global linear convergence of the proposed algorithm is established and a quadratic convergence phase of the algorithm over a certain time interval is identified. Finally, numerical simulations are conducted to validate the effectiveness of the proposed algorithm and its superiority over other first order methods, especially when the cost functions are ill-conditioned.