nils-herrmann/clean_scirepeval huggingface dataset:
Scalable Video Multicasting: A Stochastic Game Approach With Optimal Pricing

Heterogeneous multimedia content delivery over wireless networks is an important yet challenging issue. One of the challenges is maintaining the quality of service due to scarce resources in wireless communications and heavy loadings from heterogeneous demands. A promising solution is combining multicasting and scalable video coding (SVC) techniques via cross-layer design, which has been shown to effectively enhance the quality of multimedia content delivery service in the literature. Nevertheless, most existing works on SVC multicasting system focus on the static scenarios, where a snapshot of user demands is given and remains the same. In addition, the economic value of the SVC multicasting system, which is an important issue from the service provider's perspective, has seldom been explored. In this paper, we study a subscription-based SVC multicasting system with stochastic user arrival and heterogeneous user preferences. A stochastic framework based on the multidimensional Markov decision process (M-MDP) is proposed to study the negative network externality existing in the proposed system and theoretically evaluate the corresponding system efficiency. A game-theoretic analysis is conducted to understand the rational demands from heterogeneous users under different subscription pricing schemes. By transforming the original dynamic and complex M-MDP revenue optimization problem into a traditional average-reward MDP problem, we show that the optimal pricing strategy that maximizes the expected revenue of the service provider can be derived efficiently. Moreover, the overall user's valuation on the system, e.g., social welfare, is maximized under such an optimal pricing strategy. Finally, the efficiency of the proposed solutions is evaluated through simulations.
Evolutionary social information diffusion analysis

Nowadays, social networks are extremely large-scale with tremendous information flows, where understanding how the information diffuse over social networks becomes an important research issue. Most of the existing works on information diffusion analysis are based on either network structure modeling or empirical approach with dataset mining. However, the information diffusion is also heavily influenced by network users' decisions, actions and their socio-economic connections, which is generally ignored by existing works. In this paper, we propose an evolutionary game theoretic framework to model the dynamic information diffusion process in social networks. To verify our theoretical analysis, we conduct experiments by using Facebook network and real-world information spreading dataset of Memetracker. Experiment results show that the proposed game theoretic framework is effective and practical in modeling the social network users' information forwarding behaviors.
Nonintrusive component forensics of visual sensors using output images

Rapid technology development and the widespread use of visual sensors have led to a number of new problems related to protecting intellectual property rights, handling patent infringements, authenticating acquisition sources, and identifying content manipulations. This paper introduces nonintrusive component forensics as a new methodology for the forensic analysis of visual sensing information, aiming to identify the algorithms and parameters employed inside various processing modules of a digital device by only using the device output data without breaking the device apart. We propose techniques to estimate the algorithms and parameters employed by important camera components, such as color filter array and color interpolation modules. The estimated interpolation coefficients provide useful features to construct an efficient camera identifier to determine the brand and model from which an image was captured. The results obtained from such component analysis are also useful to examine the similarities between the technologies employed by different camera models to identify potential infringement/licensing and to facilitate studies on technology evolution
A game-theoretic modeling of popularity dynamics

In the big data era, numerous items such as online memes and videos are generated everyday, some of which go viral, i.e., attract lots of attention, while most diminish quickly without any influence. The recorded people's interactions with these items constitute a rich amount of popularity dynamics, e.g., hashtags' mention count dynamics. It is crucial to understand the underlying mechanisms of popularity dynamics in order to utilize the valuable attention of people efficiently. In this work, we propose a game-theoretic model to analyze and understand popularity dynamics. The model takes into account both the instantaneous incentives and long-term incentives during people's decision making process. We analyze the equilibrium of the game and show several properties at the equilibrium, which confirm with the observations from real data. By using simulations as well as experiments based on real-world popularity dynamics data, we validate the effectiveness of the theory. We find that our theory can fit the real data well and can even predict the future dynamics.
Distributed cooperative routing algorithms for maximizing network lifetime

In this paper, we study the impact of cooperative routing for maximizing the network lifetime in sensor network applications. We assume nodes in the network are equipped with a single omnidirectional antenna and they perform cooperative transmission to achieve transmit diversity. We propose a joint cooperative transmission and energy aware routing algorithm to prolong the network lifetime. In contrast to the previous works, our approach uses the maximum lifetime power allocation, instead of minimum power allocation. Using the maximum lifetime power allocation, the cooperative nodes allocate their transmit power according to the channel condition and the residual energy in the nodes. Our proposed scheme combines the maximum lifetime power allocation and the energy aware routing to maximize the network lifetime. We study the performance of the cooperative routing in terms of network lifetime (defined as the time until the first node dies) and the total delivered packets before the first node dies. We demonstrate that the proposed solution achieves 1 ~ 3.5 and 1 ~ 2 times longer network lifetime and more total delivered packets compared to noncooperative routing, when it is used with MTE and FA algorithms, respectively. Furthermore, the maximum lifetime power allocation achieves 1 ~ 2 times longer lifetime, compared to minimum power allocation in MTE and FA routing schemes. We also provide distributed implementation of the proposed algorithm
Information theoretic framework of trust modeling and evaluation for ad hoc networks

The performance of ad hoc networks depends on cooperation and trust among distributed nodes. To enhance security in ad hoc networks, it is important to evaluate trustworthiness of other nodes without centralized authorities. In this paper, we present an information theoretic framework to quantitatively measure trust and model trust propagation in ad hoc networks. In the proposed framework, trust is a measure of uncertainty with its value represented by entropy. We develop four Axioms that address the basic understanding of trust and the rules for trust propagation. Based on these axioms, we present two trust models: entropy-based model and probability-based model, which satisfy all the axioms. Techniques of trust establishment and trust update are presented to obtain trust values from observation. The proposed trust evaluation method and trust models are employed in ad hoc networks for secure ad hoc routing and malicious node detection. A distributed scheme is designed to acquire, maintain, and update trust records associated with the behaviors of nodes' forwarding packets and the behaviors of making recommendations about other nodes. Simulations show that the proposed trust evaluation system can significantly improve the network throughput as well as effectively detect malicious behaviors in ad hoc networks.
Throughput maximization for energy efficient multi-node communications using actor-critic approach

We investigate the problem of average throughput maximization per total expended energy in packetized multinode wireless sensor communications. We consider a CDMA like multiple access scenario where multi transmitters are communicating with one receiving node. Since the transmitting nodes are typically distributed in different locations for wireless sensor applications, a good transmission strategy should be employed in each node to maximize throughput per unit energy in the node. We propose to use a distributed actor-critic algorithm to independently learn a good transmission strategy for each transmitting node. The resulting strategy adapts to the incoming traffic rate, buffer condition, and channel condition, which is influenced by both the location of the transmitting node and the other nodes' transmission strategy. Our proposed method achieves 1.5 to 6 times throughput per energy compared to the simple constant signal to interference ratio (CSIR) policy, particularly in high packet arrival. Moreover, the proposed algorithm is robust in tracking packet arrival rate variation.
Power allocation for OFDM using adaptive beamforming over wireless networks

The performance of a multiuser wireless network using orthogonal frequency-division modulation (OFDM), combined with power control and adaptive beamforming for uplink transmission is presented here. A network-wide adaptive power control algorithm is used to achieve the desired signal-to-interference-and-noise-ratio at each OFDM subcarrier and increase the power efficiency of the network. As a result, we can achieve a better overall error probability for a fixed total transmit power. With the assumption of fixed-modulation for all subcarriers, transmit powers and beamforming weight vectors at each subcarrier are updated jointly, using an iterative algorithm that converges to the optimal solution for the entire network. Unlike most of the loading algorithms, this approach considers fixed bit allocation and optimizes the power allocation and reduces the interference for the entire network, rather than a single transmitter. We also propose joint time-domain beamforming and power control to reduce the complexity resulting from the number of beamformers and fast Fourier transformed blocks. The proposed algorithm is also extended to COFDM and we show that it improves the performance of those systems.
Repeated spectrum sharing game with self-enforcing truth-telling mechanism

Dynamic spectrum access has become a promising approach that can coordinate different users' access to adapt to spectrum dynamics to improve spectrum efficiency. However, users competing for an open spectrum may have no incentive to cooperate with each other, and they may even exchange false private information about their channel conditions in order to get more access to the spectrum. Therefore, in this paper, we propose a self-enforcing truth-telling mechanism by modeling the distributed spectrum access as a repeated game. In this game, if any greedy user deviates from cooperation, punishment will be triggered. Through the Bayesian mechanism design, users have no incentive to reveal false channel conditions, and the competing users are enforced to cooperate with each other honestly. The simulation results show that the proposed scheme can greatly improve the spectrum efficiency by alleviating mutual interference; furthermore, the best strategy for each user is demonstrated to be reporting the actual channel condition.
Cost-effective low-power architectures of video coding systems

A new low-power design technique, multirate, has been used along with other methods such as look-ahead and pipelining in designing the cost-effective low-power architectures of video coding systems. We demonstrate both low-power and high-speed can be accomplished at algorithm/architecture level. Based on the calculation and simulation results, the design can achieve significant power saving in the range of 60%-80% or speedup factor of two depending on the needs of users.
Time-Reversal Division Multiple Access in Multi-Path Channels

Multi-path effect makes high speed broadband communications a very challenging task due to the severe inter-symbol interference (ISI). By concentrating energy in both spatial and temporal domains, time-reversal (TR) transmission technique provides a great potential of low-complexity energy-efficient communications. In this paper, we develop a new concept of time-reversal division multiple access (TRDMA) as a wireless channel access method based on its high-resolution spatial focusing effect. We propose to use TR structure in a multi-user downlink system over large delay spread channels, where the signals of different users are separated solely by TRDMA. Both the single-transmit-antenna scheme and its enhanced version with multiple-transmit-antenna are developed and evaluated in this paper. We investigate the system performance in terms of the effective SINR and the achievable sum rate of the multi-user system. It is shown in both analytical and simulation results that satisfying performances can be achieved in the proposed TRDMA multi-user downlink system.
WLC21-6: Protocol-Aware Design Criteria and Performance Analysis for Distributed Space-Time Coding

In this paper, we consider the design of distributed space-time codes for wireless networks. Distributed space-time coding (DSTC) can be achieved through node cooperation to emulate multiple transmit antennas. We derive the distributed space-time codes design criteria for different scenarios based on the pairwise error probability (PEP) analysis. First, we consider the decode-and-forward (DAF) protocol and prove that space-time codes, designed to achieve full diversity and maximum coding gain in the MIMO channels, will achieve full diversity but not necessarily maximizing the coding gain if used with the DAF protocol. Next, we consider the amplify-and-forward (AAF) protocol and prove that a space-time code designed to achieve full diversity and maximum coding gain in MIMO channels will achieve the same if used with the AAF protocol.
Differential Modulation With Threshold-Based Decision Combining for Cooperative Communications

Differential modulation is widely known as a practical alternative that provides a good tradeoff between receiver complexity and performance. However, the available differential schemes for wireless relay networks require perfect synchronization and/or provide limited transmission rates. This paper proposes a threshold-based differential decode-and-forward cooperative scheme that not only alleviates the problems of synchronization and rate limitation, but also efficiently exploits the cooperative relay channels via the use of a predetermined decision threshold. In the proposed scheme, the source information is forwarded by the relay only if it is correctly decoded. The properly designed threshold enables the destination to decide whether the received signal from the relay contains information such that the received signals from the source and the relay can be efficiently combined and jointly decoded. Bit error rate (BER) performance analysis of the proposed scheme is analyzed in the case of differential M-ary PSK signals. The analysis focuses on the case when the relay is able to judge whether each decoded symbol is corrected or not. The obtained BER performance in this case serves as a performance benchmark, and the proposed differential decode-and-forward scheme can achieve it in an ideal situation that the error propagation at the relay can be negligible. A tight BER approximation is first derived, and then BER upper bound and lower bound are determined. Based on the tight BER approximation, joint optimum decision threshold and power allocation are numerically evaluated. Both analytical and simulation results reveal that the decision threshold and the power allocation depend on qualities of the communication channels. Interestingly, when the link quality between relay and destination is very good, the effect of the threshold dominates the effect of the power allocation at high signal-to-noise ratio. Extensive simulation results are provided to validate the merit of the proposed scheme and confirm the theoretical analysis.
Stable Throughput Region and Admission Control for Device-to-Device Cellular Coexisting Networks

Device-to-device (D2D) communication is proposed as a vital technique to enhance system capacity in cellular networks, which requires efficient interference modeling and managements to improve spectral efficiency. In practice, even when two wireless connections share the same resources, the interference between them may not always exist if there is no conflict at packet-level transmissions. To explore the real effect of interference, in this paper, we establish a cross-layer model for D2D communications underlaying cellular network and derive the closed-form stable throughput region. Then, we formulate an optimization problem to obtain the maximal achievable packet rate for cellular link, which determines whether the D2D pair can share the same resources with a specific cellular link. By dividing the original optimization problem into several simplified subproblems, the optimal solution can be calculated with low complexity. Subsequently, our model is extended to a generalized scenario where multiple D2D pairs share the same resources with one cellular link. Due to the complexity of obtaining closed-form expressions on stable throughput regions, we propose an algorithm to determine whether the transmissions of the cellular link and the multiple D2D pairs can satisfy the QoS requirements simultaneously. Furthermore, a low-complexity dynamic admission control strategy is introduced to deal with the admission process for new D2D requests. As a consequence, the cellular spectrum can allow access of many more D2D pairs than what the conventional model can. The significant improvements are verified by numeral simulations.
Connectivity-Aware Network Maintenance via Relays Deployment

In this paper, we address the network maintenance problem, in which we aim to maximize the lifetime of a sensor network by adding a set of relays to it. The network lifetime is defined as the time until the network becomes disconnected. The Fiedler value, which is the algebraic connectivity of a graph, is used as an indicator of the network health. The network maintenance problem is formulated as a standard semi- definite programming (SDP) optimization problem that can be solved efficiently in polynomial time. First, we present a network maintenance algorithm that obtains the near-optimum locations for a given set of relays. Second we propose a routing algorithm, namely, Weighted Minimum Power Routing (WMPR) algorithm, that significantly increases the network lifetime due to the efficient utilization of the deployed relays. Third, we propose an adaptive network maintenance algorithm that relocates the deployed relays based on the network health indicator. Finally, we consider the network repair problem, in which we find the minimum number of relays along with their near-optimum locations to reconnect a disconnected network. We propose an iterative network repair algorithm that utilizes the network maintenance algorithm.
Undetectable image tampering through JPEG compression anti-forensics

Recently, a number of digital image forensic techniques have been developed which are capable of identifying an image's origin, tracing its processing history, and detecting image forgeries. Though these techniques are capable of identifying standard image manipulations, they do not address the possibility that anti-forensic operations may be designed and used to hide evidence of image tampering. In this paper, we propose an anti-forensic operation capable of removing blocking artifacts from a previously JPEG compressed image. Furthermore, we show that by using this operation along with another anti-forensic operation which we recently proposed, we are able to fool forensic methods designed to detect evidence of JPEG compression in decoded images, determine an image's origin, detect double JPEG compression, and identify cut-and-paste image forgeries.
Repeated open spectrum sharing game with cheat-proof strategies

Dynamic spectrum access has become a promising approach to improve spectrum efficiency by adaptively coordinating different users' access according to spectrum dynamics. However, users who are competing with each other for spectrum may have no incentive to cooperate, and they may even exchange false private information about their channel conditions in order to get more access to the spectrum. In this paper, we propose a repeated spectrum sharing game with cheat-proof strategies. By using the punishment-based repeated game, users get the incentive to share the spectrum in a cooperative way; and through mechanism-design-based and statistics-based approaches, user honesty is further enforced. Specific cooperation rules have been proposed based on the maximum total throughput and proportional fairness criteria. Simulation results show that the proposed scheme can greatly improve the spectrum efficiency by alleviating mutual interference.
Systematic space-time trellis code construction for correlated Rayleigh-fading channels

The potential for capacity increase in multiple-antenna wireless communication systems has drawn considerable attention to space-time codes. However, most of the existing space-time code construction methods have assumed ideal channel models: either quasi-static fading or fast fading. In this work, we propose a systematic space-time trellis code construction method for correlated fading channels. We derive the performance criteria that take into account both spatial and temporal channel correlation, assuming that the space-time correlation matrix is of full rank. Moreover, we introduce a new design criterion and analyze the properties of the space-time trellis codes satisfying the proposed criterion. Using the design criterion, we develop a code construction procedure that jointly considers diversity advantage and coding advantage for an arbitrary number of transmit antennas and any memoryless modulation. The flexibility of the proposed code construction method is demonstrated by designing space-time trellis codes for two, three, and four transmit antennas with quaternary phase-shift keying (QPSK), 8PSK (phase-shift keying), and 4ASK (amplitude-shift keying) modulations. The simulation results demonstrate that not only can our method generate new codes for an arbitrary number of antennas, but in some special cases, where previously proposed codes exist, our codes also perform very well.
A fast sphere decoding framework for space-frequency block codes

In order to make the multi-antenna OFDM systems an attractive choice for practical applications, implementation issues such as decoding complexity must be addressed successfully. In this paper, we propose a computationally efficient decoding algorithm for space-frequency block codes. The central part of the algorithm is a complex-domain, modulation-independent sphere decoding framework. The simulation results demonstrate that the proposed algorithm can significantly reduce the decoding complexity. For the 64 QAM modulation, we observe up to about 73% reduction in the required FLOP count per code block compared to the previously proposed methods without noticeable performance degradation.