nils-herrmann/clean_scirepeval huggingface dataset:
Multiband differential modulation for UWB communication systems

In this paper, we propose a differential encoding and decoding scheme for multiband UWB systems. The proposed scheme incorporates frequency-domain differential en/decoding with the hopping multiband OFDM modulation. To capture the effect of multipath-rich clustering property of UWB channels, we characterize the pairwise error probability performance of the proposed scheme in terms of cluster and ray arrival rates. It turns out that the diversity advantage does not strongly depend on the random-clustering of UWB channels, and we can achieve the same diversity gain in different channel environments. However, the system performance relies on the clustering behavior through the coding gain. Simulation results show that the proposed differential scheme achieves good performance in the short-range line-of-sight scenarios. In addition, the jointly encoded differential multiband UWB scheme is able to yield superior performance to the uncoded coherent multiband UWB system at high SNR
Parallel programmable video co-processor design

Modern video applications call for computationally intensive data processing at very high data rate. In order to meet the high-performance/low-cost constraints, the state-of-the-art video processor should be a programmable design which performs various tasks in video applications without sacrificing the computational power and the manufacturing cost in exchange for such flexibility. In this paper, we present a programmable video co-processor design that is capable of performing FIR/IIR filtering, subband filtering, and most discrete orthogonal transforms (DT), for the host processor in video applications. The computational speed of this co-processor is as fast as that of ASIC designs which are optimized for individual specific applications. We also show that the system can be easily reconfigured to perform multirate FIR/IIR/DT operations at negligible hardware overhead. Hence, we can either double the processing speed on the fly based on the same processing elements, or apply this feature to the low-power implementation of this co-processor.
On Outage Probability for Two-Way Relay Networks With Stochastic Energy Harvesting

In this paper, we propose an optimal relay transmission policy by using a stochastic energy harvesting (EH) model for the EH two-way relay network, wherein the relay is solar-powered and equipped with a finite-sized battery. In this policy, the long-term average outage probability is minimized by adapting the relay transmission power to the wireless channel states, battery energy amount, and causal solar energy states. The designed problem is formulated as a Markov decision process (MDP) framework, and conditional outage probabilities for both decode-and-forward (DF) and amplify-and-forward (AF) cooperation protocols are adopted as the reward functions. We uncover a monotonic and bounded differential structure for the expected total discounted reward, and prove that such an optimal transmission policy has a threshold structure with respect to the battery energy amount in sufficiently high SNRs. Finally, the outage probability performance is analyzed and an interesting saturated structure for the outage performance is revealed, i.e., the expected outage probability converges to the battery empty probability in high SNR regimes, instead of going to zero. Furthermore, we propose a saturation-free condition that can guarantee a zero outage probability in high SNRs. Computer simulations confirm our theoretical analysis and show that our proposed optimal transmission policy outperforms other compared policies.
Fairness dynamics in multimedia colluders’ social networks

Multimedia social network analysis is a research area with growing importance, in which the social network members share multimedia contents with all different purposes and analyzing their behavior help design more secured and efficient multimedia and networking systems. In this paper, we focus on multimedia fingerprinting social network, in which multi-user collusion being a powerful attack, where a group of attackers collectively undermine the traitor tracing capability. During collusion, different colluders have different objective thus, the colluders form a social network and an how to achieve agreement on distributing the risk/profit among colluders and ensure fairness of the attack is a crucial question. This paper models the dynamics among colluders as a non-cooperative game, propose a general model of utility functions and study four different bargaining solutions of this game.
Data-driven stochastic scheduling for solar-powered sensor communications

This paper presents a data-driven approach of finding optimal scheduling policies for a solar-powered sensor node that attempts to maximize net bit rates by adapting its transmission to the changes of channel fading and battery recharge. The problem is formulated as a discounted Markov decision process (MDP) framework, whereby the energy harvesting process is stochastically quantized into several representative solar states with distinct energy arrivals and is totally driven by historical data records at a sensor node. We evaluate the average net bit rate of the optimal transmission scheduling policy, and computer simulations show that the proposed policy significantly outperforms other schemes with or without the knowledge of short-term energy harvesting and channel fading patterns.
Renewal-theoretical dynamic spectrum access in cognitive radio network with unknown primary behavior

Dynamic spectrum access in cognitive radio networks can greatly improve the spectrum utilization efficiency. Nevertheless, interference may be introduced to the Primary User (PU) when the Secondary Users (SUs) dynamically utilize the PU's licensed channels. If the SUs can be synchronous with the PU's time slots, the interference is mainly due to their imperfect spectrum sensing of the primary channel. However, if the SUs have no knowledge about the PU's exact communication mechanism, additional interference may occur. In this paper, we propose a dynamic spectrum access protocol for the SUs confronting with unknown primary behavior and study the interference caused by their dynamic access. Through analyzing the SUs' dynamic behavior in the primary channel which is modeled as an ON-OFF process, we prove that the SUs' communication behavior is a renewal process. Based on the Renewal Theory, we quantify the interference caused by the SUs and derive the corresponding closed-form expressions. With the interference analysis, we study how to optimize the SUs' performance under the constraints of the PU's communication quality of service (QoS) and the secondary network's stability. Finally, simulation results are shown to verify the effectiveness of our analysis.
An efficient cooperation protocol to extend coverage area in cellular networks

In this paper, we propose a bandwidth efficient cooperation protocol to extend coverage area in cellular networks. An important question, however, in implementing any cooperation protocol is how to assign cooperating partners. We introduce a BS-controlled relay-assignment algorithm to assign cooperating users. First, we derive a lower bound on the outage performance of any practical relay assignment protocol. The lower bound can be achieved by a hypothetical Genie-aided protocol that places a relay at the optimal theoretical location for every source in the network. Then we describe and analyze the performance of the base-station/access-point (BS/AP) controlled protocol. The BS/AP-controlled protocol can be implemented at the BS or the AP, and it tries to emulate the Genie-aided protocol. Simulation results for rural cellular systems are provided. By utilizing the proposed protocol, simulation results indicate a significant gain in coverage area over the direct transmission scheme under fairly the same bandwidth efficiency and fixed average transmitted power. For the rural cellular system case, coverage extension of about 250% can be achieved by the BS/AP-controlled protocol
A computationally efficient and secure time scheme for wireless applications

Wireless mobile computing devices are used extensively to access the Internet for critical applications and services, which must be secured by computationally efficient algorithms and schemes. Computationally efficient security schemes, however, require accurate time synchronization between client and application servers, which is very challenging due to its susceptibility to stochastic noise on the transmission path and to message delay attacks where an adversary can intentionally delay measurement messages in order to compromise the scheme. In statistically noisy networks, accurate time synchronization requires filtering of a large number of measurements to reduce stochastic noise. Each measurement must be secured and, therefore, computationally efficient schemes are required to facilitate mobile computing. Efficient security schemes are also required to detect message delay attacks and to authenticate synchronization message sources (e.g. multicast host server and clients). We propose a computationally efficient time synchronization scheme, which achieves accurate and reliable time clock-offset estimates from a single measurement. This approach is based on a per node quality of service scheme, which can be easily incorporated into existing and emerging quality of service scheduling disciplines. It is designed to reduce stochastic noise by providing per node delay guarantee for synchronization. We also propose an efficient and reliable scheme to detect message delay attack. The proposed scheme compares synchronization messages round trip delay with predefined thresholds to ensure that they fall within expected limits, otherwise they are discarded.
Attack-resistant cooperation stimulation in autonomous ad hoc networks

In autonomous ad hoc networks, nodes usually belong to different authorities and pursue different goals. In order to maximize their own performance, nodes in such networks tend to be selfish, and are not willing to forward packets for the benefits of other nodes. Meanwhile, some nodes might behave maliciously and try to disrupt the network and waste other nodes' resources. In this paper, we present an attack-resilient cooperation stimulation (ARCS) system for autonomous ad hoc networks to stimulate cooperation among selfish nodes and defend against malicious attacks. In the ARCS system, the damage that can be caused by malicious nodes can be bounded, the cooperation among selfish nodes can be enforced, and the fairness among nodes can also be achieved. Both theoretical analysis and simulation results 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.
Attacks on Trust Evaluation in Distributed Networks

Evaluation of trustworthiness of participating entities is an effective method to stimulate collaboration and improve network security in distributed networks. Similar to other security related protocols, trust evaluation is an attractive target for adversaries. Currently, the vulnerabilities of trust evaluation system have not been well understood. In this paper, we present several attacks that can undermine the accuracy of trust evaluation, and then develop defense techniques. Based on our investigation on attacks and defense, we implement a trust evaluation system in ad hoc networks for securing ad hoc routing and assisting malicious node detection. Extensive simulations are performed to illustrate various attacks, the effectiveness of the proposed defense techniques, and the overall performance of the trust evaluation system.
Dynamic Chinese Restaurant Game: Theory and Application to Cognitive Radio Networks

Users in a social network are usually confronted with decision making under uncertain network state. While there are some works in the social learning literature on how to construct belief on an uncertain network state, few study has been made on integrating learning with decision making for the scenario where users are uncertain about the network state and their decisions influence with each other. Moreover, the population in a social network can be dynamic since users may arrive at or leave the network at any time, which makes the problem even more challenging. In this paper, we propose a Dynamic Chinese Restaurant Game to study how a user in a dynamic social network learns the uncertain network state and make optimal decision by taking into account not only the immediate utility but also subsequent users' negative influence. We introduce a Bayesian learning based method for users to learn the network state, and propose a Multi-dimensional Markov Decision Process based approach for users to achieve the optimal decisions. Finally, we apply the Dynamic Chinese Restaurant Game to cognitive radio networks and demonstrate from simulations to verify the effectiveness and efficiency of the proposed scheme.
Adaptive lifting coding scheme for video scene changes

The lifting scheme is used as a motivational tool for designing a better temporal subband scheme in video coding. The new subband coding scheme replaces the typical Haar filterbank. A simple criterion is used for the detection of scene changes in video sequences, and a modification to the Haar lifting scheme is developed that allows for adjusting the filterbank near a scene change. The new edge adaptive lifting scheme is applied to a scene change in video data and achieves improved performance at scene change frames when compared with the lifting Haar filterbank.
Low-complexity OFDMA channel allocation with Nash bargaining solution fairness

A fair and simple scheme to allocate subcarrier, rate, and power for multiuser OFDMA systems is considered. The problem is to maximize the overall system rate, under each user's maximal power and minimal rate constraints, while considering the fairness among users. The approach proposes the fairness and low complexity implementation based on Nash bargaining solutions and coalitions. First, a two-user algorithm is developed to bargain subcarrier usage between both users. Based on this algorithm, we develop a multiuser bargaining algorithm where optimal coalition pairs among users are constructed. Simulation results show that the proposed algorithms not only provide fair resource allocation among users, but also have comparable overall system rate with the scheme maximizing the total rate without considering fairness. They also have much higher rates than the scheme with max-min fairness. The proposed algorithms have complexity O(NlogN), where N is the number of subcarriers.
Lifetime maximization via cooperative nodes and relay deployment in wireless networks

Extending lifetime of battery-operated devices is a key design issue that allows uninterrupted information exchange among distributed nodes in wireless networks. Cooperative communications has recently emerged as a new communication paradigm that enables and leverages effective resource sharing among cooperative nodes. In this paper, a general framework for lifetime extension of battery-operated devices by exploiting cooperative diversity is proposed. The framework efficiently takes advantage of different locations and energy levels among distributed nodes. First, a lifetime maximization problem via cooperative nodes is considered and performance analysis for M-ary PSK modulation is provided. With an objective to maximize the minimum device lifetime under a constraint on bit-error-rate performance, the optimization problem determines which nodes should cooperate and how much power should be allocated for cooperation. Since the formulated problem is NP hard, a closed-form solution for a two-node network is derived to obtain some insights. Based on the two-node solution, a fast suboptimal algorithm is developed for multi-node scenarios. Moreover, the device lifetime is further improved by a deployment of cooperative relays in order to help forward information of the distributed nodes in the network. Optimum location and power allocation for each cooperative relay are determined with an aim to maximize the minimum device lifetime. A suboptimal algorithm is developed to solve the problem with multiple cooperative relays and cooperative nodes. Simulation results show that the minimum device lifetime of the network with cooperative nodes improves 2 times longer than the lifetime of the non-cooperative network. In addition, deploying a cooperative relay in a proper location leads up to 12 times longer lifetime than that of the non-cooperative network.
Dynamic Frequency-Intelligent Reserve-and-Switch Technique (D-FIRST) to Combat Inter-Operator Interference

In this paper, a spectrum sharing scheme that will coordinate among different co-existing cellular operators competing for the same spectrum band is proposed. Based on this scheme, the cell of an operator can be divided into several sub-regions, and mobile stations (MSs) inside each sub-region form one subset. The whole frequency band assigned to a cell is partitioned into slots dedicated to the subsets based on the quality of service (QoS) demand. When interference from other operators is detected, the victim operator can switch the frequency of the interfered MSs with the MSs in the safe region, and/or switch to the reserved band. In this way, the inter-operator interference (IOI) can be reduced. From the simulation results, it is shown that with the proposed protocol, the total power consumption of both operators can be reduced significantly. Furthermore, it has been demonstrated that in order to reduce the IOI in a high-density area, the operator should reserve more bandwidth for potential frequency-switching.
Risk-distortion analysis for video collusion attack

Collusion attack is a cost-effective attack against digital fingerprint. To develop an efficient collusion-resistant fingerprint scheme, it is very important for the detector to study the behavior of the colluders and the performance of collusion attack. Although several prior works have been proposed in the literature to analyze the performance of collusion attack, few effort has been made to explicitly study the relationship between risk, i.e., the probability of the colluders to be detected, and distortion of collusion attack. In this paper, we investigate the risk-distortion relationship of the linear video collusion attack with Gaussian fingerprint. We formulate the optimal linear collusion attack as an optimization problem, where the colluders try to minimize the distortion subject to a risk constraint. For any fixed risk constraint, the optimal distortion can be found using numerical optimization methods. By varying the risk constraint, we can obtain the risk-distortion model. We also conduct experiments to verify the proposed risk-distortion model using real video data.
Optimal rate control in wireless networks with fading channels

A dynamic programming optimization method is used to obtain the optimal rate control policy in a wireless network with fading channel. In a wireless network it is assumed that the base station is capable of transceiving data packets at two rates, either R/sub h/ or R/sub l/ (R/sub h/>R/sub l/). An optimal policy is derived which jointly minimizes the transmission delay and the number of rate switchings in the network. Numerical results indicate that by sacrificing only 1% of transmission quality in terms of the average delay one can achieve more than 50% reduction in switching load of the network. Our analytical as well as numerical results confirm that the optimal policy is a threshold policy.
Statistical Learning Over Time-Reversal Space for Indoor Monitoring System

As embedded in wireless signals, information of an indoor environment is captured during radio propagation, motivating the development of emerging wireless sensing technologies. In this paper, we propose a smart radio system that leverages the informative wireless radios to enable intelligent environment and extend human senses to perceive the world. In particular, owing to the time-reversal (TR) technique that captures changes in multipath profiles, the proposed TR indoor monitoring system (TRIMS) is capable of monitoring indoor events and detecting motion through walls in real time. A statistic model of intraclass TR resonance strength is developed and treated as the feature for TRIMS. Moreover, a prototype of TRIMS is implemented using commercial WiFi devices with three antennas. We investigate the performance of TRIMS in different single family houses with normal resident activities. In general, TRIMS can have a perfect detection rate with almost zero false alarm rates for seven target events, whereas during a two-week experiment TRIMS achieves a detection rate of 95.45% in the indoor multievent monitoring. The proposed TRIMS illustrates the potential of smart radio applications in smart homes, thanks to the ubiquitous WiFi.
Risk minimization in traitors within traitors in multimedia forensics

In digital fingerprinting and multimedia forensic systems, it is possible that multiple adversaries mount attacks collectively and effectively to undermine the forensic system's traitor tracing capability. During this collusion attack, an important issue that the adversaries need to address is the fairness of attack and ensuring that all colluders share the same risk of being caught. This paper studies the dynamics among attackers in enforcing the fairness of collusion and investigates the problem of traitors within traitors, in which some selfish colluders wish to minimize their own risk while still profiting from collusion. We explore the strategies that these selfish colluders can use to further lower their probability of being detected and analyze their performance. We show that by processing their fingerprinted copies before multi-user collusion, the selfish colluders can further reduce their risk at the cost of quality degradation of their fingerprinted copies.
Joint adaptive power and modulation management in wireless networks with antenna diversity

In multi-access wireless communication systems, power control and adaptive modulation are two important means to increase spectral efficiency, combat the time varying fading environment, and reduce cochannel interference. The overall uplink transmitting power is optimized while the overall network throughput is fixed. Each link can select a range of targeted signal-to-interference-plus-noise ratio (SINR) according to its current channel condition and each link's time average SINR is maintained as a constant to ensure fairness. Adaptive M-QAM or M-PSK modulation with antenna diversity is applied to increase spectral efficiency. The scheme can be interpreted as "water filling" each link's SINR in the time domain and allocating network throughput to different links at each time. From simulation results, our scheme reduces about 40% of overall transmitting power and increases average spectral efficiency by about 0.9 bit/s/Hz.
Scheduling algorithms for quality of service aware OFDMA wireless systems

In this paper, we investigate scheduling in multiuser OFDMA systems. The objective is to maximize the resource utilization in a network, while a required quality of service (QoS) per user is satisfied. A notion of revenue maximization is used to determine the optimal OFDMA subcarrier allocation to different users based on their required QoS. The optimal solution for the problem is presented and its performance and complexity are studied. An iterative low complexity algorithm is also proposed to achieve near optimal performance.