Showing papers by "Penn State College of Communications published in 2018"

Energy-efficient multi-UAV coverage deployment in UAV networks: A game-theoretic framework

Abstract: UAV cooperative control has been applied in many complex UAV communication networks. It remains challenging to develop UAV cooperative coverage and UAV energy-efficient communication technology. In this paper, we investigate current works about UAV coverage problem and propose a multi-UAV coverage model based on energy-efficient communication. The proposed model is decomposed into two steps: coverage maximization and power control, both are proved to be exact potential games (EPG) and have Nash equilibrium (NE) points. Then the multi-UAV energy-efficient coverage deployment algorithm based on spatial adaptive play (MUECD-SAP) is adopted to perform coverage maximization and power control, which guarantees optimal energy-efficient coverage deployment. Finally, simulation results show the effectiveness of our proposed approach, and confirm the reliability of proposed model.

Should Machines Express Sympathy and Empathy? Experiments with a Health Advice Chatbot

Abstract: When we ask a chatbot for advice about a personal problem, should it simply provide informational support and refrain from offering emotional support? Or, should it show sympathy and empat...

Spectrum Sharing Planning for Full-Duplex UAV Relaying Systems With Underlaid D2D Communications

Abstract: In this paper, we consider the spectrum sharing planning problem for a full-duplex unmanned aerial vehicle (UAV) relaying systems with underlaid device-to-device (D2D) communications, where a mobile UAV employed as a full-duplex relay assists the communication link between separated nodes without direct link. Our design aims to maximize the sum throughput under the transmit power budget, while guaranteeing the coexistence with terrestrial D2D pairs, satisfying the information causality and UAV’s trajectory constraints. First, the transmit power planning with a given trajectory is investigated, where a successive convex algorithm is developed by leveraging the D.C. (difference of two convex) programming. Then, we propose a two-step trajectory design method for the given transmit power since the constraints of D2D pairs result in a non-convex feasible set. Furthermore, an efficient spectrum sharing method for an aerial UAV and terrestrial D2D communications is designed by alternately optimizing the transmit power and UAV’s trajectory. Finally, simulation results under various parameter configurations are provided to show the effectiveness of the proposed algorithms.

Resource Allocation for Energy Harvesting-Powered D2D Communication Underlaying UAV-Assisted Networks

Abstract: In this paper, we investigate the resource allocation problem for unmanned aerial vehicle (UAV)-assisted networks, where a UAV acting as an energy source provides radio frequency energy for multiple energy harvesting-powered device-to-device (D2D) pairs with much information to be transmitted. The goal is to maximize the average throughput within a time horizon while satisfying the energy causality constraint under a generalized harvest-transmit-store model, which results in a non-convex problem. By introducing the Lagrangian relaxation method, we analytically show that the behavior of all D2D pairs at each time slot is exclusive: harvesting energy or transmitting information signals. The formulated non-convex optimization problem is thus transformed into a mixed integer nonlinear programming (MINIP). We then design an efficient resource allocation algorithm to solve this MINIP, where D.C. (difference of two convex functions) programming and golden section method are combined to achieve a suboptimal solution. Furthermore, we provide an idea to reduce the computational complexity for facilitating the application in practice. Simulations are conducted to validate the effectiveness of the proposed algorithm and evaluate the system throughput performance.

Ties, Likes, and Tweets: Using Strong and Weak Ties to Explain Differences in Protest Participation Across Facebook and Twitter Use

Abstract: Based on the theoretical concepts of social networks and technology affordances, this article argues that different social media platforms influence political participation through unique, yet complementary, routes. More specifically, it proposes that Facebook and Twitter are conducive to protest behavior through two distinct mechanisms: whereas the influence of Facebook use is more effective through communication with strong-tie networks, the impact of Twitter use is more effective through communication with weak-tie networks. To test these expectations, we analyze data from a cross-sectional, face-to-face survey on a representative sample of Chilean youths conducted in 2014. Findings in the study lend empirical support for these hypotheses. Consequently, while different social media (in this case, Facebook and Twitter) are similar in their participatory effects, the paths through which this influence occurs are distinct, a finding that highlights the importance of studying political behavior across diff...

Spectrum Inference in Cognitive Radio Networks: Algorithms and Applications

Abstract: Spectrum inference, also known as spectrum prediction in the literature, is a promising technique of inferring the occupied/free state of radio spectrum from already known/measured spectrum occupancy statistics by effectively exploiting the inherent correlations among them. In the past few years, spectrum inference has gained increasing attention owing to its wide applications in cognitive radio networks (CRNs), ranging from adaptive spectrum sensing, and predictive spectrum mobility, to dynamic spectrum access and smart topology control, to name just a few. In this paper, we provide a comprehensive survey and tutorial on the recent advances in spectrum inference. Specifically, we first present the preliminaries of spectrum inference, including the sources of spectrum occupancy statistics, the models of spectrum usage, and characterize the predictability of spectrum state evolution. By introducing the taxonomy of spectrum inference from a time-frequency-space perspective, we offer an in-depth tutorial on the existing algorithms. Furthermore, we provide a comparative analysis of various spectrum inference algorithms and discuss the metrics of evaluating the efficiency of spectrum inference. We also portray the various potential applications of spectrum inference in CRNs and beyond, with an outlook to the fifth-generation mobile communications and next generation high frequency communications systems. Last but not least, we highlight the critical research challenges and open issues ahead.

Milling and Public Warnings

Abstract: Given the potential of modern warning technology to save lives, discovering whether it is possible to craft mobile alerts for imminent events in a way that reduces people’s tendency to seek and con

Joint Beamforming for Secure Communication in Cognitive Satellite Terrestrial Networks

Abstract: This paper investigates the secure communication of a cognitive satellite terrestrial network with software-defined architecture, where a gateway is acting as a control center to offer the resource allocation for the wireless systems. Specifically, we propose beamforming (BF) schemes to utilize the interference from the terrestrial network as a green source to enhance the physical-layer security for the satellite network, provided that the two networks share the portion of millimeter-wave frequencies. Supposing that the satellite employs multibeam antenna while the base station is equipped with a uniform planar array, we first formulate a constrained joint optimization problem to minimize the total transmit power while satisfying both the quality-of-service requirement of the terrestrial user and the secrecy rate (SR) requirements of the satellite users. Since the formulated optimization problem is nonconvex and mathematically intractable, we then propose two BF schemes to obtain the optimal solutions with high computational efficiency. For the case of one eavesdropper (Eve), we present a method to convert the nonconvex SR constraint to a second-order cone one and then adopt a penalty function approach to obtain the BF weight vectors. In the case of multiple Eves, by introducing a list of auxiliary variables, we propose a two-layer iterative BF scheme using penalty function approach together with gradient-based method to calculate the BF weight vectors. Finally, simulation results are given to demonstrate the effectiveness and superiority of the proposed BF schemes.

Hybrid Time-Switching and Power Splitting SWIPT for Full-Duplex Massive MIMO Systems: A Beam-Domain Approach

Abstract: In this paper, we consider the hybrid time switching (TS) and power splitting (PS) simultaneous wireless information and power transfer (SWIPT) protocol design in a full-duplex (FD) massive MIMO system. In this system, an FD base station (BS) serves a set of half-duplex (HD) users and a set of fixed HD sensors. The whole protocol can be divided into two phases based on the idea of TS. The first phase is Training Phase , which is designed for users uplink training and sensors energy harvesting as well as downlink training. Specifically, users transmit uplink pilots for beam-domain (BD) uplink channel estimation at the BS, and the BS transmits energy signals to sensors. Based on the idea of PS, sensors utilize the received energy signals for energy harvesting and BD downlink channel estimation. In the second phase, that is Information Transmission Phase , the BS intelligently schedules users and sensors based on the BD distributions of channels to mitigate self-interference and improve transmission spectral efficiency (SE). Then, the BS forms transmit beamformers for transmitting information to users and receive beamformers for receiving signals transmitted by sensors. By optimizing transmit powers at the BS during the two phases and the TS ratio, the system achievable sum-rate is maximized. Simulation results show the superiority of the proposed protocol on SE compared with conventional massive MIMO SWIPT protocol.

Robust Secure Beamforming for 5G Cellular Networks Coexisting With Satellite Networks

Abstract: This paper studies the robust secure beamforming (BF) issue of fifth generation (5G) cellular system operating at millimeter wave frequency and coexisting with a satellite network. By employing an uniform planar array at the base station (BS) and assuming known imperfect angle-of-arrival-based channel state informations of multiple eavesdroppers (Eves), a constrained optimization problem is first formulated to maximize the worst-case achievable secrecy rate of the cellular user under the constraints of the transmit power of BS and the interference threshold of satellite earth station. Then, we propose two robust BF methods to solve the complex optimization problem for both coordinated and uncoordinated Eves. For the case of coordinated Eves, we propose a heuristic BF scheme, which transfers the worst-case problem into a min-max one such that the BF weight vectors can be obtained analytically. For uncoordinated Eves, we convert the non-convex problem into a convex one, and further propose an iterative penalty function-based algorithm to obtain the optimal BF weight vectors. Finally, simulation results are provided to confirm the effectiveness and superiority of the proposed robust BF schemes.

A One-Leader Multi-Follower Bayesian-Stackelberg Game for Anti-Jamming Transmission in UAV Communication Networks

Abstract: This paper focuses on the anti-jamming transmission problem in unmanned aerial vehicle (UAV) communication networks. Considering the incomplete information constraint and the co-channel mutual interference, a Bayesian Stackelberg game is proposed to formulate the competitive relations between UAVs (users) and the jammer. Specifically, the jammer acts as the leader, whereas users act as followers of the proposed game. Based on their utility functions, the jammer and users select their optimal power control strategies respectively. In addition, the observation error is also investigated in this paper. Due to the incomplete information constraint and the existence of co-channel mutual interference, it is challenging to obtain Stackelberg equilibrium (SE) of the proposed game. Thus, a sub-gradient based Bayesian Stackelberg iterative algorithm is proposed to obtain SE. Finally, simulations are conducted to demonstrate the performance of the proposed algorithm, and the impact of incomplete information and observation error on users’ utilities are also presented.

Secure Beamforming Designs for Secrecy MIMO SWIPT Systems

Abstract: In this letter, secure beamforming designs are investigated in a multiple-input multiple-output secrecy channels with simultaneous wireless information and power transfer. In order to achieve fairness among different multiple energy harvesting receivers, the minimum harvested energy is maximized under the secrecy rate requirements. In particular, in order to reduce the computational complexity of the semidefinite programming problem, a successive convex approximation (SCA) iterative algorithm is proposed in the perfect channel state information (CSI) case to obtain a near-optimal rank-one solution. Moreover, the original problem is extended to the imperfect CSI case by incorporating a norm-bounded error model, where an SCA-based iterative algorithm is also proposed. Simulation results reveal that the SCA-based iterative algorithm achieves the same performance as the semidefinite relaxation method with reduced complexity.

Unmanned Aerial Vehicle-Aided Communications: Joint Transmit Power and Trajectory Optimization

Abstract: This letter investigates the transmit power and trajectory optimization problem for unmanned aerial vehicle (UAV)-aided networks. Different from majority of the existing studies with fixed communication infrastructure, a dynamic scenario is considered where a flying UAV provides wireless services for multiple ground nodes simultaneously. To fully exploit the controllable channel variations provided by the UAV’s mobility, the UAV’s transmit power and trajectory are jointly optimized to maximize the minimum average throughput within a given time length. For the formulated non-convex optimization with power budget and trajectory constraints, this letter presents an efficient joint transmit power and trajectory optimization algorithm. Simulation results validate the effectiveness of the proposed algorithm and reveal that the optimized transmit power shows a water-filling characteristic in spatial domain.

Spectrum Prediction Based on Taguchi Method in Deep Learning With Long Short-Term Memory

Abstract: Spectrum prediction is a promising technology in cognitive radio networks, since it can reduce considerable time and energy consumed in spectrum sensing process. Many spectrum prediction algorithms have achieved good performance, but majority of them with shallow architecture cannot capture the inherent correlations of spectrum data very well. Long short-term memory (LSTM) neural network in deep learning has been validated to have strong capability of solving time series problems. In this paper, we develop a spectrum prediction framework with a deep learning approach on two real-world spectrum datasets. For the first dataset to predict channel occupancy states, we firstly employ the taguchi method to determine the best optimized configuration of neural network for certain spectrum point and then analyze the effect of each design hyper-parameter. Next, we build LSTM neural networks with two perspectives of regression and classification for spectrum prediction. For the second dataset to predict channel quality, we compare the prediction performance of the LSTM neural network and conventional multilayer perceptron (MLP) neural network. For both of our datasets, results show that the prediction performance varies with frequency bands. From the point of statistics, the LSTM neural network has better prediction performance than the MLP neural network and is more stable as well. Furthermore, we find that the performance of the LSTM neural network with classification perspective is slightly better than that with regression perspective in our first dataset.

Outage Analysis of Cognitive Hybrid Satellite-Terrestrial Networks With Hardware Impairments and Multi-Primary Users

Abstract: This letter investigates the effects of practical hardware impairments on a cognitive hybrid satellite-terrestrial networks (CHSTN) with multiple primary users (PUs). The widely employed shadowed-Rician fading distribution is adopted to model the satellite-terrestrial channel. CHSTN can provide comprehensive wireless coverage as well as enhanced spectrum resource usage by considering the requirements of both spectrum efficiency and reliability. Specifically, we derive the closed-form expression of the outage probability (OP) for the considered system in the presence of interference power constraints imposed by multiple adjacent terrestrial PUs. To gain further insights at high signal-to-noise ratios, the asymptotic expression for the OP is also derived. Numerical results confirm the correctness and effectiveness of our performance analysis.

Efficient multi-tasks scheduling algorithm in mobile cloud computing with time constraints

Abstract: The explosive growth of mobile devices and the rapid development of wireless networks and mobile computing technologies have stimulated the emergence of many new computing paradigms, such as Fog Computing, Mobile Cloud Computing (MCC) etc. These newly emerged computation paradigms try to promote the mobile applications’ Quality of Service (QoS) through allowing the mobile devices to offload their computation tasks to the edge cloud and provide their idle computation capabilities for executing other devices’ offloaded tasks. Therefore, it is very critical to efficiently schedule the offloaded tasks especially when the available computation, storage, communication resources and energy supply are limited. In this paper, we investigate the MCC-assisted execution of multi-tasks scheduling problem in hybrid MCC architecture. Firstly, this problem is formulated as an optimization problem. Secondly, a Cooperative Multi-tasks Scheduling based on Ant Colony Optimization algorithm (CMSACO) is put forward to tackle this problem, which considers task profit, task deadline, task dependence, node heterogeneity and load balancing. Finally, a series of simulation experiments are conducted to evaluate the performance of the proposed scheduling algorithm. Experimental results have shown that our proposal is more efficient than a few typical existing algorithms.

HF communications: Past, present, and future

Abstract: High frequency (HF) communication, commonly covering frequency range between 3 and 30 MHz, is an important wireless communication paradigm to offer over-the-horizon or even global communications with ranges up to thousands of kilometers via sky-wave propagation with ionospheric refraction It has widespread applications in fields such as emergency communications in disaster areas, remote communications with aircrafts or ships and non-light-of-the-sight military operations This tutorial article overviews the history of HF communication, demystifies the recent advances, and provides a preview of the next few years, which the authors believe will see fruitful outputs towards wideband, intelligent and integrated HF communications Specifically, we first present brief preliminaries on the unique features of HF communications to facilitate general readers in the communication community Then, we provide a historical review to show the technical evolution on the three generations of HF communication systems Further, we highlight the key challenges and research directions We hope that this article will stimulate more interests in addressing the technical challenges on the research and development of future HF radio communication systems

Physical Layer Security for Hybrid Satellite Terrestrial Relay Networks With Joint Relay Selection and User Scheduling

Abstract: In this paper, we investigate the impacts of joint relay selection and user scheduling scheme on the physical layer security for hybrid satellite-terrestrial relay systems, where multiple terrestrial relays, multiple terrestrial users, and multiple illegitimate eavesdroppers are considered in the network. To strengthen the system security against wiretapping attack, we present a joint opportunistic relay selection and the threshold based user scheduling scheme to balance the system performance and implementation complexity. Furthermore, two representative eavesdropping cases are considered, i.e., the Case I, colluding case: the eavesdroppers cooperate with each other and wiretap the information together, and the Case II, non-colluding case: the best eavesdropper will be chosen to wiretap the information channel. Besides, we derive the closed-form expressions for the average secrecy capacity based on the proposed relay selection and user scheduling scheme in the presence of two eavesdropping cases. To get more insights at high signal-to-noise ratios, the asymptotic expressions for the average secrecy capacity are also derived under two cases, from which we can get the effect of different parameters on the system performance conveniently. At last, analytical results are validated through comparison with the Monte Carlo simulations.

A Novel Cognitive Satellite Network With GEO and LEO Broadband Systems in the Downlink Case

Abstract: With the development of satellite communication, the number of satellites in space continuously increases. However, the available spectrum resources are scarce. To address the spectrum scarcity, sharing the spectrum between different communication systems is a promising option. In this paper, a novel cognitive satellite network with geostationary earth orbit (GEO) and low earth orbit (LEO) broadband systems is studied in the downlink case. First, we present a general interference analysis model and simplify it by transforming the spatial dimension into the time dimension according to the satellite motion. Based on the interference analysis, an optimization algorithm with beamhopping and adaptive power control techniques is proposed, which can simultaneously enhance the spectral efficiency and protect the primary system. The system performance of the coexistence scenario is evaluated in terms of the system throughput. Numerical results demonstrate that the spectrum-sharing method between GEO and LEO systems is feasible, and the cognitive network can achieve a high spectral efficiency. Furthermore, the factors that affect the system in the spectral coexistence scenario are analyzed.

Secrecy Outage Analysis of Buffer-Aided Cooperative MIMO Relaying Systems

Abstract: This paper investigates the secrecy outage performance of buffer-aided multirelay multiple-input multiple-output cooperative systems in the presence of a passive eavesdropper. Due to the unavailability of the channel state information of eavesdropper's channel, a buffer-aided joint transmit antenna and relay selection scheme based on the main channel is proposed to enhance the secrecy performance. Specifically, we model the evolution of the relay buffers as a Markov chain and derive new exact and asymptotic closed-form expressions for the secrecy outage probability, which provides an efficient way to assess the effect of system parameters on the secrecy outage probability. Moreover, simple asymptotic results are further exploited under two special scenarios, i.e., $L \rightarrow \infty$ and $L ot\rightarrow \infty$ (where $L$ denotes the size of the relay buffers), for characterizing the achievable secrecy diversity gain, the secrecy coding gain, and the secrecy diversity-multiplexing tradeoff. Our results reveal that: 1) a secrecy diversity gain of $N_RM{\rm min}(N_S,N_D)$ is achieved when $L ot\rightarrow \infty$ , however, when $L \rightarrow \infty$ , the secrecy diversity gain increases to $N_RM(N_S+N_D)$ , where $N_S$ , $N_R$ , and $N_D$ represent the number of antennas at the source, each of $M$ relays and the destination, respectively. 2) The eavesdropper's channel does not affect the secrecy diversity gain but only the secrecy coding gain in both the two scenarios.

Distributed Demand-Aware Channel-Slot Selection for Multi-UAV Networks: A Game-Theoretic Learning Approach

Abstract: Over the past decades, the unmanned aerial vehicle (UAV) has received unprecedented surge of scientific and military interest worldwide. This paper investigates the problem of opportunistic spectrum access for multi-UAV networks from a game-theoretic perspective. Due to the topology of the multi-UAV networks, the interference may be classified into two parts, i.e., the intra-cluster and the inter-cluster interference. Moreover, since the UAVs in the network have different tasks, the communication demand of each UAV should be taken into account. First, we formulate the demand-aware joint channel-slot selection problem as a weighted interference mitigation game, and then, design the utility function considering features of multi-UAV network, e.g., some rewards due to the channel and slots selection. We prove that the formulated game is an exact potential game with at least one pure-strategy Nash equilibrium. Next, we apply the distributed log-linear algorithm to achieve the desired optimization and overcome the constraint of dynamic communication demand of each UAV. To speed up the convergence, we also propose a low-complexity and realistic channel and slot initialization scheme for UAVs. Finally, the simulation results validate the effectiveness of the formulated game.

Physical–Social-Aware D2D Content Sharing Networks: A Provider–Demander Matching Game

Abstract: Device-to-device content sharing is widely considered as an effective response to the prevalence of multimedia content sharing and local services. To ensure its advantages, how to optimally match potential providers to demanders of contents is of importance, especially considering the randomness of content location, as well as the coexistence of altruistic, selfish, and even malicious user behaviors. Accordingly, for such a matching process, it is advisable to achieve a win–win solution, rather than sacrificing performance of either potential providers or demanders. In this work, we employ the weighted directed graph theory to model the two-sided physical–social-aware preferences, which jointly exploit the physical and social networking characteristics of both sides. Then, we study the two-sided physical–social-aware matching problem, which essentially involves the joint issue of pairing scheduling and power control with respect to potential providers and demanders. To solve it in a tractable manner, the former is cast as a two-sided one-to-one matching game, in which the potential providers and demanders rank one another by using the proposed preferences, and the latter is transformed into the preference profile establishment of this matching game. Finally, a distributed algorithm based on the Dinkelbach iteration and deferred acceptance approaches is developed. The properties of the resulting stable outcomes are then studied, and the simulation results verify the availability and efficiency of the proposed algorithm.

Time-Frequency Scheduling and Power Optimization for Reliable Multiple UAV Communications

Abstract: Unmanned aerial vehicle (UAV) communication has gained increasing interests from the industry and academia as UAV has a variety of emerging applications, such as aerial sensors, flying base stations, and mobile relays. Generally, UAVs are manipulated by remote ground control center. Thus one critical issue is that UAVs must correctly receive the control signal before following the instructions. However, the control signal quality at UAV receivers is very susceptible due to the variation of channel conditions and the effect of adjacent channel interference. To tackle these challenges, this paper investigates the issue of how to simultaneously ensure the reliability of the remote control signal for multiple UAVs. The problem is formulated as a mixed-integer programming with the goal of maximizing the minimum signal to interference-plus-noise ratio of all UAVs by jointly scheduling the time–frequency resource blocks and optimizing the power allocation. To make the problem tractable, we perform equivalent transformations via leveraging the inherent property of the formulated problem. Next, based on the decoupled constraints on different variables, we propose a low complexity block coordinate descent-based method. Furthermore, to offer better system performance, we leverage the smooth approximation theory and develop a gradient projection-based method. Finally, extensive simulation results demonstrate the effectiveness of the proposed methods under various parameter configurations.

Social Media as a Sphere for “Risky” Political Expression: A Twenty-Country Multilevel Comparative Analysis:

Abstract: In the context of the United States, research shows a positive relationship between network heterogeneity and political expression on social media at the individual level. This study builds on that...

Deeply Rooted in Memories: Toward a Comprehensive Overview of 30 Years of Memorable Message Literature.

Abstract: Knapp, Stohl, and Reardon's (1981) seminal work reported that some messages may be "remembered for a long time and have a profound influence on a person's life" (p. 27). While the foundational concepts of this framework have offered a meaningful contribution to memorable messages research, this article seeks to unpack the past three decades of the literature specific to the field of communication. The authors will highlight the trajectory and changes while considering its present use, episodes, and situations that transpire in individual lived experiences. Like Braithwaite, Schrodt, and Carr (2015), we note that memorable messages, though widely utilized, are largely descriptive and atheoretical or "undertheorized" (p. 15). To that end, and given its decades of successful use in health communication, organizational socialization, and education, we consider the value of a Theory of Memorable Messages (ToMM) that can support new directions for communication scholarship and serve as a catalyst for understanding dynamic relational interactions and exchanges in human communication.

A Circularly Polarized Frequency Beam-Scanning Antenna Fed by a Microstrip Spoof SPP Transmission Line

Abstract: In this letter, a planar frequency beam-scanning antenna with a circularly polarized (CP) radiation property is proposed. The beam scans along the narrow side and in lateral plane of the antenna. The antenna consists of two layers: Eight periodic symmetrical patches are presented on the top layer as radiation elements to generate CP beam, while microstrip spoof surface plasmon polariton transmission line is used as the feeding line, which improves the beam scanning range. The antenna has been fabricated and measured to verify the theory analysis. Measured results indicate that the main beam scans from –5° to +37° in a lateral plane within the operating frequency band from 12 to 16.5 GHz, of which an excellent CP characteristic is also realized. The peak gain of the antenna is about 9.5 dBi over the whole band.

Physical Layer Security in Overlay Cognitive Radio Networks With Energy Harvesting

Abstract: In this correspondence paper, we investigate the security and efficiency of data transmission for overlay cognitive radio networks, which consist of a pair of primary users, multiple pairs of energy-limited secondary users and multiple eavesdroppers Specifically, to achieve a better tradeoff between the security of primary transmission and the efficiency of secondary transmission, we propose an optimal relay selection (ORS) based on two energy harvesting (EH) protocols, ie, the time switching relay (TSR) protocol and power splitting relay (PSR) protocol Building in this, the exact closed-form expressions for the secrecy outage probability (SOP) of primary transmission and ergodic rate of secondary transmission are derived with the two EH protocols, respectively Moreover, to deeply analyze the secrecy performance, two asymptotic expressions for SOP of primary transmission are also derived under high main-to-eavesdropper ratio and the infinity number of secondary user conditions, respectively Through the simulation analysis, we find that the ORS based on EH protocols can achieve better performance than that of ORS without EH protocol in terms of tradeoff Moreover, PSR protocol is superior to TSR protocol

A Multi-Leader One-Follower Stackelberg Game Approach for Cooperative Anti-Jamming: No Pains, No Gains

Abstract: To tackle the multi-user and multi-channel issues in anti-jamming problems, we model the problem as a multi-leader one-follow Stackelberg game. An anti-jamming mechanism with “No Pains No Gains” idea is designed. The proposed mechanism sacrifices parts of users’ benefits to trap the jammer, while the rest of users can achieve a better performance. In this way, the system’s throughput is improved. In addition, the channel bonding technology is used to enhance the robust performance and improve system throughput further. Besides the cooperative anti-jamming problem is modeled as a multi-leader one-follower Stackelberg game, the channel selection and power allocation game of leaders is also modeled as a potential game. The existence of Nash equilibrium is proved, which guarantees the Stackelberg equilibrium of users and the jammer. A joint channel selection and power allocation algorithm is modified to approach the final equilibrium. The simulation results show that the proposed anti-jamming mechanism with channel bonding achieves higher throughput and better anti-jamming performance than non-cooperative algorithms.

How does Parallax Scrolling Influence User Experience? A Test of TIME (Theory of Interactive Media Effects)

Abstract: Parallax scrolling is a popular web technique used widely in product presentation websites, but its effect on user experience is unknown. Parallax scrolling allows the object displayed in the foreg...