This paper investigates the application of inter-cell interference coordination (ICIC) in heterogeneous networks for the LTE-Advanced downlink where picocells are overlaid onto macrocells. In LTE-Advanced, in order to perform ICIC, almost blank subframes (ABSs) are employed, where only the cell-specific reference signal (CRS) is transmitted to protect the subframes in the picocells from severe interference from the macrocells. Furthermore, multicast/broadcast over single-frequency network (MBSFN) subframes are employed to reduce the interference of the CRS on the data channel, although the control channel still suffers from interference from the CRS. When the cell range expansion (CRE), which offload the UEs from macrocells to picocells, is used to improve the system performance, the influence from the CRS increases. In order to assess the influence, the required CRE bias to improve the data channel is investigated based on a system-level simulation under various conditions such as the number of picocells, the protected subframe ratio, and the user distribution. The simulation results show that the cell-edge user throughput is improved with the CRE bias of more than 8 dB, employing ABSs. Furthermore, simulation results show that one dominant source of interference is observed for the sets of user equipment (UEs) connected to the picocells via CRE with such a bias value. Based on observation, the influence that the CRS has on the control channel, i.e., physical control format indicator channel (PCFICH), and physical downlink control channel (PDCCH) is investigated based on a link-level simulation combined with a system-level simulation. The simulation results show that protecting the PCFICH is very important compared to protecting the PDCCH, since the block error rate (BLER) performance of the PCFICH becomes worse than the required BLER of 10-3 to support various conditions, although the BLER performance of the PDCCH can exceed the required BLER of 10-2 by spanning the PDCCH over three OFDM symbols.

This paper proposes an S-parameter analysis method that uses simultaneous excitation for multi-antenna systems. In this method, OFDM (Orthogonal Frequency Division Multiplexing) and CI (Carrier Interferometry) pulse generation schemes are employed for maintaining the orthogonality among the excited signals. In OFDM excitation schemes, the characteristics of the neighboring antennas can be calculated by assigning different frequency subcarriers exclusively. CI enables the simultaneous verification of the antennas distant enough since this method can provide temporal orthogonality. Combining these two methods yields the simultaneous analyses of array antennas with both narrow and wide element spacing. The simulation of a 22 multi-antenna shows that the results of the proposed method agree well with those of the conventional method even though its computation speed is more 4 times that of the conventional method.

One important issue in cognitive transmission is for multiple secondary users to dynamically acquire spare spectrum from the single primary user. The existing spectrum sharing scheme adopts a deterministic Cournot game to formulate this problem, of which the solution is the Nash equilibrium. This formulation is based on two implicit assumptions. First, each secondary user is willing to fully exchange transmission parameters with all others and hence knows their complete information. Second, the unused spectrum of the primary user for spectrum sharing is always larger than the total frequency demand of all secondary users at the Nash equilibrium. However, both assumptions may not be true in general. To remedy this, the present paper considers a more realistic assumption of incomplete information, i.e., each secondary user may choose to conceal their private information for achieving higher transmission benefit. Following this assumption and given that the unused bandwidth of the primary user is large enough, we adopt a probabilistic Cournot game to formulate an opportunistic spectrum sharing scheme for maximizing the total benefit of all secondary users. Bayesian equilibrium is considered as the solution of this game. Moreover, we prove that a secondary user can improve their expected benefit by actively hiding its transmission parameters and increasing their variance. On the other hand, when the unused spectrum of the primary user is smaller than the maximal total frequency demand of all secondary users at the Bayesian equilibrium, we formulate a constrained optimization problem for the primary user to maximize its profit in spectrum sharing and revise the proposed spectrum sharing scheme to solve this problem heuristically. This provides a unified approach to overcome the aforementioned two limitations of the existing spectrum sharing scheme.

With the proliferation of IEEE 802.11 wireless local area networks, large numbers of wireless access points have been deployed, and it is often the case that a user can detect several access points simultaneously in dense metropolitan areas. Most owners, however, encrypt their networks to prevent the public from accessing them due to the increased traffic and security risk. In this work, we use pricing as an incentive mechanism to motivate the owners to share their networks with the public, while at the same time satisfying users' service demand. Specifically, we propose a “federated network” concept, in which radio resources of various wireless local area networks are managed together. Our algorithm identifies two candidate access points with the lowest price being offered (if available) to each user. We then model the price announcements of access points as a game, and characterize the Nash Equilibrium of the system. The efficiency of the Nash Equilibrium solution is evaluated via simulation studies as well.

Many studies and systems that incorporate elements such as “pleasure” and “fun” in the game to improve a learner's motivation have been developed in the field of learning environments. However, few are the studies of situations where many learners gather at a single computer and participate in a game-based learning environment (GBLE), and where the GBLE designs the learning process by controlling the interactions between learners such as competition, collaboration, and learning by teaching. Therefore, the purpose of this study is to propose a framework of educational control that induces and activates interaction between learners intentionally to create a learning opportunity that is based on the knowledge understanding model of each learner. In this paper, we explain the design philosophy and the framework of our GBLE called “Who becomes the king in the country of mathematics?” from a game viewpoint and describe the method of learning support control in the learning environment. In addition, we report the results of the learning experiment with our GBLE, which we carried out in a junior high school, and include some comments by a principal and a teacher. From the results of the experiment and some comments, we noticed that a game may play a significant role in weakening the learning relationship among students and creating new relationships in the world of the game. Furthermore, we discovered that learning support control of the GBLE has led to activation of the interaction between learners to some extent.

This letter investigates the problem of distributed channel selection in cognitive radio ad hoc networks (CRAHNs) with heterogeneous spectrum opportunities. Firstly, we formulate this problem as a local congestion game, which is proved to be an exact potential game. Then, we propose a spatial best response dynamic (SBRD) to rapidly achieve Nash equilibrium via local information exchange. Moreover, the potential function of the game reflects the network collision level and can be used to achieve higher throughput.

To assess the performance of maximum-likelihood (ML) based Nakagami m parameter estimators, current methods rely on Monte Carlo simulation. In order to enable the analytical performance evaluation of ML-based m parameter estimators, we study the statistical properties of a parameter Δ, which is defined as the log-ratio of the arithmetic mean to the geometric mean for Nakagami-m fading power. Closed-form expressions are derived for the probability density function (PDF) of Δ. It is found that for large sample size, the PDF of Δ can be well approximated by a two-parameter Gamma PDF.

The evolution of Internet, the growth of Internet users and the new enabled technological capabilities place new requirements to form the Future Internet. Many features improvements and challenges were imposed to build a better Internet, including securing roaming of data and services over multiple administrative domains. In this research, we propose a multi-domain access control infrastructure to authenticate and authorize roaming users through the use of the Diameter protocol and EAP. The Diameter Protocol is a AAA protocol that solves the problems of previous AAA protocols such as RADIUS. The Diameter EAP Application is one of Diameter applications that extends the Diameter Base Protocol to support authentication using EAP. The contributions in this paper are: 1) first implementation of Diameter EAP Application, called DiamEAP, capable of practical authentication and authorization services in a multi-domain environment, 2) extensibility design capable of adding any new EAP methods, as loadable plugins, without modifying the main part, and 3) provision of EAP-TLS plugin as one of the most secure EAP methods. DiamEAP Server basic performances were evaluated and tested in a real multi-domain environment where 200 users attempted to access network using the EAP-TLS method during an event of 4 days. As evaluation results, the processing time of DiamEAP using the EAP-TLS plugin for authentication of 10 requests is about 20 ms while that for 400 requests/second is about 1.9 second. Evaluation and operation results show that DiamEAP is scalable and stable with the ability to handle more than 6 hundreds of authentication requests per second without any crashes. DiamEAP is supported by the AAA working group of the WIDE Project.

In this paper, a new Hammerstein predistorter modeling for power amplifier (PA) linearization is proposed. The key feature of the model is that the cubic splines, instead of conventional high-order polynomials, are utilized as the static nonlinearities due to the fact that the splines are able to represent hard nonlinearities accurately and circumvent the numerical instability problem simultaneously. Furthermore, according to the amplifier's AM/AM and AM/PM characteristics, real-valued cubic spline functions are utilized to compensate the nonlinear distortion of the amplifier and the following finite impulse response (FIR) filters are utilized to eliminate the memory effects of the amplifier. In addition, the identification algorithm of the Hammerstein predistorter is discussed. The predistorter is implemented on the indirect learning architecture, and the separable nonlinear least squares (SNLS) Levenberg-Marquardt algorithm is adopted for the sake that the separation method reduces the dimension of the nonlinear search space and thus greatly simplifies the identification procedure. However, the convergence performance of the iterative SNLS algorithm is sensitive to the initial estimation. Therefore an effective normalization strategy is presented to solve this problem. Simulation experiments were carried out on a single-carrier WCDMA signal. Results show that compared to the conventional polynomial predistorters, the proposed Hammerstein predistorter has a higher linearization performance when the PA is near saturation and has a comparable linearization performance when the PA is mildly nonlinear. Furthermore, the proposed predistorter is numerically more stable in all input back-off cases. The results also demonstrate the validity of the convergence scheme.

For Doppler parameter estimation of forward-looking SAR, the third-order Doppler parameter can not be neglected. In this paper, the azimuth signal of the transmitter fixed bistatic forward-looking SAR is modeled as a cubic polynomial phase signal (CPPS) and multiple time-overlapped CPPSs, and the modified cubic phase function is presented to estimate the third-order Doppler parameter. By combining the cubic phase function (CPF) with Radon transform, the method can give an accurate estimation of the third-order Doppler parameter. Simulations validate the effectiveness of the algorithm.

We propose a method for calibrating the topology of distributed pan-tilt cameras (i.e. the structure of routes among and within FOVs) and its probabilistic model. To observe as many objects as possible for as long as possible, pan-tilt control is an important issue in automatic calibration as well as in tracking. In a calibration period, each camera should be controlled towards an object that goes through an unreliable route whose topology is not calibrated yet. This camera control allows us to efficiently establish the topology model. After the topology model is established, the camera should be directed towards the route with the biggest possibility of object observation. We propose a camera control framework based on the mixture of the reliability of the estimated routes and the probability of object observation. This framework is applicable both to camera calibration and object tracking by adjusting weight variables. Experiments demonstrate the efficiency of our camera control scheme for establishing the camera topology model and tracking objects as long as possible.

Multi-Channel MAC protocols increase network throughput because multiple data transmissions can take place simultaneously. However, existing Multi-Channel MAC protocols do not take full advantage of the multi-channel environment, because they lack a mechanism allowing wireless stations to acquire vacant channel and time resources. In this paper, we first establish the basic model of existing Multi-Channel MAC protocols to know the capability of the most important existing protocols. Next, under the condition that each station can use only two transceivers, we propose Multi-Channel MAC protocols that effectively utilize idle channels and potentially available time resources of stations by employing bursts and interrupted frame transfers. We assume a transceiver can behave as either a transmitter or a receiver but not both at the same time. Moreover, we show the effectiveness of our proposal by computer simulation. Furthermore, through the evaluation in the case that each station can use more than two transceivers, we confirm two transceivers' case is best solution in terms of both attained throughput and hardware complexity.

In this paper, a decentralized concurrent transmission strategy in shared channel in Ad Hoc networks is proposed based on game theory. Firstly, a static concurrent transmissions game is used to determine the candidates for transmitting by channel quality threshold and to maximize the overall throughput with consideration of channel quality variation. To achieve NES (Nash Equilibrium Solution), the selfish behaviors of node to attempt to improve the channel gain unilaterally are evaluated. Therefore, this game allows each node to be distributed and to decide whether to transmit concurrently with others or not depending on NES. Secondly, as there are always some nodes with lower channel gain than NES, which are defined as hunger nodes in this paper, a hunger suppression scheme is proposed by adjusting the price function with interferences reservation and forward relay, to fairly give hunger nodes transmission opportunities. Finally, inspired by stock trading, a dynamic concurrent transmission threshold determination scheme is implemented to make the static game practical. Numerical results show that the proposed scheme is feasible to increase concurrent transmission opportunities for active nodes, and at the same time, the number of hunger nodes is greatly reduced with the least increase of threshold by interferences reservation. Also, the good performance on network goodput of the proposed model can be seen from the results.

We quantitatively evaluate how sampling and spatio/temporal granularity in traffic monitoring affect the detectability of anomalous traffic. Those parameters also affect the monitoring burden, so network operators face a trade-off between the monitoring burden and detectability and need to know which are the optimal paramter values. We derive equations to calculate the false positive ratio and false negative ratio for given values of the sampling rate, granularity, statistics of normal traffic, and volume of anomalies to be detected. Specifically, assuming that the normal traffic has a Gaussian distribution, which is parameterized by its mean and standard deviation, we analyze how sampling and monitoring granularity change these distribution parameters. This analysis is based on observation of the backbone traffic, which exhibits spatially uncorrelated and temporally long-range dependence. Then we derive the equations for detectability. With those equations, we can answer the practical questions that arise in actual network operations: what sampling rate to set to find the given volume of anomaly, or, if the sampling is too high for actual operation, what granularity is optimal to find the anomaly for a given lower limit of sampling rate.

Network structure has a great impact both on hazard spread and network immunization. The vulnerability of the network node is associated with each other, assortative or disassortative. Firstly, an algorithm for vulnerability relevance clustering is proposed to show that the vulnerability community phenomenon is obviously existent in complex networks. On this basis, next, a new indicator called network “hyper-betweenness” is given for evaluating the vulnerability of network node. Network hyper-betweenness can reflect the importance of network node in hazard spread better. Finally, the dynamic stochastic process of hazard spread is simulated based on Monte-Carlo sampling method and a two-player, non-cooperative, constant-sum game model is designed to obtain an equilibrated network immunization strategy.

We present pseudo-preimage attacks on Davis-Meyer mode of reduced rounds of the block ciphers ARIA, Camellia, and Serpent by using Sasaki's framework. They yield preimage or second-preimage attacks on PGV hashing modes. We develop proper initial structures for applying meet-in-the-middle techniques to the block ciphers, by considering their diffusion layers, and propose a method to find matching-check equations for indirect partial matching technique with a binary matrix. These works enable us to attack 5 rounds of ARIA, 7 rounds of Camellia, and 4 rounds of Serpent faster than brute force attack.

The channel characteristics of IEEE 802.11 WLAN vary with time and this can affect packet transmission performance. For achieving robust and efficient transmission, the transmission rate is controlled by exploiting the multi-rate capability of the IEEE 802.11 physical layer (PHY) to respond to the time-varying channel condition. In this paper, we propose a novel rate adaptation scheme, called RA-MCE, in which the transmitter estimates channel quality in the MAC layer to enhance throughput performance without the need to use the RTS-CTS mechanism nor to modify the IEEE 802.11 standard. RA-MCE adaptively controls the transmission rate according to the estimated channel quality by the MAC layer channel quality estimator (MCE) that uses only local MAC layer measurements. Through extensive simulations, we validate the accuracy of MCE and evaluate the performance of RA-MCE to show that it achieves higher throughput performance than other rate adaptation schemes under various circumstances.

Test coverage is an important indicator of whether software has been sufficiently tested. However, there are several problems with the existing measurement tools for test coverage, such as their cost of development and maintenance, inconsistency, and inflexibility in measurement. We propose a consistent and flexible measurement framework for test coverage that we call the Open Code Coverage Framework (OCCF). It supports multiple programming languages by extracting the commonalities from multiple programming languages using an abstract syntax tree to help in the development of the measurement tools for the test coverage of new programming languages. OCCF allows users to add programming language support independently of the test-coverage-criteria and also to add test-coverage-criteria support independently of programming languages in order to take consistent measurements in each programming language. Moreover, OCCF provides two methods for changin the measurement range and elements using XPath and adding user code in order to make more flexible measurements. We implemented a sample tool for C, Java, and Python using OCCF. OCCF can measure four test-coverage-criteria. We also confirmed that OCCF can support C#, Ruby, JavaScript, and Lua. Moreover, we reduced the lines of code (LOCs) required to implement measurement tools for test coverage by approximately 90% and the time to implement a new test-coverage-criterion by over 80% in an experiment that compared OCCF with the conventional non-framework-based tools.

A signal model and weighted-average based estimation techniques are proposed to estimate the angle-of-arrival (AOA) parameters of multiple clusters for a low data rate ultrawide band (LR-UWB) based wireless positioning system. The optimal AOA estimation techniques for the LR-UWB wireless positioning system according to the cluster condition are introduced and it is shown that the proposed techniques are superior to the conventional technique from the standpoint of performance.

Emerging video surveillance technologies are based on foreground detection to achieve event detection automatically. Integration foreground detection with a modern multi-camera surveillance system can significantly increase the surveillance efficiency. The foreground detection often leads to high computational load and increases the cost of surveillance system when a mass deployment of end cameras is needed. This paper proposes a DSP-based foreground detection algorithm. Our algorithm incorporates a temporal data correlation predictor (TDCP) which can exhibit the correlation of data and reduce computation based on this correlation. With the DSP-oriented foreground detection, an adaptive frame rate control is developed as a low cost solution for multi-camera surveillance system. The adaptive frame rate control automatically detects the computational load of foreground detection on multiple video sources and adaptively tunes the TDCP to meet the real-time specification. Therefore, no additional hardware cost is required when the number of deployed cameras is increased. Our method has been validated on a demonstration platform. Performance can achieve real-time CIF frame processing for a 16-camera surveillance system by single-DSP chip. Quantitative evaluation demonstrates that our solution provides satisfied detection rate, while significantly reducing the hardware cost.