We propose a novel bias-free adaptive beamformer employing an affine projection algorithm with the optimal regularization parameter. The generalized sidelobe canceller affine projection algorithm suffers from a bias of a weight vectors under the condition of no reference signals for output of an array in the beamforming application. First, we analyze the bias in the algorithm and prove that the bias can be eliminated through a large regularization parameter. However, this causes slow convergence at the initial state, so the regularization parameter should be controlled. Through the optimization of the regularization parameter, the proposed method achieves fast convergence without the bias at the steady-state. Experimental results show that the proposed beamformer not only removes the bias but also achieves both fast convergence and high steady-state output signal-to-interference-plus-noise ratio.

Password-based anonymous authentication schemes provide not only password-based authentication but also user anonymity. In [15], Yang et al., proposed a password-based anonymous authentication scheme (we call it YZWB10 scheme) using the password-protected credentials. This scheme has being standardized in ISO/IEC 20009-4 that was approved to proceed to the CD stage in the 49th ISO/IEC JTC 1/SC 27 Mexico meeting. In this paper, we analyze unlinkability of the YZWB10 scheme [15]. In particular, we show that a (malicious) server in the YZWB10 scheme can specify which user actually sent the login request to the server. Unlike Yang et al.,'s claim, the YZWB10 scheme [15] does not provide unlinkability against server.

Generally, in order to extend the cell coverage of a mobile station, relay stations are used at a cell edge in a cellular system. But, received signals in a relay station of a cell edge have a large error because a neighboring cell transmits the signals for other users. Since the transmitted signals for other users are interference for received signals in the relay station of the cell edge, the relay station has a negative effect on the bit error ratio performance. The cell coverage can not be extended stably. In order to expand the cell coverage stably, the inter-cell interference has to cancel. Thus, in this paper, the technique that the inter-cell interference (ICI) is canceled by cooperative relays is proposed. Also, diversity gain is obtained by cooperative relays.

This paper studies the energy-saving problem in cognitive multicast orthogonal frequency-division multiplexing (OFDM) systems, for which a time-frequency two-dimensional model is established to enable the system energy conservation through joint temporal and spectral adaptations. The formulated two-dimensional problem, minimizing the total power consumption whilst guaranteeing the minimal-rate requirement for each multicast session and constraining the maximal perceived interference in each timeslot for the active primary user, is categorized as mixed integer non-convex programming, whose optimal solution is intractable in general. However, based on the time-sharing property, an asymptotically optimal algorithm is proposed by jointly iterating spectrum element (SE) assignment and power allocation. Moreover, a suboptimal algorithm, which carries out SE assignment and power allocation sequentially, is presented as well to reduce the computation complexity. Simulation results show the proposed joint algorithm can achieve the near-optimal solution, and the proposed sequential algorithm approximates to the joint one very well with a gap of less than 3%. Compared with the existing slot-by-slot energy-saving algorithms, the total power consumption is considerably decreased due to the combined exploitation of time and frequency dimensions.

To achieve accurate wireless-local-area-network (WLAN) positioning, the directivity and influence of multipath fading on the power absorption by the user are clarified experimentally. Based on the results, a general model of the power absorption by the user is devised. The parameters of the model are estimated using maximum-likelihood estimation (MLE) and the magnetic sensor built into modern smartphones. The proposed method compensates the power absorption and the influence of multipath fading. According to experimental evaluations, the root-mean-square error (RMSE) of the proposed method is 34% lower than that of the conventional one. Namely, RMSE of the proposed method is 1.94m in a room.

Due to low signal-to-carrier ratio and high dynamic, the frequency deviation affects the bit synchronization in GNSS receiver. This paper proposes a balance differential coherent bit synchronization algorithm, which uses the differential coherent method to eliminate the influence of the frequency deviation. By enlarging the differential distance, the proposed algorithm achieves higher bit synchronization rates. Combining two complementary differential coherent parts, the proposed algorithm avoids the unbalance problem and the attenuation of accumulation. Furthermore, a general architecture is presented to reduce the system complexity. Experimental results show that the proposed algorithm improves the sensitivity of bit synchronization by 3∼7dB compared with the previous method.

In this letter, we propose a secrecy criterion for outsourcing encrypted databases. In encrypted databases, encryption schemes revealing some information are often used in order to manipulate encrypted data efficiently. The proposed criterion is based on inference analysis for databases: We simulate attacker's inference on specified secret information with and without the revealed information from the encrypted database. When the two inference results are the same, then secrecy of the specified information is preserved against outsourcing the encrypted database. We also show that the proposed criterion is decidable under a practical setting.

For k ≥ 3, a convex geometric graph is called k-locally outerplanar if no path of length k intersects itself. In [D. Boutin, Convex Geometric Graphs with No Short Self-intersecting Path, Congressus Numerantium 160 (2003) 205-214], Boutin stated the results of the degeneracy for 3-locally outerplanar graphs. Later, in [D. Boutin, Structure and Properties of Locally Outerplanar Graphs, Journal of Combinatorial Mathematics and Combinatorial Computing 60 (2007) 169-180], a structural property on k-locally outerplanar graphs was proposed. These results are based on the existence of “minimal corner pairs”. In this paper, we show that a “minimal corner pair” may not exist and give a counterexample to disprove the structural property. Furthermore, we generalize the result on the degeneracy with respect to k-locally outerplanar graphs.

To understand the behavior of a program, developers often need to read source code fragments in various modules. System-dependence-graph-based (SDG) program slicing is a good candidate for supporting the investigation of data-flow paths among modules, as SDG is capable of showing the data-dependence of focused program elements. However, this technique has two problems. First, constructing SDG requires heavyweight analysis, so SDG is not suitable for daily uses. Second, the results of SDG-based program slicing are difficult to visualize, as they contain many vertices. In this research, we proposed variable data-flow graphs (VDFG) for use in program slicing techniques. In contrast to SDG, VDFG is created by lightweight analysis because several approximations are used. Furthermore, we propose using the fractal value to visualize VDFG-based program slice in order to reduce the graph complexity for visualization purposes. We performed three experiments that demonstrate the accuracy of VDFG program slicing with fractal value, the size of a visualized program slice, and effectiveness of our tool for source code reading.

In recent years, hybrid typestate analysis has been proposed to eliminate unnecessary monitoring instrumentations for runtime monitors at compile-time. Nop-shadows Analysis (NSA) is one of these hybrid typestate analyses. Before generating residual monitors, NSA performs the data-flow analysis which is intra-procedural flow-sensitive and partially context-sensitive to improve runtime performance. Although NSA is precise, there are some cases on which it has little effects. In this paper, we propose three optimizations to further improve the precision of NSA. The first two optimizations try to filter interferential states of objects when determining whether a monitoring instrumentation is necessary. The third optimization refines the inter-procedural data-flow analysis induced by method invocations. We have integrated our optimizations into Clara and conducted extensive experiments on the DaCapo benchmark. The experimental results demonstrate that our first two optimizations can further remove unnecessary instrumentations after the original NSA in more than half of the cases, without a significant overhead. In addition, all the instrumentations can be removed for two cases, which implies the program satisfy the typestate property and is free of runtime monitoring. It comes as a surprise to us that the third optimization can only be effective on 8.7% cases. Finally, we analyze the experimental results and discuss the reasons why our optimizations fail to further eliminate unnecessary instrumentations in some special situations.

A novel method was developed to expand and adjust the bandwidth of long-period fiber gratings (LPFGs) as band-rejection filters. The band-rejection filters were constructed by concatenating two LPFGs with an appropriate space, that causes a $pi$-phase shift. The component LPFGs with the same period and the different numbers of periods are designed to have $-$3-dB transmission at wavelengths on both sides of a resonance wavelength symmetrically, and the transmission loss of the concatenated LPFGs peaks at the -3-dB transmission wavelengths. The rejection bandwidth was widened by changing the interval between the -3-dB transmission wavelengths. The concatenated LPFGs were simulated by using a transfer-matrix method based on a discrete coupling model, and were fabricated by a point-by-point arc discharge technique on the basis of the simulation results. It was demonstrated that the rejection bandwidth at 20-dB attenuation reached 26.6,nm and was 2.7 times broader than that of a single uniform LPFG.

State-of-the-art background subtraction and foreground detection methods still face a variety of challenges, including illumination changes, camouflage, dynamic backgrounds, shadows, intermittent object motion. Detection of foreground elements via the robust principal component analysis (RPCA) method and its extensions based on low-rank and sparse structures have been conducted to achieve good performance in many scenes of the datasets, such as Changedetection.net (CDnet); however, the conventional RPCA method does not handle shadows well. To address this issue, we propose an approach that considers observed video data as the sum of three parts, namely a row-rank background, sparse moving objects and moving shadows. Next, we cast inequality constraints on the basic RPCA model and use an alternating direction method of multipliers framework combined with Rockafeller multipliers to derive a closed-form solution of the shadow matrix sub-problem. Our experiments have demonstrated that our method works effectively on challenging datasets that contain shadows.

This paper presents comprehensive comparisons on the block error rate (BLER) performance of rate-one open-loop (OL) transmit diversity schemes with four antennas for discrete Fourier transform (DFT)-precoded Orthogonal Frequency Division Multiple Access (OFDMA). One candidate scheme employs a quasi-orthogonal (QO) - space-time block code (STBC) in which four-branch minimum mean-square error (MMSE) combining is achieved at the cost of residual inter-code interference (ICI). Another candidate employs a combination of the STBC and selection transmit diversity called time switched transmit diversity (TSTD) (or frequency switched transmit diversity (FSTD)). We apply a turbo frequency domain equalizer (FDE) associated with iterative decision-feedback channel estimation (DFCE) using soft-symbol estimation to reduce channel estimation (CE) error. The turbo FDE includes an ICI canceller to reduce the influence of the residual ICI for the QO-STBC. Based on link-level simulation results, we show that a combination of the STBC and TSTD (or FSTD) is suitable as a four-antenna OL transmit diversity scheme for DFT-precoded OFDMA using the turbo FDE and iterative DFCE.

In recent years, the time variation of Internet traffic has increased due to the growth of streaming and cloud services. Backbone networks must accommodate such traffic without congestion. Traffic engineering with traffic prediction is one approach to stably accommodating time-varying traffic. In this approach, routes are calculated from predicted traffic to avoid congestion, but predictions may include errors that cause congestion. We propose prediction-based traffic engineering that is robust against prediction errors. To achieve robust control, our method uses model predictive control, a process control method based on prediction of system dynamics. Routes are calculated so that future congestion is avoided without sudden route changes. We apply calculated routes for the next time slot, and observe traffic. Using the newly observed traffic, we again predict traffic and re-calculate the routes. Repeating these steps mitigates the impact of prediction errors, because traffic predictions are corrected in each time slot. Through simulations using backbone network traffic traces, we demonstrate that our method can avoid the congestion that the other methods cannot.

A feedback vertex set F of an undirected graph G is a vertex subset of G whose removal results in a forest. Such a set F is said to be independent if F forms an independent set of G. In this paper, we study the problem of finding an independent feedback vertex set of a given graph with the minimum number of vertices, from the viewpoint of graph classes. This problem is NP-hard even for planar bipartite graphs of maximum degree four. However, we show that the problem is solvable in linear time for graphs having tree-like structures, more specifically, for bounded treewidth graphs, chordal graphs and cographs. We then give a fixed-parameter algorithm for planar graphs when parameterized by the solution size. Such a fixed-parameter algorithm is already known for general graphs, but our algorithm is exponentially faster than the known one.

We present an I/O-size second-order analog to digital converter (ADC) combined with a time-to-digital converter (TDC) and a voltage-to-time converter (VTC). Our proposed VTC is optimized for metal--oxide--metal (MOM) capacitances, and is charged to the MOM capacitances by an input voltage. In a standard 65-nm CMOS process, a signal to noise and distortion ratio (SNDR) of 50,dB (8 bits) is achievable at an input signal frequency of 78,kHz and a sampling rate of 20,MHz, where the respective area and power are 6468,mm$^{mathrm{2}}$ and 509 $mu$W. The measured maximum integral nonlinearity (INL) of the proposed ADC is $-$1.41 LSBs. The active area of the proposed ADC is smaller than an I/O buffer. The proposed ADC is useful as an ADC I/O.

In bit-patterned media recording (BPMR), the readback signal is severely corrupted by the inter-symbol interference (ISI) and inter-track interference (ITI), especially at high recording densities, due to small bit and track pitches. One way to alleviate the ITI effect is to encode an input data sequence before recording, so as to avoid some data patterns that easily cause an error at the data detection process. This paper proposes an ITI-mitigating 5/6 modulation code for a multi-track multi-head BPMR system to eliminate the data patterns that lead to severe ITI. Specifically, each of the 5 user bits is converted into a 6-bit codeword in the form of a 3-by-2 data array, based on a look-up table. Experimental results indicate that the system with the proposed coding scheme outperforms that without coding, especially when an areal density is high and/or the position jitter is large.

This paper analyzes the performance of a mobile multihop relay (MMR) system which uses intermediate mobile relay stations (RSs) to increase service coverage area and capacity of a communication system. An analytical framework for an MMR system is introduced, and a scheme for allocating the optimum radio resources to an MMR system is presented. It is very challenging to develop an analytical framework for an MMR system because more than two wireless links should be considered in analyzing the performance of such a system. Here, the joint effect of a finite queue length and an adaptive modulation and coding (AMC) scheme in both a base station (BS) and an RS are considered. The traffic characteristics from BS to RS are analyzed, and a three-dimensional finite-state Markov chain (FSMC) is built for the RS which considers incoming traffic from the BS as well. The RS packet loss rate and the RS average throughput are also derived. Moreover, maximum throughput is achieved by optimizing the amount of radio resources to be allocated to the wireless link between a BS and an RS.

Cloud computing is a widely used computing platform in business and academic communities. Performance is an important issue when a user runs an application in the cloud. The user may want to estimate the application-execution time beforehand to guarantee the application performance or to choose the most suitable cloud. Moreover, the cloud system architect and the designer need to understand the application performance characteristics, such as the scalability or the utilization of cloud platforms, to improve performance. However, because the application performance in clouds sometime fluctuates, estimation of the application performance is difficult. In this paper, we discuss the performance fluctuation of Hadoop jobs in both a public cloud and a community cloud for one to three months. The experimental results indicate phenomena that we cannot see without long-term experiments and phenomena inherent in Hadoop. The results suggest better ways to estimate Hadoop application performances in clouds. For example, we should be aware of application characteristics (CPU intensive or communication intensive), datacenter characteristics (busy or not), and time frame (time of day and day of the week) to estimate the performance fluctuation due to workload congestion in cloud platforms. Furthermore, we should be aware of performance degradation due to task re-execution in Hadoop applications.

TV white space (TVWS) brings potential opportunities to relieve the growing spectrum scarcity. Therefore organizations like the FCC have suggested the co-channel deployment of cellular networks (CNs) on condition that a keep-out distance from the protected region of TV receivers is maintained. However the consequent CN interference has not been described. In addition, considering the wide range of TV coverage, it is also inefficient and wasteful not applying the vacant spectra for secondary user (SU) communication by opportunistic access inside the TV coverage zone. In this paper, we first investigate the aggregate interference from CNs outside the protected area to find out how the interference is generated, and then research the available spectrum resource distribution for SUs inside the TV coverage zone under aggregate interference constraints to utilize TVWS more efficiently. Specifically, we model CN in three aspects. A close-form interference probability distribution function (PDF) is proposed. Since the PDF is too complex to analyze, we approximate it as Gaussian and prove the accuracy of our approximation with Kolmogorov-Smirnov test. Then, available spectra maximization is formulated as an optimization problem under both TV and SU receiver outage probability constraints. We find that available spectra demonstrate a volcano-shaped geographical distribution and optimal network-status-aware SU transmit power exists to maximize the spectra. Our analysis reveals the characteristics of interference in TVWS and contributes to the utilization improvement of white space.