In multiuser multiple-input multiple-output (MU-MIMO) wireless downlink systems, block diagonalization (BD) is a technique, where the transmit precoding matrix of each user is designed such that its subspace lies in the null space of all the other remaining users, so that multiuser interference (MUI) is completely canceled. In low signal to noise power ratio (SNR) or low signal to interference plus noise power ratio (SINR) environments, regularized BD, that lets some MUI remain and maximizes the sum rate capacity of the BD MIMO channel, was also proposed. One of the problems of both the approaches is high complexity of computation due to a lot of singular value decomposition (SVD) processes. In this paper we propose new BD techniques utilizing QR decomposition (QRD) which can be practically achieved by Gram-Schmidt orthogonalization (GSO) with lower complexity compared to the conventional method employing SVD. We can show that the performance of the proposed approaches is close to the conventional approaches, while the proposed approaches have much lower complexity.

This study formulates and solves the wire planning problem with electro-migration and interference using an effective integer linear programming (ILP)-based approach. For circuits without obstacles, the proposed approach obtains a wire planning with the minimum wiring area. An effective approach for estimating the length of feasible routing wire is proposed to handle circuits with obstacles. In addition, the space reservation technique, which allocates the ring of the free silicon space around obstacles, is presented to improve interference among routing wires and on-obstacle wires. For circuits with obstacles, the proposed method minimizes total wiring area and reduces interference. Experimental results show that the integer linear-programming-based approach effectively and efficiently minimizes wiring area of routing wires.

This letter considers the problem of detecting an offset quadrature phase shift keying (O-QPSK) modulated signal in colored Gaussian noise. The generalized likelihood ratio test (GLRT) is employed for detection. By deriving the GLRT, it is shown that the assumption of colored Gaussian noise results in a more complicated problem than with the white noise assumption that was previously examined in the literature. An efficient solution for the detection maximization problem is proposed, based on which the GLRT is implemented. Performance results are presented to illustrate the detector performance.

Impulsive noise interference is a significant problem for the Integrated Services Digital Broadcasting for Terrestrial (ISDB-T) receivers due to its effect on the orthogonal frequency division multiplexing (OFDM) signal. In this paper, an adaptive scheme to suppress the effect of impulsive noise is proposed. The impact of impulsive noise can be detected by using the guard band in the frequency domain; furthermore the position information of the impulsive noise, including burst duration, instantaneous power and arrived time, can be estimated as well. Then a time-domain window function with adaptive parameters, which are decided in terms of the estimated information of the impulsive noise and the carrier-to-noise ratio (CNR), is employed to suppress the impulsive interference. Simulation results confirm the validity of the proposed scheme, which improved the bit error rate (BER) performance for the ISDB-T receivers in both AWGN channel and Rayleigh fading channel.

This paper proposes new scheduling algorithms for best effort (BE) traffic classification in business femtocell networks. The purpose of traffic classification is to provide differentiated services to BE users depending on their traffic classes, and the concept of traffic classification is called Inter User Best Effort (IUBE) in CDMA2000 1x Evolution Data Optimized (EVDO) standard. Traffic differentiation is achieved by introducing Grade of Service (GoS) as a quality of service (QoS) parameter into the scheduler's decision metric (DM). New scheduling algorithms are called QoS Round Robin (QoS-RR), QoS Proportionally Fair (QoS-PF), QoS maximum data rate control (DRC) (QoS-maxDRC), QoS average DRC (QoS-aveDRC), QoS exponent DRC (QoS-expDRC), QoS maxDRC-PF (QoS-maxDRC-PF). Two different femtocell throughput experiments are performed using real femtocell devices in order to collect real DRC values. The first experiment examines 4, 8, 12 and 16 IUBE users, while second experiment examines 4 IUBE + 2 Voice over IP (VoIP), 8 IUBE + 2 VoIP, 12 IUBE + 2 VoIP, 16 IUBE + 2 (VoIP) users. Average sector throughput, IUBE traffic differentiation, VoIP delay bound error values are investigated to compare the performance of the proposed scheduling algorithms. In conclusion, QoS-maxDRC-PF scheduler is proposed for business femtocell environment.

Dielectric rod arrays in a metallic waveguide alter the propagation modes and group velocities of electromagnetic waves. We have focused on TE30-to-TE10 mode converters and investigated how their behavior varies with frequency. A mode converter is proposed that passes the TE10 mode at frequencies lower than 2fc, and converts the TE30 mode into the TE10 mode for frequencies higher than 3fc.

In this paper, N-CSK (N parallel Codes Shift Keying) using modified pseudo orthogonal M-sequence sets (MPOMSs) to realize the parallel combinatory spread spectrum (PC/SS) communication system for the optical communications is proposed. Moreover, the upper bound of data transmission rate and the bit error rate (BER) performance of this N-CSK system using the chip-level detection are evaluated through theoretical analysis by taking into account the scintillation, background-noise, avalanche photo-diode (APD) noise, thermal noise, and signal dependence noise. It is shown that the upper bound of data transmission rate of the proposed system is better than those of OOK/CDM and SIK/CDM. Moreover, the upper bound of data transmission rate of the proposed system can achieve about 1.5 [bit/chip] when the code length of MPOMS is 64 [chip].

Nowadays, pedestrian recognition for automotive and security applications that require accurate recognition in images taken from distant observation points is a recent challenging problem in the field of computer vision. To achieve accurate recognition, both detection and tracking must be precise. For detection, some excellent schemes suitable for pedestrian recognition from distant observation points are proposed, however, no tracking schemes can achieve sufficient performance. To construct an accurate tracking scheme suitable for pedestrian recognition from distant observation points, we propose a novel pedestrian tracking scheme using multiple cues: HSV histograms and HOG features. Experimental results show that the proposed scheme can properly track a target pedestrian where tracking schemes using only a single cue fails. Moreover, we implement the proposed scheme on NVIDIA® TeslaTM C1060 processor, one of the latest GPU, to achieve real-time processing of the proposed scheme. Experimental results show that computation time required for tracking of a frame by our implementation is reduced to 8.80 ms even though Intel® CoreTM i7 CPU 975 @ 3.33 GHz spends 111 ms.

In this letter, an improved triple-tunable frequency synthesizer structure to achieve both high frequency resolution and fast switching speed without degradation of spurious signals (spurs) level performance is proposed. According to this structure, a high performance millimeter-wave frequency synthesizer with low spurious, low phase noise, and fast switching speed, is developed. This synthesizer driven by the direct digital synthesizer (DDS) AD9956 can adjust the output of a DDS and frequency division ratios of two variable frequency dividers (VFDs) to move the spurious components outside the loop bandwidth of the phase-locked loop (PLL). Moreover, the ADF4252 based microwave PLL can further suppress the phase noise. Experimental results from the implemented synthesizer show that remarkable performance improvements have been achieved.

Many scientific applications require efficient variable-precision floating-point arithmetic. This paper presents a special-purpose Very Large Instruction Word (VLIW) architecture for variable precision floating-point arithmetic (VV-Processor) on FPGA. The proposed processor uses a unified hardware structure, equipped with multiple custom variable-precision arithmetic units, to implement various variable-precision algebraic and transcendental functions. The performance is improved through the explicitly parallel technology of VLIW instruction and by dynamically varying the precision of intermediate computation. We take division and exponential function as examples to illustrate the design of variable-precision elementary algorithms in VV-Processor. Finally, we create a prototype of VV-Processor unit on a Xilinx XC6VLX760-2FF1760 FPGA chip. The experimental results show that one VV-Processor unit, running at 253 MHz, outperforms the approach of a software-based library running on an Intel Core i3 530 CPU at 2.93 GHz by a factor of 5X-37X for basic variable-precision arithmetic operations and elementary functions.

Overcoming the highly organized and coordinated malware threats by botnets on the Internet is becoming increasingly difficult. A honeypot is a powerful tool for observing and catching malware and virulent activity in Internet traffic. Because botnets use systematic attack methods, the sequences of malware downloaded by honeypots have particular forms of coordinated pattern. This paper aims to discover new frequent sequential attack patterns in malware automatically. One problem is the difficulty in identifying particular patterns from full yearlong logs because the dataset is too large for individual investigations. This paper proposes the use of a data-mining algorithm to overcome this problem. We implement the PrefixSpan algorithm to analyze malware-attack logs and then show some experimental results. Analysis of these results indicates that botnet attacks can be characterized either by the download times or by the source addresses of the bots. Finally, we use entropy analysis to reveal how frequent sequential patterns are involved in coordinated attacks.

A monopulse angle measurement method is often utilized to measure a target angle. However, this method cannot measure correct angles for multiple targets which cannot be distinguished by range, Doppler frequency and beamwidth. When the number of targets which cannot be distinguished by these parameters is restricted to two, a method which can measure two targets angles has been proposed. However, an approximation is utilized with this method, so that measured angles have errors even though the signal-to-noise ratio is infinite. Another method which can simultaneously measure azimuths and elevations for only two targets has also been proposed. However, this conventional method requires four receivers, and is therefore difficult to apply when there is a hard ware limitation. In this paper, we propose a method to measure azimuths and elevations of two targets by using two receivers and a time division system. A pairing problem has occurred due to the time division angle measurement with this method, so we also propose an algorithm to solve this pairing problem. We finally verify the proposed method by a numerical simulation and experimentation. The results show that the angles of two targets can be measured by our proposed method by using two receivers.

In this paper, the Getis statistic is applied to ALOS- PALSAR (Advanced Land Ovserving Satellite-Phased Array L-band Synthetic Aperture Radar) images for assessing the building damage caused by the Wenchuan earthquake in 2008. As a proposed image analysis, a simulated building image using mapping and projection algorithm is first presented for analysis of the Getis statistic. The results show the high accuracy of the assessment of the proposed approach. The Getis statistic is then applied to two ALOS-PALSAR images acquired before and after the Wenchuan earthquake to assess the level of building damage. Results of the Getis statistic show that the damage level is approximately 81%.

This paper presents a low-complexity multi-mode fast Fourier transform (FFT) processor for Digital Video Broadcasting-Terrestrial 2 (DVB-T2) systems. DVB-T2 operations need 1K/2K/4K/8K/16K/32K-point multiple mode FFT processors. The proposed architecture employs pipelined shared-memory architecture in which radix-2/22/23/24 FFT algorithms, multi-path delay commutator (MDC), and a novel data scaling approach are exploited. Based on this architecture, a novel low-cost data scaling unit is proposed to increase area efficiency, and an elaborate memory configuration scheme is designed to make single-port SRAM without degrading throughput rate. Also, new scheduling method of twiddle factor is proposed to reduce the area. The SQNR performance of 32K-point FFT mode is about 45.3 dB at 11-bit internal word length for 256QAM modulation. The proposed FFT processor has a lower hardware complexity and memory size compared to conventional FFT processors.

An infinitely long monopole antenna driven by a coaxial cable is revisited. The associated Weber transform and the mode-matching method are used to obtain simple simultaneous equations for the modal coefficients. Computations are performed to illustrate the behavior of current distribution and antenna admittance in terms of antenna geometries.

In 2010, Guo and Zhang proposed a group key agreement protocol based on the chaotic hash function. This letter points out that Guo-Zhang's protocol is still vulnerable to off-line password guessing attacks, stolen-verifier attacks and reflection attacks.

In cloud computing, a cloud user pays proportionally to the amount of the consumed resources (bandwidth, memory, and CPU cycles etc.). We posit that such a cloud computing system is vulnerable to DDoS (Distributed Denial-of-Service) attacks against quota. Attackers can force a cloud user to pay more and more money by exhausting its quota without crippling its execution system or congesting links. In this paper, we address this issue and claim that cloud should enable users to pay only for their admitted traffic. We design and prototype such a charging model in a CoreLab testbed infrastructure and show an example application.

Thin-film transistors based on Liquid-crystalline phenylterthiophenes, 3-TTPPh-5 and 3-TTPPhF4-6 are fabricated with a spin-coating method. The devices exhibit p-type operation with the mobility on the order of 10-2 cm2V-1s-1. The field-effect mobilities of the transistors using 3-TTPPh-5 and 3-TTPPhF4-6 are almost independent of the temperature above room temperature. In particular, the temperature range in which the mobility is constant is between 230 and 350 K for 3-TTPPh-5.

This paper proposes a single-carrier transmission method based on an overlap frequency-domain equalizing (FDE) and a coherent averaging. FDE is a block-based equalizing technique using discrete Fourier transform. A cyclic prefix is often used to avoid inter-block interference under multipath channel conditions, which reduces transmission efficiency. An overlap FDE is a technique to avoid the cyclic prefix insertion, but the residual interferences often exist after the FDE processing according to the channel conditions. The method proposed in this paper suppresses the residual interferences by applying a coherent averaging to the FDE outputs and improve the equalization performances. Computer simulation shows the effect of the proposed technique over the multipath channels.

Measuring the relational similarity between word pairs is important in numerous natural language processing tasks such as solving word analogy questions, classifying noun-modifier relations and disambiguating word senses. We propose a supervised classification method to measure the similarity between semantic relations that exist between words in two word pairs. First, each pair of words is represented by a vector of automatically extracted lexical patterns. Then a binary Support Vector Machine is trained to recognize word pairs with similar semantic relations to a given word pair. To train and evaluate the proposed method, we use a benchmark dataset that contains 374 SAT multiple-choice word-analogy questions. To represent the relations that exist between two word pairs, we experiment with 11 different feature functions, including both symmetric and asymmetric feature functions. Our experimental results show that the proposed method outperforms several previously proposed relational similarity measures on this benchmark dataset, achieving an SAT score of 46.9.