This paper proposes a further improved technique on the stochastic functional approach for randomly rough surface scattering. The original improved technique has been established in the previous paper [Waves in Random and Complex Media, vol.19, no.2, pp.181-215, 2009] as a novel numerical-analytical method for a Wiener analysis. By deriving modified hierarchy equations based on the diagonal approximation solution of random wavefields for a TM plane wave incidence or even for a TE plane wave incidence under large roughness, large slope or low grazing incidence, such a further improved technique can provide a large reduction of required computational resources, in comparison with the original improved technique. This paper shows that numerical solutions satisfy the optical theorem with very good accuracy, by using small computational resources.

Recently, Trust has been recognized as an important factor for Grid computing security. In this paper, we propose a trust model in Grid system. It consists of Application Domain (AD), Client Domain (CD), Resource Domain (RD), and Trust Manager (TM). TM controls the relationship between RD and CD depending on the trust level value of each client and classification of each resource. Performance criteria are makespan and utilization. We evaluated our trust model in six scheduling algorithms in nine scenarios. The simulation results show that the proposed trust model improves the performance in all scheduling algorithms.

Transmission of convolutionally encoded source-codec parameters over noisy channels can benefit from the turbo principle through iterative source-channel decoding. We first formulate a recursive implementation based on sectionalized code trellises for MAP symbol decoding of binary convolutional codes. Performance is further enhanced by the use of an interpolative softbit source decoder that takes into account the channel outputs within an interleaving block. Simulation results indicate that our proposed scheme allows to exchange between its constituent decoders the symbol-level extrinsic information and achieves high robustness against channel noises.

To satisfy the requirement of a unified platform which can flexibly deal with various wireless radio systems, we proposed and implemented a heterogeneous network system composed of distributed flexible access points and a protocol-free signal processing unit. Distributed flexible access points are remote RF devices which perform the reception of multiple types of radio wave data and transfer the received data to the protocol-free signal processing unit through wired access network. The protocol-free signal processing unit performs multiple types of signal analysis by software. To realize a highly flexible and efficient radio wave data reception and transfer, we employ the recently developed compressed sensing technology. Moreover, we propose a combined Nyquist and compressed sampling method for the decoding signals to be sampled at the Nyquist rate and for the sensing signals to be sampled at the compressed rate. For this purpose, the decoding signals and the sensing signals are converted into the intermediate band frequency (IF) and mixed. In the IF band, the decoding signals are set at lower center frequencies than those of the sensing signals. The down converted signals are sampled at the rate of four times of the whole bandwidth of the decoding signals plus two times of the whole bandwidth of the sensing signals. The purpose of above setting is to simultaneously conduct Nyquist rate and compressed rate sampling in a single ADC. Then, all of odd (or even) samples are preserved and some of even (or odd) samples are randomly discarded. This method reduces the data transfer burden in dealing with the sensing signals while guaranteeing the realization of Nyquist-rate decoding performance. Simulation and experiment results validate the efficiency of the proposed method.

This paper investigates the communication range and interference range of millimeter-wave wireless personal area networks (WPAN) based on realistic system design. Firstly, the effective communication range of the millimeter-wave networks are calculated based on realistic physical (PHY) layer design and 60 GHz channel obtained from actual measurements. Secondly, an interference model is developed to facilitate the analysis of the impact of interferer-to-victim range on the victim link performance. It is found that system with BPSK modulation is able to support use cases with higher number of portable devices within a 3 m range, while system with 16QAM modulation is more suitable for fixed high speed data streaming devices within a shorter range of 1 m. Also, the interferer-to-victim range that causes no interference in all conditions is found to be approximately 40 m, while a 25 m range causes a typical bit error rate (BER) degradation of 1-digit (e.g. BER = 10-6 to 10-5).

Power-aware scheduling problem has been a recent issue in cluster systems not only for operational cost due to electricity cost, but also for system reliability. In this paper, we provide SLA-based scheduling algorithms for bag-of-tasks applications with deadline constraints on power-aware cluster systems. The scheduling objective is to minimize power consumption as long as the system provides the service levels of users. A bag-of-tasks application should finish all the sub-tasks before the deadline as the service level. We provide the power-aware scheduling algorithms for both time-shared and space-shared resource sharing policies. The simulation results show that the proposed algorithms reduce much power consumption compared to static voltage schemes.

This paper proposes approaches to perform HW/SW (Hardware/Software) partition and parallelization of computing-intensive tasks of the H.264 HiP (High Profile) decoding algorithm on an embedded coarse-grained reconfigurable multimedia system, called REMUS (REconfigurable MUltimedia System). Several techniques, such as MB (Macro-Block) based parallelization, unfixed sub-block operation etc., are utilized to speed up the decoding process, satisfying the requirements of real-time and high quality H.264 applications. Tests show that the execution performance of MC (Motion Compensation), deblocking, and IDCT-IQ (Inverse Discrete Cosine Transform-Inverse Quantization) on REMUS is improved by 60%, 73%, 88.5% in the typical case and 60%, 69%, 88.5% in the worst case, respectively compared with that on XPP PACT (a commercial reconfigurable processor). Compared with ASIC solutions, the performance of MC is improved by 70%, 74% in the typical and in the worst case, respectively, while those of Deblocking remain the same. As for IDCT_IQ, the performance is improved by 17% no matter in the typical or worst case. Relying on the proposed techniques, 1080p@30 fps of H.264 HiP@ Level 4 decoding could be achieved on REMUS when utilizing a 200 MHz working frequency.

It is known that wireless ad hoc networks employing omnidirectional communications suffer from poor network throughput due to inefficient spatial reuse. Although the use of directional communications is expected to provide significant improvements in this regard, the lack of efficient mechanisms to deal with deafness and hidden terminal problems makes it difficult to fully explore its benefits. The main contribution of this work is to propose a Medium Access Control (MAC) scheme which aims to lessen the effects of deafness and hidden terminal problems in directional communications without precluding spatial reuse. The simulation results have shown that the proposed directional MAC provides significant throughput improvement over both the IEEE802.11DCF MAC protocol and other prominent directional MAC protocols in both linear and grid topologies.

The performance of the kernel-based learning algorithms, such as SVM, depends heavily on the proper choice of the kernel parameter. It is desirable for the kernel machines to work on the optimal kernel parameter that adapts well to the input data and the learning tasks. In this paper, we present a novel method for selecting Gaussian kernel parameter by maximizing a class separability criterion, which measures the data distribution in the kernel-induced feature space, and is invariant under any non-singular linear transformation. The experimental results show that both the class separability of the data in the kernel-induced feature space and the classification performance of the SVM classifier are improved by using the optimal kernel parameter.

This paper proposes a new hybrid method for machine transliteration. Our method is based on combining a newly proposed two-step conditional random field (CRF) method and the well-known joint source channel model (JSCM). The contributions of this paper are as follows: (1) A two-step CRF model for machine transliteration is proposed. The first CRF segments a character string of an input word into chunks and the second one converts each chunk into a character in the target language. (2) A joint optimization method of the two-step CRF model and a fast decoding algorithm are also proposed. Our experiments show that the joint optimization of the two-step CRF model works as well as or even better than the JSCM, and the fast decoding algorithm significantly decreases the decoding time. (3) A rapid development method based on a weighted finite state transducer (WFST) framework for the JSCM is proposed. (4) The combination of the proposed two-step CRF model and JSCM outperforms the state-of-the-art result in terms of top-1 accuracy.

Two-step physical register deallocation (TSD) is an architectural scheme that enhances memory-level parallelism (MLP) by pre-executing instructions. Ideally, TSD allows exploitation of MLP under an unlimited number of physical registers, and consequently only a small register file is needed for MLP. In practice, however, the amount of MLP exploitable is limited, because there are cases where either 1) pre-execution is not performed; or 2) the timing of pre-execution is delayed. Both are due to data dependencies among the pre-executed instructions. This paper proposes the use of value prediction to solve these problems. This paper proposes the use of value prediction to solve these problems. Evaluation results using the SPECfp2000 benchmark confirm that the proposed scheme with value prediction for predicting addresses achieves equivalent IPC, with a smaller register file, to the previous TSD scheme. The reduction rate of the register file size is 21%.

In this letter, a new feedback equalization scheme to suppress inter-carrier interference (ICI) in an OFDM system using scattered pilot is investigated. On a fast fading channel severe ICI occurs due to a Doppler shift and it deteriorates a bit error rate (BER) seriously because of small subcarrier spacing. In an ISDB-T receiver the equalization is mainly processed in a frequency domain because the scattered pilot is transmitted over the subcarriers. However, the frequency domain equalization may not suppress severe ICI in the case of the fast fading channel with a large Doppler shift. The proposed equalization scheme uses the scattered pilot symbols transformed in a time domain as the reference signal for feedback taps. Numerical results through computer simulation show that the proposed scheme improves the BER performance especially with low carrier-to-noise ratio (CNR) conditions.

This paper presents a gate delay estimation method that takes into account dynamic power supply noise. We review STA based on static IR-drop analysis and a conventional method for dynamic noise waveform, and reveal their limitations and problems that originate from circuit structures and higher delay sensitivity to voltage in advanced technologies. We then propose a gate delay computation that overcomes the problems with iterative computations and consideration of input voltage drop. Evaluation results with various circuits and noise injection timings show that the proposed method estimates path delay fluctuation well within 1% error on average.

A low peak-to-average-power-ratio (PAPR) transceiver with a time-frequency cyclic shift orthogonal keying (TF-CSOK) technique is proposed for the uplink multi-carrier CDMA (MC-CDMA) system over multiple access interference (MAI) and multipath interference (MPI) channels. The low complexity structure of the TF-CSOK MC-CDMA system is designed to involve the FCSOK and TCSOK techniques to combat MPI and MAI effects, respectively. In particular, at the besestation, the multiuser detector employs the maximum likelihood (ML) rule and the TFSOK despreading and demapping techniques to acquire the M-ary modulation gain and diversity gain. Simulation results show that the multuser receiver has the robustness against strong MAI. Moreover, it outperforms the conventional single-carrier frequency division multiple access (SC-FDMA) system and the conventional MC-CDMA system under MAI and MPI environments.

Todays cellular systems reach their limits for data rate due to the continuously increasing amount of subscribers using wireless service for business purposes or in leisure time (smartphone effect). Thus, recent research focuses on concepts for interference management for cellular OFDMA systems. This paper addresses various techniques related to this topic, while considering the concepts with lowest complexity and backhaul costs as promising candidates to be applied first. Starting from interference canceling receivers over multi-user MIMO using fixed precoding to multi-cell interference estimation, which improves the precision of link adaptation, we discuss closed-loop cooperative transmit beamforming using multiple base stations grouped into a wireless distributed network (WDN), which is denoted as coordinated multi-point joint transmission in the 3GPP LTE-Advanced standardization. It is obvious, the more sophisticated these techniques are, the higher the demands for feedback and backhaul become. Performance results are provided by employing multi-cell simulations according to recommendations from 3GPP. In addition, feasibility of coordinated multi-point joint transmission is demonstrated in a real-time prototype setup, i.e. in the Berlin LTE-Advance Testbed.

While volunteer computing (VC) systems reach the most powerful computing platforms, they still have the problem of guaranteeing computational correctness, due to the inherent unreliability of volunteer participants. Spot-checking technique, which checks each participant by allocating spotter jobs, is a promising approach to the validation of computation results. The current spot-checking is based on the implicit assumption that participants never distinguish spotter jobs from normal ones; however generating such spotter jobs is still an open problem. Hence, in the real VC environment where the implicit assumption does not always hold, spot-checking-based methods such as well-known credibility-based voting become almost impossible to guarantee the computational correctness. In this paper, we generalize spot-checking by introducing the idea of imperfect checking. This generalization allows to guarantee the computational correctness under the situation that spot-checking is not fully-reliable and participants may distinguish spotter jobs. Moreover, we develop a generalized formula of the credibility, which enables credibility-based voting to utilize check-by-voting technique. Simulation results show that check-by-voting improves the performance of credibility-based voting, while guaranteeing the same level of computational correctness.

A fast calculation tool for state-dependent capacitance of power distribution network is proposed. The proposed method achieves linear time-complexity, which can be more than four orders magnitude faster than a conventional SPICE-based capacitance calculation. Large circuits that have been unanalyzable with the conventional method become analyzable for more comprehensive exploration of capacitance variation. The capacitance obtained with the proposed method agrees SPICE-based method completely (up to 5 digits), and time-linearity is confirmed through numerical experiments on various circuits. The maximum and minimum capacitances are also calculated using average and variance estimation. Calculation times are linear time-complexity, too. The proposed tool facilitates to build an accurate macro model of an LSI.

A multiband system can flexibly create spectral holes to avoid interference between different systems. When two systems within the same frequency band coexist, the multiband system must immediately detect the signals from all users to remove unwanted interference. The complication of creating spectral holes is to obtain an occupied frequency band and an angle-of-arrival of interfering system. These parameters must be measured at the receiver of multiband system and then fed back to the transmitter. This paper presents a channel estimator with an interference detector that is developed to implement and test it's functionality in a multiband system. The proposed estimator can precisely detect the parameters before demodulation, and quickly feed back the interfering system parameters to transmitter. The effective design and the detection error rate were evaluated via verification tests in an anechoic chamber and computer simulations. The results of the proposed technique show an ability of interference detection as well as channel estimation.

We address the issue of out-of-grammar (OOG) utterances in spoken dialogue systems by generating help messages. Help message generation for OOG utterances is a challenge because language understanding based on automatic speech recognition (ASR) of OOG utterances is usually erroneous; important words are often misrecognized or missing from such utterances. Our grammar verification method uses a weighted finite-state transducer, to accurately identify the grammar rule that the user intended to use for the utterance, even if important words are missing from the ASR results. We then use a ranking algorithm, RankBoost, to rank help message candidates in order of likely usefulness. Its features include the grammar verification results and the utterance history representing the user's experience.

This paper addresses the coexistence issue of distributed heterogeneous networks where the network nodes are cognitive radio terminals. These nodes, operating as secondary users (SUs), might interfere with primary users (PUs) who are licensed to use a given frequency band. Further, due to the lack of coordination and the dissimilarity of the radio access technologies (RATs) among these wireless nodes, they might interfere with each other. To solve this coexistence problem, we propose an architecture that enables coordination among the distributed nodes. The architecture provides coexistence solutions and sends reconfiguration commands to SU networks. As an example, time sharing is considered as a solution. Further, the time slot allocation ratios and transmit powers are parameters encapsulated in the reconfiguration commands. The performance of the proposed scheme is evaluated in terms of the coexistence between PUs and SUs, as well as the coexistence among SUs. The former addresses the interference from SUs to PUs, whereas the latter addresses the sharing of an identified spectrum opportunity among heterogeneous SU networks for achieving an efficient spectrum usage. In this study, we first introduce a new parameter named as quality of coexistence (QoC), which is defined as the ratio between the quality of SU transmissions and the negative interference to PUs. In this study we assume that the SUs have multiple antennas and employ fixed transmit power control (fixed-TPC). By using the approximation to the distribution of a weighted sum of chi-square random variables (RVs), we develop an analytical model for the time slot allocation among SU networks. Using this analytical model, we obtain the optimal time slot allocation ratios as well as transmit powers of the SU networks by maximizing the QoC. This leads to an efficient spectrum usage among SUs and a minimized negative influence to the PUs. Results show that in a particular scenario the QoC can be increased by 30%.