Cooperative transmission is an efficient approach to improve the performance of wireless communications over fading channels without the need for physical co-located antenna arrays. In this paper, we propose a novel cooperative protocol with selective decode-and-forward relays and generalized selection combining (GSC) technique at destination. The advantage of this scheme is that it not only allows us to optimize the structure of destination but also to fully exploit the diversity offered by the channels with an appropriate number of chosen strongest paths. For an arbitrary number of relays, an exact and closed-form expression of the Symbol Error Rate (SER) is derived for M-ary PSK in independent but not identically distributed Rayleigh fading channels. Various simulations are performed and their results exactly match the results of analyses.

Complex bandpass ΔΣAD modulators can provide superior performance to a pair of real bandpass ΔΣAD modulators of the same order. They process just input I and Q signals, not image signals, and AD conversion can be realized with low power dissipation, so that they are desirable for such low-IF receiver applications. This paper proposes a new architecture for complex bandpass Δ ΣAD modulators with cross-noise-coupled topology, which effectively raises the order of the complex modulator and achieves higher SQNDR (Signal to Quantization Noise and Distortion Ratio) with low power dissipation. By providing the cross-coupled quantization noise injection to internal I and Q paths, noise coupling between two quantizers can be realized in complex form, which enhances the order of noise shaping in complex domain, and provides a higher-order NTF using a lower-order loop filter in the complex ΔΣAD modulator. Proposed higher-order modulator can be realized just by adding some passive capacitors and switches, the additional integrator circuit composed of an operational amplifier is not necessary, and the performance of the complex modulator can be effectively raised without more power dissipation. We have performed simulation with MATLAB to verify the effectiveness of the proposed architecture. The simulation results show that the proposed architecture can achieve the realization of higher-order enhancement, and improve SQNDR of the complex bandpass ΔΣAD modulator.

This paper proposes a scan design for delay fault testability of dual circuits. In normal operation mode, each proposed scan flip flop operates as a master-slave flip flop. In test mode, the proposed scan design performs scan operation using two scan paths, namely master scan path and slave scan path. The master scan path consists of master latches and the slave scan path consists of slave latches. In the proposed scan design, arbitrary two-patterns can be set to flip flops of dual circuits. Therefore, it achieves complete fault coverage for robust and non-robust testable delay fault testing. It requires no extra latch unlike enhanced scan design. Thus the area overhead is low. The evaluation shows the test application time of the proposed scan design is 58.0% of that of the enhanced scan design, and the area overhead of the proposed scan design is 13.0% lower than that of the enhanced scan design. In addition, in testing of single circuits, it achieves complete fault coverage of robust and non-robust testable delay fault testing. It requires smaller test data volume than the enhanced scan design in testing of single circuits.

An adaptive algorithm to optimize the packet size in wireless mobile networks with Gauss-Markov mobility is presented. The proposed control algorithm conducts adaptive packet size control for mobile terminals that experience relatively fast changing channel conditions, which could be caused by fast mobility or other rapidly changing interference conditions. Due to the fast changing channel conditions, the packet size controller uses short channel history for channel status estimation and takes advantage of a pre-calculated probability density function (PDF) of the distance of the mobile nodes in the estimation process. The packet size is adapted to maximize the communication performance through automatic repeat request (ARQ). The adaptive packet size controlling algorithm is based on an estimation of the channel error rate and the link statistics obtained from the mobility pattern. It was found that the distribution of the link distance among mobile nodes following the Markov-Gauss mobility pattern in a circular communication range well fits the Beta PDF. By adapting the Beta PDF from the mobility pattern, the results show that it is possible to estimate the channel condition more accurately and thereby improve the throughput and utilization performance in rapidly changing wireless mobile networking systems.

In orthogonal frequency division multiplexing (OFDM) the multipath exceeding the guard interval (GI) causes inter-symbol interference (ISI) and inter-carrier interference (ICI), thereby making it difficult to achieve high data rate transmission. In this paper, the double window cancellation and combining (DWCC), introduced in [14], is analyzed by investigating SINR distribution under different delay spread channels. The analysis indicates that the extension of processing window in iterative cancellation can have an adverse effect on the performance for small interference levels. In addition, the optimal combining of DWCC and turbo equalization (TE), named TE-DWCC, is investigated by varying the iterative cancellation procedure between DWCC and channel decoder and the decision feedback type such as hard decision feedback (HDF) or soft decision feedback (SDF). Finally, by changing interference level, code rate, and decision feedback type, the performance of TE-DWCC is compared with the conventional canceller that adopts turbo equalization in the exponentially distributed slow fading channel.

This paper studies two types of documents in which an adversary can forge a signature on a chosen document. One type is that a nonce is padded on an input document. The time-stamp protocol is a good example of this type. Another is a structured document (such as PS or PDF) whose contents are described in a body part and information (such as generated time and a generator) are in a meta part. In fact, this paper shows how to forge a time-stamp, a signature on a PDF and an X.509 certificate by the extended forgery attack and numerical examples. Forged signature by the original or the extended attacks is only accepted by the clients whose length check of zero-field is loosely implemented. As a result, we found that the latest versions of Adobe's Acrobat and Acrobat Reader accept the forged time-stamp and the forged signature on a PDF document. Target of this attack is RSASSA-PKCS1-v1_5, which does not have provable security. We also show the expanded attack might forge the signature of RSASSA-PSS, which has provable security, when the length check of zero-field is omitted or loosely implemented.

An expectation for more intelligent Web is recently being reflected through the new research field called Semantic Web. In this paper, related with Semantic Web security, we introduce an RDF triple based access control model having explicit authorization propagation by inheritance and implicit authorization propagation by inference. Especially, we explain an authorization conflict problem between the explicit and the implicit authorization propagation, which is an important concept in access control for Semantic Web. We also propose a novel conflict detection algorithm using graph labeling techniques in order to efficiently find authorization conflicts. Some experimental results show that the proposed detection algorithm has much better performance than the existing detection algorithm when data size and number of specified authorizations become larger.

Multiple-input multiple- output (MIMO) and orthogonal frequency division multiplexing (OFDM) are two key techniques for broadband wireless mobile communications and channel state information (CSI) is critical for the realization and performance of MIMO-OFDM systems in doubly-selective fading channels. Channel estimation based on two-dimensional discrete-time Fourier transform interpolation (2D-DFTI) is a promising solution to obtain accurate CSI for MIMO-OFDM systems in theory because of both its robustness and high computational efficiency, however, its performance will degrade significantly in practical MIMO-OFDM systems due to the two-dimensional Gibbs phenomenon caused by virtual subcarriers and burst transmission. In this paper, we propose a novel channel estimation method based on the two-dimensional enhanced DFT interpolation (2D-EDFTI), i.e., the frequency-domain EDFTI (FD-EDFTI) concatenated with the time-domain EDFTI (TD-EDFTI), for practical burst-mode MIMO-OFDM systems with virtual subcarriers, which can increase the channel estimation accuracy effectively by mitigating the Gibbs phenomenon in frequency-domain and time-domain, respectively, while keeping good robustness and high computational efficiency. In addition to computer simulations, we further implement the 2D-EDFTI channel estimator into our real-time FPGA testbed of 44 MIMO-OFDM transmission via spatial multiplexing, together with different MIMO detectors. Both computer simulations and RF experiments demonstrate the superior performance of 2D-EDFTI channel estimation in doubly-selective fading channels, therefore, high-throughput MIMO-OFDM transmission based on different MIMO detection algorithms can always be well supported. Also, it can be applied to other MIMO-OFDM transmission schemes straightforwardly.

This paper studies the impact of dummy fill for chemical mechanical polishing (CMP)-induced capacitance variation on buffer insertion based on a virtual CMP fill estimation model. Compared with existing methods, our algorithm is more feasible by performing buffer insertion not in post-process but during early physical design. Our contributions are threefold. First, we introduce an improved fast dummy fill amount estimation algorithm based on [4], and use some speedup techniques (tile merging, fill factor and amount assigning) for early estimation. Second, based on some reasonable assumptions, we present an optimum virtual dummy fill method to estimate dummy position and the effect on the interconnect capacitance. Then the dummy fill estimation model was verified by our experiments. Third, we use this model in early buffer insertion after layer assignment considering the effects of dummy fill. Experimental results verified the necessity of early dummy fill estimation and the validity of our algorithm. Buffer insertion considering dummy fill during early physical design is necessary and our algorithm is promising.

In this paper, we propose an extension to GridFTP that optimizes its performance by dynamically adjusting the number of parallel TCP connections. GridFTP has been used as a data transfer protocol to effectively transfer a large volume of data in Grid computing. GridFTP supports a feature called parallel data transfer that improves throughput by establishing multiple TCP connections in parallel. However, for achieving high GridFTP throughput, the number of TCP connections should be optimized based on the network status. In this paper, we propose an automatic parallelism tuning mechanism called GridFTP-APT (GridFTP with Automatic Parallelism Tuning) that adjusts the number of parallel TCP connections according to information available to the Grid middleware. Through simulations, we demonstrate that GridFTP-APT significantly improves the performance of GridFTP in various network environments.

We propose an enhanced method for translating Topic Maps to RDF/RDF Schema, to realize the Semantic Web. A critical issue for the Semantic Web is to efficiently and precisely describe Web information resources, i.e., Web metadata. Two representative standards, Topic Maps and RDF have been used for Web metadata. RDF-based standardization and implementation of the Semantic Web have been actively performed. Since the Semantic Web must accept and understand all Web information resources that are represented with the other methods, Topic Maps-to-RDF translation has become an issue. Even though many Topic Maps to RDF translation methods have been devised, they still have several problems (e.g. semantic loss, complex expression, etc.). Our translation method provides an improved solution to these problems. This method shows lower semantic loss than the previous methods due to extract both explicit semantics and implicit semantics. Compared to the previous methods, our method reduces the encoding complexity of resulting RDF. In addition, in terms of reversibility, the proposed method regenerates all Topic Maps constructs in an original source when is reverse translated.

Testing PLLs (phase-locked loops) is becoming an important issue that affects both time-to-market and production cost of electronic systems. Though a PLL is the most common mixed-signal building block, it is very difficult to test due to internal analog blocks and signals. In this paper, we propose a new PLL BIST (built-in self test) using the distorted frequency detector that uses only internal digital signals. The proposed BIST does not need to load any analog nodes of the PLL. Therefore, it provides an efficient defect-oriented structural test scheme, reduced area overhead, and improved test quality compared with previous approaches.

This letter proposes two efficient decision-feedback (DF) detection schemes for space-time block code (STBC) over time-selective fading channels. The existing DF detection causes error propagation when the first symbol is not detected correctly. However, the proposed detection schemes provide two candidates according to a channel gain or an average log-likelihood ratio (LLR) based selection rule and choose a better candidate for the first symbol. Simulation results show that the proposed detection schemes reduce error propagation and yield significant signal-to-noise ratio (SNR) gain with moderate complexity, compared to the existing DF detection scheme.

A fine-grain reconfigurable VLSI for various applications including arithmetic operations is developed. In the fine-grain architecture, it is important to define a cell function which leads to high utilization of a logic block and reduction of a switch block. From the point of view, a universal-literal-based multiple-valued cell suitable for bit-serial reconfigurable computation is proposed. A series-gating differential-pair circuit is effectively employed for implementing a full-adder circuit of Sum and a universal literal circuit. Therefore, a simple logic block can be constructed using the circuit technology. Moreover, interconnection complexity can be reduced by utilizing multiple-valued signaling, where superposition of serial data bits and a start signal which indicates heading of one-word is introduced. Differential-pair circuits are also effectively employed for current-output replication, which leads to high-speed signaling to adjacent cells The evaluation is done based on 90 nm CMOS design rule, and it is made clear that the area of the proposed cell can be reduced to 78% in comparison with that of the CMOS implementatiuon. Moreover, its area-time product becomes 92% while the delay time is increased by 18%.

In this letter, we propose a new histogram equalization method to compensate for acoustic mismatches mainly caused by corruption of additive noise and channel distortion in speech recognition. The proposed method employs an improved test cumulative distribution function (CDF) by more accurately smoothing the conventional order statistics-based test CDF with the use of window functions for robust feature compensation. Experiments on the AURORA 2 framework confirmed that the proposed method is effective in compensating speech recognition features by reducing the averaged relative error by 13.12% over the order statistics-based conventional histogram equalization method and by 58.02% over the mel-cepstral-based features for the three test sets.

Multiple-input multiple-output (MIMO) maximum-SNR (max-SNR) system employs the maximum ratio combiner (MRC) at the receiver side and the maximum ratio transmitter (MRT) at the transmitter side. Its performances highly depend on MIMO channel characteristics, which vary according to both the number of antennas and their distribution between the transmitter and receiver sides. By using the decomposition of the ordered Wishart distribution in the uncorrelated Rayleigh case, we derived a closed-form expression of the largest eigenvalue probability density function (PDF). The final result yields to an expression form of the PDF where polynomials are multiplied by exponentials; it is worth underlining that, though this form had been previously observed for given couples of antennas, to date no formally-written closed-form was available in the literature for an arbitrary couple. Then, this new expression permits one to quickly and easily get the well known largest eigenvalue PDF and use it to determine the binary error probability (BEP) of the max-SNR.

We describe a statistical parametric speech synthesis system developed by a joint group from the Nagoya Institute of Technology (Nitech) and the Nara Institute of Science and Technology (NAIST) for the annual open evaluation of text-to-speech synthesis systems named Blizzard Challenge 2006. To improve our 2005 system (Nitech-HTS 2005), we investigated new features such as mel-generalized cepstrum-based line spectral pairs (MGC-LSPs), maximum likelihood linear transform (MLLT), and a full covariance global variance (GV) probability density function (pdf). A combination of mel-cepstral coefficients, MLLT, and full covariance GV pdf scored highest in subjective listening tests, and the 2006 system performed significantly better than the 2005 system. The Blizzard Challenge 2006 evaluations show that Nitech-NAIST-HTS 2006 is competitive even when working with relatively large speech databases.

In this paper, we propose a reduced-complexity radial basis function (RBF)-assisted decision-feedback equalizer (DFE)-based turbo equalization (TEQ) scheme using a novel extended fuzzy c-means (FCM) algorithm, which not only is comparable in performance to the Jacobian RBF DFE-based TEQ but also is low-complexity. Previous TEQ research has shown that the Jacobian RBF DFE TEQ considerably reduces the computational complexity with similar performance, when compared to the logarithmic maximum a posteriori (Log-MAP) TEQ. In this study, the proposed reduced-complexity RBF DFE TEQ further greatly reduces the computational complexity and is capable of attaining a similar performance in contrast to the Jacobian RBF DFE TEQ in the context of both binary phase-shift keying (BPSK) modulation and 4 quadrature amplitude modulation (QAM). With this proposal, the materialization of the RBF-assisted TEQ scheme becomes more feasible.

We describe an extension of the wideband direction-of-arrival (DOA) estimation method using a frequency-domain frequency-invariant beamformer (FDFIB). The technique uses the Matrix Pencil Method (MPM) instead of conventional methods based on the eigen-structure of the input covariance matrix. MPM offers excellent resolution compared to conventional methods.

The single-hidden-layer feedforward neural networks (SLFNs) are frequently used in machine learning due to their ability which can form boundaries with arbitrary shapes if the activation function of hidden units is chosen properly. Most learning algorithms for the neural networks based on gradient descent are still slow because of the many learning steps. Recently, a learning algorithm called extreme learning machine (ELM) has been proposed for training SLFNs to overcome this problem. It randomly chooses the input weights and hidden-layer biases, and analytically determines the output weights by the matrix inverse operation. This algorithm can achieve good generalization performance with high learning speed in many applications. However, this algorithm often requires a large number of hidden units and takes long time for classification of new observations. In this paper, a new approach for training SLFNs called least-squares extreme learning machine (LS-ELM) is proposed. Unlike the gradient descent-based algorithms and the ELM, our approach analytically determines the input weights, hidden-layer biases and output weights based on linear models. For training with a large number of input patterns, an online training scheme with sub-blocks of the training set is also introduced. Experimental results for real applications show that our proposed algorithm offers high classification accuracy with a smaller number of hidden units and extremely high speed in both learning and testing.