Reed-Solomon (RS) codes are widely used in digital communication and storage systems. Unlike usual VLSI approaches, this paper presents a high throughput fully programmable Reed-Solomon decoder on a multi-core processor. The multi-core processor platform is a 2-Dimension mesh array of Single Instruction Multiple Data (SIMD) cores, and it is well suited for digital communication applications. By fully extracting the parallelizable operations of the RS decoding process, we propose multiple optimization techniques to improve system throughput, including: task level parallelism on different cores, data level parallelism on each SIMD core, minimizing memory access, and route length minimized task mapping techniques. For RS(255, 239, 8), experimental results show that our 12-core implementation achieve a throughput of 4.35 Gbps, which is much better than several other published implementations. From the results, it is predictable that the throughput is linear with the number of cores by our approach.

Wireless capsule endoscopy (WCE) is now one of most important applications in implant body area networks (BANs). WCE requires high throughput performance due to its real-time data transmission, whereas the communication performance depends much on the transmit power, which is strictly regulated in order to satisfy a safety guideline in terms of specific absorption rate (SAR). Spatial diversity reception is well known to improve the wireless performance without any temporal and spectral resource expansion. Additionally, applying spatial diversity reception to WCE systems can be expected to not only improve the wireless communication performance but also to reduce SAR. Therefore, this paper investigates the impact of spatial diversity reception on SAR levels for the 400 MHz medical implant communication service (MICS) band. To begin with, based on finite-difference time-domain (FDTD) simulations for implant BAN propagation with a numerical human body model, we first calculate the BER performance and derive the required transmit power to secure a permissible BER. Then, this paper calculates the local peak SAR under the required transmit power when the implant transmitter moves through the digestive organs. Finally, our simulation results demonstrate that applying spatial diversity reception can significantly reduce SAR in implant BANs.

Yield-driven clock skew scheduling was previously formulated as a minimum cost-to-time ratio cycle problem, by assuming that variational path delays are in Gaussian distributions. However in today's nanometer technology, process variations show growing impacts on this assumption, as variational delays with non-Gaussian distributions have been observed on these paths. In this paper, we propose a novel yield-driven clock skew scheduling method for arbitrary distributions of critical path delays. Firstly, a general problem formulation is proposed. By integrating the cumulative distribution function (CDF) of critical path delays, the formulation is able to handle path delays with any distributions. It also generalizes the previous formulations on yield-driven clock skew scheduling and indicates their statistical interpretations. Generalized Howard algorithm is derived for finding the critical cycles of the underlying timing constraint graphs. Moreover, an effective algorithm based on minimum balancing is proposed for the overall yield improvement. Experimental results on ISCAS89 benchmarks show that, compared with two representative existing methods, our method remarkably improves the yield by 10.25% on average (up to 14.66%).

This study examines the robustness of image quality factors in various types of environment illumination using a parameter design in the field of quality engineering. Experimental results revealed that image quality factors are influenced by environment illuminations in the following order: minimum luminance, maximum luminance and gamma.

In large-scale collaborative computing, users and resource providers organize various Virtual Organizations (VOs) to share resources and services. A VO organizes other sub-VOs for the purpose of achieving the VO goal, which forms hierarchical VO environments. VO participants agree upon a certain policies, such as resource sharing amount or user accesses. In this letter, we provide an optimal resource sharing mechanism in hierarchical VO environments under resource sharing agreements. The proposed algorithm enhances resource utilization and reduces mean response time of each user.

In this paper, a hybrid parallel implementation of inverse matrix computation using SMW formula is proposed. By aggregating the memory bandwidth in the hybrid parallel implementation, the bottleneck due to the memory bandwidth limitation in the authors previous multicore implementation has been dissolved. More than 8 times of speed up is also achieved with dual-core 8-nodes implementation which leads more than 20 simulation steps per second, or near real-time performance.

Network survivability is defined as the ability of a network keeping connected under failures and/or attacks. In this paper, we propose two stochastic models; binomial model and negative binomial model, to quantify the network survivability and compare them with the existing Poisson model. We give mathematical formulae of approximate network survivability for respective models and use them to carry out the sensitivity analysis on model parameters. Throughout numerical examples it is shown that the network survivability can change drastically when the number of network nodes is relatively small under a severe attack mode which is called the Black hole attack.

Random telegraph noise (RTN) is a phenomenon that is considered to limit the reliability and performance of circuits using advanced devices. The time constants of carrier capture and emission and the associated change in the threshold voltage are important parameters commonly included in various models, but their extraction from time-domain observations has been a difficult task. In this study, we propose a statistical method for simultaneously estimating interrelated parameters: the time constants and magnitude of the threshold voltage shift. Our method is based on a graphical network representation, and the parameters are estimated using the Markov chain Monte Carlo method. Experimental application of the proposed method to synthetic and measured time-domain RTN signals was successful. The proposed method can handle interrelated parameters of multiple traps and thereby contributes to the construction of more accurate RTN models.

An analytical performance evaluation model is presented in this paper. A time-splitting transmitter circuit employing a selectively activated flip-driver (SAFD) is presented and its performance is estimated by the new model. The optimal partitioning method which maximizes the performance of a given bus-invert (BI) coding circuit is also presented. When a bus is optimally partitioned, an ordinary BI circuit can reduce the number of bus transitions by about 25%, while an SAFD circuit can remove about 35% of them. The newly developed method is verified by simulations whose results correspond very well to the values predicted by the model.

From an information-theoretic point of view, it is well known that the capacity of relay channels comprising of three terminals is much greater than that of two terminal direct channels especially for low SNR region. Previously invented relay coding strategies have not been designed to achieve this relaying gain occurring in the low SNR region. In this paper, we propose a new simple coding strategy for a relay channel with low SNR or, equivalently, for a very noisy relay channel. The multiplicative repetition is utilized to design this simple coding strategy. We claim that the proposed strategy is simple since the destination and the relay can decode with almost the same computational complexity by sharing the same structure of decoder. An appropriate static power allocation which yields the maximum throughput close to the optimal one in low SNRs is also suggested. Under practical constraints such as equal time-sharing etc., the asymptotic performance of this simple strategy is within 0.5 dB from the achievable rate of a relay channel. Furthermore, the performance at few thousand bits enjoys a relaying gain by approximately 1 dB.

This paper is concerned with coding theorems in the optimistic sense for separate coding of two correlated general sources X1 and X2. We investigate the achievable rate region Ropt (X1,X2) such that the decoding error probability caused by two encoders and one decoder can be arbitrarily small infinitely often under a certain rate constraint. We give an inner and an outer bounds of Ropt (X1,X2), where the outer bound is described by using new information-theoretic quantities. We also give two simple sufficient conditions under which the inner bound coincides with the outer bound.

In this paper, a complete SSTA scheme is proposed to calculate the output waveform of a logic cell on any random selected point in the process variational space, or the mean value and variance of the output signal with very high accuracy and acceptable CPU cost. At first, Miller capacitances between the input nodes and internal nodes of a logic cell are introduced to construct the improved MCSM model so as to improve the modeling accuracy. Secondly, the stochastic collocation method jointed with the Modified Nested Sparse Grid technique is adopted for SSTA procedure to avoid the exponential increase of the collocation points number caused by tensor product. Thirdly, a Nominal waveform based Fast Simulation Method is developed to speedup the simulation on each collocation point. At last, Automatic Waveform Construction Technique is developed to construct the output waveform with the approximation points as little as possible to decrease the computational cost while guaranteeing high accuracy. Numerical results are also given to demonstrate the efficiency of the proposed algorithm.

In recent years, the demand for low-power design has remained undiminished. In this paper, a pseudo power gating (SPG) structure using a normal logic cell is proposed to extend the power gating to an ultrafine grained region at the gate level. In the proposed method, the controlling value of a logic element is used to control the switching activity of modules computing other inputs of the element. For each element, there exists a submodule controlled by an input to the element. Power reduction is maximized by controlling the order of the submodule selection. A basic algorithm and a switching activity first algorithm have been developed to optimize the power. In this application, a steady maximum depth constraint is added to prevent the depth increase caused by the insertion of the control signal. In this work, various factors affecting the power consumption of library level circuits with the SPG are determined. In such factors, the occurrence of glitches increases the power consumption and a method to reduce the occurrence of glitches is proposed by considering the parity of inverters. The proposed SPG method was evaluated through the simulation of the netlist extracted from the layout using the VDEC Rohm 0.18 µm process. Experiments on ISCAS'85 benchmarks show that the reduction in total power consumption achieved is 13% on average with a 2.5% circuit delay degradation. Finally, the effectiveness of the proposed method under different primary input statistics is considered.

Recently, cooperative spectrum sensing is being studied to greatly improve the sensing performance of cognitive radio networks. To develop an adaptable cooperative sensing algorithm, an important issue is how to properly induce selfish users to participate in spectrum sensing work. In this paper, a new cognitive radio spectrum sharing scheme is developed by employing the trust-based bargaining model. The proposed scheme dynamically adjusts bargaining powers and adaptively shares the available spectrum in real-time online manner. Under widely different and diversified network situations, this approach is so dynamic and flexible that it can adaptively respond to current network conditions. Simulation results demonstrate that the proposed scheme can obtain better network performance and bandwidth efficiency than existing schemes.

Many learning machines such as normal mixtures and layered neural networks are not regular but singular statistical models, because the map from a parameter to a probability distribution is not one-to-one. The conventional statistical asymptotic theory can not be applied to such learning machines because the likelihood function can not be approximated by any normal distribution. Recently, new statistical theory has been established based on algebraic geometry and it was clarified that the generalization and training errors are determined by two birational invariants, the real log canonical threshold and the singular fluctuation. However, their concrete values are left unknown. In the present paper, we propose a new concept, a quasi-regular case in statistical learning theory. A quasi-regular case is not a regular case but a singular case, however, it has the same property as a regular case. In fact, we prove that, in a quasi-regular case, two birational invariants are equal to each other, resulting that the symmetry of the generalization and training errors holds. Moreover, the concrete values of two birational invariants are explicitly obtained, hence the quasi-regular case is useful to study statistical learning theory.

We propose a chip identification (ID) generating scheme with random variation of transistor characteristics in SRAM bitcells. In the proposed scheme, a unique fingerprint is generated by grounding both bitlines in write operations. Through minor modifications, this scheme can be implemented for existing SRAMs. It has high speed, and it can be implemented in a very small area overhead. The generated fingerprint mainly reflects threshold voltages of load transistors in the bitcells. We fabricated test chips in a 65-nm process and obtained 12,288 sets of unique 128-bit fingerprints, which are evaluated in this paper. The failure rate of the IDs is found to be 2.110-12.

Permutation polynomial based interleavers over integer rings, in particular quadratic permutation polynomials have been widely studied. In this letter, higher degree permutation polynomials for interleavers are considered for interleavers and permutation polynomials superior to quadratic permutation polynomials are found for some lengths.

Two-dimensional (2-D) codes for optical code-division multiple access (O-CDMA) systems can increase the number of subscribers and simultaneous users as compared to one-dimensional time-spreading codes. Multiple-wavelength optical orthogonal code (MWOOC), which is one of the 2-D codes, uses prime sequences as a wavelength-hopping code and an optical orthogonal code (OOC) as a time-spreading code. MWOOCs have some advantages over other 2-D codes especially in high bit-rate O-CDMA systems. The only drawback of MWOOC is that the performance degrades significantly when the number of wavelengths is not prime. Recently a generalized class of modified prime sequence codes (MPSCs), which includes the class of original MPSCs as its subclass, was presented. An important property of generalized MPSCs is that the codes can be constructed over not only prime fields but also extension fields. It has been shown that the correlation property of generalized MPSCs is the same as that of the original MPSCs. This paper investigates MWOOC with generalized prime sequences, which can be obtained in the process of generating the generalized MPSCs, as a wavelength-hopping code. Use of the generalized prime sequences can solve the nonprime problem of MWOOCs. The average error probability of the proposed MWOOCs is formulated theoretically and numerical results are compared with that of the original schemes. It is shown that nonprime numbers, such as 2m, 3m and 5m, can be also taken as the number of wavelengths without degrading the system performance in the proposed systems.

The interference rejection combining (IRC) receiver, which can suppress inter-cell interference, is effective in improving the cell-edge user throughput. The IRC receiver is typically based on the minimum mean square error (MMSE) criteria, and requires a covariance matrix including the interference signals, in addition to a channel matrix from the serving cell. Therefore, in order to clarify the gain from the IRC receiver, the actual estimation error of these matrices should be taken into account. In a system performance evaluation, the link performance modeling of the IRC receiver, i.e., the output signal-to-interference-plus-noise power ratio (SINR) after IRC reception including the estimation errors, is very important in evaluating the actual performance of the IRC receiver in system level simulations. This is because these errors affect the suppression of the interference signals for the IRC receiver. Therefore, this paper investigates and proposes IRC receiver modeling schemes for the covariance matrix and channel estimation errors. As the modeling scheme for the covariance matrix, we propose a scheme that averages the conventional approximation using the complex Wishart distribution in the frequency domain to address issues that arise in a frequency selective fading channel. Furthermore, we propose a modeling scheme for the channel estimation error according to the ideal channel response of all cells and a channel estimation filter to address channel fading fluctuations. The results of simulations assuming the LTE/LTE-Advanced downlink with two transmitter and receiver antenna branches show that the proposed modeling scheme for the covariance matrix estimation error accurately approximates the performance of a realistic IRC receiver, which estimates the covariance matrix and channel matrix of the serving cell based on the demodulation reference signal (DM-RS), even in a frequency selective fading channel. The results also show that the proposed modeling scheme for the channel estimation error is a robust scheme in terms of the r.m.s. delay spread of a channel model compared to the scheme using the mean square error (MSE) statistic of the estimated channel coefficients based on a channel estimation filter.

Bag of visual words is a promising approach to object categorization. However, in this framework, ambiguity exists in patch encoding by visual words, due to information loss caused by vector quantization. In this paper, we propose to incorporate patch-level contextual information into bag of visual words for reducing the ambiguity mentioned above. To achieve this goal, we construct a hierarchical codebook in which visual words in the upper hierarchy contain contextual information of visual words in the lower hierarchy. In the proposed method, from each sample point we extract patches of different scales, all of which are described by the SIFT descriptor. Then, we build the hierarchical codebook in which visual words created from coarse scale patches are put in the upper hierarchy, while visual words created from fine scale patches are put in the lower hierarchy. At the same time, by employing the corresponding relationship among these extracted patches, visual words in different hierarchies are associated with each other. After that, we design a method to assign patch pairs, whose patches are extracted from the same sample point, to the constructed codebook. Furthermore, to utilize image information effectively, we implement the proposed method based on two sets of features which are extracted through different sampling strategies and fuse them using a probabilistic approach. Finally, we evaluate the proposed method on dataset Caltech 101 and dataset Caltech 256. Experimental results demonstrate the effectiveness of the proposed method.