This paper deals with the random number generation problem under the framework of a separate coding system for correlated memoryless sources posed and investigated by Slepian and Wolf. Two correlated data sequences with length n are separately encoded to nR1, nR2 bit messages at each location and those are sent to the information processing center where the encoder wish to generate an approximation of the sequence of independent uniformly distributed random variables with length nR3 from two received random messages. The admissible rate region is defined by the set of all the triples (R1,R2,R3) for which the approximation error goes to zero as n tends to infinity. In this paper we examine the asymptotic behavior of the approximation error inside and outside the admissible rate region. We derive an explicit lower bound of the optimal exponent for the approximation error to vanish and show that it can be attained by the universal codes. Furthermore, we derive an explicit lower bound of the optimal exponent for the approximation error to tend to 2 as n goes to infinity outside the admissible rate region.

The subspace algorithm can be utilized for the blind detection of space-time block codes (STBC) without knowledge of channel state information (CSI) both at the transmitter and receiver. However, its performance degrades when the channels are correlated. In this letter, we analyze the impact of channel correlation from the orthogonality loss between the transmit signal subspace (TSS) and the statistical noise subspace (SNS). Based on the decoding property of the subspace algorithm, we propose a revised detection in favor of the channel correlation matrix (CCM) only known to the receiver. Then, a joint transmit-receive preprocessing scheme is derived to obtain a further performance improvement when the CCM is available both at the transmitter and receiver. Analysis and simulation results indicate that the proposed methods can significantly improve the blind detection performance of STBC over the correlated channels.

An adaptive subcarrier allocation (SA) algorithm is proposed for both the enhancement of system capacity and the practical implementation in a clustered OFDM system. The proposed algorithm is based on the two dimensional comparison of the channel gain in both rows and columns of the channel matrix to achieve higher system capacity. Simulation results demonstrate that the proposed algorithm outperforms the SA algorithm based on only one dimensional comparison in terms of system capacity, and furthermore, it performs as well as the optimal SA algorithm at relatively low computational cost.

We developed a comprehensive simulation system for evaluating satellite-based navigation services in highly built-up areas; the system can accommodate Global Positioning System (GPS) multipath effects, as well as line-of-sight (LOS) and dilution of position (DOP) issues. For a more realistic simulation covering multipath and diffracted signal propagations, a 3D-ray tracing method was combined with a satellite orbit model and three-dimensional (3D) geographic information system (GIS) model. An accuracy estimation model based on a 3D position determination algorithm with a theoretical delay-locked loop (DLL) correlation computation could measure the extent to which multipath mitigation improved positioning accuracy in highly built-up areas. This system could even capture the multipath effect from an invisible satellite, one of the greatest factors in accuracy deterioration in highly built-up areas. Further, the simulation results of satellite visibility, DOP, and multipath occurrence were mapped to show the spatial distribution of GPS availability. By using object-oriented programming, our simulation system can be extended to other global navigation satellite systems (GNSSs) simply by adding the orbital information of the corresponding GNSS satellites. We demonstrated the applicability of our simulation system in an experimental simulation for Shinjuku, an area of Tokyo filled with skyscrapers.

This paper discusses the behavior of the second-order modes (Hankel singular values) of linear continuous-time systems under typical frequency transformations, such as lowpass-lowpass, lowpass-highpass, lowpass-bandpass, and lowpass-bandstop transformations. Our main result establishes the fact that the second-order modes are invariant under any of these typical frequency transformations. This means that any transformed system that is generated from a prototype system has the same second-order modes as those of the prototype system. We achieve the derivation of this result by describing the state-space equations and the controllability/observability Gramians of transformed systems.

Repacking is an efficient scheme for bandwidth packing problem (BPP) in centralized networks (CNs), where a central unit allocates bandwidth to the rounding terminals. In this paper, we study its performance by proposing a new formulation of the BPP in the CN, and introducing repacking scheme into next fit algorithm in terms of the online constraint. For the realistic applications, the effect of call demand distribution is also exploited by means of simulation. The results show that the repacking efficiency is significant (e.g. the minimal improvement about 13% over uniform distribution), especially in the scenarios where the small call demands dominate the network.

Grey world algorithm is a well-known color constancy algorithm. It is based on the Grey-World assumption i.e., the average reflectance of surfaces in the world is achromatic. This algorithm is simple and has low computational costs. However, for the images with several colors, the light source color could not be estimated correctly using the Grey World algorithm. In this paper, we propose a Multi-scale Adaptive Grey World algorithm (MAGW). First, multi-scale images are obtained based on wavelet transformation and the illumination color is estimated from different scales images. Then according to the estimated illumination color, the original image is mapped into the image under a canonical illumination with supervision of an adaptive reliability function, which is based on the image entropy. The experimental results show that our algorithm is effective and also has low computational costs.

We propose a new genetic fuzzy discretization method with feature selection for the pattern classification problems. Traditional discretization methods categorize a continuous attribute into a number of bins. Because they are made on crisp discretization, there exists considerable information loss. Fuzzy discretization allows overlapping intervals and reflects linguistic classification. However, the number of intervals, the boundaries of intervals, and the degrees of overlapping are intractable to get optimized and a discretization process increases the total amount of data being transformed. We use a genetic algorithm with feature selection not only to optimize these parameters but also to reduce the amount of transformed data by filtering the unconcerned attributes. Experimental results showed considerable improvement on the classification accuracy over a crisp discretization and a typical fuzzy discretization with feature selection.

Adaptive hybrid genetic algorithm concatenated with improved parallel interference cancellation, i.e. adaptive hybrid genetic algorithm parallel interference cancellation (AHGAPIC) was proposed. A study is conducted on the application of AHGAPIC to soft decoding high rate multi-user detection with diversity reception for dual-rate wideband DS-CDMA spread spectrum communications, aiming to mitigate the effect of multiple access interference. The relevant research has revealed that the local search capability of hybrid genetic algorithm (HGA) is still not good enough. Therefore, first, two evolutionary operations, i.e. inversion and insertion are merged into HGA to constitute a novel algorithm. With its moderate local search capability, this new algorithm can search for the global optimum region according to the information entropy, and then it is made adaptively vary its probabilities of crossover and mutation depending on the fitness values of the solutions to form the adaptive hybrid genetic algorithm (AHGA). Second, AHGA is utilized to effectively identify the better and better binary string to maximize the log-likelihood function of dual-rate multi-user detection. As AHGA converges to the optimum region, the control factor of the improved parallel interference cancellation (IPIC) detector is set to be the ratio of the average fitness value to the maximum fitness value of the population of AHGA. Finally, equipped with both the control factor and the binary string with the maximum fitness value as the initial data, the IPIC detector can rapidly find out the approximately optimum soft decoding vector. Then, it can obtain the approximately global optimum estimate point on the basis of the soft decoding rule, corresponding to the transmitted data bits. A lower bound of computational complexity has been achieved through simulations and qualitative analyses. The property of the proposed algorithm to converge rapidly leads to lower computational complexity. Emulation results have shown that the AHGAPIC soft decoding high rate multi-user detector is superior to other suboptimum detectors considered in this paper in terms of two points. They are the mitigation of multiple access interference and the resistance to near-far effects. Its performance is close to the sequential group optimum multi-user detector but with a shorter time delay.

We propose a novel clustering scheme considering non-uniform correlation distribution derived by experimental environment property. Firstly, we investigate the entropy property of actual environment, and then show that its spatial correlation is not uniformly distributed. Based on this result, we present the clustering strategy which provides the efficient data aggregation. Through the simulation under the non-uniform correlation distribution, we show the advantage of the proposed scheme in terms of the energy consumption property per node and the network lifetime.

Conventional clock and data recovery (CDR) using a phase locked loop (PLL) suffers from problems such as long lock time, low frequency acquisition and harmonic locking. Consequently, a CDR system using a time to digital converter (TDC) is proposed. The CDR consists of simple arithmetic calculation and a TDC, allowing a fully digital realization. In addition, utilizing a TDC also allows the CDR to have a very wide frequency acquisition range. However, deterministic jitter is caused with each sample, because the system's sampling time period is changing slightly at each data edge. The proposed system does not minimize jitter, but it tolerates small jitter. Therefore, the system offers a faster lock time and a smaller sampling error. This proposed system has been verified on system level in a Verilog-A environment. The proposed method achieves faster locking within just a few data bits. The peak to peak jitter of the recovered clock is 60 ps and the RMS jitter of the recovered clock is 30 ps, assuming that the TDC resolution is 10 ps. In applications where a small jitter error can be tolerated, the proposed CDR offers the advantage of fast locking time and a small sampling error.

An integrated multi-level simulation environment is developed for a highly collision-resistant RFID system. An analog/mixed-signal (AMS) simulator for a circuit-level description of analog front-end power/signal transmission through electro-magnetic coupling is concurrently connected to a tailored software simulator for system-level description of digital back-end processing of TH-CDMA based anti-collision communication. The feasibility of the RFID system in which more than 1,000 transponders can be identified by a single reader in 400 msec is successfuly explored, under a practical presence of field disturbances such as background noises in communication channels as well as variations of electro-magnetic coupling strengths for power transmission.

In this letter, we propose a enhanced framework for a Personalized User Interface (PUI). This framework allows users to access and customize virtual objects in virtual environments in the sense of sharing user centric context with virtual objects. The proposed framework is enhanced by integrating a unified context-aware application for virtual environments (vr-UCAM 1.5) into virtual objects in the PUI framework. It allows a virtual object to receive context from both real and virtual environments, to decide responses based on context and if-then rules, and to communicate with other objects individually. To demonstrate the effectiveness of the proposed framework, we applied it to a virtual heritage system. Experimental results show that we enhance the accessibility and the customizability of virtual objects through the PUI. The proposed framework is expected to play an important role in VR applications such as education, entertainment, and storytelling.

We present a computationally efficient sequential detection scheme using a modified Fano algorithm (MFA) for V-BLAST systems. The proposed algorithm consists of the following three steps: initialization, tree searching, and optimal selection. In the first step, the proposed detection scheme chooses several candidate symbols at the tree level of one. Based on these symbols, the MFA then finds the remaining transmitted symbols from the second tree level in the original tree structure. Finally, an optimal symbol sequence is decided among the most likely candidate sequences searched in the previous step. Computer simulation shows that the proposed scheme yields significant saving in complexity with very small performance degradation compared with that of sphere detection (SD).

Power supply noise waveforms are acquired in a voltage domain by an on-chip monitor at resolutions of 0.3 ns/1.2 mV, in a digital test circuit consisting of 0.18-µm CMOS standard logic cells. Concurrently, magnetic field variation on a printed circuit board (PCB) due to power supply current of the test circuit is measured by an off-chip magnetic probing technique. An equivalent circuit model that unifies on- and off-chip impedance network of the entire test setup for EMI analysis is used for calculating the on-chip voltage-mode power supply noise from the off-chip magnetic field measurements. We have confirmed excellent consistency in frequency components of power supply noises up to 300 MHz among those derived by the on-chip direct sensing and the off-chip magnetic probing techniques. These results not only validate the state-of-the art EMI analysis methodology but also promise its connectivity with on-chip power supply integrity analysis at the integrated circuit level, for the first time in both technical fields.

Detecting edge directions and estimating the exact value of a missing line are currently active research areas in deinterlacing processing. This paper proposes a spatial domain fuzzy rule that is based on an interpolation algorithm, which is suitable to the region with high motion or scene change. The algorithm utilizes fuzzy theory to find the most accurate edge direction with which to interpolate missing pixels. The proposed fuzzy direction oriented interpolator operates by identifying small pixel variations in seven orientations (0°, 45°, -45°, 63°, -63°, 72°, and -72°), while using rules to infer the edge direction. The Bayesian network model selects the most suitable deinterlacing method among three deinterlacing methods and it successively builds approximations of the deinterlaced sequence, by evaluating three methods in each condition. Detection and interpolation results are presented. Experimental results show that the proposed algorithm provides a significant improvement over other existing deinterlacing methods. The proposed algorithm is not only for speed, but also effective for reducing deinterlacing artifacts.

This paper proposes a design technique to reduce the power dissipation of CML driver for on-chip transmission-lines. CML drivers can operate at higher frequency than conventional static CMOS logic drivers. On the other hand, the power dissipation is larger than that of CMOS static logic drivers. The proposed method reduces the power dissipation by using an impedance-unmatched driver instead of the conventional impedance-matched driver. Measurement results show that the proposed method reduces the power dissipation by 32% compared with a conventional design at 12.5 Gbps.

We measured the complex permittivities of whole blood and blood plasma in quasi millimeter and millimeter wave bands using a coaxial probe method. The validity of these measurements was confirmed by comparing with those of a different measurement method, i.e., a dielectric tube method. It is shown that the complex permittivities of the blood samples are similar to those of water in quasi millimeter and millimeter wave bands. Furthermore, the temperature dependences of the complex permittivities of the samples were measured.

In this paper, we propose tight performance upper bounds for convolutional codes terminated with an input sequence of finite length. To obtain the upper bounds, a generalized weight enumerator of single error event is defined to represent the relation between the Hamming distance of the coded output and the Hamming distance of the selected input bits of a terminated convolutional code. In the generalized weight enumerator of single error event, codewords composed of multiple error events are not counted to provide tighter performance upper bounds. The upper bounds on frame error rate (FER) and average bit error rate (BER) of selected bits are computed from the generalized weight enumerators of single error event. A simple method is presented to compute the weight enumerator of a terminated convolutional code based on a modified trellis diagram.

To improve the channel estimation accuracy of multiple-input multiple-output (MIMO) multiplexing, we previously proposed iterative QR-decomposition with M-algorithm (QRD-M) with decision directed channel estimation. In this paper, to keep the computational complexity low while further improving the transmission performance, we will modify previously proposed iterative QRD-M by incorporating cyclic redundancy check (CRC) coding. In the proposed method, transmitted signals are ranked according to their results of CRC decoding and the received signal-to-interference plus noise power ratio (SINR). In the modified M-algorithm, since the results of Turbo decoding and CRC decoding are used to generate the surviving symbol replica, the accuracy of signal detection in the following steps can be improved. Furthermore, based on the results of CRC decoding, iterative process can be terminated before reaching the maximum allowable number of iterations. Computer simulation results show that the loss in the required average received signal energy per bit-to-noise power spectrum density ratio Eb/N0 for average packet error rate (PER) = 10-2 is only about 0.4 dB from maximum likelihood detection (Full MLD) with ideal channel estimation.