In this study, a wideband 3/4 elliptical ring patch operating millimeter wave band is proposed. Using this structure, the patch antenna is designed for circular polarization and wide-band operation at about 32.1-40 GHz for millimeter wave communication. Simulated and measured results for main parameters such as voltage standing wave ratio (VSWR), impedance bandwidth, axial ratio, radiation patterns and gains are also discussed. The study shows that modeling of such antennas, with simplicity in designing and feeding, can well meet the requirements of millimeter-wave wireless communication systems.

This paper presents an analysis of the effects of RF filter characteristics on the system performance of an impulse radio. The impulse radio system transmits modulated pulses having very short time duration. Information can be extracted in the receiver side based on the cross-correlation between received and reference pulses. Accordingly, the pulse distortion due to in-band group delay variation can cause serious degradation in system performance. In general, RF band pass filters inevitably cause non-uniform group delays to the signal passing through the filter that are proportional to its skirt characteristic due to its resonance phenomenon. In this work, a small signal scattering parameter, S21, which is a frequency domain parameter, and its Fourier transform are utilized to characterize the output pulse waveform under the condition that the input and output ports are matched. The output pulse waveform of the filter is predicted based on the convolution integral between the input pulse and filter transfer function, and the analysis result is compared with previously reported experimental result. The resulting bit error rate performances in a bi-phase modulation and a pulse position modulation based impulse radio system are also calculated. Moreover, improvement of system performance by the pulse shaping method, a potential solution for pulse waveform distortion, is analyzed.

A training-based vector channel estimation method has been proposed for single-user code-division multiple access (CDMA) systems in fast-varying correlated multipath fading channels. In this paper, we extend it in an iterative way to multiuser multiple-input multiple-output (MIMO) CDMA systems where both the transmitter and receiver have multiple antennas. In the training period, we propose to add the minimum mean square error (MMSE) front end before channel estimation to suppress multiuser interference (MUI) from substreams with difference spreading codes, so then we can get good initial vector channel estimation for each user. In the data transmission period, we proposed to add MMSE/parallel interference cancellation (PIC) front end to suppress MUI, interference suppression, and vector channel estimation in an iterative way. The perfect channel estimation is assumed in Liu et al., and the inter-play between channel estimation and multiuser detection is not discussed either. On the contrary, the novelty of the proposed method is that we add MMSE/PIC front end (in addition to matched filter) before channel estimation and we repeatedly switch between MMSE/PIC front end and channel estimation.

This paper presents an automatic edge segment based algorithm for the detection of moving objects that has been specially developed to deal with the variations in illumination and contents of background. We investigated the suitability of the proposed edge segment based moving object detection algorithm in comparison with the traditional intensity based as well as edge pixel based detection methods. In our method, edges are extracted from video frames and are represented as segments using an efficiently designed edge class. This representation helps to obtain the geometric information of edge in the case of edge matching and shape retrieval; and creates effective means to incorporate knowledge into edge segment during background modeling and motion tracking. An efficient approach for background edge generation and a robust method of edge matching are presented to effectively reduce the risk of false alarm due to illumination change and camera motion while maintaining the high sensitivity to the presence of moving object. The proposed method can be successfully realized in video surveillance applications in home networking environment as well as various monitoring systems. As, video coding standard MPEG-4 enables content based functionality, it can successfully utilize the shape information of the detected moving objects to achieve high coding efficiency. Experiments with real image sequences, along with comparisons with some other existing methods are presented, illustrating the robustness of the proposed algorithm.

Simple-relay aided resource allocation (SRARA) schemes are incorporated with throughput guarantee scheduling (TGS) in IEEE 802.16 type time division duplex--orthogonal frequency division multiple access (TDD-OFDMA) downlink in order to enhance service coverage, where the amount of resources at each relay is limited due to either its available power which is much smaller than base station (BS) power or the required overhead. The performance of SRARA schemes is evaluated with both proportional fair (PF) and TGS schedulers at 64 kbps and 128 kbps user throughput requirements when total RS power is set to 500 mW or 1 W. For SRARA with RSs of relatively lower power (500 mW), schemes that put total power into only one subchannel offer larger coverage than when both subchnnels are used with equal power allocation, while the RS with evenly power-allocated two subchannels could provide larger coverage gain for a relatively higher power (1 W). Depending upon the target throughputs it is shown which of the relay scheme or scheduler design would play more important role in improving coverage. In a lower target (64 kbps), more improvement comes from relay scheme rather than scheduler design. For a relatively higher level (128 kbps), it comes from scheduler design rather than relay due to the fact that simple relay can't help using strictly limited amount of resources.

This paper presents an efficient diagnosis scheme for RAMs. Three March-based algorithms are proposed to diagnose simple functional faults of RAMs. A March-15N algorithm is used for locating and partially diagnosing faults of bit-oriented or word-oriented memories, where N represents the address number. Then a 3N March-like algorithm is used for locating the aggressor words (bits) of coupling faults (CFs) in word-oriented (bit-oriented) memories. It also can distinguish the faults which cannot be identified by the March-15N algorithm. Thus, the proposed diagnosis scheme can achieve full diagnosis and locate aggressors with (15N + 3mN) Read/Write operations for a bit-oriented RAM with m CFs. For word-oriented RAMs, a March-like algorithm is also proposed to locate the aggressor bit in the aggressor word with 4 log2B Read/Write operations, where B is the word width. Analysis results show that the proposed diagnosis scheme has higher diagnostic resolution and lower time complexity than the previous fault location and fault diagnosis approaches. A programmable built-in self-diagnosis (BISD) design is also implemented to perform the proposed diagnosis algorithms. Experimental results show that the area overhead of the BISD is small--only about 2.17% and 0.42% for 16 K8-bit and 16 K128-bit SRAMs, respectively.

In this paper, we propose a sequential type-based detection scheme for wireless sensor networks in the case of spatially and temporally identically and independently distributed observations. First, we investigate the optimal sequential detection rule of the proposed scheme, and then with the motivation of reducing the computational complexity of the optimal detection rule, we consider an approximation scheme and derive a suboptimal detection rule. We also compare the performances of the type-based sequential detection scheme with those of the non-sequential type-based detection scheme in terms of both average number of observations and total energy consumption, and determine the region of individual node power where the proposed scheme outperforms the non-sequential scheme. In addition, we show that the approximated detection rule provides the similar results as the optimal detection rule with a significant reduction of the computational complexity, which makes the approximated detection rule useful for real-time applications.

Spatial power/ground level variation causes power/ground level mismatch between driver and receiver, and the mismatch affects gate propagation delay. This paper proposes a timing analysis method based on a concept called "PG level equalization" which is compatible with conventional STA frameworks. We equalize the power/ground levels of driver and receiver. The charging/discharging current variation due to equalization is compensated by replacing output load. We present an implementation method of the proposed concept, and demonstrate that the proposed method works well for multiple-input gates and RC load model.

One method for achieving high-speed waveform digitizing uses time-interleaved A-D Converters (ADCs). It is known that, in this method, using multiple ADCs enables sampling at a rate higher than the sampling rate of the ADC being used. Degradation of the dynamic range, however, results from such factors as phase error in the sampling clock applied to the ADC, and mismatched frequency characteristics among the individual ADCs. This paper describes a method for correcting these mismatches using a digital signal processing (DSP) technique. This method can be applied to any number of interleaved ADCs, and it does not require any additional hardware; good correction and improved accuracy can be obtained simply by adding a little to the computing overhead.

We consider power and rate adaptations in multicarrier (MC) direct-sequence code-division multiple-access (DS/CDMA) communications under the assumption that channel state information is provided at both the transmitter and the receiver. We propose, as a power allocation strategy in the frequency domain, to transmit each user's DS waveforms over the user's sub-band with the largest channel gain, rather than transmitting identical DS waveforms over all sub-bands. We then adopt channel inversion power adaptation in the time domain, where the target user's received power level maintains at a fixed value. We also investigate rate adaptation in the time domain, where the data rate is adapted such that a desired transmission quality is maintained. We analyze the BER performance of the proposed power and rate adaptations with fixed average transmission power, and show that power adaptation in both the frequency and the time domains or combined power adaptation in the frequency domain and rate adaptation in the time domain make significant performance improvement over the power adaptation in the frequency domain only. We also compare the performance of the proposed power and rate adaptation schemes in MC-DS/CDMA systems to that of power and rate adapted single carrier DS/CDMA systems with RAKE receiver.

We have been investigating a new class of ubiquitous services, called Activity Logging, which takes advantage for private and public sensors and the RFID tags on real-world objects. The purpose of Activity Logging is to digitally record users' interests with real-world objects and users' context to describe the users' activity. Such digital information acquired from a range of sensors and tags, if being accumulated, forms a great data source for users to recall their activities later or to share the activities with others. This paper explores the design space to realize Activity Logging, and proposes a simple mobile device called Activity Recorder that marries public and private sensors to provide a powerful Activity Logging service. An Activity Recorder contains a range of private sensors, and has communication capability to work with public sensors around the user.

The link structure of the Web is generally viewed as the webgraph. Web structure mining is a research area that mainly aims to find hidden communities by focusing on the webgraph, and communities or their cores are supposed to constitute dense subgraphs. Therefore, structure mining can actually be realized by enumerating such substructures, and Kleinberg's biclique model is well-known among them. In this paper, we examine some candidate substructures, including conventional bicliques, and attempt to find useful information from the real web data. Especially, we newly exploit isolated cliques for our experiments of structure mining. As a result, we discovered that isolated cliques that lie over multiple domains can stand for useful communities, which implies the validity of isolated clique as a candidate substructure for structure mining. On the other hand, we also observed that most of isolated cliques on the Web correspond to menu structures and are inherent in single domains, and that isolated cliques can be quite useful for detecting harmful link farms.

Based on the concept of sliding mode control, we study the problem of steady state covariance assignment for bilinear stochastic systems. We find that the invariance property of sliding mode control ensures nullity of the matched bilinear term in the system on the sliding mode. By suitably using Ito calculus, the controller u(t) can be designed to force the feedback gain matrix G to achieve the goal of steady state covariance assignment. We also compare our method with other approaches via simulations.

In this paper, we propose a novel migration method. In this method, the resultant placement retains the structure of the original placement, called model placement, as much as possible. For this purpose, we minimize the sum of the difference in area between the model placement and the relocated one and the total amount of displacement between them. Moreover, to achieve a short runtime, we limit the solution space and change the packing origin in the optimization process. We construct the system on Sequence-Pair. Experimental results show that our approach preserves the chip area and the overall circuit structure with 98% less runtime than that realized by naive simulated annealing.

A multiple-output function can be represented by a binary decision diagram for characteristic function (BDD_for_CF). This paper presents a method to represent multiple-output incompletely specified functions using BDD_for_CFs. An algorithm to reduce the widths of BDD_for_CFs is presented. This method is useful for decomposition of incompletely specified multiple-output functions. Experimental results for radix converters, adders, a multiplier, and lists of English words show that this method is useful for the synthesis of LUT cascades. An implementation of English words list by LUT cascades and an auxiliary memory is also shown.

This paper proposes a method (Group-Linking Method) that has control over the complexity of the sequential function to construct Finite Memory Machines with minimal order--the machines have the largest number of states based on their memory taps. Finding a machine with maximum number of states is a nontrivial problem because the total number of machines with memory order k is (256)2k-2, a pretty large number. Based on the analysis of Group-Linking Method, it is shown that the amount of data necessary to reconstruct an FMM is the set of strings not longer than the depth of the machine plus one, which is significantly less than that required for traditional greedy-based machine learning algorithm. Group-Linking Method provides a useful systematic way of generating unified benchmarks to evaluate the capability of machine learning techniques. One example is to test the learning capability of recurrent neural networks. The problem of encoding finite state machines with recurrent neural networks has been extensively explored. However, the great representation power of those networks does not guarantee the solution in terms of learning exists. Previous learning benchmarks are shown to be not rich enough structurally in term of solutions in weight space. This set of benchmarks with great expressive power can serve as a convenient framework in which to study the learning and computation capabilities of various network models. A fundamental understanding of the capabilities of these networks will allow users to be able to select the most appropriate model for a given application.

Most studies into multiple-input multiple-output (MIMO) antenna systems have aimed at determining the capacity-achieving (CA) input covariance given a certain degree of channel state information (CSI) at the transmitter and/or the receiver side. From the practical perspective, however, there is a growing interest in investigating the scenario where the system performance is power-limited as opposed to rate-limited. Of particular concern is the open problem of solving the optimal power-saving (PS) input covariance for spatially correlated MIMO channels when only the long-term (slow-varying) channel spatial covariance information is available at the transmitter. In an attempt to achieve this goal, this paper analyzes the characteristics of the optimal PS input covariance given the knowledge of channel spatial covariance information and the rate constraint of the transmission. Sufficient and necessary conditions of the optimal PS input covariance are derived. By considering the large-system regimes, we further devise an efficient iterative algorithm to compute the asymptotic optimal PS input covariance. Numerical results will show that the asymptotic solution is very effective in that it gives promising results even for MIMO systems with only a few antennas at the transmitter and the receiver.

In this letter, we propose a new digital image watermarking method using interval arithmetic. This is a new application of interval arithmetic. Experimental results show that the proposed method gives a watermarked image of better quality and is robust against some attacks.

A temporal correlation based port combination algorithm that customizes the router design in Network-on-Chip (NoC) is proposed for reconfigurable systems in order to minimize required hardware amount. Given the traffic characteristics of the target application and the expected hardware amount reduction rate, the algorithm automatically makes the port combination plan for the networks. Since the port combination technique has the advantage of almost keeping the topology including two-surface layout, it does not affect the design of the other layer, such as task mapping and scheduling. The algorithm shows much better efficiency than the algorithm without temporal correlation. For the multimedia stream processing application, the algorithm can save 55% of the hardware amount without performance degradation, while the none temporal correlation algorithm suffers from 30% performance loss.

This paper proposes a behavioral level partitioning method for efficient behavioral synthesis from a large sequential program consisting of a set of functions. Our method optimally determines functions to be inlined into the main module and the other functions to be synthesized into sub modules in such a way that the overall datapath is minimized while the complexity of individual modules is lower than a certain level. The partitioning problem is formulated as an integer programming problem. Experimental results show the effectiveness of the proposed method.