Selection relaying is a promising technique for practical implementation of cooperative systems with multiple relay nodes. However, to select the best relay, global channel knowledge is required at the selecting entity, which may result in considerable signaling overhead. In this paper, we consider the relay selection problem in dual-hop amplify-and-forward (AF) communication systems with partial channel state information (CSI). Relay selection strategies aiming at minimizing either the outage probability or the bit error rate (BER) with quantized CSI available are presented. We also propose a target rate based quantizer to efficiently partition the SNR range for outage minimized relay selection, and a target BER based quantizer for BER minimized relay selection. Simulation results show that near optimal performance is achievable with a few bits feedback to the selecting entity.

This paper proposes a method for detecting ellipses from an image despite (1) multiple colors within the ellipses, (2) partially occluded ellipses' boundaries, (3) noisy, locally deformed boundaries of ellipses, (4) presence of multiple objects other than the ellipses in the image, and (5) combinations of (1) through (4). After boundary curves are obtained by edge detection, by utilizing the first-order difference curves of the edge orientation of each pixel in the boundary curves, a segment-reconnect method obtains boundary clusters. Then, a modified RANSAC detects ellipses by choosing five pixels randomly from the boundary clusters, where overlapped ellipses are merged. Experimental results using synthesized images and real images demonstrate the effectiveness of the proposed method together with comparison with the Randomized Hough Transform, a well-known conventional method.

In this letter, a novel 4-way X-band spatial power divider/combiner has been developed using a modified quasi-Yagi antenna transition. The divider has an insertion loss of less than 0.5 dB and a power balance of +/-0.8 dB over a bandwidth of 3.5 GHz in the X-band. A power combiner amplifier using this circuit and four MMIC amplifiers has been demonstrated with 84% combining efficiency. The obtained results show that the modified quasi-Yagi antenna is a suitable element to develop a broadband spatial power combiner.

The Hough transform is known to be an effective technique for target detection and track initiation in search radars. However, most papers have focused on the simplistic applications of this technique which consider a 2-D data space for the Hough transform. In this paper, a new method based on xthe Hough transform is introduced for detecting targets in a 3-D data space. The data space is constructed from returned surveillance radar signal using the range and bearing information of several successive scans. This information is mapped into a 3-D x-y-t Cartesian data space. Targets are modeled with four parameters in this data space. The proposed 3-D Hough detector is then used to detect the existent targets in the 3-D surveillance space by mapping the returned signal of the radar from the data space to the parameter space. This detector, which is constructed of two detection stages, integrates the returned data of each target non-coherently along its 3-D trajectory in one parameter space cell related to this target. Hence, the detection performance will improve. The effectiveness of the new 3-D Hough detector is demonstrated through deriving the detection statistics analytically and comparing the results with those of several comprehensive simulations. The performance improvement of this detector is shown by comparing its detection range with the conventional detector. The proposed detector is also evaluated with real radar data and its efficiency is confirmed.

We propose the multi-domain adaptive learning that enables us to find a point meeting possibly time-varying specifications simultaneously in multiple domains, e.g. space, time, frequency, etc. The novel concept is based on the idea of feasibility splitting -- dealing with feasibility in each individual domain. We show that the adaptive projected subgradient method (Yamada, 2003) realizes the multi-domain adaptive learning by employing (i) a projected gradient operator with respect to a ‘fixed’ proximity function reflecting the time-invariant specifications and (ii) a subgradient projection with respect to ‘time-varying’ objective functions reflecting the time-varying specifications. The resulting algorithm is suitable for real-time implementation, because it requires no more than metric projections onto closed convex sets each of which accommodates the specification in each domain. A convergence analysis and numerical examples are presented.

We propose a new Internet group management protocol (IGMP) which can be used in passive optical network (PON) especially for IPTV services which dramatically reduces the channel change response time caused by traditional IGMP. In this paper, the newly proposed IGMP is introduced in detail and performance analysis is also included. Simulation results demonstrated the performance of the newly proposed IGMP, whereby, viewers can watch the shared IPTV channels without the channel change response time when channel request reaches a threshold.

Substrate noise analysis has become increasingly important in recent LSI design. This is because substrate noise, which affects PLLs, causes jitter that results in timing error. Conventional analysis techniques of substrate noise are, however, impractical for large-scale designs that have hundreds of millions of transistors because the computational complexity is too huge. To solve this problem, we have developed a fast substrate noise analysis technique for large-scale designs, in which a chip is divided into multiple domains and the circuits of each domain are reduced into a macro model. Using this technique, we have designed a processor chip for use in the supercomputer (die size: 20 mm 21 mm, frequency: 3.2 GHz, transistor count: 350M). Computation time with this design is five times faster than that with a 1/3000 scale design using a conventional technique, while resulting discrepancy with measured period jitter is less than 15%.

This paper proposes a new realization technique of image rejection function by noise-coupling architecture, which is used for a complex bandpass ΔΣAD modulator. The complex bandpass ΔΣAD modulator processes just input I and Q signals, not image signals, and the AD conversion can be realized with low power dissipation. It realizes an asymmetric noise-shaped spectra, which is desirable for such low-IF receiver applications. However, the performance of the complex bandpass ΔΣAD modulator suffers from the mismatch between internal analog I and Q paths. I/Q path mismatch causes an image signal, and the quantization noise of the mirror image band aliases into the desired signal band, which degrades the SQNDR (Signal to Quantization Noise and Distortion Ratio) of the modulator. In our proposed modulator architecture, an extra notch for image rejection is realized by noise-coupled topology. We just add some passive capacitors and switches to the modulator; the additional integrator circuit composed of an operational amplifier in the conventional image rejection realization is not necessary. Therefore, the performance of the complex modulator can be effectively raised without additional power dissipation. We have performed simulation with MATLAB to confirm the validity of the proposed architecture. The simulation results show that the proposed architecture can achieve the realization of image-rejection effectively, and improve the SQNDR of the complex bandpass ΔΣAD modulator.

Multi-user multiple input multiple output (MU-MIMO) systems have attracted much attention as a technology that enhances the total system capacity by generating a virtual MIMO channel between a base station and multiple terminal stations. Extensive evaluations are still needed because there are many more system parameters in MU-MIMO than in single user (SU)-MIMO and the MU-MIMO performance in actual environments is still not well understood. This paper describes the features and effectiveness of a 1616 MU-MIMO testbed in an actual indoor environment. Moreover, we propose a simple adaptive modulation scheme for MU-MIMO-OFDM transmission that employs a bit interleaver in the frequency and space domains. We evaluate the frequency efficiency by obtaining the bit error rate of this testbed in an actual indoor environment. We show that 1644-user MU-MIMO transmission using the proposed modulation scheme achieves the frequency utilization of 870 Mbps and 1 Gbps (respective SNRs: 31 and 36 dB) with a 20-MHz bandwidth.

In this paper, the exact distribution of the channel capacity of MISO (multiple-input single-output) systems subject to co-channel interference is derived from an information theoretic viewpoint. It is found that the MISO channel capacity in the interference-limited channel follows the F-distribution. By using these capacity distributions, the outage capacity in Rayleigh fading channels can be accurately computed. We confirm the accuracy of our analysis by performing simulations. Our results exactly match those of the empirical simulations of interference-limited systems.

In this paper, we obtain some refinement of representation theorems for context-free languages by using Dyck languages, insertion systems, strictly locally testable languages, and morphisms. For instance, we improved the Chomsky-Schützenberger representation theorem and show that each context-free language L can be represented in the form L=h(D ∪ R), where D is a Dyck language, R is a strictly 3-testable language, and h is a morphism. A similar representation for context-free languages can be obtained, using insertion systems of weight (3,0) and strictly 4-testable languages.

A novel method to efficiently synthesize hardware from a large behavioral description in behavioral synthesis is proposed. For a program with functions executable in parallel, this proposed method determines a behavioral partitioning which simultaneously minimizes the overall datapath area and the complexity of the controller while maximizing performance of a synthesized circuit by fully exploiting function-level parallelism of a behavioral description. This method is formulated as an integer programming problem. Experimental results demonstrate that this method leads to a shift of the explorable design space so that superior solutions which could not be explored by earlier work are included, showing the effectiveness of our proposed method.

This paper proposes closed form solutions to the L2-sensitivity minimization subject to L2-scaling constraints for second-order state-space digital filters with real poles. We consider two cases of second-order digital filters: distinct real poles and multiple real poles. The proposed approach reduces the constrained optimization problem to an unconstrained optimization problem by appropriate variable transformation. We can express the L2-sensitivity by a simple linear combination of exponential functions and formulate the L2-sensitivity minimization problem by a simple polynomial equation. As a result, L2-sensitivity is expressed in closed form, and its minimization subject to L2-scaling constraints is achieved without iterative calculations.

This paper proposes an improved method of reversible data hiding with increased capacity. The conventional method determines whether to embed a data bit in an image block according to the statistics of pixels in that block. Some images have pixel statistics that are inadequate for data hiding, and seldom or never have data embedded in them. The proposed method modulates the statistics invertibility to overcome such disadvantages, and is also able to improve the quality of the image containing the hidden data using block-adaptive modulation. Simulationresults show the effectiveness of the proposed method.

The number of threats on the Internet is rapidly increasing, and anomaly detection has become of increasing importance. High-speed backbone traffic is particularly degraded, but their analysis is a complicated task due to the amount of data, the lack of payload data, the asymmetric routing and the use of sampling techniques. Most anomaly detection schemes focus on the statistical properties of network traffic and highlight anomalous traffic through their singularities. In this paper, we concentrate on unusual traffic distributions, which are easily identifiable in temporal-spatial space (e.g., time/address or port). We present an anomaly detection method that uses a pattern recognition technique to identify anomalies in pictures representing traffic. The main advantage of this method is its ability to detect attacks involving mice flows. We evaluate the parameter set and the effectiveness of this approach by analyzing six years of Internet traffic collected from a trans-Pacific link. We show several examples of detected anomalies and compare our results with those of two other methods. The comparison indicates that the only anomalies detected by the pattern-recognition-based method are mainly malicious traffic with a few packets.

M-spotty byte error control codes are very effective for correcting/detecting errors in semiconductor memory systems that employ recent high-density RAM chips with wide I/O data (e.g., 8, 16, or 32 bits). In this case, the width of the I/O data is one byte. A spotty byte error is defined as random t-bit errors within a byte of length b bits, where 1 ≤ t ≤ b. Then, an error is called an m-spotty byte error if at least one spotty byte error is present in a byte. M-spotty byte error control codes are characterized by the m-spotty distance, which includes the Hamming distance as a special case for t = 1 or t = b. The MacWilliams identity provides the relationship between the weight distribution of a code and that of its dual code. The present paper presents the MacWilliams identity for the m-spotty weight enumerator of m-spotty byte error control codes. In addition, the present paper clarifies that the indicated identity includes the MacWilliams identity for the Hamming weight enumerator as a special case.

This letter investigates the space-time block codes from quasi-orthogonal design as a tradeoff between high transmission rate and low decoding complexity. By studying the role orthogonality plays in space-time block codes, upper bound of transmission rate and lower bound of decoding complexity for quasi-orthogonal design are claimed. From this point of view, novel algorithms are developed to construct specific quasi-orthogonal designs achieving these bounds.

To detect the natural clusters for irregularly shaped data distribution is a difficult task in pattern recognition. In this study, we propose an efficient clustering algorithm for irregularly shaped clusters based on the advantages of spectral clustering and Affinity Propagation (AP) algorithm. We give a new similarity measure based on neighborhood dispersion analysis. The proposed algorithm is a simple but effective method. The experimental results on several data sets show that the algorithm can detect the natural clusters of input data sets, and the clustering results agree well with that of human judgment.

In this letter, we learned overcomplete filters to model rich priors of nature images. Our approach extends the Gaussian Scale Mixture Fields of Experts (GSM FOE), which is a fast approximate model based on Fields of Experts (FOE). In these previous image prior model, the overcomplete case is not considered because of the heavy computation. We introduce the assumption of quasi-orthogonality to the GSM FOE, which allows us to learn overcomplete filters of nature images fast and efficiently. Simulations show these obtained overcomplete filters have properties similar with those of Fields of Experts', and denoising experiments also show the superiority of our model.

In this paper, we study lower bounds on the query complexity of testing algorithms for various problems. Given an oracle that returns information of an input object, a testing algorithm distinguishes the case that the object has a given property P from the case that it has a large distance to having P with probability at least . The query complexity of an algorithm is measured by the number of accesses to the oracle. We introduce two reductions that preserve the query complexity. One is derived from the gap-preserving local reduction and the other is from the L-reduction. By using the former reduction, we show linear lower bounds on the query complexity for testing basic NP-complete properties, i.e., 3-edge-colorability, directed Hamiltonian path/cycle, undirected Hamiltonian path/cycle, 3-dimensional matching and NP-complete generalized satisfiability problems. Also, using the second reduction, we show a linear lower bound on the query complexity of approximating the size of the maximum 3-dimensional matching.