Arrayed waveguide grating (AWG) is a promising technology for constructing high-speed large-capacity WDM switches, because it can switch fast, is scalable to large size and consumes little power. To take the full advantage of high-speed AWG, the routing control of a massive AWG-based switch should be as simple as possible. In this paper, we focus on the self-routing design of AWG-based switches with O(1) constant routing complexity and propose a novel construction of self-routing AWG switches that can guarantee the attractive nonblocking property for both the wavelength-to-wavelength and wavelength-to-fiber request models. We also fully analyze the proposed design in terms of its blocking property, hardware cost and crosstalk performance and compare it against traditional designs. It is expected that the proposed construction will be useful for the design and all-optical implementation of future ultra high-speed optical packet/burst switches.

In this paper, we propose a distance-based howling canceller with high speech quality. We have developed a distance-based howling canceller that uses only distance information by noticing the property that howling occurs according to the distance between a loudspeaker and a microphone. This method estimates the distance by transmitting a pilot signal from the loudspeaker to the microphone. Multiple frequency candidates for each howling are computed from the estimated distance and eliminated by cascading notch filters that have nulls at them. However degradation of speech quality occurs at the howling canceller output. The first cause is a shot noise occurrence at the beginning and end of the pilot signal transmission due to the discontinuous change of the amplitude. We thus develop a new pilot signal that is robust against ambient noises. We can then reduce the shot noise effect by taking the amplitude small. The second one is a speech degradation caused from overlapped stopbands of the notch filters. We thus derive a condition on the bandwidths so that stopbands do not overlap, and propose an adaptive bandwidth scheme which changes the bandwidth according to the distance.

We report on the spurious suppression effect in low-microwave power transmitters by high temperature superconducting (HTS) bandpass filters (BPFs) which are promising for devices requiring BPFs with high-frequency selectivity. Some of the major issues on the power BPFs with HTS planar circuits for wireless communication applications are reviewed. As a case study for the HTS filter and its spurious suppression effect, this paper describes an example of the measured power spectrum density (PSD) on the suppression effect by one of our developed power BPFs with YBCO films for the 5 GHz band. It was designed with equivalent cascade resonators of 16 poles. We demonstrated the effect by HTS power filter in a power amplifier for the 5 GHz band.

Transmission delay in audio communications is a well-known obstacle to achieving smooth communication. However, it is not known what kinds of effects are caused by small delays. We hypothesized that the small delay in the listener's responses disturbs the speaker's "verbal conditioning," where the verbal behavior of the speaker varies in accordance with the listener's responses. We examined whether the small delays in the listener's responses disturb the speaker's verbal conditioning using an artificial-grammar learning task. The results suggested that a 300-ms delay disturbed the participants' verbal conditioning although they were not adequately aware of the delay.

This paper presents methods for controlling the intensity of emotional expressions and speaking styles of an arbitrary speaker's synthetic speech by using a small amount of his/her speech data in HMM-based speech synthesis. Model adaptation approaches are introduced into the style control technique based on the multiple-regression hidden semi-Markov model (MRHSMM). Two different approaches are proposed for training a target speaker's MRHSMMs. The first one is MRHSMM-based model adaptation in which the pretrained MRHSMM is adapted to the target speaker's model. For this purpose, we formulate the MLLR adaptation algorithm for the MRHSMM. The second method utilizes simultaneous adaptation of speaker and style from an average voice model to obtain the target speaker's style-dependent HSMMs which are used for the initialization of the MRHSMM. From the result of subjective evaluation using adaptation data of 50 sentences of each style, we show that the proposed methods outperform the conventional speaker-dependent model training when using the same size of speech data of the target speaker.

In this paper, we propose a subcarrier resource allocation algorithm for managing the video quality degradation for multiuser orthogonal frequency division multiplex (OFDM) systems. The proposed algorithm exploits the unequal importance existing in different picture types for video coding and the diversity of subcarriers for multiuser systems. A model-based performance metric is first derived considering the error concealment and error propagation properties of the H.264 video coding structure. Based on the information on video quality enhancement existing in a packet to be transmitted, we propose the distortion management algorithm for balancing the subcarriers and power usages for each user and minimizing the overall video quality degradation. In the simulation results, the proposed algorithm demonstrates a more gradual video quality degradation for different numbers of users compared with other resource allocation schemes.

In 2006, Tanaka has proposed an efficient variant of Maurer-Yacobi's identity-based non-interactive key sharing scheme. In Tanaka's scheme, the computational complexity to generate each user's secret information is much smaller than that of Maurer-Yacobi's scheme. Tanaka's original key sharing scheme does not provide completeness, and so Tanaka has corrected the original scheme to provide completeness. In this paper, we show that Tanaka's corrected key sharing scheme is not secure against collusion attacks. That is, two users can collaborate to factorize a system modulus with their secret information and thus break the key sharing scheme.

MPLS-based path technology shows promise as a means of realizing reliable IP networks. Real-time services such as VoIP and video-conference supplied through a multi-domain MPLS network must be able to guarantee end-to-end QoS of the inter-domain paths. Thus, it is important to allocate an appropriate QoS class to the inter-domain paths in each domain traversed by the inter-domain paths. Because each domain has its own policy for QoS class allocation, it is necessary to adaptively allocate the optimum QoS class based on estimation of the QoS class allocation policies in other domains. This paper proposes two kinds of adaptive QoS class allocation schemes, assuming that the arriving inter-domain path requests include the number of downstream domains traversed by the inter-domain paths and the remaining QoS value toward the destination nodes. First, a measurement-based scheme, based on measurement of the loss rates of inter-domain paths in the downstream domains, is proposed. This scheme estimates the QoS class allocation policies in the downstream domains, using the measured loss rates of path requests. Second, a state-dependent type scheme, based on measurement of the arrival rates of path requests in addition to the loss rates of paths in the downstream domains, is also proposed. This scheme allows an appropriate QoS class to be allocated according to the domain state. This paper proposes an application of the Markov decision theory to the modeling of state-dependent type scheme. The performances of the proposed schemes are evaluated and compared with those of the other less complicated non-adaptive schemes using a computer simulation. The results of the comparison reveal that the proposed schemes can adaptively increase the number of inter-domain paths accommodated in the considered domain, even when the QoS class allocation policies change in the other domains and the arrival pattern of path requests varies in the considered domain.

In RFID systems, collision resolution is a significant issue in fast tag identification. This letter presents a dynamic frame-slotted ALOHA algorithm that uses a collision factor (DFSA-CF). This method enables fast tag identification by estimating the next frame size with the collision factor in the current frame. Simulation results show that the proposed method reduces slot times Required for RFID identification. When the number of tags is larger than the frame size, the efficiency of the proposed method is greater than those of conventional algorithms.

Similar to orthogonal frequency-division multiplexing (OFDM) systems, orthogonal frequency-division multiple access (OFDMA) is vulnerable to carrier frequency offset (CFO). Since the CFO of each user is different, CFO compensation in OFDMA uplink is much more involved than that in OFDM systems. It has been shown that the zero-forcing (ZF) compensation method is a simple yet effective remedy; however, it requires the inversion of a large matrix and the computational complexity can be very high. Recently, we have developed a low-complexity iterative method to alleviate this problem. In this paper, we consider the theoretical aspect of the algorithm. We specifically analyze the output signal-to-interference-plus-noise-ratio (SINR) of the algorithm. Two approaches are used for the analysis; one is simple but approximated, and the other is complicated but exact. The convergence problem is also discussed. In addition to the analysis, we propose a pre-compensation (PC) method enhancing the performance of the algorithm. Simulations show that our analysis is accurate and the PC method is effective.

Nonnegative matrix factorization (NMF) and its extensions such as Nonnegative Tensor Factorization (NTF) have become prominent techniques for blind sources separation (BSS), analysis of image databases, data mining and other information retrieval and clustering applications. In this paper we propose a family of efficient algorithms for NMF/NTF, as well as sparse nonnegative coding and representation, that has many potential applications in computational neuroscience, multi-sensory processing, compressed sensing and multidimensional data analysis. We have developed a class of optimized local algorithms which are referred to as Hierarchical Alternating Least Squares (HALS) algorithms. For these purposes, we have performed sequential constrained minimization on a set of squared Euclidean distances. We then extend this approach to robust cost functions using the alpha and beta divergences and derive flexible update rules. Our algorithms are locally stable and work well for NMF-based blind source separation (BSS) not only for the over-determined case but also for an under-determined (over-complete) case (i.e., for a system which has less sensors than sources) if data are sufficiently sparse. The NMF learning rules are extended and generalized for N-th order nonnegative tensor factorization (NTF). Moreover, these algorithms can be tuned to different noise statistics by adjusting a single parameter. Extensive experimental results confirm the accuracy and computational performance of the developed algorithms, especially, with usage of multi-layer hierarchical NMF approach [3].

In multi-hop wireless networks, communication quality depends on the selection of a path between source and destination nodes from several candidate paths. Exploring how path selection affects communication quality is important to characterize the best path. To do this, in [1], we used expected transmission count (ETX) as a metric of communication quality and theoretically characterized minimum route ETX, which is the ETX of the best path, in a static one-dimensional random multi-hop network. In this paper, we characterize minimum route ETX in static two-dimensional multi-hop networks. We give the exact formula of minimum route ETX in a two-dimensional network, assuming that nodes are located with lattice structure and that the ETX function satisfies three conditions for simplifying analysis. This formula can be used as an upper bound of minimum route ETX without two of the three conditions. We show that this upper bound is close to minimum route ETX by comparing it with simulation results. Before deriving the formula, we also give the formula for a one-dimensional network where nodes are located at constant intervals. We also show that minimum route ETX in the lattice network is close to that in a two-dimensional random network if the node density is large, based on a comparison between the numerical and simulation results.

An algorithm for blind signal separation (BSS) of convolutive mixtures is presented. In this algorithm, the BSS problem is treated as multidimensional independent component analysis (ICA) by introducing an extended signal vector which is composed of current and previous samples of signals. It is empirically known that a number of conventional ICA algorithms solve the multidimensional ICA problem up to permutation and scaling of signals. In this paper, we give theoretical justification for using any conventional ICA algorithm. Then, we discuss the remaining problems, i.e., permutation and scaling of signals. To solve the permutation problem, we propose a simple algorithm which classifies the signals obtained by a conventional ICA algorithm into mutually independent subsets by utilizing temporal structure of the signals. For the scaling problem, we prove that the method proposed by Koldovský and Tichavský is theoretically proper in respect of estimating filtered versions of source signals which are observed at sensors.

In this letter, a closed form approximation for the average sum rate of random beamforming is derived. It provides a near-exact approximation for arbitrary numbers of beams, users, and received SNR. The approximation is also applied to an average-sense multimode random beamforming scheme which optimizes the number of random beams without any type of instantaneous channel information. The proposed scheme shows better sum rate performance than random beamforming as well as an existing dual mode random beamforming scheme based on instantaneous channel information, while the number of feedback bits for beam index is reduced compared to random beamforming.

Recently, a promising packet forwarding architecture COPE was proposed to essentially improve the throughput of multihop wireless networks, where each network node can intelligently encode multiple packets together and forward them in a single transmission. However, COPE is still in its infancy and has the following limitations: (1) COPE adopts the FIFO packet scheduling and thus does not provide different priorities for different types of packets. (2) COPE simply classifies all packets destined to the same nexthop into small-size or large-size virtual queues and examines only the head packet of each virtual queue to find coding solutions. Such a queueing structure will lose some potential coding opportunities, because among packets destined to the same nexthop at most two packets (the head packets of small-size and large-size queues) will be examined in the coding process, regardless of the number of flows. (3) The coding algorithm adopted in COPE is fast but cannot always find good solutions. In order to address the above limitations, in this paper we first present a new queueing structure for COPE, which can provide more potential coding opportunities, and then propose a new packet scheduling algorithm for this queueing structure to assign different priorities to different types of packets. Finally, we propose an efficient coding algorithm to find appropriate packets for coding. Simulation results demonstrate that this new COPE architecture can further greatly improve the node transmission efficiency.

Lower-dimensional transformations in similar sequence matching show different performance characteristics depending on the type of time-series data. In this paper we propose a hybrid approach that exploits multiple transformations at a time in a single hybrid index. This hybrid approach has advantages of exploiting the similar effect of using multiple transformations and reducing the index maintenance overhead. For this, we first propose a new notion of hybrid lower-dimensional transformation that extracts various features using different transformations. We next define the hybrid distance to compute the distance between the hybrid transformed points. We then formally prove that the hybrid approach performs similar sequence matching correctly. We also present the index building and similar sequence matching algorithms based on the hybrid transformation and distance. Experimental results show that our hybrid approach outperforms the single transformation-based approach.

In this paper, we propose a novel Hidden-terminal and Exposed-terminal Interference aware routing metric (HEI-ETT) for Multi-Radio and Multi-Rate wireless mesh networks in which each stationary mesh node is equipped with multi-radio interfaces that relays traffic to the extend networks by using multi-hop transmissions. We have two main design goals for HEI-ETT. First, we will characterize interferences as Hidden-terminal Interference and Exposed-terminal Interference regardless of inter- or intra-flow interference and should take into account both interference effects while computing the path metric. Second, an efficient transmission rate adaptation should be employed in HEI-ETT to enhance the network throughput. We incorporated our metric in well known Optimized Link State Routing protocol version 2 (OLSRv2) which is one of the two standard routing protocols for MANETs and evaluated the performance of our metric by simulation. The results show that our metric outperforms existing metrics such as ETX, ETT and WCETT.

An improved dual-band design method is presented for the 180coupler. It uses the non-uniform impedance ring structure for the arbitrary power division and a π-shaped branch for the dual-band operation The increased design freedom offered by the proposed structure helps to extend the useful dual-band operation range.

This paper proposes a method providing efficient test compression. The proposed method is for robust testable path delay fault testing with scan design facilitating two-pattern testing. In the proposed method, test data are interleaved before test compression using statistical coding. This paper also presents test architecture for two-pattern testing using the proposed method. The proposed method is experimentally evaluated from several viewpoints such as compression rates, test application time and area overhead. For robust testable path delay fault testing on 11 out of 20 ISCAS89 benchmark circuits, the proposed method provides better compression rates than the existing methods such as Huffman coding, run-length coding, Golomb coding, frequency-directed run-length (FDR) coding and variable-length input Huffman coding (VIHC).

In this letter, we propose a new scheme for the tag structure of the EPCglobal Class-1 Generation-2 (EPC C1 Gen2) standard equipped with a channel encoding block and the corresponding decoding block in the receiver of the reader system. The channel coded tag is designed to fully accommodate the EPC C1 Gen2 standard. The use of the proposed channel encoding block increases the number of logic gates in the tag by no more than 5%. The proposed reader system is designed to be used in the mixed tag modes as well, where the channel coded tags and existing tags co-exist in the same inventory round. The performances of the proposed tags and the corresponding reader systems are also presented by comparing the number of EPC error frames and the tag identification time with those of the conventional tags and reader systems.