The photo-mask cost of standard-cell-based ASICs has been increased so prohibitively that low-volume production LSIs are difficult to fabricate due to high non-recurring engineering (NRE) cost including mask cost. Recently, user-programmable devices, such as FPGAs are started to be used for low-volume consumer products. However, FPGAs cannot be replaced for general purpose because of its lower speed-performance and higher power consumption. In this paper, we propose the user-programmable architecture called VPEX (Via Programmable logic device using EXclusive-or array), in which the hardware logic can be programmed by changing layout patterns on 2 via-layers. The logic element (LE) of VPEX consists of complex-gate-type EXclusive OR (EXOR) and Inverter (NOT) gates. The single LE can output 12 logics which include NOT, Buffer (BUF), all 2-inputs logic functions, 3-inputs AOI21 and inverted-output multiplexer (MUXI) by changing via-1 layout pattern. Furthermore, via-1 layout is optimized for high-throughput EB direct writing, so mask-less programming will be realized in VPEX. We compared the performance of area, speed, and power consumption of VPEX with that of standard-cell-based ASICs and FPGAs. As a result, the speed performance of VPEX was much better than FPGAs and about 1.3-1.6 times worse than standard-cells. We believe that the combination of VPEX architecture and EB direct writing is the best solution for low-volume production LSIs.

This paper presents our developed decoder which adopts the idea of statically optimizing part of the knowledge sources while handling the others dynamically. The lexicon, phonetic contexts and acoustic model are statically integrated to form a memory-efficient state network, while the language model (LM) is dynamically incorporated on the fly by means of extended tokens. The novelties of our approach for constructing the state network are (1) introducing two layers of dummy nodes to cluster the cross-word (CW) context dependent fan-in and fan-out triphones, (2) introducing a so-called "WI layer" to store the word identities and putting the nodes of this layer in the non-shared mid-part of the network, (3) optimizing the network at state level by a sufficient forward and backward node-merge process. The state network is organized as a multi-layer structure for distinct token propagation at each layer. By exploiting the characteristics of the state network, several techniques including LM look-ahead, LM cache and beam pruning are specially designed for search efficiency. Especially in beam pruning, a layer-dependent pruning method is proposed to further reduce the search space. The layer-dependent pruning takes account of the neck-like characteristics of WI layer and the reduced variety of word endings, which enables tighter beam without introducing much search errors. In addition, other techniques including LM compression, lattice-based bookkeeping and lattice garbage collection are also employed to reduce the memory requirements. Experiments are carried out on a Mandarin spontaneous speech recognition task where the decoder involves a trigram LM and CW triphone models. A comparison with HDecode of HTK toolkits shows that, within 1% performance deviation, our decoder can run 5 times faster with half of the memory footprint.

We have previously proposed a noise-robust speaker verification method using fundamental frequency (F0) extracted using the Hough transform. The method also incorporates an automatic stream-weight and decision threshold estimation technique. It has been confirmed that the proposed method is effective for white noise at various SNR conditions. This paper evaluates the proposed method in more practical in-car and elevator-hall noise conditions. The paper first describes the noise-robust F0 extraction method and details of our robust speaker verification method using multi-stream HMMs for integrating the extracted F0 and cepstral features. Details of the automatic stream-weight and threshold estimation method for multi-stream speaker verification framework are also explained. This method simultaneously optimizes stream-weights and a decision threshold by combining the linear discriminant analysis (LDA) and the Adaboost technique. Experiments were conducted using Japanese connected digit speech contaminated by white, in-car, or elevator-hall noise at various SNRs. Experimental results show that the F0 features improve the verification performance in various noisy environments, and that our stream-weight and threshold optimization method effectively estimates control parameters so that FARs and FRRs are adjusted to achieve equal error rates (EERs) under various noisy conditions.

This study deals with two linear precoders: the maximization of the minimum Euclidean distance between received symbol-vectors, called here max-dmin, and the maximization of the post-processing signal-to-noise ratio termed max-SNR or beamforming. Both have been designed for reliable MIMO transmissions operating over uncorrelated Rayleigh fading channels. Here, we will explain why performances in terms of bit error rates show a significant enhancement of the max-dmin over the max-SNR whenever the number of antennas is increased. Then, from theoretical developments, we will demonstrate that, like the max-SNR precoder, the max-dmin precoder achieves the maximum diversity order, which is warrant of reliable transmissions. The current theoretical knowledge will be applied to the case-study of a system with two transmit- or two receive-antennas to calculate the probability density functions of two channel parameters directly linked to precoder performances for uncorrelated Rayleigh fading channels. At last, this calculation will allow us to quickly get the BER of the max-dmin precoder further to the derivation of a tight semi-theoretical approximation.

Delay jitter degrades the quality of delay-sensitive live media streaming. We investigate the use of multipath transmission with two paths to reduce delay jitter and, in this paper, propose a nearly equal delay path set configuration (NEED-PC) scheme that further improves the performance of the multipath delay jitter reduction method for delay-sensitive live media streaming. The NEED-PC scheme configures a pair of a maximally node-disjoint paths that have nearly equal path delays and satisfy a given delay constraint. The results of our simulation experiments show that path sets configured by the NEED-PC scheme exhibit better delay jitter reduction characteristics than a conventional scheme that chooses the shortest path as the primary path. We evaluate the performance of path sets configured by the NEED-PC scheme and find that the NEED-PC scheme reduces delay jitter when it is applied to a multipath delay jitter reduction method. We also investigate the trade-off between reduced delay jitter and the increased traffic load incurred by applying multipath transmission to more flows. The results show that the NEED-PC scheme is practically effective even if the amount of additional redundant traffic caused by using multipath transmission is taken into account.

We present a novel method of integrating the likelihoods of multiple feature streams, representing different acoustic aspects, for robust speech recognition. The integration algorithm dynamically calculates a frame-wise stream weight so that a higher weight is given to a stream that is robust to a variety of noisy environments or speaking styles. Such a robust stream is expected to show discriminative ability. A conventional method proposed for the recognition of spoken digits calculates the weights from the entropy of the whole set of HMM states. This paper extends the dynamic weighting to a real-time large-vocabulary continuous speech recognition (LVCSR) system. The proposed weight is calculated in real-time from mutual information between an input stream and active HMM states in a search space without an additional likelihood calculation. Furthermore, the mutual information takes the width of the search space into account by calculating the marginal entropy from the number of active states. In this paper, we integrate three features that are extracted through auditory filters by taking into account the human auditory system's ability to extract amplitude and frequency modulations. Due to this, features representing energy, amplitude drift, and resonant frequency drifts, are integrated. These features are expected to provide complementary clues for speech recognition. Speech recognition experiments on field reports and spontaneous commentary from Japanese broadcast news showed that the proposed method reduced error words by 9.2% in field reports and 4.7% in spontaneous commentaries relative to the best result obtained from a single stream.

We have attempted to recognize reverberant speech using a novel speech recognition system that depends on not only the spectral envelope and amplitude modulation but also frequency modulation. Most of the features used by modern speech recognition systems, such as MFCC, PLP, and TRAPS, are derived from the energy envelopes of narrowband signals by discarding the information in the carrier signals. However, some experiments show that apart from the spectral/time envelope and its modulation, the information on the zero-crossing points of the carrier signals also plays a significant role in human speech recognition. In realistic environments, a feature that depends on the limited properties of the signal may easily be corrupted. In order to utilize an automatic speech recognizer in an unknown environment, using the information obtained from other signal properties and combining them is important to minimize the effects of the environment. In this paper, we propose a method to analyze carrier signals that are discarded in most of the speech recognition systems. Our system consists of two nonlinear discriminant analyzers that use multilayer perceptrons. One of the nonlinear discriminant analyzers is HATS, which can capture the amplitude modulation of narrowband signals efficiently. The other nonlinear discriminant analyzer is a pseudo-instantaneous frequency analyzer proposed in this paper. This analyzer can capture the frequency modulation of narrowband signals efficiently. The combination of these two analyzers is performed by the method based on the entropy of the feature introduced by Okawa et al. In this paper, in Sect. 2, we first introduce pseudo-instantaneous frequencies to capture a property of the carrier signal. The previous AM analysis method are described in Sect. 3. The proposed system is described in Sect. 4. The experimental setup is presented in Sect. 5, and the results are discussed in Sect. 6. We evaluate the performance of the proposed method by continuous digit recognition of reverberant speech. The proposed system exhibits considerable improvement with regard to the MFCC feature extraction system.

We propose a new mobility management scheme using Label Switched Path (LSP) of Multi Protocol Label Switching (MPLS) for seamless service in Broadband Convergence Network (BcN) in Korea, and verify that the proposed scheme has lower latency time than the existing ones through the separation of control plane from data plane for handover signaling.

With the rapid advances in wireless network communication, multimedia presentation has become more applicable. However, due to the limited wireless network resource and the mobility of Mobile Host (MH), QoS for wireless streaming is much more difficult to maintain. How to decrease Call Dropping Probability (CDP) in multimedia traffic while still keeping acceptable Call Block Probability (CBP) without sacrificing QoS has become an significant issue in providing wireless streaming services. In this paper, we propose a novel Dynamic Resources Adjustment (DRA) algorithm, which can dynamically borrow idle reserved resources in the serving cell or the target cell for handoffing MHs to compensate the shortage of bandwidth in media streaming. The experimental simulation results show that compared with traditional No Reservation (NR), and Resource Reservation in the six neighboring cells (RR-nb), and Resource Reservation in the target cell(RR-t), our proposed DRA algorithm can fully utilize unused reserved resources to effectively decrease the CDP while still keeping acceptable CBP with high bandwidth utilization.

This letter presents a novel frame splitting scheme for an error-robust audio streaming over packet-switching networks. In our approach to perceptual audio coding, an audio frame is split into several subframes based on the network configuration such that each packet can be decoded independently at the receiver. Through a subjective comparison category rating (CCR) test, it is discovered that our approach enhances the quality of the decoded audio signal under the lossy packet-switching networks environment.

In this paper, we propose a novel MAC protocol with the patterned preamble technique to improve performance in terms of low power, channel utilization, and delay in wireless sensor networks. B-MAC is one of typical MAC protocols for wireless sensor networks using the duty cycle in order to achieve low-power operation. Since it works in an asynchronous fashion, B-MAC employs extended preamble and preamble sampling techniques. Even if it has outstanding performance in idle state, the overhead of these techniques is very large when packets are sent and received, because there is a lot of waste in the traditional preamble method. Instead of the simple preamble, our proposed MAC solution is to introduce more intelligent preamble with some patterns consisting of 2 phases (Tx phase & Ack phase). With this concept we implement real source code working on the mica2 platform with Tinyos-1.x version. Also, the test set-up is presented, and the test results demonstrate that the proposed protocol provides better performance in terms of delay compared to B-MAC.

In this letter, we propose a new preamble structure for channel estimation in a MIMO OFDM-based WLAN system. Both backward compatibility with IEEE 802.11a and low overhead are considered in designing the preamble. Simulation results show that the proposed preamble has low overhead and good performance gain for channel estimation.

A rate control scheme is described for zero-forcing beamforming (ZFBF) multiuser multiple-input and multiple-output (MU-MIMO) systems with a QR-decomposition maximum likelihood detector (MLD) at the receiver. For selected users, a modulation-and-coding set is selected for each substream by estimating the per-substream post-MLD signal-to-interference-plus-noise ratio. Iterative modified QR-decomposition MLD is employed at the receiver to achieve the throughput expected from the transmitter. The simulation results demonstrated that the proposed rate-control scheme achieved the target packet error rate while increasing the throughout for ZFBF-MU-MIMO systems as the number of user candidates increases.

We focus on the relationship between the linearization method and linear complexity and show that the linearization method is another effective technique for calculating linear complexity. We analyze its effectiveness by comparing with the logic circuit method. We compare the relevant conditions and necessary computational cost with those of the Berlekamp-Massey algorithm and the Games-Chan algorithm. The significant property of a linearization method is that it needs no output sequence from a pseudo-random number generator (PRNG) because it calculates linear complexity using the algebraic expression of its algorithm. When a PRNG has n [bit] stages (registers or internal states), the necessary computational cost is smaller than O(2n). On the other hand, the Berlekamp-Massey algorithm needs O(N2) where N ( 2n) denotes period. Since existing methods calculate using the output sequence, an initial value of PRNG influences a resultant value of linear complexity. Therefore, a linear complexity is generally given as an estimate value. On the other hand, a linearization method calculates from an algorithm of PRNG, it can determine the lower bound of linear complexity.

In a key scheduling algorithm (KSA) of stream ciphers, a secret key is expanded into a large initial state. An internal state reconstruction method is known as a general attack against stream ciphers; it recovers the initial state from a given pair of plaintext and ciphertext more efficiently than exhaustive key search. If the method succeeds, then it is desirable that the inverse of KSA is infeasible in order to avoid the leakage of the secret key information. This paper shows that it is easy to compute a secret key from an initial state of RC4. We propose a method to recover an -bit secret key from only the first bits of the initial state of RC4 using linear equations with the time complexity less than that of one execution of KSA. It can recover the secret keys of which number is 2103.6 when the size of the secret key is 128 bits. That is, the 128-bit secret key can be recovered with a high probability when the first 128 bits of the initial state are determined using the internal state reconstruction method.

In a Cognitive Radio system, it is essential to recognize and avoid sources of interference signals. This paper describes a study on a location sensing scheme for interference signals, which utilizes multi-beam phased array antenna for cognitive wireless networks. This paper also elucidates its estimation accuracy of the interference location for the radio communication link using an OFDM signal such as WiMAX. Furthermore, we use the frequency spectrum of the received OFDM interference signal, to create a method that can estimate the propagation status. This spectrum can be monitored by using a software defined radio receiver.

Random unitary beamforming is one of the schemes that can reduce the amount of feedback information in multiuser diversity techniques with multiple-antenna downlink transmission. In Multiple-Input Multiple-Output (MIMO) systems, throughput performance is greatly improved using AMC (Adaptive Modulation and Coding). Throughput performance is also improved by allocating power among streams appropriately. In random unitary beamforming, the transmitter has only partial channel state information (CSI) of each receiver. Thus, it is difficult for random unitary beamforming to use conventional power allocation methods that assumes that all receivers has full CSI. In this paper, we propose a new scheduling algorithm with power allocation for downlink random unitary beamforming that improves throughput performance without full CSI. We provide numerical results of the proposed scheduling algorithm and compare them to those of the conventional random unitary beamforming scheduling algorithm. We show that random unitary beamforming achieves the best system throughput performance with two transmit antennas. We also show that the proposed algorithm attains higher throughput with the small increase of feedback than the random unitary beamforming scheduling algorithm.

The concept of placing enormous Solar Power Satellite (SPS) systems in space represents one of a handful of new technological options that might provide large scale, environmentally clean base load power to terrestrial markets. Recent advances in space exploration have shown a great need for antennas with high resolution, high gain and low side lobe level (SLL). The last characteristic is of paramount importance especially for the Microwave Power Transmission (MPT) in order to achieve higher transmitting efficiency (TE) and higher beam collection efficiency (BCE). In order to achieve low side lobe levels, statistical methods play an important role. Various interesting properties of a large antenna arrays with randomly, uniformly and combined spacing of elements have been studied, especially the relationship between the required number of elements and their appropriate spacing from one viewpoint and the desired SLL, the aperture dimension, the beamwidth and TE from the other. We propose a new unified approach in searching for reducing SLL by exploiting the interaction of deterministic and stochastic workspaces of proposed algorithms. Our models indicate the side lobe levels in a large area around the main beam and strongly reduce SLL in the entire visible range. A new concept of designing a large antenna array system is proposed. Our theoretic study and simulation results clarify how to deal with the problems of side lobes in designing a large antenna array, which seems to be an important step toward the realization of future SPS/MPT systems.

Many devices are expected to be networked with wireless appliances such as radio frequency identification (RFID) tags and wireless sensors, and the number of such appliances will greatly exceed the number of PCs and mobile telephones. This may lead to an essential change in the network architecture. This paper proposes a new network architecture called the appliance defined ubiquitous network (ADUN), in which wireless appliances will be networked without network protocol standards. Radio space information rather than individual appliance signals is carried over the ADUN in the form of a stream with strong privacy/security control. It should be noted that this is different from the architectural principles of the Internet. We discuss a network-appliance interface that is sustainable over a long period, and show that the ADUN overhead will be within the scope of the broadband network in the near future.

This letter describes a millimeter wave slot array antenna using a rectangular waveguide and a ferrite. The radiation direction of the leaky wave from the slot array can be scanned by applying a dc bias magnetic field parallel to the ferrite. The radiation pattern of a prototype antenna has been measured at 40 GHz. The main beam direction changes from 10 to 3 degree by the bias magnetic field of 0.73 T.