We define a family of 2e+1-periodic binary threshold sequences and a family of p2-periodic binary threshold sequences by using Carmichael quotients modulo 2e (e > 2) and 2p (p is an odd prime), respectively. These are extensions of the construction derived from Fermat quotients modulo an odd prime in our earlier work. We determine exact values of the linear complexity, which are larger than half of the period. For cryptographic purpose, the linear complexities of the sequences in this letter are of desired values.

In our previous research, to achieve unequal error protection (UEP), we proposed a scheme which encodes the data by randomly switching between several codes which use different signal constellations and showed the effectiveness in AWGN channels. In this letter, we propose our UEP system using MMSE-FDE for fast and selective fading by using the fact that importance levels are changed every few symbols, i.e., every block, in the proposed system. We confirmed the improvement in BER performance and the effectiveness of adaptive equalization for the proposed system in fading channels. Moreover, in fading channels we confirmed the validity of the theoretical tradeoff shown in static conditions.

Because large earthquakes have repeatedly occurred in subduction zones, it is important to observe seismic activities on the sea floor. An ocean bottom cabled seismometers (OBCS) system is the most suitable tool for this purpose since data can be obtained in real-time. Although the existing OBCS systems are useful for the study of seismic activities, the number of stations is limited due to their cost. Therefore, lower cost in both production and installation is desired. We have developed a new OBCS system utilizing IP technologies. IP technologies yield the new OBCS system that are more compact and less expensive, while a large amount of complex hardware is used in the existing OBCS system. System reliability is ensured by using IP network technologies that provide redundancy. The new OBCS system was first installed to observe the Niigata-Kobe tectonic zone in the Japan Sea on September 2010. Although this first OBCS system has a total length of 25 km, it has been proven that seismic data can be successfully obtained and that the new OBCS system is effective and useful for the dense observation of seismogenic activities on the sea floor around Japan.

Multicast routing with Quality-of-Service (QoS) guarantees is the key to efficient content distribution and sharing. Developing QoS-aware multicast routing algorithm is an important open topic. This paper investigates QoS-aware multicast routing problem with K constraints where K > 2. The contributions made in this paper include a heuristic that employs the concept of nonlinear combination to extend the existing well-known algorithm for fast computation of a QoS multicast tree, and a Fully Polynomial Time Approximation Scheme (FPTAS) to approximate a multicast routing tree with QoS guarantees. The theoretical analyses and simulations conducted on both algorithms show that the algorithms developed in this paper are general and flexible, thus are applicable to the various networking systems.

In this letter, we first present a new construction method for uncorrelated binary periodic Complementary sequence sets (CSS). Next, the uncorrelated periodic CSSs are used as pilot sequences for multiple-input multiple-output (MIMO) channel estimation. Later on, we propose a low-complexity periodic correlator. Finally, simulation results verify the optimality of pilot sequences for MIMO channel estimation.

This paper deals with an integral method analyzing the diffraction of a transverse electric (TE) wave by a perfectly conductive periodic surface. The conventional integral method fails to work for a critical angle of incidence. To overcome such a drawback, this paper applies the method of image Green's function. We newly obtain an image integral equation for the basic surface current in the TE case. The integral equation is solved numerically for a very rough sinusoidal surface. Then, it is found that a reliable solution can be obtained for any real angle of incidence including a critical angle.

A 4th-order programmable continuous-time filter (CTF) for hard-disk-drive (HDD) read channels was developed with 65-nm CMOS process technology. The CTF cutoff frequency and boost are programmable by switching units of the operational trans-conductance amplifier (OTA) banks and the capacitor banks. The switches are operated by lifted local-supply voltage to reduce on-resistance of the transistors. The CTF characteristics were robust against process technology variations and supply voltage and temperature ranges due to the introduction of a digitally assisted compensation scheme with analog auto-tuning circuits and digital calibration sequences. The digital calibration sequences, which fit into the operation sequence of the HDD read channel, compensate for the tuning circuits of the process technology variations, and the tuning circuits compensate for the CTF characteristics over the supply voltage and temperature ranges. As a result, the CTF had a programmability of 100–1000-MHz cutoff frequency and 0–12-dB boost.

In this letter, we analyze the influence of motion and out-of-focus blur on both frequency spectrum and cepstrum of an iris image. Based on their characteristics, we define two new discriminative blur features represented by Energy Spectral Density Distribution (ESDD) and Singular Cepstrum Histogram (SCH). To merge the two features for blur detection, a merging kernel which is a linear combination of two kernels is proposed when employing Support Vector Machine. Extensive experiments demonstrate the validity of our method by showing the improved blur detection performance on both synthetic and real datasets.

This paper investigates the non-data-aided (NDA) carrier frequency estimation of amplitude and phase shift keying (APSK) signals. The true Cramer-Rao bound (CRB) for NDA frequency estimation of APSK signals are derived and evaluated numerically. Characteristic and jitter variance of NDA Luise and Reggiannini (L&R) frequency estimator are analyzed. Verified by Monte Carlo simulations, the analytical results are shown to be accurate for medium-to-high signal-to-noise ratio (SNR) values. Using the proposed closed-form expression, parameters of the algorithm are optimized efficiently to minimize the jitter variance.

The RFID tag system has received a lot of attention for ubiquitous computing. An RFID tag is attached to an object. With the unique ID of the RFID tag, a user identifies the object provided with the RFID tag and derives appropriate information about the object. One important application in the RFID technology is localizing RFID tags, which can be very useful in acquiring the position information concerning the RFID tags. It can be applied to navigation systems and positional detection systems for mobile robots. This paper proposes a new adaptive multi-range-sensing method for 3D localization of passive RFID tags by using a probabilistic approach. In this method, a mobile object (human, robot, etc.) with an RFID reader estimates the positions of RFID tags with multiple communication ranges dynamically. The effectiveness of the proposed method was demonstrated in experiments.

The mining of a complete set of frequent subgraphs from labeled graph data has been studied extensively. Furthermore, much attention has recently been paid to frequent pattern mining from graph sequences (dynamic graphs or evolving graphs). In this paper, we define a novel subgraph subsequence class called an “induced subgraph subsequence” to enable the efficient mining of a complete set of frequent patterns from graph sequences containing large graphs and long sequences. We also propose an efficient method for mining frequent patterns, called “FRISSs (Frequent Relevant, and Induced Subgraph Subsequences)”, from graph sequences. The fundamental performance of the method is evaluated using artificial datasets, and its practicality is confirmed through experiments using a real-world dataset.

Mel Frequency Cepstral Coefficients (MFCC) are the most popular acoustic features used in automatic speech recognition (ASR), mainly because the coefficients capture the most useful information of the speech and fit well with the assumptions used in hidden Markov models. As is well known, MFCCs already employ several principles which have known counterparts in the peripheral properties of human hearing: decoupling across frequency, mel-warping of the frequency axis, log-compression of energy, etc. It is natural to introduce more mechanisms in the auditory periphery to improve the noise robustness of MFCC. In this paper, a k-nearest neighbors based frequency masking filter is proposed to reduce the audibility of spectra valleys which are sensitive to noise. Besides, Moore and Glasberg's critical band equivalent rectangular bandwidth (ERB) expression is utilized to determine the filter bandwidth. Furthermore, a new bandpass infinite impulse response (IIR) filter is proposed to imitate the temporal masking phenomenon of the human auditory system. These three auditory perceptual mechanisms are combined with the standard MFCC algorithm in order to investigate their effects on ASR performance, and a revised MFCC extraction scheme is presented. Recognition performances with the standard MFCC, RASTA perceptual linear prediction (RASTA-PLP) and the proposed feature extraction scheme are evaluated on a medium-vocabulary isolated-word recognition task and a more complex large vocabulary continuous speech recognition (LVCSR) task. Experimental results show that consistent robustness against background noise is achieved on these two tasks, and the proposed method outperforms both the standard MFCC and RASTA-PLP.

This report focuses on a design method for gradient index (GRIN) lens antennas with controllable aperture field distributions. First, we derive differential equations representing optical paths in a gradient index medium with two optical surfaces by using geometrical optics, and then we formulate a novel design method for GRIN lens antennas based on these equations. The Levenberg-Marquardt algorithm is applied as a nonlinear least squares method to satisfy two conditions-focusing and shaping the aperture field distribution-thus realizing a prescribed radiation pattern. The conditions can be fulfilled by optimizing only the index (or permittivity) distribution, whereas the shapes of the optical surfaces remain as free parameters that can be utilized for other purposes, such as reducing reflection losses that occur on the surfaces, as illustrated in this report. A plano-concave GRIN lens is designed as an example, applying the proposed method, to realize a sidelobe level of -30 dB pseudo Taylor distribution, and a maximum sidelobe level of -29.1 dB was observed, indicating it is sufficiently accurate for practical use. In addition, we discuss the convergence of this method considering the relationship between the number of the initial conditions and the differential order of the design equations, factoring in scale invariance of the design equations.

We propose an optimal access-point (AP) selection algorithm for maximizing the aggregated throughput of each AP (system throughput) while preserving newly arrived-user throughput in multi rate WLAN system. In our algorithm, newly arrived users cooperate with a wireless local area network (WLAN) system they are trying to use, i.e., they are willing to move toward an appropriate AP before the newly arrived user connects to AP. To select the AP by using our AP selection algorithm, the newly arriving users request two novel parameter values, “the minimum acceptable throughput” with which newly arrived users can be satisfied and “the minimum movable distance” in which a user can move to an appropriate AP. While preserving these conditions, we maximize system throughput. When users cannot obtain a throughput greater than “the minimum acceptable throughput” with our proposed AP selection algorithm, they are rejected. Because, if users use streaming applications, which have strict bandwidth demands, with a very low bit-rate connection, they will not be satisfied. Thus, the newly arrived users having low bit-rate connection may be allowed to be rejected before the newly arrived user connects. In this paper, we show the optimal AP by using theoretical proof. We discuss the effectiveness of our proposed AP selection algorithm by using numerical analysis. We also clarify and analyze the characteristics of system throughput. Moreover, we show that a newly arrived user can select the movable distance and acceptable throughput by using examples from graphs depicting every position of newly arrived users. By using the graphs, we also show the relationship between the two parameters (the movable distance and the acceptable throughput) and the optimal AP, and the relationship between the two parameters and optimal system throughput when the movable distance and acceptable throughput are variable.

This paper proposes applying our inter-cell interference (ICI) cancellation method to fractional frequency reuse (FFR) and evaluates the resulting spectral efficiency improvement. With our ICI cancellation method based on base station cooperation, the control station generates ICI replica signals by simple linear processing. Moreover, FFR effectively utilizes frequency resources by both allowing users in the cell-center region to access all available sub-channels and increasing the transmission power to users in the cell-edge region. FFR provides the conditions under which the ICI cancellation method works effectively. Computer simulations show that the average spectral efficiency of the proposed method is comparable to that of cooperative MU-MIMO, which can completely remove ICI.

In this paper, a low-complexity symbol-spaced turbo frequency domain equalization (FDE) algorithm based on Laurent decomposition is proposed for precoded binary continuous phase modulation (CPM) with modulation index h=1/2. At the transmitter, a precoder is utilized to eliminate the inherent memory of the CPM signal. At the receiver, a matched filter based on Laurent decomposition is utilized to make the detection symbol-spaced. As a result, the symbol-spaced iteration can be taken between the equalizer and the decoder directly without a CPM demodulator, and we derive a symbol-spaced soft interference cancellation frequency domain equalization (SSIC-FDE) algorithm for binary CPM with h=1/2. A new data block structure for FDE of partial response CPM is also presented. The computational complexity analysis and simulations show that this approach provides a complexity reduction and an impressive performance improvement over previously proposed turbo FDE algorithm for binary CPM with h=1/2 in multi-path fading channels.

We present a new framework of the data-reusing (DR) adaptive algorithms by incorporating a constraint on noise, referred to as a noise constraint. The motivation behind this work is that the use of the statistical knowledge of the channel noise can contribute toward improving the convergence performance of an adaptive filter in identifying a noisy linear finite impulse response (FIR) channel. By incorporating the noise constraint into the cost function of the DR adaptive algorithms, the noise constrained DR (NC-DR) adaptive algorithms are derived. Experimental results clearly indicate their superior performance over the conventional DR ones.

We propose a 2Nr MIMO ARQ scheme that uses multi-strata space-time codes composed of two layers. The phase and transmit power of each layer are assigned adaptively at each transmission round to mitigate the inter-layer interference and improve the block error rate by retransmission. Simulation results show that the proposed scheme achieves better performance than the conventional schemes in terms of the throughput and the block error rate.

This letter summarizes three talks in the tutorial session of the 13th Asia-Pacific Network Operations and Management Symposium (APNOMS2011), which focused on the disaster recovery and further emergency management regarding the Great East Japan Earthquake of 2011. We present the damage and restoration of communication networks and points to a future disaster-resilient society.

In this paper, a hybrid overlay/underlay cognitive radio system is modeled as an M/M/1 queue where the rate of arrival and the service capacity are subject to Poisson alternations. Each packet as a customer arriving at the queue makes a decision to join the queue or not. Upon arrival, the individual decision of each packet is optimized based on his observation about the queue length and the state of system. It is shown that the individually optimal strategy for joining the queue is characterized by a threshold of queue length. Thus, the individual optimal threshold of queue length is analyzed in detail in this work.