This paper proposes adaptive transmit window control based on both location of mobile stations and traffic load for channel state based packet transmissions in CDMA cellular downlink communications. The proposed scheme constrains downlink packet transmissions by employing a transmit window individually given to each mobile station. The transmit window size is adjusted by using the optimum threshold value, which is selected with regard to both the mobile locations and the traffic load. The simulation results show that the proposed scheme improved the transmission delay and fairness of service compared with the conventional scheme.

A 0.13-µm CMOS 2.4-GHz low-noise balun-mixer is proposed, where a noise-canceling transconductance stage is adopted for low-noise characteristics. A current-bleeding circuit with an LC resonator is also adopted to further improve the noise figure of the proposed balun-mixer, without additional DC power consumption. The measured results show a DSB NF of 5.5 dB over output IF frequency ranges of 10 to 100 MHz, a conversion gain of 19 dB, and an input P1 dB of -16 dBm. The proposed balun-mixer is implemented in 0.13-µm CMOS technology and consumes only 4.5 mA from a 1.5-V supply voltage.

In this paper, the feasibility of composite right/left-handed transmission lines for realizing proximity coupled interconnects is reported. The proposed interconnects' resonant length can be miniaturized due to the zeroth order resonance supported by a composite right/left-handed transmission line resonator. In addition, the proposed interconnects can achieve broadside coupling because the zeroth order resonance occurs in the fast-wave region. Simulated and measured electric field distributions are shown to explain the broadside coupling phenomenon. To validate the arbitrary size and broadside coupling of the proposed interconnects, simulated and measured transmission characteristics are presented. The results show that low insertion loss can be achieved by using single and double broadside coupling between interconnects.

The beamforming weights which can suppress the interfering signal toward out-of-cell mobile stations in downlink are designed for a time division duplexing based OFDMA system when the channel information is not perfect. The derived beamforming weights do not improve the average SINR performance monotonously with the increased transmit SNR if the inverse of the transmit SNR is used as the regularization factor of the beamforming weights and the channel information obtained by the BS to design the BF weights is not perfect. Therefore, we suggest a simple scheme to select the regularization factor. The proposed beamforming weights improve the performance monotonously with the increased transmit SNR and achieve near-optimal performance. The performance achieved by applying the beamforming weights used in uplink to downlink beamforming is also investigated.

Recently several weighted clustering algorithms have been proposed, however, to the best of our knowledge; there is none that propagates weights to other nodes without weight message for leader election, normalizes node parameters and considers neighboring node parameters to calculate node weights. In this paper, we propose an Energy Efficient and Stable Weight Based Clustering (EE-SWBC) algorithm that elects cluster heads without sending any additional weight message. It propagates node parameters to its neighbors through neighbor discovery message (HELLO Message) and stores these parameters in neighborhood list. Each node normalizes parameters and efficiently calculates its own weight and the weights of neighboring nodes from that neighborhood table using Grey Decision Method (GDM). GDM finds the ideal solution (best node parameters in neighborhood list) and calculates node weights in comparison to the ideal solution. The node(s) with maximum weight (parameters closer to the ideal solution) are elected as cluster heads. In result, EE-SWBC fairly selects potential nodes with parameters closer to ideal solution with less overhead. Different performance metrics of EE-SWBC and Distributed Weighted Clustering Algorithm (DWCA) are compared through simulations. The simulation results show that EE-SWBC maintains fewer average numbers of stable clusters with minimum overhead, less energy consumption and fewer changes in cluster structure within network compared to DWCA.

Generalized quasi-cyclic (GQC) codes form a wide and useful class of linear codes that includes thoroughly quasi-cyclic codes, finite geometry (FG) low density parity check (LDPC) codes, and Hermitian codes. Although it is known that the systematic encoding of GQC codes is equivalent to the division algorithm in the theory of Grobner basis of modules, there has been no algorithm that computes Grobner basis for all types of GQC codes. In this paper, we propose two algorithms to compute Grobner basis for GQC codes from their parity check matrices; we call them echelon canonical form algorithm and transpose algorithm. Both algorithms require sufficiently small number of finite-field operations with the order of the third power of code-length. Each algorithm has its own characteristic. The first algorithm is composed of elementary methods and is appropriate for low-rate codes. The second algorithm is based on a novel formula and has smaller computational complexity than the first one for high-rate codes with the number of orbits (cyclic parts) less than half of the code length. Moreover, we show that a serial-in serial-out encoder architecture for FG LDPC codes is composed of linear feedback shift registers with the size of the linear order of code-length; to encode a binary codeword of length n, it takes less than 2n adder and 2n memory elements.

The paper introduces both high-speed transmission and quality of system to offer the Internet services on a HFC (Hybrid Fiber Coaxial) network. This utilizes modulating the phase and the amplitude to the signal of the IPMS (Internet Protocol Multicasting Service). An IP-cable transmitter, IP-cable modem, and IP-cable management servers that support 30-Mbps IPMS on the HFC were developed. The system provides a 21 Mbps HDTV transporting stream on a cable TV network. It can sustain a clear screen for a long time.

In this paper, the new residue number system (RNS) moduli sets {22n, 2n -1, 2n+1 -1} and {22n, 2n -1, 2n-1 -1} are introduced. These moduli sets have 4n-bit dynamic range and well-formed moduli which can result in high-performance residue to binary converters as well as efficient RNS arithmetic unit. Next, efficient residue to binary converters for the proposed moduli sets based on mixed-radix conversion (MRC) algorithm are presented. The converters are ROM-free and they are realized using carry-save adders and modulo adders. Comparison with the other residue to binary converters for 4n-bit dynamic range moduli sets shown that the presented designs based on new moduli sets {22n, 2n -1, 2n+1 -1} and {22n, 2n -1, 2n-1 -1} are improved the conversion delay and result in hardware savings. Also, the proposed moduli sets can lead to efficient binary to residue converters, and they can speed-up internal RNS arithmetic processing, compared with the other 4n-bit dynamic range moduli sets.

This study utilizes a new adaptive sense current controller to get an accurate power supply. The proposed controller effectively reduces output ripple voltage of converters operated over the load current range. This reduction is realized using an adaptive sense current circuit that automatically adjusts the inductor current according to operational conditions. The proposed boost converter is designed and fabricated with a standard TSMC 3.3/5 V 0.35-µm 2P4M CMOS technology. The experimental results show that the power-conversion efficiency of the proposed boost converter is 2-5% higher than that of the conventional converter with a current-limited circuit. The proposed circuit greatly reduces (i.e. by 76%) output ripple voltage compared with the conventional circuit at a 10 mA loading current.

In OFDM systems, the estimation/correction of carrier frequency offset (CFO) is crucial to maintain orthogonality among subcarriers. However, the CFO estimation suffers from DC offset (DCO) generated in low-cost direct-conversion receivers (DCRs). More seriously, in practice, DCO is time-varying due to the automatic gain control. In this paper, a novel CFO estimator in the presence of time-varying DCO is proposed. It is shown the residual DCO after high-pass filtering varies in a linear fashion. Based on this observation and the periodicity of the training sequence, we derive a CFO estimator independent of DCO. Also, the residual DCO can be estimated, using the obtained CFO. The validity of the proposed estimation method is demonstrated by simulations.

One of the most important challenges in speaker recognition is intersession variability (ISV), primarily cross-channel effects. Recent NIST speaker recognition evaluations (SRE) include a multilingual scenario with training conversations involving multilingual speakers collected in a number of other languages, leading to further performance decline. One important reason for this is that more and more researchers are using phonetic clustering to introduce high level information to improve speaker recognition. But such language dependent methods do not work well in multilingual conditions. In this paper, we study both language and channel mismatch using a support vector machine (SVM) speaker recognition system. Maximum likelihood linear regression (MLLR) transforms adapting a universal background model (UBM) are adopted as features. We first introduce a novel language independent statistical binary-decision tree to reduce multi-language effects, and compare this data-driven approach with a traditional knowledge based one. We also construct a framework for channel compensation using feature-domain latent factor analysis (LFA) and MLLR supervector kernel-based nuisance attribute projection (NAP) in the model-domain. Results on the NIST SRE 2006 1conv4w-1conv4w/mic corpus show significant improvement. We also compare our compensated MLLR-SVM system with state-of-the-art cepstral Gaussian mixture and SVM systems, and combine them for a further improvement.

Cognitive Radio (CR) is expected to bring about a more flexible wireless communication environment by the efficient utilization of spectrum resources. In this paper, a CR coexisting with IEEE 802.11 Wireless Local Area Networks (WLANs) is proposed. In the Distributed Coordination Function (DCF) access scheme in IEEE 802.11 WLAN, a station (STA) transmits a data frame by executing a random backoff procedure after Distributed Inter Frame Space (DIFS) period, and the destination STA of the data frame responds with Ack frame to the source STA after Short Inter Frame Space (SIFS) period. After the Ack frame is transmitted, the same procedures are repeated. The proposed CR terminal recognizes the DIFS period and the SIFS period, and then it transmits CR signals during these periods with the transmission power that does not affect the IEEE 802.11 WLAN protocol. Thus, the proposed CR terminals recognize the periods during which IEEE 802.11 STAs do not transmit any frames and they use the periods to transmit CR signals. In this paper, IEEE 802.11 WLAN STA that has the capability for the proposed CR technique in addition to the normal 802.11 WLAN capability is considered and the improved average throughputs by the CR communications are evaluated in the computer simulation, and then the effectiveness of the proposed method is clarified.

This paper presents an accurate and systematic method to model the equivalent circuit of pulse generator in the electrical fast transients/burst test (EFT/B). Firstly, a new analytical expression is presented to express the generator's charging and discharging process under open-condition (1000-Ω), which all its coefficients are determined according to the output waveform specified by the manufacturer. And then, with adoption of the step source, the transfer function of the pulse forming network in Laplace domain is deduced, which is ready for the network synthesis. Based on above discussion, the parameterized method and the technique of constant-resistance are adopted for the network synthesis. Finally, the equivalent circuit is renormalized and improved to meet the specification under matching-condition (50-Ω). In this way, the equivalent circuit of EFT/B generator is obtained and can be adjusted conveniently to satisfy the different manufacturers. The PSPICE simulation with a certain load is validated by measurement.

In this letter, we propose a speech reinforcement technique based on soft decision under both the far-end and near-end noise environments. We amplify the estimated clean speech signal at the far-end based on the estimated ambient noise spectrum at the near-end, as opposed to reinforcing the noisy far-end speech signal, so that it can be heard more intelligibly in far-end noisy environments. To obtain an effective reinforcement technique, we adopt the soft decision scheme incorporating a speech absence probability (SAP) in the frequency dependent signal-to-noise ratio (SNR) recovery method where the clean speech spectrum is estimated and the reinforcement gain is inherently derived and modified within the unified framework. Performance of the proposed method is evaluated by a subjective testing under various noisy environments. This is an improvement over previous approaches.

The purpose of this paper is to study sender authenticated key agreements by a third party, which uses the received parameters to verify the fact that a sender of a message knows his long-term private key. In particular, we propose a standard model for the protocol among three entities for the first time. The security of this protocol depends on the difficulty of solving two new problems related to one-way isomorphisms and the decision co-bilinear Diffie-Hellman problem on multiplicative cyclic groups. It is the first time that the security of a key agreement has been formally proven by using negligible probability. We believe that our contribution gives many applications in the cryptographic community.

In this paper, we present a forecasting method for the view of Mt. Fuji as an application of Earth observation data (EOD) obtained by satellites. We defined the Mt. Fuji viewing index (FVI) that characterises how well the mountain looks on a given day, based on photo data produced by a fixed-point observation. A long-term predictor of FVI, ranging from 0 to 30 days, was constructed through support vector machine regression on climate and earth observation data. It was found that the aerosol mass concentration (AMC) improves prediction performance, and such performance is particularly significant in the long-term range.

In the latest video coding frameworks, efficiency of motion vector (MV) coding is becoming increasingly important because of the growing bit rate portion of motion information. However, neither the conventional median predictor, nor the newer schemes such as the minimum bit rate prediction scheme and the hybrid scheme, can effectively eliminate the local redundancy of motion vectors. In this paper, we present the prioritized reference decision scheme for efficient motion vector coding, based on the H.264/AVC framework. This scheme makes use of a boolean indicator to specify whether the median predictor is to be used for the current MV or not. If not, the median prediction is considered not suitable for the current MV, and this information is used for refining the possible space of a group of reference MVs including 4 neighboring MVs and the zero MV. This group of MVs is organized to be a prioritized list so that the reference MV with highest priority is to be selected as the prediction value. Furthermore, the boolean indicators are coded into the modified code words of mb_type and sub_mb_type, so as to reduce the overhead. By applying the proposed scheme, the structure and the applicability problems with the state-of-the-art MBP scheme have been overcome. Experimental result shows that the proposed scheme achieves a considerable reduction of bits for MVDs, compared with the conventional median prediction algorithm. It also achieves a better and much stabler performance than MBP-based MV coding.

Adaptive polarization mode dispersion (PMD) compensation is required for the speed-up and advancement of the present optical communications. The combination of a tunable PMD compensator and its adaptive control method achieves adaptive PMD compensation. In this paper, we report an effective search control algorithm for the feedback control of the PMD compensator. The algorithm is based on the hill-climbing method. However, the step size changes randomly to prevent the convergence from being trapped at a local maximum or a flat, unlike the conventional hill-climbing method. The randomness depends on the Gaussian probability density functions. We conducted transmission simulations at 160 Gb/s and the results show that the proposed method provides more optimal compensator control than the conventional hill-climbing method.

In this letter, we propose a novel frequency-domain equalizer (FDE) for single-carrier systems characterized by severe inter-symbol interference (ISI) channels; it consists of a linear FDE and an iterative block noise-predictor (IBNP). Unlike the FDE with time-domain noise predictor (FDE-NP), the proposed scheme allows the feedback equalizer being an uncausal filter, and performs the noise prediction in an iterative manner. For this reason, FDE-IBNP can remove both precursor and postcursor ISI, and alleviate the impact of error-propagation. Besides, our scheme has lower computational complexity than the present iterative block equalizers.

In the present paper, we propose a novel cyber-attack detection model based on two multivariate-analysis methods to the audit data observed on a host machine. The statistical techniques used here are the well-known Hayashi's quantification method IV and cluster analysis method. We quantify the observed qualitative audit event sequence via the quantification method IV, and collect similar audit event sequence in the same groups based on the cluster analysis. It is shown in simulation experiments that our model can improve the cyber-attack detection accuracy in some realistic cases where both normal and attack activities are intermingled.