A novel one-transistor dynamic random access memory (1T DRAM) cell has been proposed for a low-voltage operation and longer data retention time. The proposed 1T DRAM cell has three features compared with a conventional 1T DRAM cell: low body doping concentration, a recessed gate structure, and a P + poly-Si gate. Simulation results show that the proposed 1T DRAM cell has < 1-ns program time and > 100-ms data retention time under the condition of sub-1-V operating voltage.

Using the recursive generalized eigendecomposition method, we develop a recursive form solution to the data least squares (DLS) problem in which the error is assumed to lie in the data matrix only. We apply it to a linear channel equalizer. Simulations shows that the DLS-based equalizer outperforms the ordinary least squares-based one in a channel equalization problem.

In this paper, we propose a robust timing synchronization algorithm for wireless MAN OFDM systems. The proposed algorithm is composed of frame synchronization and FFT timing synchronization. The conventional correlation scheme for estimation of timing offset has an ambiguity in the detection of accurate symbol timing. The proposed scheme, however, shows a clear peak at the correct timing by using the conjugate-symmetric characteristic of preamble and is able to control the FFT window position continuously with the 1-st order loop filter. Simulation results demonstrate the superiority of the proposed algorithm.

In this letter, we propose an approach to incorporate a statistical model for the voiced/unvoiced (V/UV) speech decision under background noise environments. Our approach consists of splitting the input noisy speech into two separate bands and applying a statistical model for each band. We compute and compare the likelihood ratio (LR) for each band based on the statistical model and estimated noise statistics for the V/UV decision. According to the simulation test, the proposed V/UV decision shows a better performance compared with the selectable mode vocoder (SMV) V/UV decision algorithm, particularly in clean and white noise environments.

In this letter, a new estimation filtering is proposed when a delay between signal generation and signal estimation exists. The estimation filter is developed under a maximum likelihood criterion using only the finite observations on the delay interval. The proposed estimation filter is represented in both matrix form and iterative form. It is shown that the filtered estimate has good inherent properties such as time-invariance, unbiasedness and deadbeat. Via numerical simulations, the performance of the proposed estimation filtering is evaluated by the comparison with that of the existing fixed-lag smoothing, which shows that the proposed approach could be appropriate for fast estimation of signals that vary relatively quickly. Moreover, the on-line computational complexity of the proposed estimation filter is shown to be maintained at a lower level than the existing one.

Video transmission over mobile worldwide interoperability for microwave access (WiMAX) can be serverly degraded due to the effect of fading and handoff. In this paper, we propose a channel adaptive error resilience scheme for video transmission over mobile WiMAX. When the channel condition begins to trigger handoff, the current frame is stored in the long-term memory for the forward error correction, and the following frames are encoded by using double motion vectors (MVs) in the sense of multi-hypothesis motion compensation. Even if a whole frame is lost, we can reconstruct the following frames using the stored frame in the long-term memory. However, the error propagation still remains in this forward error resilience method. To refresh the erroneous frames to the decoder, the encoder utilizes the channel adaptive refreshing (CAR). In the CAR, the channel rate is first predicted using channel parameter, a carrier to interference and noise ratio (CINR), and the encoder adaptively determines the number of blocks to be encoded in the intra mode based on the feedback information. Performance evaluations are presented to demonstrate the effectiveness of the proposed method.

We propose three operation modes, namely, DCF uplink, Downlink, and CTS uplink modes to solve the unfairness problem between uplink and downlink as well as improve the performance of delay and throughput. The proposed scheme only requires modifying AP's functionalities without any changes of STAs, and is fully backward compatible to the legacy DCF. Its analytical result is validated against simulation and performance evaluation shows the proposed scheme is superior to the traditional IEEE 802.11 WLAN.

This letter presents delayed perturbation bounds (DPBs) for receding horizon controls (RHCs) of continuous-time systems. The proposed DPBs are obtained easily by solving convex problems represented by linear matrix inequalities (LMIs). We show, by numerical examples, that the RHCs have larger DPBs than conventional linear quadratic regulators (LQRs).

In order to keep up with the growing need for memory bandwidth at low cost, a new synchronous DRAM (SDRAM) architecture is proposed. The SDRAM has programmable latency, burst length, and burst type for wide variety of applications. The experimental 16M SDRAM (2M8) achieves a 125-Mbyte/s data rate using 0.5-µm twin well CMOS technology.

In this paper, a new maximum likelihood filter with finite impulse response (FIR) structures is proposed for state space signal models with both system and observation noises. This filter is called the maximum likelihood FIR (MLF) filter. The proposed MLF filter doesn't require a priori information of the window initial state and processes the finite observations on the most recent window linearly. The proposed MLF filter is first represented in a batch form, and then in an iterative form for computational advantage. The proposed MLF filter has good inherent properties such as time-invariance, unbiasedness, deadbeat, robustness. The validity of the proposed MLF filter is illustrated by a computer simulation on a sinusoidal signal.

Recently, notable improvements in voice activity detection (VAD) problem have been achieved by adopting several machine learning techniques. Among them, the deep neural network (DNN) which learns the mapping between the noisy speech features and the corresponding voice activity status with its deep hidden structure has been one of the most popular techniques. In this letter, we propose a novel approach which enhances the robustness of DNN in mismatched noise conditions with multi-task learning (MTL) framework. In the proposed algorithm, a feature enhancement task for speech features is jointly trained with the conventional VAD task. The experimental results show that the DNN with the proposed framework outperforms the conventional DNN-based VAD algorithm.

There has been much interest in a spatial query which acquires sensor readings from sensor nodes inside specified geographical area of interests. A centralized approach performs the spatial query at a server after acquiring all sensor readings. However, it incurs high wireless transmission cost in accessing all sensor nodes. Therefore, various in-network spatial search methods have been proposed, which focus on reducing the wireless transmission cost. However, the in-network methods sometimes incur unnecessary wireless transmissions because of dead space, which is spatially indexed but does not contain real data. In this paper, we propose a hybrid spatial query processing algorithm which removes the unnecessary wireless transmissions. The main idea of the hybrid algorithm is to find results of a spatial query at a server in advance and use the results in removing the unnecessary wireless transmissions at a sensor network. We compare the in-network method through several experiments and clarify our algorithm's remarkable features.

In this paper, we propose a new software reliability growth model which is the mixture of two exponential reliability growth models, one of which has the reliability growth and the other one does not have the reliability growth after the software is released upon completion of testing phase. The mixture of two such models is characterized by a weighted factor p, which is the proportion of reliability growth part within the model. Firstly, this paper discusses an optimal software release problem with regard to the expected total software cost incurred during the warranty period under the proposed software reliability growth model, which generalizes Kimura, Toyota and Yamada's (1999) model with consideration of the weighted factor. The second main purpose of this paper is to apply the Bayesian approach to the optimal software release policy by assuming the prior distributions for the unknown parameters contained in the proposed software reliability growth model. Some numerical examples are presented for the purpose of comparing the optimal software release policies depending on the choice of parameters by the non-Bayesian and Bayesian methods.

In this paper, a chromatic adaptation model (CAM) based on the dependence on LMS cone responses of the human visual system (HVS) is proposed for TV and PC monitors under a variety of viewing conditions. We derived the proposed CAM based on Breneman's corresponding color data. The results of the experiments were carried out to assess the proposed model performance in terms of color fidelity by comparing complex images on a LCD monitor. We confirmed that the proposed model performed better to predict corresponding colors under various viewing conditions. Therefore, the reproduced colors, which are viewed in real surround viewing conditions, are perceived the same as original object colors, when the proposed CAM was applied to color display devices such as CRT, LCD, and PDP.

A modified proportional fairness (PF) scheduling scheme for OFDMA systems with imperfect channel quality indicator is suggested. It is based on user grouping, and in system level simulations, the proposed scheme improves average user throughput considerably when compared to conventional PF scheduling without grouping.

In this paper, we compare the major issues associated with TDMA and S-CDMA (Synchronous-Code Division Multiple Access), which is considered as a new cable modem standard technology for upstream channel. We mainly deal with the following 3 topics: MAC protocol, modem structure and BER (Bit Error Rate) performance comparison between TDMA and S-CDMA. Especially, we derive BER of TDMA and S-CDMA schemes in the ε-mixture impulse noise model which appropriately reflects impulse noise characteristics of the upstream channel by using various parameters.

A single-chip ubiquitous sensor network (USN) system-on-a-chip (SoC) for small program memory size and low power has been proposed and integrated in a 0.18-µm CMOS technology. Proposed single-chip USN SoC is mainly consists of radio for 868/915 MHz, analog building block, complete digital baseband physical layer (PHY) and media access control (MAC) functions. The transceiver's analog building block includes a low-noise amplifier, mixer, channel filter, receiver signal-strength indication, frequency synthesizer, voltage-controlled oscillator, and power amplifier. In addition, digital building block consists of differential binary phase-shift keying (DPSK) modulation, demodulation, carrier frequency offset compensation, auto-gain control, embedded 8-bit microcontroller, and digital MAC function. Digital MAC function supports 128 bit advanced encryption standard (AES), cyclic redundancy check (CRC), inter-symbol timing check, MAC frame control, and automatic retransmission. These digital MAC functions reduce the processing power requirements of embedded microcontroller and program memory size by up to 56%. The cascaded noise figure and sensitivity of the overall receiver are 9.5 dB and -99 dBm, respectively. The overall transmitter achieves less than 6.3% error vector magnitude (EVM). The current consumption is 14 mA for reception mode and 16 mA for transmission mode.

In the area of wireless sensor networks, the efficient spatial query processing based on the locations of sensor nodes is required. Especially, spatial queries on two sensor networks need a distributed spatial join processing among the sensor networks. Because the distributed spatial join processing causes lots of wireless transmissions in accessing sensor nodes of two sensor networks, our goal of this paper is to reduce the wireless transmissions for the energy efficiency of sensor nodes. In this paper, we propose an energy-efficient distributed spatial join algorithm on two heterogeneous sensor networks, which performs in-network spatial join processing. To optimize the in-network processing, we also propose a Grid-based Rectangle tree (GR-tree) and a grid-based approximation function. The GR-tree reduces the wireless transmissions by supporting a distributed spatial search for sensor nodes. The grid-based approximation function reduces the wireless transmissions by reducing the volume of spatial query objects which should be pushed down to sensor nodes. Finally, we compare naive and existing approaches through extensive experiments and clarify our approach's distinguished features.

In this paper, we propose a new algorithm of enhancing covariance matrix estimate to be used for estimating the directions-of-arrival (DOAs) of multiple incoherent signals incident on a uniform circular array. The underlying covariance matrix possesses a special theoretical property such as having spatial stationarity. The proposed enhancement approach based on the use of this property is found to provide improved DOA estimates in comparison to the unenhanced MUSIC for narrowband incoherent signals.

We present an algorithm for computing the Minkowski sum of two surfaces of revolution with parallel axes, each defined as a rotational sweep of a slope-monotone closed curve. This result is an extension of that due to Sugihara et al., where the Minkowski sum for two slope-monotone closed curves in the plane is defined.