In this study, a computationally efficient ranging scheme exploiting a minimum mean square error (MMSE) and a matrix-pencil (MP) technique is proposed for the IEEE 802.15.4a chirp spread spectrum (CSS) system. Based on the characteristics of the CSS signal, a practical methodology for the MMSE process is devised and the appropriate values of parameters, which are cutoff bandwidth, number of samples and sampling duration in frequency domain, are investigated and numerically determined to enhance the performance. The performance of proposed scheme is analyzed in terms of the computational complexity and the ranging estimation errors. Simulation results demonstrate that the proposed scheme performs as well as the conventional scheme at remarkably reduced computational costs.

A non-deterministic finite automaton (NFA)-based parallel string matching scheme is proposed. To parallelize the operations of NFAs, a graphic processing unit (GPU) is adopted. Considering the resource occupancy of threads and size of the shared memory, the optimized resource allocation is performed in the proposed string matching scheme. Therefore, the performance is enhanced significantly in all evaluations.

A chirp spread spectrum (CSS) system uses a chirp signal which changes the instantaneous frequency according to time for spreading a transmission bandwidth. In the CSS system, the transmission performance can be simply improved by increasing the time-bandwidth product which is known as the processing gain. However, increasing the transmission bandwidth is limited because of the spectrum regulation. In this letter, we propose a correlation-based chirp rate allocation method to improve the transmission performance by analyzing the cross-correlation coefficient in the same time-bandwidth product. In order to analyze the transmission performance of the proposed method, we analytically derive the cross-correlation coefficient according to the time-bandwidth separation product and simulate the transmission performance. The simulation results show that the proposed method can analytically allocate the optimal chirp rate and improve the transmission performance.

In this letter, we propose a Hadoop-based Video Transcoding System (HVTS), which is designed to run on all major cloud computing services. HVTS is highly adapted to the structure and policies of Hadoop, thus it has additional capacities for transcoding, task distribution, load balancing, and content replication and distribution. To evaluate, our proposed system, we carry out two performance tests on our local testbed, transcoding and robustness to data node and task failures. The results confirmed that our system delivers satisfactory performance in facilitating seamless streaming services in cloud computing environments.

This paper suggests utterance verification system using state-level log-likelihood ratio with frame and state selection. We use hidden Markov models for speech recognition and utterance verification as acoustic models and anti-phone models. The hidden Markov models have three states and each state represents different characteristics of a phone. Thus we propose an algorithm to compute state-level log-likelihood ratio and give weights on states for obtaining more reliable confidence measure of recognized phones. Additionally, we propose a frame selection algorithm to compute confidence measure on frames including proper speech in the input speech. In general, phone segmentation information obtained from speaker-independent speech recognition system is not accurate because triphone-based acoustic models are difficult to effectively train for covering diverse pronunciation and coarticulation effect. So, it is more difficult to find the right matched states when obtaining state segmentation information. A state selection algorithm is suggested for finding valid states. The proposed method using state-level log-likelihood ratio with frame and state selection shows that the relative reduction in equal error rate is 18.1% compared to the baseline system using simple phone-level log-likelihood ratios.

A downlink transmit diversity scheme is proposed for [1] WCDMA low chip rate (1.28 Mcps) Time Division Duplex (LCR-TDD) systems. In the proposed Time Switched Transmit Diversity (TSTD) scheme, two spatially separated antennas are alternately used at a base station in order to transmit consecutive sub-frames on the downlink physical channels. The proposed TSTD scheme takes advantage of the frame structure of the WCDMA LCR-TDD, where TSTD transmission is possible with a single power amplifier. Simply adding switching components in front of the transmit antennas yields a considerable gain compared with a non-diversity mode system. A new power control algorithm is also proposed for generating power control command for efficient use of TSTD. A performance gain of up to 5 dB, compared with a non-diversity scheme, is achieved in terms of the frame error rate for varying Eb/No and mobile speeds. From the viewpoint of both complexity and performance, the TSTD scheme is a simple and effective transmit diversity method that can increase downlink capacity in the WCDMA LCR-TDD systems.

This paper proposes a hardware-based parallel pattern matching engine using a memory-based bit-split string matcher architecture. The proposed bit-split string matcher separates the transition table from the state table, so that state transitions towards the initial state are not stored. Therefore, total memory requirements can be minimized.

In this paper, an efficient method to reduce computational complexity for pedestrian detection is presented. Since trilinear interpolation is not used, the amount of required operations for histogram of oriented gradient (HOG) feature calculation is significantly reduced. By calculating multi-scale HOG features with integral HOG in a two-stage approach, both high detection rate and speed are achieved in the proposed method.

With the aim of improving speaker identification, we propose a likelihood-based integration method to combine the speaker identification results obtained through multiple microphones. In many cases, the composite result has lower error rate than that by any single channel. The proposed integration method can achieve more reliable identification performance in the ubiquitous robot companion (URC) environment in which the robot is connected to a server through an extremely high broadband penetration rate.

In this letter, we propose a novel resource allocation scheme to enhance downlink system performance for orthogonal frequency division multiple access (OFDMA) and time division duplex (TDD) based femtocell networks. In the proposed scheme, the macro base station (mBS) and femto base stations (fBSs) service macro user equipments (mUEs) and femto user equipments (fUEs) in inner and outer zones in different periods to reduce interference substantially. Simulations show the proposed scheme outperforms femtocell networks with fractional frequency reuse (FFR) systems in terms of the system capacity and outage probability for mUEs and fUEs.

In this paper we propose a mobile positioning method based on a recursive least squares (RLS) algorithm for suppressing the non-line of sight (NLOS) effects in cellular systems. The proposed method finds the position of a mobile station from TOAs measured by three BSs. Simulation results show that the proposed method has a fast convergence time and greatly reduces the positioning error especially in NLOS situations. Thus it is expected that the proposed method can be effectively used in a dense urban environment.

In this letter, a new segment-level speech/nonspeech classification method based on the Poisson polling technique is proposed. The proposed method makes two modifications from the baseline Poisson polling method to further improve the classification accuracy. One of them is to employ Poisson mixture models to more accurately represent various segmental patterns of the observed frequencies for frame-level input features. The other is the soft counting-based frequency estimation to improve the reliability of the observed frequencies. The effectiveness of the proposed method is confirmed by the experimental results showing the maximum error reduction of 39% compared to the segmentally accumulated log-likelihood ratio-based method.

Backlight dimming techniques have been researched much to obtain high power saving on display modules, especially those which are based on LCD. The use of LED as a light source in a backlight module has opened a wider chance to perform local dimming as an improvement of a conservative global dimming approach. However, local dimming techniques are sometimes observed to obtain worse performance than global dimming ones in terms of power saving or image fidelity. We observed that even some of their results show visible artifacts. In this paper, we propose a novel backlight dimming technique called hybrid dimming, which combines local and global dimming approaches effectively. We do local dimming to obtain the initial backlight levels while calculating its SSIM index, which is a human visual system-aware image quality metric. We then make sure that these backlight levels don't exceed the ones obtained from a human visual system-aware global dimming with similar image fidelity. As a result, our proposed method can gain better power saving than a human visual system-aware global dimming and prior local dimming techniques, while making little difference in the image fidelity and suppressing visible block artifacts in the results. Experimental results showed that the proposed technique can achieve up to 14, 2.2, and 2.4 times higher power saving ratio than human visual system-aware global dimming and two well-designed local dimming techniques, respectively.

We present an adaptive power saving (APS) scheme to reduce downlink energy consumption of the transmit power in the cellular relay network (CRN). In the APS scheme, some cell topologies operating in 2-hop mode using relay stations (RSs) are converted to that of 3-hop mode and others are simultaneously converted to that of single-hop mode when the offered traffic load becomes very low, especially during night periods. By this means, we show the APS scheme outperforms the conventional CRN (CCRN) scheme in terms of energy consumption.

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.

Management of applications in the new world of pervasive computing requires new mechanisms to be developed for admission control, QoS negotiation, allocation and scheduling. To solve such resource-allocation and QoS provisioning problems within pervasive and ubiquitous computational environments, distribution and decomposition of the computation are important. In this paper we present a QoS-based welfare economic resource management model that models the actual price-formation process of an economy. We compare our economy-based approach with a mathematical approach we previously proposed. We use the constructs of application benefit functions and resource demand functions to represent the system configuration and to solve the resource allocation problems. Finally empirical studies are conducted to evaluate the performance of our proposed pricing model and to compare it with other approaches such as priority-based scheme and greedy method.

In this paper, we consider conventional signaling link fault tolerance and error correction mechanisms to provide reliable services of mobile multimedia telecommunication network based on ATM (Asynchronous Transfer Mode) technology. Also, we propose an efficient signaling protocol interworking architecture and a reliable distributed interworking network architecture between SS7 based FPLMTS and ATM networks. Besides, we evaluate the performance of proposed method through computer simulation. According to the results, proposed signaling architecture shows efficient and fast fault restoration characteristics than conventional MTP-3/3b based network. Functional signaling protocol stack and network architecture of proposed fast rerouting mechanism provide reliable and efficient restoration performance in view of interworking between SS7 based FPLMTS and ATM networks.

This paper suggests word voiceprint models to verify the recognition results obtained from a speech recognition system. Word voiceprint models have word-dependent information based on the distributions of phone-level log-likelihood ratio and duration. Thus, we can obtain a more reliable confidence score for a recognized word by using its word voiceprint models that represent the more proper characteristics of utterance verification for the word. Additionally, when obtaining a log-likelihood ratio-based word voiceprint score, this paper proposes a new log-scale normalization function using the distribution of the phone-level log-likelihood ratio, instead of the sigmoid function widely used in obtaining a phone-level log-likelihood ratio. This function plays a role of emphasizing a mis-recognized phone in a word. This individual information of a word is used to help achieve a more discriminative score against out-of-vocabulary words. The proposed method requires additional memory, but it shows that the relative reduction in equal error rate is 16.9% compared to the baseline system using simple phone log-likelihood ratios.

A chip is described that integrates two multimedia VLIW processor cores with a hardware streaming engine. It can implement a real-time videophone, or an MPEG4 codec. Each processor core has identical resources, and shares the memory and system I/O interface units. With its symmetric structure, applications can be executed on either processor without constraints. To accelerate multimedia-specific applications, the architecture of this processor has several features. It merges the features of a RISC and a DSP, its instruction set is extended to accelerate both video and audio applications, and it supports an efficient embedded memory system, to reduce both the bandwidth and the latency for multimedia applications needing frequent memory accesses. The chip size will be 100 mm2 die that contains 700 K logic gates, 60 KB RAM, and 16 KB ROM, in a 0.25-µm CMOS standard cell technology. At 65 MHz operating frequency, it can process H.263 video coding at CIF 15 frames/sec, and G.723.1 audio coding with an 80% processing time allocation.

This paper proposes a new pattern matching architecture with multi-character processing for deep packet inspection. The proposed pattern matching architecture detects the start point of pattern matching from multi-character input using input text alignment. By eliminating duplicate hardware components using process element tree, hardware cost is greatly reduced in the proposed pattern matching architecture.