This letter presents a model with queueing theory to analyze the performance of non-saturated IEEE 802.11 DCF networks. We use the closed queueing network model and derive an approximate representation of throughput which can reveal the relationship between the throughput and the total offered load under finite traffic load conditions. The accuracy of the model is verified by extensive simulations.

Recently, dynamic power supply voltage techniques, such as an Envelope Elimination and Restoration power amplifier (EER-PA) or Envelope-Tracking Power amplifier (ET-PA), have been attracting much attention because they can maintain high efficiency in large back-off region [1]-[6]. The dynamic power supply voltage techniques cause strong nonlinearity compared to a conventional power amplifier, hence a memoryless Digital Predistortion (DPD) technique is indispensable for these efficiency enhancement techniques. However, the performance of the memoryless DPD is degraded due to the frequency response of the envelope amplifier in the dynamic power supply voltage techniques [7]-[9]. In this paper, we clarify the degradation mechanisms of the memoryless DPD for the EER-PA due to the frequency response of the envelope amplifier based on the results of two-tone tests, and propose an analytical model for improving the performance of the memoryless DPD developed for the EER-PA. In addition, a prototype EER-PA is developed and we demonstrate that the residual distortion of the developed EER-PA with conventional memoryless DPD algorithm is compensated by the new algorithm based on the proposed analytical model. In the two-tone test, third-order intermodulation distortion (IMD3) with a tone spacing from 100 kHz to 4 MHz is improvement by up to 25 dB by the memoryless DPD algorithm based on the proposed model. Measured adjacent channel leakage power ratio (ACPR) of the developed EER-PA is improved from -22.5 dBc to -42.5 dBc in the OFDM signal test with 1.08 MHz bandwidth.

More and more mobile devices adopt multi-battery and dynamic voltage scaling policy (DVS) to reduce the energy consumption and extend the battery runtime. However, since the nonlinear characteristics of the multi-battery are not considered, the practical efficiency is not good enough. In order to reduce the energy consumption and extend the battery runtime, this paper proposes an approach based on the battery characteristics to implement the co-optimization of the multi-battery scheduling and dynamic voltage scaling on multi-battery powered systems. In this work, considering the nonlinear discharging characteristics of the existing batteries, we use the Markov process to depict the multi-battery discharging behavior, and build a multi-objective optimal model to denote the energy consumption and battery states, then propose a binary tree based algorithm to solve this model. By means of this method, we get an optimal and applicable scheme about multi-battery scheduling and dynamic voltage scaling. Experimental results show that this approach achieves an average improvement in battery runtime of 17.5% over the current methods in physical implementation.

In this paper, we present a speech enhancement technique based on the ambient noise classification that incorporates the Gaussian mixture model (GMM). The principal parameters of the statistical model-based speech enhancement algorithm such as the weighting parameter in the decision-directed (DD) method and the long-term smoothing parameter of the noise estimation, are set according to the classified context to ensure best performance under each noise. For real-time context awareness, the noise classification is performed on a frame-by-frame basis using the GMM with the soft decision framework. The speech absence probability (SAP) is used in detecting the speech absence periods and updating the likelihood of the GMM.

We consider secret key agreement for multiple terminals based on radio propagation characteristics in a wireless relaying system where more than two terminals communicate with each other via a relay. In this system, the multiple terminals share a common secret key generated from their radio propagation characteristics with the help of the relay in the presence of an eavesdropper. In this paper, we present three secret key agreement schemes: an amplify-and-forward (AF) scheme, a signal-combining amplify-and-forward (SC-AF) scheme, and a multiple-access amplify-and-forward (MA-AF) scheme. The key idea of these schemes is that each terminal shares the fading coefficients between all terminals and the relay, and use them as the source of a secret key. The AF scheme is based on a conventional amplify-and-forward two-way relaying method, whereas in the SC-AF scheme and the MA-AF scheme, we apply the idea of analog network coding to secret key agreement. We analyze eavesdropping strategies and show that the AF scheme is not secure if the eavesdropper is located near the relay and can receive signals from the relay without multipath fading and noise. Simulation results show that the SC-AF and MA-AF schemes are effective.

This paper proposes a new three-mode resonator, which consists of a parallel-coupled microstrip line resonator embedded with a slotline resonator, and develops a compact low-loss bandpass filter (BPF) with a sharp roll-off response because of four transmission zeros (TZ) located very near the passband. Resonance mechanism and properties of the three modes are first analyzed by using an eigen-mode analysis, and then an equivalent circuit model is established for expressing a novel coupling scheme of the developed BPF. It is made clear from the results of circuit analysis that the four TZs are produced because of multiple paths between the input/output stub lines formed by the three resonant modes and the direct source/load coupling. The validity of the proposed resonator and filter is supported by the comparison between simulated and measured results.

This paper proposes a high-precision, high-speed keypoint matching method using two-stage randomized trees (RTs). The keypoint classification uses conventional RTs for high-precision, real-time keypoint matching. However, the wide variety of view transformations for templates expressed by RTs make it diffidult to achieve high-precision classification for all transformations with a single RTs. To solve this problem, the proposed method classifies the template view transformations in the first stage and then, in the second stage, classifies the keypoints using the RTs that corresponds to each of the view transformations classified in the first stage. Testing demonstrated that the proposed method is 88.5% more precise than SIFT, and 63.5% more precise than using conventional RTs for images in which the viewpoint of the object is rotated by 70 degrees. We have also shown that the proposed method supports real-time keypoint matching at 12 fps.

In this paper, we propose an effective mutation operators for Cooperative Genetic Algorithm (CGA) to be applied to a practical Nurse Scheduling Problem (NSP). The nurse scheduling is a very difficult task, because NSP is a complex combinatorial optimizing problem for which many requirements must be considered. In real hospitals, the schedule changes frequently. The changes of the shift schedule yields various problems, for example, a fall in the nursing level. We describe a technique of the reoptimization of the nurse schedule in response to a change. The conventional CGA is superior in ability for local search by means of its crossover operator, but often stagnates at the unfavorable situation because it is inferior to ability for global search. When the optimization stagnates for long generation cycle, a searching point, population in this case, would be caught in a wide local minimum area. To escape such local minimum area, small change in a population should be required. Based on such consideration, we propose a mutation operator activated depending on the optimization speed. When the optimization stagnates, in other words, when the optimization speed decreases, the mutation yields small changes in the population. Then the population is able to escape from a local minimum area by means of the mutation. However, this mutation operator requires two well-defined parameters. This means that user have to consider the value of these parameters carefully. To solve this problem, we propose a periodic mutation operator which has only one parameter to define itself. This simplified mutation operator is effective over a wide range of the parameter value.

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.

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.

Power consumption due to transmissions in base stations (BSs) has been a major contributor to communication-related CO2 emissions. A power optimization model is developed in this study with respect to radio resource allocation and activation in a multiple Component Carrier (CC) environment. We formulate and solve the power-minimization problem of the BS transceivers for multiple-CC networks with carrier aggregation, while maintaining the overall system and respective users' utilities above minimum levels. The optimized power consumption based on this model can be viewed as a lower bound of that of other algorithms employed in practice. A suboptimal scheme with low computation complexity is proposed. Numerical results show that the power consumption of our scheme is much better than that of the conventional one in which all CCs are always active, if both schemes maintain the same required utilities.

A novel hybrid latch based flip-flop scheme is introduced in this paper. A pulse generator is eliminated to simplify clock distribution and save power. It also achieves high speed by shortening the critical data path. In addition, it avoids output node glitches which exist in conventional hybrid latch based flip-flops. HSPICE simulation results revealed that the proposed PHLFF performs best among referenced schemes. It can reduce 47.5% power dissipation, 16.5% clock-to-output latency and 56.4% PDP, as compared to conventional HLFF.

The current version of IEEE 802.15.4 MAC protocol does not support energy-efficient mobility for the low-power device. In this paper, we propose an energy-efficient sleep mode as part of the IEEE 802.15.4 that can conserve energy by considering mobility of mobile sensor devices. The proposed energy-efficient sleep mode dynamically extends the sleep interval if there is no data to transmit from the device or receive from corresponding nodes.

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.

In this paper, to reduce the memory size requirements of IFFT for OFDM-based applications, we propose a new IFFT design technique based on a combined integer mapping of three IFFT input signals: modulated data, pilot and null signals. The proposed method focuses on reducing the size of memory cells in the first two stages of the single-path delay feedback (SDF) IFFT architectures since the first two stages require 75% of the total memory cells. By simulations of 2048-point IFFT design for cognitive radio systems, it is shown that the proposed IFFT design method achieves more than 13% reduction in gate count and 11% reduction in power consumption compared with conventional IFFT design.

Most large-scale Peer-to-Peer (P2P) live streaming systems are constructed as a mesh structure, which can provide robustness in the dynamic P2P environment. The pull scheduling algorithm is widely used in this mesh structure, which degrades the performance of the entire system. Recently, network coding was introduced in mesh P2P streaming systems to improve the performance, which makes the push strategy feasible. One of the most famous scheduling algorithms based on network coding is R2, with a random push strategy. Although R2 has achieved some success, the push scheduling strategy still lacks a theoretical model and optimal solution. In this paper, we propose a novel optimal pull-push scheduling algorithm based on network coding, which consists of two stages: the initial pull stage and the push stage. The main contributions of this paper are: 1) we put forward a theoretical analysis model that considers the scarcity and timeliness of segments; 2) we formulate the push scheduling problem to be a global optimization problem and decompose it into local optimization problems on individual peers; 3) we introduce some rules to transform the local optimization problem into a classical min-cost optimization problem for solving it; 4) We combine the pull strategy with the push strategy and systematically realize our scheduling algorithm. Simulation results demonstrate that decode delay, decode ratio and redundant fraction of the P2P streaming system with our algorithm can be significantly improved, without losing throughput and increasing overhead.

Mirrored serpentine microstrip lines are proposed for a parallel high speed digital signaling to reduce the peak far-end crosstalk (FEXT) voltage. Mirrored serpentine microstrip lines consist of two serpentine microstrip lines, each one equal to a conventional normal serpentine microstrip line. However, one serpentine microstrip line of the mirrored serpentine microstrip lines is flipped in the length direction, and thus, two serpentine microstrip lines face each other. Time domain reflectometry measurements show that the peak FEXT voltage of the mirrored serpentine microstrip lines is reduced by 56.4% of that of conventional microstrip lines and 30.0% of that of conventional normal serpentine microstrip lines.

We propose a fast and precise transient response and frequency characteristics simulation method for switching converters. This method uses a behavioral simulation tool without using a SPICE-like analog simulator. The nonlinear operation of the circuit is considered, and the nonlinear function is realized by defining the nonlinear formula based on the circuit operation and by applying feedback. To assess the accuracy and simulation time of the proposed simulation method, we designed current-mode buck and boost converters and fabricated them using a 0.18-µm high-voltage CMOS process. The comparison in the transient response and frequency characteristics among SPICE, the proposed program on a behavioral simulation tool which we named NSTVR (New Simulation Tool for Voltage Regulators) and experiments of fabricated IC chips showed good agreement, while NSTVR was more than 22 times faster in transient response and 85 times faster in frequency characteristics than SPICE in CPU time in a boost converter simulation.

Although there have been enormous investments into English education all around the world, not many differences have been made to change the English instruction style. Considering the shortcomings for the current teaching-learning methodology, we have been investigating advanced computer-assisted language learning (CALL) systems. This paper aims at summarizing a set of POSTECH approaches including theories, technologies, systems, and field studies and providing relevant pointers. On top of the state-of-the-art technologies of spoken dialog system, a variety of adaptations have been applied to overcome some problems caused by numerous errors and variations naturally produced by non-native speakers. Furthermore, a number of methods have been developed for generating educational feedback that help learners develop to be proficient. Integrating these efforts resulted in intelligent educational robots – Mero and Engkey – and virtual 3D language learning games, Pomy. To verify the effects of our approaches on students' communicative abilities, we have conducted a field study at an elementary school in Korea. The results showed that our CALL approaches can be enjoyable and fruitful activities for students. Although the results of this study bring us a step closer to understanding computer-based education, more studies are needed to consolidate the findings.

In this letter, a novel association method called ELBA (efficient load balancing association) is proposed for improved load balancing in IEEE 802.15.4-based WSNs (wireless sensor networks). ELBA adds new nodes to the network in an efficient load-balancing manner by exploiting not only RSSI (received signal strength indicator), which is used in the standard, but also traffic-load, the number of allocated GTSs (guaranteed time slots), and the number of parent nodes and child nodes. Simulation results show that ELBA offers better performance in load balancing and preventing congestion.