This paper proposes a utility function-based scheduling algorithm for integrated real-time and non-real-time services in long-term evolution systems. The proposed utility function satisfies the target dropping ratio of real-time users; it uses the delay constraint and increases the throughput of non-real-time users by scheduling real-time users together with non-real-time users. Simulation results show that the proposed scheduling algorithm significantly improves the throughput of non-real-time users without sacrificing the quality of service of real-time users.

We consider secure wireless communications, where a source is communicating to a destination in the presence of K (K > 1) eavesdroppers. The source and destination both are equipped with multiple antennas, while each eavesdropper has a single antenna. The source aims to maximize the communication rate to the destination, while concealing the message from all the eavesdroppers. Combined with selective diversity, we propose a heuristic secrecy transmission scheme where the multiple-input-multiple-output (MIMO) secrecy channel is simplified into a multiple-input-single-output (MISO) one with the highest orthogonality to the eavesdropper channels. Then convex optimization is applied to obtain the optimal transmit covariance matrix for this selected MISO secrecy channel. Numerical results are provided to illustrate the efficacy of the proposed scheme.

To assess the performance of maximum-likelihood (ML) based Nakagami m parameter estimators, current methods rely on Monte Carlo simulation. In order to enable the analytical performance evaluation of ML-based m parameter estimators, we study the statistical properties of a parameter Δ, which is defined as the log-ratio of the arithmetic mean to the geometric mean for Nakagami-m fading power. Closed-form expressions are derived for the probability density function (PDF) of Δ. It is found that for large sample size, the PDF of Δ can be well approximated by a two-parameter Gamma PDF.

We quantitatively evaluate how sampling and spatio/temporal granularity in traffic monitoring affect the detectability of anomalous traffic. Those parameters also affect the monitoring burden, so network operators face a trade-off between the monitoring burden and detectability and need to know which are the optimal paramter values. We derive equations to calculate the false positive ratio and false negative ratio for given values of the sampling rate, granularity, statistics of normal traffic, and volume of anomalies to be detected. Specifically, assuming that the normal traffic has a Gaussian distribution, which is parameterized by its mean and standard deviation, we analyze how sampling and monitoring granularity change these distribution parameters. This analysis is based on observation of the backbone traffic, which exhibits spatially uncorrelated and temporally long-range dependence. Then we derive the equations for detectability. With those equations, we can answer the practical questions that arise in actual network operations: what sampling rate to set to find the given volume of anomaly, or, if the sampling is too high for actual operation, what granularity is optimal to find the anomaly for a given lower limit of sampling rate.

In order to implement multidimensional scaling (MDS) efficiently, we propose a new method named “global mapping analysis” (GMA), which applies stochastic approximation to minimizing MDS criteria. GMA can solve MDS more efficiently in both the linear case (classical MDS) and non-linear one (e.g., ALSCAL) if only the MDS criteria are polynomial. GMA separates the polynomial criteria into the local factors and the global ones. Because the global factors need to be calculated only once in each iteration, GMA is of linear order in the number of objects. Numerical experiments on artificial data verify the efficiency of GMA. It is also shown that GMA can find out various interesting structures from massive document collections.

A compact and wide stopband low-pass filter (LPF) which consists of a hairpin structural resonator, a chip-capacitor, and inductor lines is proposed in this paper. With the capacitor loaded, the hairpin structure realized three transmission zeros in the stopband. The LPF with one hairpin unit was designed using the conventional prototype design procedure in the passband. To further improve the stopband characteristics, the LPF with three hairpin units was studied and designed with the same manner as in a one unit LPF. The finally designed three-hairpin LPF showed mostly 60 dB rejection characteristics in the conjunction with defected ground condition for avoiding the spurious response at the stopband. The measurement results agreed well with simulated ones.

In this paper, we consider a stabilization problem for the cart-pendulum system based on discrete mechanics, which is known as a good discretizing method for mechanical systems and has not been really applied to control theory. First, the continuous and discrete cart-pendulum systems are explained. We next propose a transformation method that converts a discrete-time input derived from the discrete-time optimal regulator theory into a continuous-time zero-order hold input, and carry out some simulations on stabilization of the cart-pendulum system by the transformation method. Then, we apply not only our proposed method but also existing methods to an experimental laboratory of the cart-pendulum system and perform some experiments in order to verify the availability of the proposed method.

In this paper, we propose a duplicate document detection model recognizing both partial duplicates and near duplicates. The proposed model can detect partial duplicates as well as exact duplicates by splitting a large document into many small sentence fingerprints. Furthermore, the proposed model can detect even near duplicates, the result of trivial revisions, by filtering the common words and reordering the word sequence.

A method for efficiently representing the state equation in a class of max-plus linear systems is proposed. We introduce a construct referred to as 'cell' in which the list of possible longest paths is stored. By imposing interval constraints on the system parameters, we can reduce the complexity of the state equation. The proposed method would be useful in scheduling applications for systems with adjustable system parameters.

Packet classification is essential for supporting advanced network services such as firewalls, quality-of-service (QoS), virtual private networks (VPN), and policy-based routing. The rules that routers use to classify packets are called packet filters. If two or more filters overlap, a conflict occurs and leads to ambiguity in packet classification. This study proposes an algorithm that can efficiently detect and resolve filter conflicts using tuple based search. The time complexity of the proposed algorithm is O(nW +s), and the space complexity is O(nW), where n is the number of filters, W is the number of bits in a header field, and s is the number of conflicts. This study uses the synthetic filter databases generated by Class-Bench to evaluate the proposed algorithm. Simulation results show that the proposed algorithm can achieve better performance than existing conflict detection algorithms both in time and space, particularly for databases with large numbers of conflicts.

Phase structure of nonlinear dynamical system is governed by the vector field and decides the trajectories. Accordingly, the power spectra of trajectories include the structural field effect on the phase space. In this paper, we develop a method for analyzing phase structure using power spectra of trajectories and reconstitute a potential function in the system.

Monolithic integration of various kinds of optical components on a silicon wafer is the key to making silicon (Si) photonics practical technology. Applying silicon photonics to telecommunications further requires low insertion loss and polarization independence. We propose an integration concept for telecommunications based on Si and related materials and demonstrate monolithic integration of passive and dynamic functional components. This article shows the great potential of Si photonics technology for telecommunications.

It becomes so important to observe a wild life for obtaining not only knowledge of its biological behaviors but also interactions with human beings in terms of geoenvironmental investigation and assessment. A sensor network is considered to be a suitable and powerful tool to monitor and observe a wild life in fields. In order to monitor/observe seabirds, a sensor network is deployed in Awashima island, Japan. A sensor platform is useful for early and quick deployment in fields. Atlas, a server-client type sensor platform, is used with several sensors, i.e., infrared sensors, thermometers within a nest and a sound sensor. The experimental results and the first outcome of observation have been reported. Particularly emphasized is that an infrared sensor has detected a leaving and returning of seabirds, and has identified that a leaving and returning is affected by sunrises and sunsets. An infrared sensed data has also shown a chick's practice before flying to the south. These facts and knowledge have not been clearly obtained by observation of human beings, so have demonstrated the usefulness of sensor networking for ecology observations.

A planar high-pass filter (HPF) by using cross-couplings in multi-layer structure is proposed in this paper. The HPF consists of parallel plate and gap type capacitors and inductor lines on the bottom conductor. The one block of the HPF has a ladder T-section in the bridge T configuration. The one block HPF is, thus, coarsely designed in the manner of the proto-type HPF and the performance is optimized by circuit simulator. With the gap capacitor adjusted the proposed HPF illustrates the steep slope characteristics near the cut-off frequency by the attenuation pole. In order to improve the stopband performance, the cascaded two block HPF is examined. Its measured results show the good agreement with the simulated ones giving the second attenuation pole by an inductive cross-coupling.

Face detection has been an independent technology playing an important role in more and more fields, which makes it necessary and urgent to have its architecture reconfigurable to meet different demands on detection capabilities. This paper proposed a face detection architecture, which could be adjusted by the user according to the background, the sensor resolution, the detection accuracy and speed in different situations. This user adjustable mode makes the reconfiguration simple and efficient, and is especially suitable for portable mobile terminals whose working condition often changes frequently. In addition, this architecture could work as an accelerator to constitute a larger and more powerful system integrated with other functional modules. Experimental results show that the reconfiguration of the architecture is very reasonable in face detection and synthesized report also indicates its advantage on little consumption of area and power.

In this letter, we introduce two different resource allocation and Tx power management schemes, called resource control and fixed power (RCFP) and fixed resource and power control (FRPC), in an LTE-Advanced femtocell network. We analyze and compare the two schemes in terms of the system throughput for downlink and energy consumption of home evolved NodeB (HeNB) Tx power according to the number of HeNBs and home user equipment (HUE)'s user traffic density (C). The simulation results show that the FRPC scheme has better performance in terms of system throughput for macro user equipments (MUEs) and energy consumption in low C.

This paper proposes a novel sub-architecture to optimize the data flow of REMUS-II (REconfigurable MUltimedia System 2), a dynamically coarse grain reconfigurable architecture. REMUS-II consists of a µPU (Micro-Processor Unit) and two RPUs (Reconfigurable Processor Unit), which are used to speeds up control-intensive tasks and data-intensive tasks respectively. The parallel computing capability and flexibility of REMUS-II makes itself an excellent candidate to process multimedia applications, which require a large amount of memory accesses. In this paper, we specifically optimize the data flow to deal with those performance-hazard and energy-hungry memory accessing in order to meet the bandwidth requirement of parallel computing. The RPU internal memory could work in multiple modes, like 2D-access mode and transformation mode, according to different multimedia access patterns. This novel design can improve the performance up to 26% compared to traditional on-chip memory. Meanwhile, the block buffer is implemented to optimize the off-chip data flow through reducing off-chip memory accesses, which reducing up to 43% compared to direct DDR access. Based on RTL simulation, REMUS-II can achieve 1080p@30 fps of H.264 High Profile@ Level 4 and High Level MPEG2 at 200 MHz clock frequency. The REMUS-II is implemented into 23.7 mm2 silicon on TSMC 65 nm logic process with a 400 MHz maximum working frequency.

To improve simulation precision, the signal model of navigation satellite signal simulators is illustrated, and the generation mechanism and evaluation criteria of an important error source-phase jitter in baseband signal generation, are studied subsequently. An improved baseband signal generator based on dual-ROM look-up table structure is designed with the application of a newly-established concept-virtual sampling rate. Pre-storage of typical baseband signal data and sampling rate conversion adaptive to Doppler frequency shifts are adopted to achieve the high-precision simulation of baseband signals. Performance analysis of the proposed baseband signal generator demonstrates that it can successfully suppress phase jitter and has better spectral performance, generating high-precision baseband signals, which paves the way to improving the overall precision of navigation satellite signal simulators.

An AdaBoost-based face detection system is proposed, on a Coarse Grain Reconfigurable Architecture (CGRA) named “REMUS-II”. Our work is quite distinguished from previous ones in three aspects. First, a new hardware-software partition method is proposed and the whole face detection system is divided into several parallel tasks implemented on two Reconfigurable Processing Units (RPU) and one micro Processors Unit (µPU) according to their relationships. These tasks communicate with each other by a mailbox mechanism. Second, a strong classifier is treated as a smallest phase of the detection system, and every phase needs to be executed by these tasks in order. A phase of Haar classifier is dynamically mapped onto a Reconfigurable Cell Array (RCA) only when needed, and it's quite different from traditional Field Programmable Gate Array (FPGA) methods in which all the classifiers are fabricated statically. Third, optimized data and configuration word pre-fetch mechanisms are employed to improve the whole system performance. Implementation results show that our approach under 200 MHz clock rate can process up-to 17 frames per second on VGA size images, and the detection rate is over 95%. Our system consumes 194 mW, and the die size of fabricated chip is 23 mm2 using TSMC 65 nm standard cell based technology. To the best of our knowledge, this work is the first implementation of the cascade Haar classifier algorithm on a dynamically CGRA platform presented in the literature.

We propose a built-in planar lens for coupling light to a waveguide on a 2-D photonic crystal (PhC) membrane. A 2-D PhC waveguide with the built-in lens has been fabricated with AlGaAs. Improvement in coupling performance is discussed in comparison to waveguides with straight ends as cleaved.