The purpose of this study is to establish a whole-body averaged specific absorption rate (WB-SAR) estimation method using the power absorbed by humans; a cylindrical-external field scanning technique is used to measure the radiated RF (radio-frequency) power. This technique is adopted with the goal of simplifying the estimation of the exposure dosimetry of humans who have different postures and/or sizes. In this paper, to validate the proposed measurement method, we subject numerical human phantom models and cylindrical scanning conditions to FDTD analysis. We design a radiation system that uses a dielectric lens to achieve plane-wave irradiation of tested human phantoms in order to develop an experimental WB-SAR measurement system for UHF far-field exposure condition. In addition, we use a constructed SAR measurement system to confirm absorbed power estimations of simple geometrical phantoms and so estimate measurement error of the measurement system. Finally, we discuss the measurement results of WB-SARs for male adult and child human phantom models.

Estimating the number of signals (NIS) is an important goal in array signal processing, such as direction-of-arrival (DOA) estimation. A common approach for solving this problem is to use an eigenvalue of the array covariance matrix and information criterion, such as the Akaike information criterion (AIC) and minimum description length (MDL). However they suffer serious degradation, when the incoming signals are coherent. To estimate the NIS of the coherent signals impinging on a uniform linear array (ULA), a method for estimating the number of signals without eigendecomposition (MENSE) is proposed. The accuracy of the NIS estimation performance of MENSE is superior to the other algorithms equipped with preprocessing such as the spatial smoothing preprocessing (SSP) and forward/backward spatial smoothing techniques (FBSS) to decorrelate the coherency of signals. Instead of using SSP or FBSS preprocessing, MENSE uses the Hankel correlation matrices. The Hankel correlation matrices can not only decorrelate the coherency of signals but also suppress the influence of noise. However, in severe conditions like low signal-to-noise ratio (SNR) or a closely spaced signals impinging on a ULA, the NIS estimation metric of MENSE has some bias which causes estimation error. In this paper, we pay attention to the multiplicity defined by the ratio of the geometric mean to the arithmetic mean. Accordingly, we propose a new estimation metric that has less bias than that in MENSE. The Computer simulation results show that the proposed method is superior to MENSE in the above severe conditions.

This letter presents a novel multi-carrier code division multiple access (MC-CDMA) system called time domain synchronous MC-CDMA (TDS-MC-CDMA). Aided by the new training sequence (TS) with perfect autocorrelation in the time domain and flat frequency response in the frequency domain, the proposed TDS-MC-CDMA system outperform the traditional MC-CDMA system in terms of spectrum efficiency by about 10%. Simulations are carried out to demonstrate the good performance of the proposed scheme.

Given a set of objects, a skyline query finds the objects that are not dominated by others. We consider a skyline query for sets of objects in a database in this paper. Let s be the number of objects in each set and n be the number of objects in the database. The number of sets in the database amounts to nCs. We propose an efficient algorithm to compute convex skyline of the nCs sets. We call the retrieve skyline objectsets as "convex skyline objectsets". Experimental evaluation using real and synthetic datasets demonstrates that the proposed skyline objectset query is meaningful and is scalable enough to handle large and high dimensional databases. Recently, we have to aware individual's privacy. Sometimes, we have to hide individual values and are only allowed to disclose aggregated values of objects. In such situation, we cannot use conventional skyline queries. The proposed function can be a promising alternative in decision making in a privacy aware environment.

In this Letter, the maximum likelihood (ML) estimator for the parameters of a real sinusoid in additive white Gaussian noise using irregularly-spaced samples is derived. The ML frequency estimate is first determined by a one-dimensional search, from which optimum amplitude and phase estimates are then computed. It is shown that the estimation performance of the ML method can attain Cramér-Rao lower bound when the signal-to-noise ratio is sufficiently large.

We propose a time-frequency interleave (TFI) structure of single carrier (SC) frequency domain equalization (FDE) to combat spectral nulls of wireless channels. Permuted copies of block data are transmitted in the TFI-FDE, providing the same diversity order as maximal-ratio receiver combining. The spectral nulls are compensated by uncorrelated spectral components of the same channel. It shows 4 dB diversity gains at BER of 10-2 over an indoor channel. The TFI-FDE is computationally-efficient in combination with fast Fourier transform. This TFI-FDE fits SC systems with single antenna. It needs no channel state information at the transmitter.

This article presents a unified analytical framework to evaluate the bit error probability (BEP) of M-QAM, R-QAM and M-PAM modulation schemes for different types of fading channels, modeled with Hoyt, Rice, Rayleigh, Nakagami and Log-normal distributions. The mathematical development is obtained for maximal-ratio combining multichannel reception and assumes independent fading paths. The new BEP expressions are written in terms of the integral of the moment generating funcion of the instantaneos signal-to-noise ratio. The advantage of this approach is that it can be applied to any type of fading, and the integrals, even though they do not provide exact expressions, can be numerically evaluated.

In this paper, joint water filling and maximal ratio transmission (joint WF-MRT) downlink transmit diversity for a single-carrier distributed antenna network (SC DAN) is proposed. The joint WF-MRT transmit weight allocates the transmit power in both transmit antenna dimension and frequency dimension, i.e., the power allocation is done both across frequencies based on WF theorem and across transmit antennas based on MRT strategy. The cumulative distribution function (CDF) of the channel capacity achievable by joint WF-MRT transmit diversity is evaluated by Monte-Carlo numerical computation method. The channel capacities achievable with joint WF-MRT, MRT, and WF transmit weight (WF transmit weight is done across transmit antennas and frequencies based on WF theorem) are compared. It is shown that the joint WF-MRT transmit weight provides the highest channel capacity among three transmit weights.

A previous study proposed a downlink scheduling of real time variable rate (RT-VR), non real time variable rate (NRT-VR), and best effort (BE) traffic forwarding classes[1] to support QoS of the WiMax network. However, the study did not consider scheduling extended real time variable rate (ERT-VR) service, which defines the additional requirement of jitter performance when compared with RT-VR service. This article studies the supplementing function in ERT-VR service to complete QoS scheduling of downlink traffic in the WiMax network. Simulation results indicate that the proposed scheme not only satisfies delay time, but also guarantees the jitter requirement of ERT-VR traffic.

In this letter a new active element the Current Follower Transconductance Amplifier (CFTA) for the realization of the current-mode analog blocks is presented. The element is a combination of the Current Follower (CF) and the Balanced Output Transconductance Amplifier (BOTA). Possible internal structure of the CFTA is presented. The usage of the new active element is shown on the design of the Kerwin-Huelsman-Newcomb (KHN) structure working in the current mode. The frequency filter using the CFTA elements has been designed using the signal-flow graphs. The circuit structure employs three CFTA elements and two grounded passive elements. The filter enables realizing not only the basic functions as the low- (LP), band- (BP) and high-pass (HP) but also the notch and all-pass (AP) filter. The advantage of the structure presented is that the outputs of the filter are at high impedance and hence it is not necessary to use other auxiliary active elements. The properties of the filter proposed were verified by sensitivity and AC analyses in the PSPICE program.

In a ZigBee network, a finite address space is allocated to every potential parent device and a device may disallow a join request once this address space is exhausted. When a new node (child) requests to a coordinator (parent) to join a ZigBee network, the coordinator checks its address space. If it has sufficient address space, the coordinator accepts the new node as its child in the ZigBee network. If the new node has router capability (JoinAsRouter), it becomes a router in the ZigBee network. However, this association procedure makes ZigBee networks inefficient for routing, because the coordinator checks only the maximum and current numbers of child nodes. In the worst case, the network will be arranged so that the router nodes are crowded in the network. Therefore, we propose the KMCD-IME (Keeping the Maximum Communication Distance and Initial Mutual Exclusion among router nodes) algorithm with two additional conditions when a new node joins the ZigBee network. The first condition maintains the maximum communication distance between the new node and the would-be parent node. The second condition is the Initial Mutual Exclusion among router nodes. The router nodes are evenly spread across the network by KMCD-IME and an effective routing topology is formed. Therefore, the KMCD-IME algorithm extends the lifetime of the ZigBee network.

In a direct-sequence spread spectrum communication system, its multiple access interference, security and user number are mainly decided by correlation, linear span and family size of spreading sequences employed by such a system, respectively. In this letter, based on several families of the known sequences, a method for improving their linear span and family sizes is presented. It is worthy of mentioning that although the number of the proposed sequences with linear span not less than that of the known sequences is enormously increased, the former's correlation distribution is the same as the latter's one. In addition, the proposed sequences include No sequences and the known sequences mentioned above as special cases.

Bandwidth and gain enhancement of microstrip patch antennas (MPAs) is proposed using reflective metasurface (RMS) as a superstrate. Two different types of the RMS, namely- the double split-ring resonator (DSR) and double closed-ring resonator (DCR) are separately investigated. The two antenna prototypes were manufactured, measured and compared. The experimental results confirm that the RMS loaded MPAs achieve high-gain as well as bandwidth improvement. The desinged antenna using the RMS as a superstrate has a high-gain of over 9.0 dBi and a wide impedance bandwidth of over 13%. The RMS is also utilized to achieve a thin antenna with a cavity height of 6 mm, which is equivalent to λ/21 at the center frequency of 2.45 GHz. At the same time, the cross polarization level and front-to-back ratio of these antennas are also examined.

In this paper, we propose a genetic algorithm (GA) based equalization approach for direct sequence ultra-wideband (DS-UWB) wireless communication systems, where the GA is combined with a RAKE receiver to combat the inter-symbol interference (ISI) due to the frequency selective nature of UWB channels for high data rate transmission. The proposed GA based equalizer outperforms significantly the RAKE and the RAKE-minimum mean square error (MMSE) receivers according to results obtained from intensive simulation work. The RAKE-GA receiver also provides bit-error-rate (BER) performance very close to that of the optimal RAKE-maximum likelihood detection (MLD) approach, while offering a much lower computational complexity.

Kernel logistic regression (KLR) is a powerful and flexible classification algorithm, which possesses an ability to provide the confidence of class prediction. However, its training--typically carried out by (quasi-)Newton methods--is rather time-consuming. In this paper, we propose an alternative probabilistic classification algorithm called Least-Squares Probabilistic Classifier (LSPC). KLR models the class-posterior probability by the log-linear combination of kernel functions and its parameters are learned by (regularized) maximum likelihood. In contrast, LSPC employs the linear combination of kernel functions and its parameters are learned by regularized least-squares fitting of the true class-posterior probability. Thanks to this linear regularized least-squares formulation, the solution of LSPC can be computed analytically just by solving a regularized system of linear equations in a class-wise manner. Thus LSPC is computationally very efficient and numerically stable. Through experiments, we show that the computation time of LSPC is faster than that of KLR by two orders of magnitude, with comparable classification accuracy.

Various contrast enhancement methods such as histogram equalization (HE) and local contrast enhancement (LCE) have been developed to increase the visibility and details of a degraded image. We propose an image contrast enhancement method based on the global and local adjustment of gray levels by combining HE with LCE methods. For the optimal combination of both, we introduce a discrete entropy. Evaluation of our experimental results shows that the proposed method outperforms both the HE and LCE methods.

In recent years, the mining of a complete set of frequent subgraphs from labeled graph data has been studied extensively. However, to the best of our knowledge, no method has been proposed for finding frequent subsequences of graphs from a set of graph sequences. In this paper, we define a novel class of graph subsequences by introducing axiomatic rules for graph transformations, their admissibility constraints, and a union graph. Then we propose an efficient approach named "GTRACE" for enumerating frequent transformation subsequences (FTSs) of graphs from a given set of graph sequences. The fundamental performance of the proposed method is evaluated using artificial datasets, and its practicality is confirmed by experiments using real-world datasets.

In sensor networks, many studies have been proposed to process in-network aggregation efficiently. Unlike general aggregation queries, skyline query processing compares multi-dimensional data for the result. Therefore, it is very difficult to process the skyline queries in sensor networks. It is important to filter unnecessary data for energy-efficient skyline query processing. Existing approaches get rid of unnecessary data transmission by deploying filters to whole sensors. However, network lifetime is reduced due to energy consumption for transmitting filters. In this paper, we propose a lazy filtering-based in-network skyline query processing algorithm to reduce energy consumption by transmitting filters. Our algorithm creates the skyline filter table (SFT) in the data gathering process which sends data from sensor nodes to the base station and filters out unnecessary data transmissions using it. The experimental results show that our algorithm reduces false positive by 53% and improves network lifetime by 44% on average over the existing method.

An upper bound is established for certain exponential sums on the rational points of an elliptic curve over a residue class ring ZN , N=pq for two distinct odd primes p and q. The result is a generalization of an estimate of exponential sums on rational point groups of elliptic curves over finite fields. The bound is applied to showing the pseudorandomness of a large family of binary sequences constructed by using elliptic curves over ZN .

The code division multiplexing (CDM)-based MIMO channel sounder architecture is efficient at measuring fast fading MIMO channels. This paper examines loosely synchronous (LS), CAZAC, Kasami, and Chaotic sequences as probing signals in the CDM architecture. After comparing the performance of the channel measurement among the sequences, it is concluded that the LS sequences are the most appropriate codes for the probing signals. However, because LS sequences have a significant drawback in that the number of transmit antennas is limited to less than 4, we propose using a hybrid architecture combining CDM with TDM for supporting a greater number of transmit antennas. The simulation results show that the proposed scheme can improve the measurement performance when more than 4 transmit antennas are used.