An OFDMA based channel access scheme is proposed for dynamic spectrum access to utilize frequency spectrum efficiently. Though the OFDMA based scheme is flexible enough to change the bandwidth and channel of the transmitted signals, the OFDMA signal has large PAPR (Peak to Average Power Ratio). In addition, if the OFDMA receiver does not use a filter to extract sub-carriers before FFT (Fast Fourier Transform) processing, the designated sub-carriers suffer large interference from the adjacent channel signals in the FFT processing on the receiving side. To solve the problems such as PAPR and adjacent channel interference encountered in the OFDMA based scheme, this paper proposes a novel dynamic channel access scheme using overlap FFT filter-bank based on single carrier modulation. It also shows performance evaluation results of the proposed scheme by computer simulation.

Due to the advancement of software radio and RF technology, cognitive radio(CR) has become an enabling technology to realize dynamic spectrum access through its spectrum sensing and reconfiguration capability. Robust and reliable spectrum sensing is a key factor to discover spectrum opportunity. Single cognitive radios often fail to provide such reliable information because of their inherent sensitivity limitation. Primary signals that are subject to detection by cognitive radios may become weak due to several factors such as fading and shadowing. One approach to overcome this problem is to perform spectrum sensing by using multiple CRs or multiple spectrum sensors. This approach is known as distributed sensing because sensing is carried out through cooperation of spatially distributed sensors. In distributed sensing, sensors should perform spectrum sensing and forward the result to a destination where data fusion is carried out. Depending on the channel conditions between sensors (sensor-to-sensor channel) and between the sensor and the radio (user-channel), we explore different spectrum sensing algorithms where sensors provide the sensing information either cooperatively or independently. Moreover we investigate sensing schemes based on soft information combining (SC), hard information combining (HC). Finally we propose a two-stage detection scheme that uses both SC and HC. The newly proposed detection scheme is shown to provide improved performance compared to sensing based on either HC or SC alone. Computer simulation results are provided to illustrate the performances of the different sensing algorithms.

The synthesis of single- and double-wall carbon nanotubes by gas flow-modified, catalyst-supported chemical vapor deposition (CCVD) is reported. We have investigated the gas flow condition dependence on the synthesis of carbon nanotubes (CNTs) by placing blocks in the CCVD reactor. Carbon nanotubes having large diameters are preferentially grown under turbulent flow conditions. This indicates that the diameter distribution of CNTs can be controlled by modification of the gas flow condition in the CCVD.

This letter provides a study on the end-to-end performance of multi-hop wireless communication systems equipped with re-generative (decode-and-forward) relays over Rayleigh fading channels. More specifically, the probability density function (pdf) of the tightly approximated end-to-end signal-to-noise ratio (SNR) of the systems is derived. Using this approximation allows us to avoid considering all possible combinations of correct and erroneous decisions at the relays for which the end-to-end transmission is error-free. The proposed analysis offers a simple and unifying approach as well as reduces computation burden in evaluating important multi-hop system's performance metrics. Simulations are performed to verify the accuracy and to show the tightness of the theoretical analysis.

We carried out degradation analysis of a blue phosphorescent organic light emitting diode by both impedance spectroscopy and transient electroluminescence (EL) spectroscopy. The number of semicircles observed in the Cole-Cole plot of the modulus became three to two after the device was operated for 567 hours. Considering the effective layer thickness of the initial and degraded devices did not change by degradation and combining the analysis of the Bode-plot of the imaginary part of the modulus, the relaxation times of emission layer and hole-blocking with electron transport layers changed to nearly the same value by the increase of the resistance of emission layer. Decay time of transient EL of the initial device was coincident with that of the degraded one. These phenomena suggest that no phosphorescence quenching sites are generated in the degraded device, but the number of the emission sites decrease by degradation.

Scanning packet payload at a high speed has become a crucial task in modern network management due to its wide variety applications on network security and application-specific services. Traditionally, Deterministic finite automatons (DFAs) are used to perform this operation in linear time. However, the memory requirements of DFAs are prohibitively high for patterns used in practical packet scanning, especially when many patterns are compiled into a single DFA. Existing solutions for memory blow-up are making a trade-off between memory requirement and memory access of processing per input character. In this paper we proposed a novel method to drastically reduce the memory requirements of DFAs while still maintain the high matching speed and provide worst-case guarantees. We removed the duplicate transitions between states by dividing all the DFA states into a number of groups and making each group of states share a merged transition table. We also proposed an efficient algorithm for transition sharing between states. The high efficiency in time and space made our approach adapted to frequently updated DFAs. We performed several experiments on real world rule sets. Overall, for all rule sets and approach evaluated, our approach offers the best memory versus run-time trade-offs.

In a Direct-Sequence/Spread-Spectrum (DS/SS) system, a RAKE receiver is used to improve a bit error rate (BER) performance. The RAKE receiver can collect more signal energy through independent paths and achieve path diversity. The RAKE receiver obtains further diversity gain through fractional sampling. However, the power consumption of the RAKE receiver increases in proportion to a sampling rate and does not always maximize the signal-to-noise ratio (SNR). Therefore, sampling rate selection schemes have been proposed to reduce the average sampling rate without degrading the BER. These schemes select the tap positions and the sampling rate depending on channel conditions and the power consumption can be reduced. In this paper, sampling rate selection schemes for the DS/SS system are investigated through an experiment since there have been no numerical results through an experiment. Numerical results show that the power consumption can be reduced even through the experiment without the degradation of the BER.

In this paper, for systematically evaluating estimation methods of node characteristics, we first propose a social network generation model called LRE (Linkage with Relative Evaluation). LRE is a network generation model, which aims to reproduce the characteristics of a social network. LRE utilizes the fact that people generally build relationships with others based on relative evaluation, rather than absolute evaluation. We then extensively evaluate the accuracy of the estimation method called SSI (Structural Superiority Index). We reveal that SSI is effective for finding good nodes (e.g., top 10% nodes), but cannot be used for finding excellent nodes (e.g., top 1% nodes). For alleviating the problems of SSI, we propose a novel scheme for enhancing existing estimation methods called RENC (Recursive Estimation of Node Characteristic). RENC reduces the effect of noise by recursively estimating node characteristics. By investigating the estimation accuracy with RENC, we show that RENC is quite effective for improving the estimation accuracy in practical situations.

This paper presents the analysis and design of a reflection-cancelling transverse slot-pair array antenna with baffles by using the Spectrum of Two-Dimensional Solutions (S2DS) method. For the transverse slot array, the slot spacings with more than one free-space wavelength cause the grating-lobes. The baffles suppress the grating-lobes effectively. A one-dimensional slot array is extracted from the 2D array with in-phase excitation by assuming periodicity in the transversal direction. The uniform excitation over the finite array is synthesized iteratively to demonstrate the fast and accurate results by S2DS. A unit design model with the baffles is introduced to determine the initial parameters of the slot-pairs, which greatly accelerate the iterations process. Experiments at 25.3 GHz demonstrate the suppression of the grating lobes to the level less than -20.0 dB and also the good uniformity of the aperture field distribution.

This paper presents the dual-band bandpass filters (BPFs) design composed of λ/2 and symmetrically/asymmetrically paired λ/4 stepped impedance resonators (SIRs) for the WLAN applications. The filters cover both the operating frequencies of 2.45 and 5.2 GHz. The dual-coupling mechanism is used in the filter design to provide alternative routes for signals of selected frequencies. A prototype filter is composed of λ/2 and symmetrical λ/4 SIRs. The enhanced wide-stopband filter is then developed from the filter with the symmetrical λ/4 SIRs replaced by the asymmetrical ones. The asymmetrical λ/4 SIRs have their higher resonances frequencies isolated from the adjacent I/O SIRs and extend the enhanced filter an upper stopband limit beyond ten time the fundamental frequency. Also, the filter might possess a cross-coupling structure which introduces transmission zeros by the passband edges to improve the signal selectivity. The tapped-line feed is adopted in this circuit to create additional attenuation poles for improving the stopband rejection levels. Experiments are conducted to verify the circuit performance.

The cognitive radio technique promises to manage and allocate the scarce radio spectrum in the highly varying and disparate modern environments. This paper considers a cognitive radio scenario composed of two queues for the primary (licensed) users and cognitive (unlicensed) users. According to the Markov process, the system state equations are derived and an optimization model for the system is proposed. Next, the system performance is evaluated by calculations which show the rationality of our system model. Furthermore, discussions among different parameters for the system are presented based on the experimental results.

In this Letter, a robust system identification method is proposed for the generalized sidelobe canceller using dual microphones. The conventional transfer-function generalized sidelobe canceller employs the non-stationarity characteristics of the speech signal to estimate the relative transfer function and thus is difficult to apply when the noise is also non-stationary. Under the assumption of W-disjoint orthogonality between the speech and the non-stationary noise, the proposed algorithm finds the speech-dominant time-frequency bins of the input signal by inspecting the system output and the inter-microphone time delay. Only these bins are used to estimate the relative transfer function, so reliable estimates can be obtained under non-stationary noise conditions. The experimental results show that the proposed algorithm significantly improves the performance of the transfer-function generalized sidelobe canceller, while only sustaining a modest estimation error in adverse non-stationary noise environments.

A spectrum sharing method is proposed for systems that share the same frequency band or adjacent bands with services that have different priorities. The proposed method adaptively controls transmission power according to information provided by the high-priority system receivers. We give the theoretical capacities achieved by low-priority systems when the proposed method and a conventional method (constant transmit power) are applied. Numerical results confirm that the proposed method attains 1.5-2 times larger capacity than the conventional method.

In this paper, a new approach to channel order selection of single-input multiple-output (SIMO), finite impulse response (FIR) channels is proposed for blind channel estimation. The approach utilizes cross spectral density (CSD) of the channel outputs, and minimizes the distance between two CSD's, one calculated non-parametrically from the observed output data, and the other calculated from the blindly estimated channel parameters. The CSD criterion is numerically tested on randomly generated SIMO-FIR channels, and shown to be very effective compared to existing channel order selection methods especially under low SNR settings. Blind estimates of the channels with the selected channel order also show superiority of the CSD criterion.

A critical problem after a natural/manmade disaster is to provide immediate post-disaster communication links between the disaster victims and some overlay networks. This paper proposes a novel scheme that uses the surviving Mobile handSets (MS) as sensing nodes to form an auto-configured Hierarchical Cognitive Radio Network (H-CRN). The implementation of this H-CRN is explained through detailed problem scenario statement and step-by-step implementation of automatic identification of emergency situation by the MS nodes. An overview of the cross-layer framework used by the MS nodes is also presented. This novel scheme is tested through some hypothesis along with probability calculations for successful identification of emergency situation, formation of ad hoc group and Emergency Beacon Message (EBM) transmission.

In this paper, a spectral domain method named the SDF (Spectral Density Fitting) method for intra-die spatial correlation function extraction is presented. Based on theoretical analysis of random field, the spectral density, as the spectral domain counterpart of correlation function, is employed to estimate the parameters of the correlation function effectively in the spectral domain. Compared with the existing extraction algorithm in the original spatial domain, the SDF method can obtain the same quality of results in the spectral domain. In actual measurement process, the unavoidable measurement error with arbitrary frequency components would greatly confound the extraction results. A filtering technique is further developed to diminish the high frequency components of the measurement error and recover the data from noise contamination for parameter estimation. Experimental results have shown that the SDF method is practical and stable.

Two adaptive energy detectors are proposed for cognitive radio systems to detect the primary users. Unlike the conventional energy detector (CED) where a decision is made after receiving all samples, our detectors make a decision with the sequential arrival of samples. Hence, the sample size of the proposed detectors is adaptive. Simulation results show that for a desired performance, the average sample size of the proposed detectors is much less than that of the CED. Therefore, they are more agile than the CED.

To mitigate the asynchronous ICI (Inter-Cell Interference), SCM (Spatial Covariance Matrix) of the asynchronous ICI plus background noise should be accurately estimated for MIMO-OFDMA (Multiple-input Multiple-output-Orthogonal Frequency Division Multiple Access) system. Generally, it is assumed that the SCM of the asynchronous ICI plus background noise is estimated by using training symbols. However, it is difficult to measure the interference statistics for a long time and considering that training symbols are not appropriate for OFDMA system such as LTE (3GPP Long Term Evolution). Therefore, noise reduction method is required to improve the estimation accuracy. Although the conventional time-domain low-pass type weighting method can be effective for noise reduction, it causes significant estimation error due to the spectral leakage in practical OFDM system. Therefore, we propose a time-domain sinc type weighing method which can not only reduce noise effectively minimizing estimation error caused by the spectral leakage but also can be implemented using frequency-domain weighted moving average filter easily. We also consider the iterative CFR (Channel Frequency Response) and SCM estimation method which can effectively reduce the estimation error of both CFR and SCM, and improve the performance for LTE system. By using computer simulation, we show that the proposed method can provide up to 2.5 dB SIR (Signal to Interference Ratio) gain compared with the conventional method, and verify that the proposed method is attractive and suitable for implementation with stable operation.

The key issue in cognitive radio is to design a reliable spectrum sensing method that is able to detect the signal in the target channel as well as to recognize its type. In this paper, focusing on classifying different orthogonal frequency-division multiplexing (OFDM) signals, we propose a two-step detection and identification approach based on the analysis of the cyclic autocorrelation function. The key parameters to separate different OFDM signals are the subcarrier spacing and symbol duration. A symmetric peak detection method is adopted in the first step, while a pulse detection method is used to determine the symbol duration. Simulations validate the proposed method.

This Letter proposes an optimal gain filter for the perceptual acoustic echo suppressor. We designed an optimally-modified log-spectral amplitude estimation algorithm for the gain filter in order to achieve robust suppression of echo and noise. A new parameter including information about interferences (echo and noise) of single-talk duration is statistically analyzed, and then the speech absence probability and the a posteriori SNR are judiciously estimated to determine the optimal solution. The experiments show that the proposed gain filter attains a significantly improved reduction of echo and noise with less speech distortion.