In the recently developed Flexible Wireless System (FWS), the same platform needs to deal with different wireless systems. This increases nonlinear distortion in its wideband power amplifier (PA) because the PA needs to concurrently amplify multi-band signals. By taking higher harmonics as well as inter- and cross-modulation distortion into consideration, we have developed a method to analytically evaluate the adjacent channel leakage power ratio (ACPR) and error vector magnitude (EVM) on the basis of the PA's nonlinear characteristics. We devise a novel method for modeling the PA amplifying dual-band signals. The method makes it possible to model it merely by performing a one-tone test, making use of the Volterra series expansion and the general Wiener model. We then use the Mehler formula to derive the closed-form expressions of the PA's output power spectral density (PSD), ACPR, and EVM. The derivations are based on the assumption that the transmitted signals are complex Gaussian distributed in orthogonal frequency division multiplexing (OFDM) transmission systems. We validate the method by comparing measurement and simulation results and confirm it can appropriately predict the ACPR and EVM performance of the nonlinear PA output with OFDM inputs. In short, the method enables correct modeling of a wideband PA that amplifies dual-band signals merely by conducting a one-tone test.

This letter introduces innovative VAD based on horizontal spectral entropy with long-span of time (HSELT) feature sets to improve mobile ASR performance in low signal-to-noise ratio (SNR) conditions. Since the signal characteristics of nonstationary noise change with time, we need long-term information of the noisy speech signal to define a more robust decision rule yielding high accuracy. We find that HSELT measures can horizontally enhance the transition between speech and non-speech segments. Based on this finding, we use the HSELT measures to achieve high accuracy for detecting speech signal form various stationary and nonstationary noises.

Spectrum sensing is one of the main functions in cognitive radio networks. To improve the sensing performance and increase spectrum efficiency, a number of cooperative spectrum sensing methods have been proposed. However, most of these methods focused on a single-channel environment. In this letter, we present a novel cooperative spectrum sensing method based on cooperator selection in a multi-channel cognitive radio network. Using reinforcement learning, a cognitive radio user can select reliable and robust cooperators, without any a priori knowledge. Using the proposed method, a cognitive radio user can achieve better sensing capability and overcome performance degradation problems due to malicious users or erratic user behavior. Numerical results show that the proposed method can achieve excellent performance.

Spectral subtraction (SS) is an additive noise removal method which is derived in an extensive framework. In spectral subtraction, it is assumed that speech and noise spectra follow Gaussian distributions and are independent with each other. Hence, noisy speech also follows a Gaussian distribution. Spectral subtraction formula is obtained by maximizing the likelihood of noisy speech distribution with respect to its variance. However, it is well known that noisy speech observed in real situations often follows a heavy-tailed distribution, not a Gaussian distribution. In this paper, we introduce a q-Gaussian distribution in the non-extensive statistics to represent the distribution of noisy speech and derive a new spectral subtraction method based on it. We found that the q-Gaussian distribution fits the noisy speech distribution better than the Gaussian distribution does. Our speech recognition experiments using the Aurora-2 database showed that the proposed method, q-spectral subtraction (q-SS), outperformed the conventional SS method.

We propose an accurate and scalable solution to the perspective-n-point problem, referred to as ASPnP. Our main idea is to estimate the orientation and position parameters by directly minimizing a properly defined algebraic error. By using a novel quaternion representation of the rotation, our solution is immune to any parametrization degeneracy. To obtain the global optimum, we use the Grobner basis technique to solve the polynomial system derived from the first-order optimality condition. The main advantages of our proposed solution lie in accuracy and scalability. Extensive experiment results, with both synthetic and real data, demonstrate that our proposed solution has better accuracy than the state-of-the-art noniterative solutions. More importantly, by exploiting vectorization operations, the computational cost of our ASPnP solution is almost constant, independent of the number of point correspondences n in the wide range from 4 to 1000. In our experiment settings, the ASPnP solution takes about 4 milliseconds, thus best suited for real-time applications with a drastically varying number of 3D-to-2D point correspondences.

In cognitive radio networks, the primary user (PU) can lease a fraction of its licensed spectrum to the secondary users (SUs) in exchange for their cooperative transmission if it has a minimum transmission rate requirement and is experiencing a bad channel condition. However, due to the selfish nature of the SUs, they may not cooperate to meet the PU's Quality of Service (QoS) requirement. On the other hand, the SUs may not exploit efficiently the benefit from cooperation if they compete with each other and collaborate with the PU independently. Therefore, when SUs belong to the same organization and can work as a group, how to stimulate them to cooperate with the PU and thus guarantee the PU's QoS requirement, and how to coordinate the usage of rewarded spectrum among these SUs after cooperation are critical challenges. In this paper, we propose a two-level bargaining framework to address the aforementioned problems. In the proposed framework, the interactions between the PU and the SUs are modeled as the upper level bargaining game while the lower level bargaining game is used to formulate the SUs' decision making process on spectrum sharing. We analyze the optimal actions of the users and derive the theoretic results for the one-PU one-SU scenario. To find the solutions for the one-PU multi-SU scenario, we put forward a revised numerical searching algorithm and prove its convergence. Finally, we demonstrate the effectiveness and efficiency of the proposed scheme through simulations.

In order to evaluate the goodness of frequency hopping (FH) sequence design, the periodic Hamming correlation function is used as an important measure. But aperiodic Hamming correlation of FH sequences matters in real applications, while it received little attraction in the literature compared with periodic Hamming correlation. In this paper, the new aperiodic Hamming correlation lower bounds for FH sequences, with respect to the size of the frequency slot set, the sequence length, the family size, the maximum aperiodic Hamming autocorrelation and the maximum aperiodic Hamming crosscorrelation are established. The new aperiodic bounds are tighter than the Peng-Fan bounds. In addition, the new bounds include the second powers of the maximum aperiodic Hamming autocorrelation and the maximum aperiodic Hamming crosscorrelation but the Peng-Fan bounds do not include them. For the given sequence length, the family size and the frequency slot set size, the values of the maximum aperiodic Hamming autocorrelation and the maximum aperiodic Hamming crosscorrelation are inside of an ellipse which is given by the new aperiodic bounds.

A wireless emergency communication network with a fixed allocation of spectrum resources cannot meet the tremendous demand for spectrum access when a crisis occurs. It is necessary to develop an effective spectrum access scheme to improve the performance of emergency communication systems. In this paper, we study a new emergency communication system combines cognitive radio technology and an emergency communication network. Emergency users can utility resources in a general network when traffic becomes congested in an emergency network. Non-reciprocal spectrum access scheme (NRA) and reciprocal spectrum access scheme (RA) for two heterogeneous cognitive networks, namely emergency network and general network are proposed to compare with traditional spectrum access scheme (TA). User behavior with each scheme is modeled by continuous-time Markov chains. Moreover, the blocking and dropping probabilities of users in two heterogeneous cognitive networks are derived as the performance metrics. In addition, the throughput and the spectrum utilization rate of the system are evaluated. Finally, we compare the performance of three dynamic spectrum access schemes. The simulation results show that the RA scheme is an effective scheme to enhance the performance of emergency systems.

An improved spectrum sensing method based on PN autocorrelation (PNAC) for Digital Terrestrial Television Multimedia Broadcasting (DTMB) system is proposed in this paper. The low bound of miss-detection probability and the decision threshold for a given false alarm probability are studied. The performances of proposed method and existing methods are compared through computer simulations under both non-time dispersive channel and time dispersive channel. Simulation results show that the proposed method has better performance than the original PNAC-based method, and is more robust to both carrier frequency offset (CFO) and time dispersion of the channel than the existing method based on PN cross-correlation (PNCC).

A technique that enables a SSCG to fine-tune an output signal frequency and a spread ratio is presented. Proposed SSCG achieves the output signal frequency from 1.2 GHz to 3.0 GHz and the spread ratio from 0 to 30000 ppm. The fine-tuning technique achieves 30 ppm adjustment of the output signal frequency and 200 ppm adjustment of the spread ratio. This technique is achieved by controlling a triangular modulation signal characteristics generated by a proposed digital controlled wave generator. A proposed multi-modulus divider can have a divide ratio of 4/5 and 8/9. This SSCG has been fabricated in a 0.13-µm CMOS process. The output signal frequency-range and the spread ratio are achieved fluently from 0.1 to 3.0 GHz and from 0 to 30000 ppm, respectively. EMI noise is suppressed at less than 17.1 dB at the output signal frequency of 3.0 GHz and spread ratio of 30000 ppm.

Dynamic spectrum leasing (DSL) is regarded as a promising dynamic spectrum sharing (DSS) scheme both to improve the spectrum revenue of primary users (PUs) and to guarantee the QoS of secondary users (SUs). A pricing-based DSL termed PBDSL is formulated as a Stackelberg DSL game model, where PUs as players entering the interacting game with multiple SUs. The strategic design contains both optimal spectrum pricing schemes (including unit spectrum/interference price and interference sensitivity distributed adjustments) of PUs for the specific shared/leased spectrum and optimal transmission strategies (e.g., transmit power and bandwidth) of SUs. To capture two types of competition relationships among multiple SUs and between SUs and PUs, we investigate two intra-game models of multiple PUs and SUs, respectively, which interact with each other to constitute the final Stackelberg DSL game. The existence and uniqueness of Stackelberg equilibrium solution (SES) are analyzed and proved for presented games, based on which a joint multi-stage PBDSL algorithm is presented to approximate the optimal equilibrium strategies. Numerical results demonstrate the convergence property of the interactive decision-making process, and verify the effectiveness of the proposed algorithm, in a comparison with the Nash equilibrium solution (NES)-based approach.

In this article, we propose a method to reduce the impact of primary traffic on spectrum sensing performance. In practice, the sensing performance is degraded by noise-only sample in the spectrum sensing time. Therefore, we employ a time of primary user (PU) signal arrival detector in order to remove the noise-only portion. Then, we employ equal-weight-based energy detection (EWED) to provide the detection decision. The analysis and simulation results show that there exists an optimal early time of arrival (ToA) false alarm which provides better performance compared to the use of a single EWED scheme.

As means to control interface reactions between HfO2 and Ge(100), chemical vapor deposition (CVD) of ultrathin Ta-rich oxide using Tri (tert-butoxy) (tert-butylimido) tantalum (Ta-TTT) on chemically-cleaned Ge(100) has been conducted prior to atomic-layer controlled CVD of HfO2 using tetrakis (ethylmethylamino) hafnium (TEMA-Hf) and O3. The XPS analysis of chemical bonding features of the samples after the post deposition N2 annealing at 300 confirms the formation of TaGexOy and the suppression of the interfacial GeO2 layer growth. The energy band structure of HfO2/TaGexOy/Ge was determined by the combination of the energy bandgaps of HfO2 and TaGexOy measured from energy loss signals of O 1s photoelectrons and from optical absorption spectra and the valence band offsets at each interface measured from valence band spectra. From the capacitance-voltage (C-V) curves of Pt-gate MIS capacitors with different HfO2 thicknesses, the thickness reduction of TaGexOy with a relative dielectric constant of 9 is a key to obtain an equivalent SiO2 thickness (EOT) below 0.7 nm.

An SiO2/Si-cap/Si0.55Ge0.45 heterostructure was fabricated on p-type Si(100) and strained silicon on insulator (SOI) substrates by low pressure chemical vapor deposition (LPCVD) and subsequent thermal oxidation in an O2 + H2 gas mixture. Chemical bonding features and valence band offsets in the heterostructures were evaluated by using high-resolution x-ray photoelectron spectroscopy (XPS) measurements and thinning the stack layers with a wet chemical solution.

Automatic modulation classification (AMC) is an important function of radio surveillance systems in order to identify unknown signals. Many previous works on AMC have utilized signal cyclostationarity, particularly spectral correlation density (SCD), but many of them fail to address several implementation issues, such as the assumption of perfect knowledge of the symbol rate. In this paper, we discuss several practical issues, e.g. cyclic frequency mismatch, which may affect the SCD, and propose compensation techniques to overcome those issues. We also propose a novel feature extraction technique from the SCD, which utilizes the SCD of not only the original received signal, but also the squared received signal. A symbol rate estimation technique which complements the feature extraction is also proposed. Finally, the classification performance of the system is evaluated through Monte Carlo simulations using a wide variety of modulated signals, and simulation results show that the proposed technique can estimate the symbol rate and classify modulation with a probability of above 0.9 down to SNRs of 5 dB.

We have fabricated Pt/Si-rich oxide (SiOx)/TiN stacked MIM diodes and studied an impact of the structural asymmetry on their resistive switching characteristics. XPS analyses show that a TiON interfacial layer was formed during the SiOx deposition on TiN by RF-sputtering in an Ar + O2 gas mixture. After the fabrication of Pt top electrodes on the SiOx layer, and followed by an electro-forming process, distinct bi-polar type resistive switching was confirmed. For the resistive switching from high to low resistance states so called SET process, there is no need to set the current compliance. Considering higher dielectric constant of TiON than SiOx, the interfacial TiON layer can contribute to regulate the current flow through the diode. The clockwise resistive switching, in which the reduction and oxidation (Red-Ox) reactions can occur near the TiN bottom electrode, shows lower RESET voltages and better switching endurance than the counter-clockwise switching where the Red-Ox reaction can take place near the top Pt electrode. The result implies a good repeatable nature of Red-Ox reactions at the interface between SiOx and TiON/TiN in consideration of relatively high diffusibility of oxygen atoms through Pt.

A novel and energy-efficient algorithm with Quality-of-Service (QoS) guarantee is proposed for cooperative spectrum sensing (CSS) with soft information fusion and hard information fusion. By weighting the sensing performance and the consumption of system resources in a utility function that is maximized with respect to the number of secondary users (SUs), it is shown that the optimal number of SUs is related to the price of these QoS requirements.

Identification of early aspects is the critical problem in aspect-oriented requirement engineering. But the representation of crosscutting concerns is various, which makes the identification difficult. To address the problem, this paper proposes the AspectQuery method based on goal model. We analyze four kinds of goal decomposition models, then summarize the main factors about identification of crosscutting concerns and conclude the identification rules based on a goal model. A goal is crosscutting concern when it satisfies one of the following conditions: i) the goal is contributed to realize one soft-goal; ii) parent goal of the goal is candidate crosscutting concern; iii) the goal has at least two parent goals. AspectQuery includes four steps: building the goal model, transforming the goal model, identifying the crosscutting concerns by identification rules, and composing the crosscutting concerns with the goals affected by them. We illustrate the AspectQuery method through a case study (a ticket booking management system). The results show the effectiveness of AspectQuery in identifying crosscutting concerns in the requirement phase.

Time domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) has higher spectral efficiency than the standard cyclic prefix OFDM (CP-OFDM) OFDM by replacing the random CP with the known training sequence (TS), which could be also used for synchronization and channel estimation. However, TDS-OFDM requires suffers from performance loss over fading channels due to the iterative interference cancellation has to be used to remove the mutual interferences between the TS and the useful data. To solve this problem, the novel TS based OFDM transmission scheme, referred to as the unified time-frequency OFDM (UTF-OFDM), is proposed in which the time-domain TS and the frequency-domain pilots are carefully designed to naturally avoid the interference from the TS to the data without any reconstruction. The proposed UTF-OFDM based flexible frame structure supports effective channel estimation and reliable channel equalization, while imposing a significantly lower complexity than the TDS-OFDM system at the cost of a slightly reduced spectral efficiency. Simulation results demonstrate that the proposed UTF-OFDM substantially outperforms the existing TDS-OFDM, in terms of the system's achievable bit error rate.

During the production of speech signals, the vowel onset point is an important event containing important information for many speech processing tasks, such as consonant-vowel unit recognition and speech end-points detection. In order to realize accurate automatic detection of vowel onset points, this paper proposes a reliable method using the energy characteristics of homomorphic filtered spectral peaks. The homomorphic filtering helps to separate the slowly varying vocal tract system characteristics from the rapidly fluctuating excitation characteristics in the cepstral domain. The distinct vocal tract shape related to vowels is obtained and the peaks in the estimated vocal tract spectrum provide accurate and stable information for VOP detection. Performance of the proposed method is compared with the existing method which uses the combination of evidence from the excitation source, spectral peaks, and modulation spectrum energies. The detection rate with different time resolutions, together with the missing rate and spurious rate, are used for comprehensive evaluation of the performance on continuous speech taken from the TIMIT database. The detection accuracy of the proposed method is 74.14% for ±10 ms resolution and it increases to 96.33% for ±40 ms resolution with 3.67% missing error and 4.14% spurious error, much better than the results obtained by the combined approach at each specified time resolution, especially the higher resolutions of ±10±30 ms. In the cases of speech corrupted by white noise, pink noise and f-16 noise, the proposed method also shows significant improvement in the performance compared with the existing method.