In this letter, we focus on detecting a random primary user (PU) network for cognitive radio systems in a cooperative manner by using maximum likelihood (ML) detection. Different from traditional PU network models, the random PU network model in this letter considers the randomness in the PU network topology, and so is better suited for describing the infrastructure-less PU network such as an ad hoc network. Since the joint pdf required for the ML detection is hard to obtain in a closed form, we derive approximate ones from the Gaussian approximation. The performance of the proposed algorithm is comparable to the optimal one.

In this letter we propose a practical sensing-based opportunistic spectrum sharing scheme for cognitive radio (CR) downlink MIMO systems. Multi-antennas are exploited at the secondary transmitter to opportunistically access the primary spectrum and effectively achieve a balance between secondary throughput maximization and mitigation of interference probably caused to primary radio link. We first introduce a brief secondary frame structure, in which a sensing phase is exploited to estimate the effective interference channel. According to the sensing result and taking the interference caused by the primary link into account, we propose an enhanced signal-to-leakage-and-noise ratio (SLNR)-based precoding scheme for the secondary transmitter. Compared to conventional schemes where perfect knowledge of the channels over which the CR transmitter interferes with the primary receiver (PR) is assumed, our proposed scheme shows its superiority and simulation results validate this.

This paper investigates the use of cooperative spectrum sensing (CSS) to detect primary user (PU) signals during spectrum sharing between the PU and the secondary user (SU). In particular, we employ a variant of CSS (which achieves space diversity), called weighted gain combining CSS (W-CSS), which has the potential to achieve increased diversity gain and enhance detection performance. In a typical W-CSS system, the SU needs to obtain the PU signal power information in order to set the proper weight value. However, as it is hard for the SU to ascertain whether the PU is present or absent, this is difficult to obtain. To address this problem, a PU signal power estimation algorithm is introduced. In addition, we also analyze the statistics of the estimator and derive the detection probability of the W-CSS when the PU signal power estimation algorithm is applied. The analysis and related simulation results reveal that the detection probability of the proposed W-CSS under time-variant Rayleigh fading asymptotically approaches the detection probability in an additive white Gaussian noise channel as the number of antennas is increased. This also follows results from our Monte Carlo simulations, showing that multiple antenna elements could suppress the effect of Rayleigh fading. In short, the accuracy of the estimation algorithm is affected by channel variation (especially in the case of fast Rayleigh fading). Hence, to address this problem, we employ multiple antenna elements with a square-law combining energy detector in the W-CSS.

In this paper, a Spectrum-Aware Routing (SAR) protocol for cognitive radio ad hoc networks, (CRAHN), is proposed which is robust to primary user activity and node failures. The protocol allows nodes to collect spectrum information during a spectrum management interval followed by a transmission period. Cognitive users discover routes by joint channel and next hop selection (synchronization) in the transmission intervals. A restricted geographical routing approach is adopted to avoid performance degradation specially due to routing overhead. We also add spectrum mobility capabilities to routes in our proposed method to provide robustness to primary user activity. SAR protocol performance is investigated through simulations of different scenarios and is compared with the most similar work, CAODV protocol. The results indicate that SAR can achieve significant reduction in control overhead as well as improved throughput.

The circuit switching device by the electrical contact needs the high reliability and long lifetime. The very important factor for the high reliability, long lifetime and electromagnetic noise of the electrical contact is to suppress the duration and electromagnetic noise of arc discharge. Usually, the suppression of arc duration method is applying the external magnetic field. But, this method was not able to suppress the metallic arc duration and increased the voltage fluctuation at arc duration. Therefore, the new method for suppressing the duration and noise for electrical contact is expected. In this paper, a new method for suppressing duration and EM noise of arc discharge by applying housing pressure is proposed. To investigate the availability of proposed method, the measurement and some considerations on arc duration, voltage-fluctuation and current noise up to GHz frequency band generated by breaking contact in the applied pressure relay housing are reported. Firstly, voltage waveform and duration of the arc are measured. The effects of the pressure in the relay housing on the duration of the metallic and gaseous phase arcs are discussed. Secondary, voltage fluctuation, the spectrogram of contact voltage and current noise up to GHz frequency band are discussed. In the results, the proposed method with applying pressure makes shorter both durations of metallic and gaseous phases. The shorter duration of metallic phase is an advantage of the proposed method beyond the applying external magnetic field. As the housing pressure is increase, the voltage fluctuation and current noise becomes smalls. The proposed method can suppress the voltage fluctuation as well as arc duration. Consequently, the proposed method is on of the good solution to suppress the duration and electromagnetic noise of the arc discharge from electrical contact and result of this study indicates the basic considerations necessary to ensure good lifetime and EMC designs for electrical contacts.

In this letter, we propose a dissimilarity metric (DM) to measure the deviation of a cognitive radio from the network in terms of local sensing reports. Utilizing the probability mass function of the DM, we present a dissimilarity-based attacker detection algorithm to distinguish Byzantine attackers from honest users. The proposed algorithm is able to identify the attackers without a priori information of the attacking styles and is robust against both independent and dependent attacks.

A novel long-term sub-band entropy (LT-SubEntropy) measure, which uses improved long-term spectral analysis and sub-band entropy, is proposed for voice activity detection (VAD). Based on the measure, we can accurately exploit the inherent nature of the formant structure on speech spectrogram (the well-known as voiceprint). Results show that the proposed VAD is superior to existing standard VAD methods at low SNR levels, especially at variable-level noise.

At the stage of software debugging, the effective interaction between software debugging engineers and fault localization techniques can greatly improve fault localization performance. However, most fault localization approaches usually ignore this interaction and merely utilize the information from testing. Due to different goals of testing and fault localization, the lack of interaction may lead to the issue of information inadequacy, which can substantially degrade fault localization performance. In addition, human work is costly and error-prone. It is vital to study and simulate the pattern of debugging engineers as they apply their knowledge and experience to this interaction to promote fault localization effectiveness and reduce their workload. Thus this paper proposes an effective fault localization approach to simulate this interaction via feedback. Based on results obtained from fault localization techniques, this approach utilizes test data generation techniques to automatically produce feedback for interacting with these fault localization techniques, and then iterate this process to improve fault localization performance until a specific stopping condition is satisfied. Experiments on two standard benchmarks demonstrate the significant improvement of our approach over a promising fault localization technique, namely the spectrum-based fault localization technique.

A price-based spectrum investment and pricing scheme in cooperative cognitive radio networks is presented to use wireless resource more efficiently in technical and economic aspects. We analyze the impact of cooperative communications and the relationship between spectrum hole cost and leasing cost in the optimal decision of SAP.

The present paper proposes a new method for constructing polyphase asymmetric zero-correlation zone (A-ZCZ) sequence sets. The proposed method can generate A-ZCZ sequence sets that cannot be obtained from methods proposed by other researchers and is a generalized version of our previously proposed method. An A-ZCZ sequence set can be regarded as a ZCZ sequence set. The newly obtained A-ZCZ sequence sets include quasi-optimal ZCZ sequence sets of which the zero-cross-correlation zone (ZCCZ) length between different sequence subsets is larger than the mathematical upper bound of conventional ZCZ sequence sets. A new method for extending the A-ZCZ sequence sets is also presented in the present paper.

The power of laser radar received echoes varies over a large range due to many factors such as target distance, size, reflection ratio, etc, which leads to the difficulty of decoding codes from the received noise buried signals for spectrum code modulated laser radar. Firstly, a pseudo-random noise (PN) code modulated laser radar model is given, and the problem to be addressed is discussed. Then, a novel method based on Inter Symbol Interference (ISI) is proposed for resolving the problem, providing that only Additive White Gaussian Noise (AWGN) exists. The ISI effect is introduced by using a high pass filter (HPF). The results show that ISI improves laser radar receiver decoding ratio, thus the peak of the correlation function of decoded codes and modulation codes. Finally, the effect of proposed method is verified by a simple experiment.

We propose a primary traffic based multihop relaying algorithm with cooperative transmission (PTBMR-CT). It enlarges the hop transmission distances to reduce the number of cognitive relays on the route from the cognitive source (CS) to the cognitive destination (CD). In each hop, from the cognitive nodes in a specified area depending on whether the primary source (PS) transmits data to the primary destination (PD), the cognitive node that is farthest away from the cognitive relay that sends data is selected as the other one that receives data. However, when the PS is transmitting data to the PD, from the cognitive nodes in a specified area, another cognitive node is also selected and prepared to be the cognitive relay that receives data of cooperative transmission. Cooperative transmission is performed if the PS is still transmitting data to the PD when the cognitive relay that receives data of the next hop transmission is being searched. Simulation results show that the average number of cognitive relays is reduced by PTBMR-CT compared to conventional primary traffic based farthest neighbor relaying (PTBFNR), and PTBMR-CT outperforms conventional PTBFNR in terms of the average end-to-end reliability, the average end-to-end throughput, the average required transmission power of transmitting data from the CS to the CD, and the average end-to-end transmission latency.

A flexible and computationally efficient method for spectral analysis of sinusoidal signals using the Basis Pursuit De-Noising (BPDN) is proposed. This method estimates a slotted Auto-Correlation Function (ACF) and computes the spectrum as the sparse representation of the ACF in a dictionary of cosine functions. Simulation results illustrate flexibility and effectiveness of the proposed method.

A sensing efficiency optimization scheme based on two-stage spectrum sensing that maximizes the achievable throughput of the secondary network and minimizes the average sensing time is proposed in this paper. A selection method for the threshold is proposed and proved to ensure optimal sensing performance. An effective iterative algorithm is presented to solve the constructed efficiency optimization problem.

Existing pose estimation algorithms suffer from either low performance or heavy computation cost. In this letter, we present an approach to improve the attractive algorithm called Orthogonal Iteration. A new form of fundamental equations is derived which reduces the computation cost significantly. And paraperspective camera model is used instead of weak perspective camera model during initialization which improves the stability. Experiment results validate the accuracy and stability of the proposed algorithm and show that its computational complexity is favorably compare to the O(n) non-iterative algorithm.

A differential pair of convergent and divergent lenses with adjustable lens spacing (“differential lens”) was devised as a varifocal lens and was successfully integrated into an object-space telecentric lens to build a focus mechanism with constant magnification. This integration was done by placing the front principal point of the varifocal lens at the rear focal point of the telecentric lens within a practical tolerance of positioning. Although the constant-magnification focus mechanism is a parallel projection system, a system for perfect perspective projection imaging without shifting the projection center during focusing could be built simply by properly setting this focus mechanism between an image-taking lens with image-space telecentricity and an image sensor. The focus resolution experimentally obtained was 0.92 µm (σ) for the parallel projection system with a depth range of 1.0 mm and this was 0.25 mm (σ) for the perspective projection system with a range from 120 to 350 mm within a desktop space. A marginal image resolution of 100 lp/mm was obtained with optical distortion of less than 0.2% in the parallel projection system. The differential lens could work up to 55 Hz for a sinusoidal change in lens spacing with a peak-to-valley amplitude of 425 µm when a tiny divergent lens that was plano-concave was translated by a piezoelectric positioner. Therefore, images that were entirely in focus were generated at a frame rate of 30 Hz for an object moving at a speed of around 150 mm/s in depth within the desk top space. Thus, three-dimensional (3-D) imaging that provided 3-D resolution based on fast focusing was accomplished in both microscopic and macroscopic spaces.

With the wide usage of multispectral images, a fast efficient multidimensional clustering method becomes not only meaningful but also necessary. In general, to speed up the multidimensional images' analysis, a multidimensional feature vector should be transformed into a lower dimensional space. The Hilbert curve is a continuous one-to-one mapping from N-dimensional space to one-dimensional space, and can preserves neighborhood as much as possible. However, because the Hilbert curve is generated by a recurve division process, 'Boundary Effects' will happen, which means data that are close in N-dimensional space may not be close in one-dimensional Hilbert order. In this paper, a new efficient approach based on the space-filling curves is proposed for classifying multispectral satellite images. In order to remove 'Boundary Effects' of the Hilbert curve, multiple Hilbert curves, z curves, and the Pseudo-Hilbert curve are used jointly. The proposed method extracts category clusters from one-dimensional data without computing any distance in N-dimensional space. Furthermore, multispectral images can be analyzed hierarchically from coarse data distribution to fine data distribution in accordance with different application. The experimental results performed on LANDSAT data have demonstrated that the proposed method is efficient to manage the multispectral images and can be applied easily.

To improve the robustness and transparency of spread spectrum (SS) based watermarking, this paper presents a new informed embedding strategy, which we call selective host-interference cancellation. We show that part of the host-interference in SS-based watermarking is beneficial to blind watermark extraction or detection, and can be utilized rather than removed. Utilizing this positive effect of the host itself can improve the watermark robustness without significantly sacrificing the media fidelity. The proposed strategy is realized by selectively applying improved SS (ISS) modulation to traditional SS watermarking. Theoretically, the error probability of the new method under additive white Gaussian noise attacks is several orders of magnitude lower than that of ISS for high signal-to-watermark ratios, and the required minimum watermark power is reduced by 3dB. Experiments were conducted on real audio signals, and the results show that our scheme is robust against most of common attacks even in high-transparency or high-payload applications.

In this letter, we analyze the influence of motion and out-of-focus blur on both frequency spectrum and cepstrum of an iris image. Based on their characteristics, we define two new discriminative blur features represented by Energy Spectral Density Distribution (ESDD) and Singular Cepstrum Histogram (SCH). To merge the two features for blur detection, a merging kernel which is a linear combination of two kernels is proposed when employing Support Vector Machine. Extensive experiments demonstrate the validity of our method by showing the improved blur detection performance on both synthetic and real datasets.

This paper describes a blind watermarking scheme through cyclic signal processing. Due to various rapid networks, there is a growing demand of copyright protection for multimedia data. As efficient watermarking of images, there exist two major approaches: a quantization-based method and a correlation-based method. In this paper, we proposes a correlation-based watermarking technique of three-dimensional (3-D) polygonal models using the fast Fourier transforms (FFTs). For generating a watermark with desirable properties, similar to a pseudonoise signal, an impulse signal on a two-dimensional (2-D) space is spread through the FFT, the multiplication of a complex sinusoid signal, and the inverse FFT. This watermark, i.e., spread impulse signal, in a transform domain is converted to a spatial domain by an inverse wavelet transform, and embedded into 3-D data aligned by the principle component analysis (PCA). In the detection procedure, after realigning the watermarked mesh model through the PCA, we map the 3-D data on the 2-D space via block segmentation and averaging operation. The 2-D data are processed by the inverse system, i.e., the FFT, the division of the complex sinusoid signal, and the inverse FFT. From the resulting 2-D signal, we detect the position of the maximum value as a signature. For 3-D bunny models, detection rates and information capacity are shown to evaluate the performance of the proposed method.