Copies Of Signal Research Articles

Research on Satellite Concealment Communication Method Based on WFRFT

Satellite signal concealment technology protects the safety of signal waveform by using signals with high power and specific parameter characteristics. However, with the development of modulation recognition and Successive Interference Cancellation (SIC) technology, the cover signal using conventional modulation methods can be cracked by non-cooperative receivers. In order to meet the safety communication requirements of portable satellite communication terminals, the idea of using local signal copies for self-interference cancellation in Paired Carrier Multiple Access (PCMA) is used for reference. This paper proposes a satellite secure communication method suitable for portable terminals, and introduces Weighted-type FRactional Fourier Transform (WFRFT) as a modulation method to mask the signal, thereby increase the difficulty of non-cooperative parties in identifying and demodulating the cover signal. Simulation shows that the method proposed in this paper improves the security of signal transmission, and the loss of the system's bit error rate is within an acceptable range after signal separation, which is suitable for practical use.

MultiSense

In recent years, we have seen efforts made to simultaneously monitor the respiration of multiple persons based on the channel state information (CSI) retrieved from commodity WiFi devices. Existing approaches mainly rely on spectral analysis of the CSI amplitude to obtain respiration rate information, leading to multiple limitations: (1) spectral analysis works when multiple persons exhibit dramatically different respiration rates, however, it fails to resolve similar rates; (2) spectral analysis can only obtain the average respiration rate over a period of time, and it is unable to capture the detailed rate change over time; (3) they fail to sense the respiration when a target is located at the "blind spots" even the target is close to the sensing devices. To overcome these limitations, we propose MultiSense, the first WiFi-based system that can robustly and continuously sense the detailed respiration patterns of multiple persons even they have very similar respiration rates and are physically closely located. The key insight of our solution is that the commodity WiFi hardware nowadays is usually equipped with multiple antennas. Thus, each individual antenna can receive a different mix copy of signals reflected from multiple persons. We successfully prove that the reflected signals are linearly mixed at each antenna and propose to model the multi-person respiration sensing as a blind source separation (BSS) problem. Then, we solve it using independent component analysis (ICA) to separate the mixed signal and obtain the reparation information of each person. Extensive experiments show that with only one pair of transceivers, each equipped with three antennas, MultiSense is able to accurately monitor respiration even in the presence of four persons, with the mean absolute respiration rate error of 0.73 bpm (breaths per minute).

Output Homogenization and Synchronization of Heterogeneous Nonlinear Multiagent Networks

In this article, we are concerned with the output synchronization of a group of heterogeneous agents with nonlinear dynamics. It is shown that via dynamic coupling, the output synchronization problem is transformed into a family of output homogenization and internal-model-based synchronization problems. In contrast to conventional approaches, the adopted approach does not rely on the generation of a specific reference trajectory, to be tracked by all agents. Based on this premise, we propose a distributed state-feedback protocol driving all the heterogeneous multiagent individual systems onto a copy of a virtual reference signal. Invoking the results from the theory of output regulation and cooperative control, the state-feedback controller synthesis is conducted to achieve the output synchronization of heterogeneous multiagent networks. Immediate extensions of the obtained results to observer-based control are also discussed. The effectiveness of the proposed output synchronization algorithm is verified through theoretical analysis and case studies.

Detection of replay spoof speech using teager energy feature cues

The vulnerability of Automatic Speaker Verification (ASV) systems to spoofing or presentation attacks is still an open security issue. In this context, replay spoofing attacks pose a great threat to an ASV system since they can be easily performed (using a playback device, and without needing any technical skill). In this paper, we analyze replay speech signals in terms of reverberation that may occur during recording of the speech signal. Such reverberation introduces delay and changes in amplitude, producing close copies of speech signals, which significantly influences the replay components. To that effect, we propose to exploit the capabilities of the Teager Energy Operator (TEO) to compute a running estimate of subband energies for replay vs. genuine signals. We have used a linearly-spaced Gabor filterbank to obtain a narrowband filtered signal. The TEO has the ability to track the instantaneous changes of a signal. Experiments are performed on the ASVspoof 2017 Challenge version 2.0 database using a Gaussian Mixture Model (GMM) as pattern classifier. Furthermore, we compared our results with state-of-the-art feature sets, namely, Constant Q Cepstral Coefficients (CQCC), Linear Frequency Cepstral Coefficients (LFCC), Mel Frequency Cepstral Coefficients (MFCC), and used their score-level fusion with the proposed feature sets, i.e., Teager Energy Cepstral Coefficients (TECC), in order to obtain possible complementary information that further reduces the Equal Error Rate (EER). Relatively low EERs are obtained with score-level fusion of CQCC, MFCC, LFCC, and TECC feature sets, resulted in 6.68% and 10.45% on development and evaluation sets, respectively. Moreover, for the evaluation dataset, we also studied the performance of the TECC feature set on different Replay Configurations (RC), namely, for acoustic environments, playback, and recording devices. For all the levels of threat conditions (i.e., low, medium, and high-level) to an ASV system, the proposed feature set performed better compared to existing state-of-the-art feature sets. In addition to the ASVspoof 2017 Challenge database, we also performed experiments on other spoofing databases, namely, the ASVspoof 2015 Challenge, BTAS 2016, and ASVspoof 2019 Challenge databases. For all the spoofing databases used in this study, the proposed TECC feature set perform significantly better than the other feature sets.

Passive optical phase noise cancellation.

We report on the realization of an optical phase noise cancellation technique by passively embedding the optical phase noise information into a radio frequency signal and creating a copy of the optical frequency signal, which is pre-corrected by the amount of phase noise introduced by optical phase perturbations. Neither phase discrimination nor an active servo controller is required due to the open-loop design, mitigating some technical problems, such as the limited compensation speed and finite phase/timing jitter, in conventional phase noise cancellation. We experimentally demonstrate that this technique maintains the same delay-limited bandwidth and phase noise suppression capability as in conventional techniques, but significantly shortens the response speed and phase recovery time. Passive decoupling optical phase perturbation represents a powerful technique in the domains of optical frequency standard comparisons and tools for future optical atomic clocks, which are now under investigation for a potential redefinition of the International Time Scale.

Macrodiversity Reception with Distributed Hard-Decision Receivers for Maritime Wireless Sensor Networks.

Maritime wireless sensor networks are considered to be the primary means of monitoring methods in the marine environment. The transmission between sensor node and sink node in maritime wireless sensor networks is usually unreliable due to the harsh propagation environment. To extend the transmission range or to enhance the transmission reliability between sensor nodes and sink node, we propose a macrodiversity reception scheme in the sink node equipped with distributed multiple hard-decision receivers. Multiple receivers are divided into several clusters and placed at different locations to receive different signal copies suffering from different fadings. Furthermore, a cascaded combining strategy based on hard-decision information is used to reduce the overall complexity of receiving side. The experimental results in the ocean scenarios show that the macrodiversity reception scheme with two antenna clusters has a transmission gain of 3–4 dB compared with the single antenna reception when the package loss rate is . The study casts a new method for reliable transmission in maritime wireless sensor networks using commercial transceivers which can only output hard-decision results.

Corollary Discharge Versus Efference Copy: Distinct Neural Signals in Speech Preparation Differentially Modulate Auditory Responses.

Actions influence sensory processing in a complex way to shape behavior. For example, during actions, a copy of motor signals-termed "corollary discharge" (CD) or "efference copy" (EC)-can be transmitted to sensory regions and modulate perception. However, the sole inhibitory function of the motor copies is challenged by mixed empirical observations as well as multifaceted computational demands for behaviors. We hypothesized that the content in the motor signals available at distinct stages of actions determined the nature of signals (CD vs. EC) and constrained their modulatory functions on perceptual processing. We tested this hypothesis using speech in which we could precisely control and quantify the course of action. In three electroencephalography (EEG) experiments using a novel delayed articulation paradigm, we found that preparation without linguistic contents suppressed auditory responses to all speech sounds, whereas preparing to speak a syllable selectively enhanced the auditory responses to the prepared syllable. A computational model demonstrated that a bifurcation of motor signals could be a potential algorithm and neural implementation to achieve the distinct functions in the motor-to-sensory transformation. These results suggest that distinct motor signals are generated in the motor-to-sensory transformation and integrated with sensory input to modulate perception.

Improvement for performance radio frequency in wireless communication based on impulse signal

<p><span>This research presents the improved performance of mobile wireless communication channel is based on non-line of sight because the mobile propagation channel is very hard to work with direct path between the transmitter and mobile receiver because of city-based area has objects such as rise building, trees, surround structures, and other objects. The mobile wireless spread radio channels have radio propagation mechanisms as a reflection, diffraction, and scattering effect on radio signal as lessening, </span>and distortion or spread time. The most important thing to make real is that the wireless channel is a multipath radio channel. Multipath copies of the same signal with distinct amplitudes, stages and delay times for all multipaths between the transmitter and the receiver. The multipath fading is defined by its impulse response, which includes the facts about the relative time of the recipient's arrival of various indices of multipath additives. The impulse response expresses great characteristics in the time domain such the large bandwidth frequencies and the amplitude output only the value impulse response δ(t) equal to one when the value of time t=0, otherwise, the value impulse response δ(t) equal to zero in all values of the time. Over a time period reaction, the cellular radio channel could be designed as a linear filter with various impulses.</p>

Robust Power Optimization for Downlink Cloud Radio Access Networks with Physical Layer Security.

Since the cloud radio access network (C-RAN) transmits information signals by jointly transmission, the multiple copies of information signals might be eavesdropped on. Therefore, this paper studies the resource allocation algorithm for secure energy optimization in a downlink C-RAN, via jointly designing base station (BS) mode, beamforming and artificial noise (AN) given imperfect channel state information (CSI) of information receivers (IRs) and eavesdrop receivers (ERs). The considered resource allocation design problem is formulated as a nonlinear programming problem of power minimization under the quality of service (QoS) for each IR, the power constraint for each BS, and the physical layer security (PLS) constraints for each ER. To solve this non-trivial problem, we first adopt smooth -norm approximation and propose a general iterative difference of convex (IDC) algorithm with provable convergence for a difference of convex programming problem. Then, a three-stage algorithm is proposed to solve the original problem, which firstly apply the iterative difference of convex programming with semi-definite relaxation (SDR) technique to provide a roughly (approximately) sparse solution, and then improve the sparsity of the solutions using a deflation based post processing method. The effectiveness of the proposed algorithm is validated with extensive simulations for power minimization in secure downlink C-RANs.

Multi-target Detection with an Arbitrary Spacing Distribution.

Motivated by the structure reconstruction problem in single-particle cryo-electron microscopy, we consider the multi-target detection model, where multiple copies of a target signal occur at unknown locations in a long measurement, further corrupted by additive Gaussian noise. At low noise levels, one can easily detect the signal occurrences and estimate the signal by averaging. However, in the presence of high noise, which is the focus of this paper, detection is impossible. Here, we propose two approaches-autocorrelation analysis and an approximate expectation maximization algorithm-to reconstruct the signal without the need to detect signal occurrences in the measurement. In particular, our methods apply to an arbitrary spacing distribution of signal occurrences. We demonstrate reconstructions with synthetic data and empirically show that the sample complexity of both methods scales as SNR-3 in the low SNR regime.

Multipath Suppression for Continuous Wave Radar via Slepian Sequences

In continuous wave (CW) radar systems, multiple signal copies impinge the receiver simultaneously. Often, undesired multipath and direct-path copies are many times stronger than potential targets. When applying matched filter signal processing techniques, the undesired signal components can mask weaker targets and decrease performance of post-processing techniques, such as target indication or estimation. In this manuscript, we propose a method of rejecting multipath-scattered returns over a continuous region in range and Doppler. We explore the computational cost of this method and additionally propose an approximate method of rejection which leverages the well-known discrete prolate spheroidal sequences (DPSS)–typically referred to as Slepian sequences–to gain a computational advantage. Results are shown to decrease the effective noise floor when applying matched filtering techniques as well as increase target signal-to-interference-plus-noise ratio (SINR) outside of an undesired multipath region. Comparisons are shown to traditional CW multipath removal in terms of rejection performance and run-time.

Motor Behavior Selectively Inhibits Hair Cells Activated by Forward Motion in the Lateral Line of Zebrafish

SummaryHow do sensory systems disambiguate events in the external world from signals generated by the animal’s own motor actions? One strategy is to use an “efference copy” of the motor command to inhibit the sensory input caused by active behavior [1]. But does inhibition of self-generated inputs also block transmission of external stimuli? We investigated this question in the lateral line, a sensory system that allows fish and amphibians to detect water currents and that contributes to behaviors such as rheotaxis [2] and predator avoidance [3, 4]. This mechanical sense begins in hair cells grouped into neuromasts dotted along the animal’s body [5]. Each neuromast contains two populations of hair cells, activated by deflection in either the anterior or posterior direction [6], as well as efferent fibers that are active during motor behavior to suppress afferents projecting to the brain [7, 8, 9, 10, 11, 12]. To test how far the efference copy signal modulates responses to external stimuli, we imaged neural and synaptic activity in larval zebrafish during fictive swimming. We find that efferents transmit a precise copy of the motor signal and a single spike in the motor nerve can be associated with ∼50% inhibition of glutamate release. The efference copy signal acted with high selectivity on hair cells polarized to be activated by posterior deflections, as would occur during forward motion. During swimming, therefore, “push-pull” encoding of stimulus direction by afferents of opposite polarity is disrupted while still allowing a subset of hair cells to detect stimuli originating in the external world.

Evaluation of OFDM Channel Sounding Techniques with Three Modulation Sequences

This paper presents an evaluation of multicarrier channel sounding techniques using different random and pseudo-random sequences to modulate the OFDM sounding signal. The Random (Rand), Pseudo-Noise (PN) and Zadoff-Chu (ZC) were tested, both in laboratory simulations and in field measurements. For the laboratory simulations Matlab routines were used to generate OFDM signals modulated with each of the three sounding signals, that were then convoluted with a synthesized transfer function of a test channel with six multipath components and added Gaussian noise and Doppler fading. The resulting signals are then correlated with a copy of the original signal to provide the multipath power delay profiles. The root mean square deviation (RMSD) and the relationship between peak power and mean power (PAPR) were used as metrics for the comparison between the test transfer function and the simulation detected multipath delay profiles, showing slight advantages of the ZC sequence. The three sequences were then used in field measurements to characterize an urban channel at 700 MHz. In the field measurements, the ZC sequence showed the lowest detection threshold, allowing for the detection of a larger number of multipath components.

All-Optical Wavelength Conversion in an InP Photonic Integrated Turbo-Switch

We experimentally demonstrate all-optical wavelength conversion of 56 Gb/s non-return-to-zero (NRZ) signals in an Indium Phosphide (InP) photonic integrated circuit implementing a turbo-switch. The circuit consists of two cascaded semiconductor optical amplifiers (SOAs) with a bandpass filter in between. In this configuration, cross gain modulation (XGM) between a modulated input signal and a continuous wave (CW) light in the first SOA allows to generate a wavelength converted copy of the input signal, while the second SOA, fed by the probe signal selected by the filter, ensures a fast gain recovery. Operations in down- and up-conversion are shown by ER and BER measurements, demonstrating the effectiveness of the photonic integrated circuit (PIC).

Wavelength conversion using fiber cross-phase modulation driven by two pump waves.

Wavelength conversion using all-optical phase modulation in a fiber driven by two pump waves is investigated. The operation features are analyzed using an all-optical phase modulation model with two parallel-/cross-polarized pump waves to generate a phase-preserving copy of the optical signal at an exact frequency up-/down-shifted by the two-pump detuning. The conversion efficiency is experimentally verified using a 300-m highly-nonlinear fiber. The results agree well with a theoretical prediction. The conversion bandwidth over 4 THz is achieved and error-free wavelength conversion for a 32-GBd polarization-division multiplexed 16QAM signal is demonstrated. The technique's applicability to a large-capacity wavelength-division multiplexed signals is also discussed.

Stochastic Cooperative Communications Using a Geometrical Probability Approach for Wireless Networks

In cooperative communications, signals are relayed to increase transmission range and user throughput. However, selection and coordination of relay stations (RSs) usually require channel state information (CSI) and control signaling, resulting in high system overhead, latency, and complexity. In this paper, we propose a cooperation scheme for wireless networks, called stochastic cooperative communications based on geometrical probability (SCCGP). SCCGP has a low operational overhead and provides link capacity guarantee statistically. For cellular networks, a base station selects randomly a number of RSs in a hexagonal cell that have a fixed amplification factor, and the target user employs selective combining on the signal copies from multiple relaying paths. For ad hoc networks, the RSs are selected randomly in the circular area between a pair of communicating stations. Using a geometrical probability approach and the Cassini oval model, we derived the distribution functions of the cascaded path loss over a random two-hop relaying path, average received signal-to-noise ratio, and link capacity over multiple relaying paths. Furthermore, we transform the distribution functions into closed forms by using Taylor expansions. The mathematical proof and numerical results have shown that the closed-form distribution functions are valid and can be used to analyze the capacity of SCCGP and determine the minimum number of random RSs needed to satisfy an outage requirement. The SCCGP scheme can improve the user capacity considerably without the need of much coordination and CSI among the RSs. The derived distribution functions of the cascaded path loss over random two-hop paths can also be used in the interference management in multi-source-destination systems and other problems.

USING ARTIFICIAL NEURAL NETWORKS FOR TIME DIFFERENCE OF ARRIVAL TARGET LOCALIZATION BASED ON REDUCED DISCRETE COSINE TRANSFORM

The angular coordinates of the pulse source are determined by comparing the signals received simultaneously on several channels. To solve this issue, the application of neural networks is highly important. In this article, the application of the artificial neural network (ANN) approach to the task of target localization is discussed. The research was performed on the basis of a feature extraction technique executed by a discrete cosine transform, which allowed to obtain a compact representation of the signal energy subjected to digital processing. The author defines the angle-of-arrival estimation scheme based on time difference of arrival estimators and the particular problem of estimating constant delays as informative parameters embedded into received signals that are noisy and damped copies of the reference signal. The adaptive element framework is used for synthesis of the feedforward ANN which is fed with the reduced set of the most sensitive discrete cosine transform (DCT) coefficients, which provide a concise representation of the first-order cyclostationary random process. The investigation on the delay estimation accuracy has been carried out to evaluate the performance of the ANNs with different size of their hidden layer and various numbers of the DCT coefficients at their input. It has been proved that five DCT coefficients are enough for the discrimination of the phase shift in the whole range. In turn, it results in the reliable delay estimation produced by the trained ANN that contains eight neurons in its hidden layer.

VEGFA amplification/increased gene copy number and VEGFA mRNA expression in renal cell carcinoma with TFEB gene alterations

Amplification of vascular endothelial growth factor A (VEGFA) has been recently reported in TFEB-amplified renal cell carcinomas regardless the level of TFEB amplification. We sought to determine VEGFA amplification by fluorescent in situ hybridization (FISH) and VEGFA mRNA expression by in situ hybridization (RNAscope 2.5) in a series of 10 renal cell carcinomas with TFEB gene alterations, either amplification and/or rearrangement (t(6;11) renal cell carcinoma). TFEB gene rearrangement was demonstrated in eight cases, whereas the remaining two cases showed a high level of TFEB (> 10 copies of fluorescent signals) gene amplification without evidence of rearrangement. Among the eight t(6;11) renal cell carcinomas (TFEB-rearranged cases), one case displayed a high level of TFEB gene amplification and two showed increased TFEB gene copy number (3–4 copies of fluorescent signals). Those three cases behaved aggressively. By FISH, VEGFA was amplified in all three cases with TFEB amplification and increased VEGFA gene copy number was observed in the two aggressive cases t(6;11) renal cell carcinomas with an overlapping increased number of TFEB fluorescent signals. Overall, VEGFA mRNA expression was observed in 8 of 10 cases (80%); of these 8 cases, 3 cases showed high-level TFEB amplification, one case showed TFEB rearrangement with increased TFEB gene copy number, whereas four showed TFEB gene rearrangement without increased copy number. In summary, VEGFA amplification/increased gene copy number and VEGFA mRNA expression occur in TFEB-amplified renal cell carcinoma, but also in a subset of t(6;11) renal cell carcinoma demonstrating aggressive behavior, and in unamplified conventional t(6;11) renal cell carcinoma suggesting VEGFA as potential therapeutic target in these neoplasms even in the absence of TFEB amplification. We finally propose that all the renal tumors showing morphological characteristics suggesting t(6;11) renal cell carcinoma and all unclassified renal cell carcinomas, either high grade or low grade, should immunohistochemically be evaluated for cathepsin K and/or Melan-A and if one of them is positive, tested for TFEB gene alteration and VEGFA gene amplification.

Privacy-Preserving Reversible Information Hiding Based on Arithmetic of Quadratic Residues

The phenomenal advances of cloud computing technology have given rise to the research area of privacy-preserving signal processing, which aims to preserve information privacy even when the signals are processed in an insecure environment. Privacy-preserving information hiding is a multidisciplinary study that has opened up a great deal of intriguing real-life applications, such as data exfiltration prevention, data origin authentication, and electronic data management. Information hiding is a practice of embedding intended messages into carrier signals through imperceptible alterations. In view of some content-sensitive scenarios, however, the ability to preserve perfect copies of signals is of crucial importance, for instance, considering the inadequate robustness of recent artificial intelligence-aided automated systems against noise perturbations. Reversibility of information hiding systems is a valuable property that permits recovery of original carrier signals if desired. In this paper, we propose a novel privacy-preserving reversible information hiding scheme inspired by the mathematical concept of quadratic residues. A quadratic residue has four (not necessarily distinct) square roots, which enables payloads to be encoded in a dynamic fashion. Furthermore, a predictive model based upon the projection theorem is devised to assist carrier signal recovery. The experimental results showed significant improvements over the state-of-the-art methods with regard to capacity, fidelity, and reversibility.

Efficient Receive Diversity in Distributed Sensor Networks Using Selective Sample Forwarding

We study the potential of exploiting receive diversity in a distributed wireless sensor network (WSN). In contrast to other approaches, we fully rely on diversity combining on signal level by introducing selective sample forwarding to a centralized receiver. That way, we use the WSN as a distributed antenna array and still take the rather limited data rates between the sensor nodes into consideration. In particular, we consider a distributed ground network in the wild to track bats in their natural habitat. The bats are equipped with a sensor node of only 2 g, which limits the energy budget available for communication. The main challenges to be addressed are the limited bandwidth between nodes and the need for accurate time synchronization to combine signal copies constructively at a central node. We study the performance based on a GNURadio implementation both in simulations as well as in laboratory experiments. Our results clearly indicate a substantial performance gain while keeping the data rate in the distributed sensor network in a feasible range.