Contrastive Clustering for Unsupervised Recognition of Interference Signals

Interference signals recognition plays an important role in anti-jamming communication.With the development of deep learning,many supervised interference signals recognition algorithms based on deep learning have emerged recently and show better performance than traditional recognition algorithms.However,there is no unsupervised interference signals recognition algorithm at present.In this paper,an unsupervised interference signals recognition method called double phases and double dimensions contrastive clustering(DDCC)is proposed.Specifically,in the first phase,four data augmentation strategies for interference signals are used in data-augmentation-based(DA-based)contrastive learning.In the second phase,the original dataset’s k-nearest neighbor set(KNNset)is designed in double dimensions contrastive learning.In addition,a dynamic entropy parameter strategy is proposed.The simulation experiments of 9 types of interference signals show that random cropping is the best one of the four data augmentation strategies;the feature dimensional contrastive learning in the second phase can improve the clustering purity;the dynamic entropy parameter strategy can improve the stability of DDCC effectively.The unsupervised interference signals recognition results of DDCC and five other deep clustering algorithms show that the clustering performance of DDCC is superior to other algorithms.In particular,the clustering purity of our method is above 92%,SCAN’s is 81%,and the other three methods’are below 71%when jammingnoise-ratio(JNR)is−5 dB.In addition,our method is close to the supervised learning algorithm.

Four-Parameter Signal Decomposition and Related Adaptive Time-Frequency Distribution

We propose a four-parameter adaptive signal decomposition method and related adaptive time-frequency distribution, which is positive, cross-term interference-free energy distribution and yields better time and frequency resolution. The elementary functions are dilations, translations, rotations and modulations of single Gaussian window function, which are obtained by successively matching the signal local natures. So the coefficients and parameters, obtained from the decomposition process, can provide an interpretation of signal structure and can be used for the analysis and synthesis of signals.

Interference and Spectral Efficiency Analysis in Two-hop Cellular Network with Fixed Relays in FDD Mode

This paper presented a scheme of two-hop cellular network with fixed relay nodes (FRN). Based on this scheme, co-channel interference and signal interference ratio(SIR) received by base station(BS) and FRN were analyzed. Both the theoretical analysis and simulation results show that the SIR can be improved significantly when relays are employed in the network. The higher spectral efficiency can be obtained due to the improved two-hop link quality through the use of adaptive modulation and coding (AMC). The antenna height of FRN and the cell radius of BS and that of FRN influence SIR received by BS and FRN and the system spectral efficiency greatly. The proper antenna height of FRN and cell radius of BS and that of FRN were also given to get the highest spectral efficiency.

Industrial Fault Signals Propagation and Current Signature Analysis

Motor current signature analysis provides good results in laboratory environment. In real life situation, electrical machines usually share voltage and current from common terminals and would easily influence each other. This will result in considerable amount of interferences among motors and doubt in identity of fault signals. Therefore, estimating the mutual influence of motors will help identifying the original signal from the environmental noise. This research aims at modelling the propagation of signals that are caused by faults of induction motors in power networks. Estimating the propagation pattern of fault signal leads to a method to discriminate and identify the original source of major events in industrial networks. Simulation results show that source of fault could be identified using this approach with a higher certainty than anticipated output coming of any individual diagnosis.

Underdetermined Blind Source Separation of Adjacent Satellite Interference Based on Sparseness

The problem of underdetermined blind source separation of adjacent satellite interference is proposed in this paper. Density Clustering algorithm(DC-algorithm) presented in this article is different from traditional methods. Sparseness representation has been applied in underdetermined blind signal source separation. However, some difficulties have not been considered, such as the number of sources is unknown or the mixed matrix is ill-conditioned. In order to find out the number of the mixed signals, Short Time Fourier Transform(STFT) is employed to segment received mixtures. Then, we formulate the blind source signal as cluster problem. Furthermore, we construct Cost Function Pair and Decision Coordinate System by using density clustering. At the end of this paper, we discuss the performance of the proposed method and verify the novel method based on several simulations. We verify the proposed method on numerical experiments with real signal transmission, which demonstrates the validity of the proposed method.

Performance analysis of complex wavelet packet based multicarrier CDMA system over Nakagami-m fading channels

On the basis of analyzing the principle of multicarrier code division multiple access (MC-CDMA), an optimized complex wavelet packet based MC-CDMA system (CWP-MC-CDMA) is proposed. The system performances with equal gain combining (EGC) technique and maximum ratio combining (MRC) technique in Nakagami-m fading channels are investigated, respectively; and the corresponding bit error rate (BER) expression is derived. The system can overcome the decrease of spectrum efficiency of discrete Fourier transform (DFT) based conventional MC-CDMA (DFT-MC-CDMA) due to inserting a cyclic prefix (CP). Theoretical analysis and simulation results show that the CWP-MC-CDMA system outperforms DFT-MC-CDMA as well as the real wavelet packet based MC-CDMA (RWP-MC-CDMA) system, and has superior ability to combat multi-path fading and multi-access interference (MAI). Moreover, the BER performance of the proposed system is also superior to that of the conventional MC-CDMA with CP.

A combined signal processing approach against coherent interference with pressure and particle velocity

Comparing with traditional underwater acoustic system which only utilizes pressure information, combine sensor system processes pressure together with particle velocity information of sound field. More information certainly brings nicer processing result. By using spatial directional information collected by combine sensor, the Coherent Interference Energy Suppress (CIES) technology, which can effectively suppress coherent interference and detect linear spectrum signal and wide-band continuous-spectrum signal as well, is presented. Current research has shown favorite result, and further research is going on.

Denoising lidar signal by combining wavelet improved threshold with wavelet domain spatial filtering

Lidar is an effective tool for remotely monitoring target or object, but the lidar signal is often affected by various noises or interferences. Therefore, detecting the weak signals buried in noises is a fundamental and important problem in the lidar systems. In this paper, an effective noise reduction method combining wavelet improved threshold with wavelet domain spatial filtration is presented to denoise pulse lidar signal and is investigated by detecting the simulating pulse lidar signals in noise. The simulation results show that this method can effectively identify the edge of signal and detect the weak lidar signal buried in noises.

Complex-wave retrieval based on blind signal separation

In tile process of the reconstruction of digital holography. the traditional methods of diffraction and filtration are commonly adopted to recover the original complex-wave signal. Influenced by twin-image and zero-order terms, the above-mentioned methods, however, either limit tile field of vision or result in the loss of the amplitude and phase. A new method for complex-wave retrieval is presented, which is based on blind signal separation. Three frames of holograms are captured by a charge coupled device （CCD） camera to form an observation signal. The term containing only amplitude and phase of complex-wave is separated, by means of independent component analysis, from the observation signal, which effectively eliminates the zero-order term. Finally. the complex-wave retrieval of pure phase wavefront is achieved. Experimental results show that this method can better recover the amplitude and phase of the original complex-wave even when there is a frequency spectrum mixture in the hologram.

Experimental demonstration of indoor interfered visible light communication system employing successive interference cancellation

Multipath interference induced power fading occurs when the transmission path lengths from the light emitting diodes to a single receiver are different in a visible light communication system. To solve this problem, we apply a QR-decomposition-based channel equalizer （QR-CE） to achieve successive interference cancellation for a discrete Fourier transform spreading （DFT-S） orthogonal frequency division multiplexing （OFDM） signal. We experimentally demonstrate a 200 Mb/s DFT-S OFDM over a 2 m free-space transmission. The experimental results show that a DFT-S OFDM with QR-CE attains much better bit error rate performance than a DFT-S OFDM with conventional CEs. The impacts of several parameters on a QR-CE are also investigated.

Realization of Magnetic Signal Acquisition Scheme for Banknotes

In order to solve the problem of low signal-to-noise ratio（about 15 d B） in magnetic signal acquisition of banknotes, a new method of magnetic signal acquisition and processing is proposed taking RMB as an example. In this method, weak signa detection is performed to reduce the noise accompanied with the signal. Seven orders of Chebyshev（Ⅰ） filter and the anti-jamming technology are used in the PCB layout, and grounding modes are introduced to reduce the noise of the amplitude waveform. The proposed method reduce the final output noise by 2/3 and the sig nal-to-noise ratio is increased to 24 d B. The experimental results show that the magnetic signal of RMB banknotes are acquired by the circuit stability, which provides an important guarantee for the improvements of the anti-counterfeit and discrimination for banknotes performance.

Photon-counting chip-interleaved iterative PIC detector over atmospheric turbulence channels

A photon-counting-based iterative parallel interference cancellation （PIC） scheme for free-space optical communications in the presence of multiple-access interference, shot noise, background radiation, and turbulence fading is designed. An efficient chip-level iterative equivalent noise estimation algorithm is also derived. Simulation results show that the proposed scheme can achieve a single-user performance, bound with the fast convergence property. More importantly, it can eliminate the bit-error rate floor of the conventional optical code-division multiple-access system with the aid of a relatively short spreading code length.

Modified fast Fourier transform in FBMC for satellite communications

In this paper,a Doppler scaling fast Fourier transform（Doppler-FFT）algorithm for filter bank multi-carrier（FBMC）is proposed,which can efficiently eliminate the impact of the Doppler scaling in satellite communications.By introducing a Doppler scaling factor into the butterfly structure of the fast Fourier transform（FFT）algorithm,the proposed algorithm eliminates the differences between the Doppler shifts of the received subcarriers,and maintains the same order of computational complexity compared to that of the traditional FFT.In the process of using the new method,the Doppler scaling should be estimated by calculating the orbital data in advance.Thus,the inter-symbol interference（ISI）and the inter-carrier interference（ICI）can be completely eliminated,and the signal to interference and noise ratio（SINR）will not be affected.Simulation results also show that the proposed algorithm can achieve a 0.4 d B performance gain compared to the frequency domain equalization（FDE）algorithm in satellite communications.