Turbo Message Passing Based Burst Interference Cancellation for Data Detection in Massive MIMO-OFDM Systems

This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst interference may occur only on data symbols but not on pilot symbols, which means that interference information cannot be premeasured. To cancel the burst interference, we first revisit the uplink multi-user system and develop a matrixform system model, where the covariance pattern and the low-rank property of the interference matrix is discussed. Then, we propose a turbo message passing based burst interference cancellation(TMP-BIC) algorithm to solve the data detection problem, where the constellation information of target data is fully exploited to refine its estimate. Furthermore, in the TMP-BIC algorithm, we design one module to cope with the interference matrix by exploiting its lowrank property. Numerical results demonstrate that the proposed algorithm can effectively mitigate the adverse effects of burst interference and approach the interference-free bound.

FAST IMPLEMENTATION OF ORTHOGONAL EMPIRICAL MODE DECOMPOSITION AND ITS APPLIGA-TION INTO HARMONIC DETECTION

Since the empirical mode decomposition （EMD） lacks strict orthogonality, the method of orthogonal empirical mode decomposition （OEMD） is innovationally proposed. The primary thought of this method is to obtain the intrinsic mode function （IMF） and the residual function by auto-adaptive band-pass filtering. OEMD is proved to preserve strict orthogonality and completeness theoretically, and the orthogonal basis function of OEMD is generated, then an algorithm to implement OEMD fast, IMF binary searching algorithm is built based on the point that the analytical band-pass filtering preserves perfect band-pass feature in the frequency domain. The application into harmonic detection shows that OEMD successfully conquers mode aliasing, avoids the occurrence of false mode, and is featured by fast computing speed. Furthermore, it can achieve harmonic detection accurately combined with the least square method.

PCCP broken wire detection based on orthogonal electromagnetic principle

Aiming at the major failure mode of prestressed concrete cylinder pipes (PCCP),namely the fracture of prestressed steel wires,the broken wire detection technology based on orthogonal electromagnetic principle is studied. The detection system model is established and optimized by using COMSOL finite element simulation software. Furthermore,the theoretical analysis of the wire-breaking effect is carried out. The influence of factors on broken wire signal characteristics such as edge effect,circumferential relative position of the detector and broken wires,excitation frequency and relative permeability of steel wires is analyzed,which provides a theoretical guidance for the field detection. The influence of the steel cylinder structure on the simulation results is analyzed,which provides a reference for the improvement of calculation efficiency. The corresponding detection system is designed and implemented. Concretely,a high-voltage and high-power sinusoidal signal coil drive scheme based on sinusoidal pulse width modulation technology and an intelligent power module is innovatively proposed and the corresponding protection circuit is designed. The broken wire signal could be effectively extracted through a lock-in amplifier. The experimental results show that this system can effectively identify the broken wires with low cost.

Enhancing the Accuracy for Target Detection by Using Fast Orthogonal Search (FOS)

Target detection and bearing estimation are mainly obtained through spectral analysis of received signals. The detection performance of the periodogram and its variants methods is evaluated. The variants methods Performance evaluation through the Receiver Operating Characteristics （ROCs） are presented and compared from the viewpoint of probability of detection （Pd）, probability of false alarm （Pfa） by computer simulation. When the sinusoid frequency does not correspond to one of the spectral bins （mid-bin frequency situation）, the performance of all the mentioned detectors degrades. This research investigates the development of a bearing estimation method using Fast Orthogonal Search （FOS） to enhance spectral estimation which, improves both target detection and bearing estimation in case of low SNR inputs.

Fifth-order phase-sensitive detection of ultrafast polarization beats in cascade four-level system

We study the colour-locked twin-noisy-field correlation effects in the fifth-order nonlinear susceptibility of ultrafast polarization beats in a cascade four-level system. More importantly, the fifth-order phase-sensitive heterodyne detection of ultrafast polarization beats has been exploited. The fifth-order nonlinear optical response can be controlled and modified through the colour-locked correlation of twin noisy fields. Thus, this method with the phase dispersion information is a good way to measure the real and imaginary parts of the fifth-order nonlinear susceptibility.

A NEW ML DETECTION ALGORITHM FOR ORTHOGONAL MULTICODE SYSTEM IN NAKAGAMI FADING CHANNEL

Based on the Maximum-Likelihood (ML) criterion, this paper proposes a novel noncoherent detection algorithm for Orthogonal Multicode (OM) system in Nakagami fading channel. Some theoretical analysis and simulation results are presented. It is shown that the proposed ML algorithm is at least 0.7 dB better than the conventional Matched-Filter (MF) algorithm for uncoded systems, in both non-fading and fading channels. For the consideration of practical application, it is further simplified in complexity. Compared with the original ML algorithm, the simplified ML algorithm can provide significant reduction in complexity with small degradation in performance.

Infrared Image Small Target Detection Based on Bi-orthogonal Wavelet and Morphology

An image multi-scale edge detection method based on anti-symmetrical bi-orthogonal wavelet is given in theory. Convolution operation property and function as a differential operator are analyzed,which anti-symmetrical bi-orthogonal wavelet transform have. An algorithm for wavelet reconstruction in which multi-scale edge can be detected is put forward. Based on it, a detection method for small target in infrared image with sea or sky background based on the anti-symmetrical bi-orthogonal wavelet and morphology is proposed. The small target detection is considered as a process in which structural background is removed, correlative background is suppressed, and noise is restrained. In this approach, the multi-scale edge is extracted by means of the anti-symmetrical bi-orthogonal wavelet decomposition. Then, module maximum chains formed by complicated background of clouds, sea wave and sea-sky-line are removed, and the image background becomes smoother. Finally, the morphology based edge detection method is used to get small target and restrain undulate background and noise. Experiment results show that the approach can suppress clutter background and detect the small target effectively.

GS-orthogonalization OMP method for space target detection via bistatic space-based radar

A space-based bistatic radar system composed of two space-based radars as the transmitter and the receiver respectively has a wider surveillance region and a better early warning capability for high-speed targets,and it can detect focused space targets more flexibly than the monostatic radar system or the ground-based radar system.However,the target echo signal is more difficult to process due to the high-speed motion of both space-based radars and space targets.To be specific,it will encounter the problems of Range Cell Migration(RCM)and Doppler Frequency Migration(DFM),which degrade the long-time coherent integration performance for target detection and localization inevitably.To solve this problem,a novel target detection method based on an improved Gram Schmidt(GS)-orthogonalization Orthogonal Matching Pursuit(OMP)algorithm is proposed in this paper.First,the echo model for bistatic space-based radar is constructed and the conditions for RCM and DFM are analyzed.Then,the proposed GS-orthogonalization OMP method is applied to estimate the equivalent motion parameters of space targets.Thereafter,the RCM and DFM are corrected by the compensation function correlated with the estimated motion parameters.Finally,coherent integration can be achieved by performing the Fast Fourier Transform(FFT)operation along the slow time direction on compensated echo signal.Numerical simulations and real raw data results validate that the proposed GS-orthogonalization OMP algorithm achieves better motion parameter estimation performance and higher detection probability for space targets detection.

Infrared small target detection using sparse representation

Sparse representation has recently been proved to be a powerful tool in image processing and object recognition.This paper proposes a novel small target detection algorithm based on this technique.By modelling a small target as a linear combination of certain target samples and then solving a sparse 0-minimization problem,the proposed apporach successfully improves and optimizes the small target representation with innovation.Furthermore,the sparsity concentration index（SCI） is creatively employed to evaluate the coefficients of each block representation and simpfy target identification.In the detection frame,target samples are firstly generated to constitute an over-complete dictionary matrix using Gaussian intensity model（GIM）,and then sparse model solvers are applied to finding sparse representation for each sub-image block.Finally,SCI lexicographical evalution of the entire image incorparates with a simple threshold locate target position.The effectiveness and robustness of the proposed algorithm are demonstrated by the exprimental results.

An Overview of Non.Orthogonal Multiple Access

In recent years, non-orthogonal multiple access(NOMA) has attracted a lot of attention as a novel and promising power-domain us-er multiplexing scheme for Long-Term Evolution(LTE) enhancement and 5G. NOMA is able to contribute to the improvement ofthe tradeoff between system capacity and user fairness(i.e., cell-edge user experience). This improvement becomes in particularemphasized in a cellular system where the channel conditions vary significantly among users due to the near-far effect. In this arti-cle, we provide an overview of the concept, design and performance of NOMA. In addition, we review the potential benefits and is-sues of NOMA over orthogonal multiple access(OMA) such as orthogonal frequency division multiple access(OFDMA) adoptedby LTE, and the status of 3GPP standardization related to NOMA.

MIXED SCHEME FOR IMAGE EDGE DETECTION BASED ON WAVELET TRANSFORM

A mixed scheme based on Wavelet Transformation (WT) is proposed for image edge detection. The scheme combines the wavelet transform and traditional Sobel and LoG (Laplacian of Gaussian) operator edge-detection algorithms. The precise theory analysis is given to show that the wavelet transformation has an advantage for signal processing. Simulation results show that the new scheme is better than only using the Sobel or LoG methods. Complexity analysis is also given and the conclusion is acceptable, therefore the proposed scheme is effective for edge detection.

AN ADAPTIVE MEASUREMENT SCHEME BASED ON COMPRESSED SENSING FOR WIDEBAND SPECTRUM DETECTION IN COGNITIVE WSN

An Adaptive Measurement Scheme (AMS) is investigated with Compressed Sensing (CS) theory in Cognitive Wireless Sensor Network (C-WSN). Local sensing information is collected via energy detection with Analog-to-Information Converter (AIC) at massive cognitive sensors, and sparse representation is considered with the exploration of spatial temporal correlation structure of detected signals. Adaptive measurement matrix is designed in AMS, which is based on maximum energy subset selection. Energy subset is calculated with sparse transformation of sensing information, and maximum energy subset is selected as the row vector of adaptive measurement matrix. In addition, the measurement matrix is constructed by orthogonalization of those selected row vectors, which also satisfies the Restricted Isometry Property (RIP) in CS theory. Orthogonal Matching Pursuit (OMP) reconstruction algorithm is implemented at sink node to recover original information. Simulation results are performed with the comparison of Random Measurement Scheme (RMS). It is revealed that, signal reconstruction effect based on AMS is superior to conventional RMS Gaussian measurement. Moreover, AMS has better detection performance than RMS at lower compression rate region, and it is suitable for large-scale C-WSN wideband spectrum sensing.

Joint MAP channel estimation and data detection for OFDM in presence of phase noise from free running and phase locked loop oscillator

This paper addresses a computationally compact and statistically optimal joint Maximum a Posteriori(MAP)algorithm for channel estimation and data detection in the presence of Phase Noise(PHN)in iterative Orthogonal Frequency Division Multiplexing(OFDM)receivers used for high speed and high spectral efficient wireless communication systems.The MAP cost function for joint estimation and detection is derived and optimized further with the proposed cyclic gradient descent optimization algorithm.The proposed joint estimation and detection algorithm relaxes the restriction of small PHN assumptions and utilizes the prior statistical knowledge of PHN spectral components to produce a statistically optimal solution.The frequency-domain estimation of Channel Transfer Function(CTF)in frequency selective fading makes the method simpler,compared with the estimation of Channel Impulse Response(CIR)in the time domain.Two different time-varying PHN models,produced by Free Running Oscillator(FRO)and Phase-Locked Loop(PLL)oscillator,are presented and compared for performance difference with proposed OFDM receiver.Simulation results for joint MAP channel estimation are compared with Cramer-Rao Lower Bound(CRLB),and the simulation results for joint MAP data detection are compared with“NO PHN"performance to demonstrate that the proposed joint MAP estimation and detection algorithm achieve near-optimum performance even under multipath channel fading.

LMMSE-based SAGE channel estimation and data detection joint algorithm for MIMO-OFDM system

A new channel estimation and data detection joint algorithm is proposed for multi-input multi-output （MIMO） - orthogonal frequency division multiplexing （OFDM） system using linear minimum mean square error （LMMSE）- based space-alternating generalized expectation-maximization （SAGE） algorithm. In the proposed algorithm, every sub-frame of the MIMO-OFDM system is divided into some OFDM sub-blocks and the LMMSE-based SAGE algorithm in each sub-block is used. At the head of each sub-flame, we insert training symbols which are used in the initial estimation at the beginning. Channel estimation of the previous sub-block is applied to the initial estimation in the current sub-block by the maximum-likelihood （ML） detection to update channel estimatjon and data detection by iteration until converge. Then all the sub-blocks can be finished in turn. Simulation results show that the proposed algorithm can improve the bit error rate （BER） performance.

Symbols detection for frequency-selective V-BLAST OFDM systems

As the combining form of the orthogonal frequency-division multiplexing (OFDM) technique and the vertical Bell Labs layered space-time (V-BLAST) architecture, the V-BLAST OFDM system can better meet the demand of next-generation (NextG) broadband mobile wireless multimedia communications. The symbols detection problem of the V-BLAST OFDM system is investigated under the frequency-selective fading environment. The joint space-frequency demultiplexing operation is proposed in the V-BLAST OFDM system. Successively, one novel half-rate rotational invariance joint space-frequency coding scheme for the V-BLAST OFDM system is proposed. By elegantly exploiting the above rotational invariance property, we derive one direct symbols detection scheme without knowing channels state information (CSI) for the frequency-selective V-BLAST OFDM system. Extensive simulation results demonstrate the validity of the novel half-rate rotational invariance joint space-frequency coding scheme and the performance of the direct symbols detection scheme.

A SIMPLIFIED QRD-M SIGNAL DETECTION ALGORITHM FOR MIMO-OFDM SYSTEMS

QR Decompositon with an M-algorithm(QRD-M) has good performance with low complexity,which is considered as a promising technique in Multiple-Input Multiple-Output(MIMO) detections.This paper presented a simplified QRD-M algorithm for MIMO Orthogonal Frequency Division Multiplexing(MIMO-OFDM) systems.In the proposed scheme,each surviving path is expanded only to partial branches in order to carry out a limited tree search.The nodes are expanded on demand and sorted in a distributed manner,based on the novel expansion scheme which can pre-determine the children's ascending order by their local distances.Consequently,the proposed scheme can significantly decrease the complexity compared with conventional QRD-M algorithm.Hence,it is especially attractive to VLSI implementation of the high-throughput MIMO-OFDM systems.Simulation results prove that the proposed scheme can achieve a performance very close to the conventional QRD-M algorithm.

Greater than 200 Gb/s Transmission Using Direct-Detection Optical OFDM Superchannel

In this paper, we propose directdetection optical orthogonal frequency division multiplexing superchannel （DDOOFDMS） and optical multiband receiving method （OMBR） to support a greater than 200 Gb/s data rate and longer distance for direct-detection systems. For the new OMBR, we discuss the optimum carriertosideband power ratio （CSPR） in the cases of backtoback and post transmission. We derive the analytical form for CSPR and theoretically verify it. A low overhead training method for estimating I/Q imbalance is also introduced in order to improve performance and maintain high system throughput. The experiment results show that these proposals enable an unprecedented data rate of 214 Gb/s （190 Gb/s without overhead） per wavelength over an unprecedented distance of 720 km SSMF in greater than 100 Gb/s DDOFDM systems.

Research on Phase Detection of Liquid Crystal Optical Device

The technology for phase detection of liquid crystal optical device is a difficult research in current domestic and overseas. However, for the existing liquid crystal optical device, aiming at the poor anti-vibration capability and poor versatile of phase detection, the complexity of phase retrieval algorithm, we propose a new phase measurement principle and experimental methods of liquid crystal optical device. It is a phase measurement method based on the combination of phase- shifting interferometer and phase conjugation technology. The deflection characteristics of the liquid crystal device means the device can implement phase modulation to only one direction of polarized light while is completely transparent to orthogonal polarized light. We put forward the phase shift of the orthogonal polarization phase shift interferometer method, using phase shifting interference as well as the combination of phase conjugate means to achieve its phase measurement. So we can retrieves devices modulation phase simply and efficiently combines with phase- shifting interferometer technology.

PILOT-BASED FREQUENCY OFFSET DETECTION SCHEME IN OFDM SYSTEM

The frequency offset information is extracted from local pilot amplitude characteristics, which suffer much less distortion in frequency-selective fading channels than those utilizing frequency domain correlation techniques. Simulation shows that the performance of this scheme has better performance than the existing frequency domain pilot-based frequency offset detection scheme.

Dynamic multi-user detection scheme based on CVA-SSAOMP algorithm in uplink grant-free NOMA

In the uplink grant-free non-orthogonal multiple access(NOMA)scenario,since the active user at the sender has a structured sparsity transmission characteristic,the compressive sensing recovery algorithm is initially applied to the joint detection of the active user and the transmitted data.However,the existing compressed sensing recovery algorithms with unknown sparsity often require noise power or signal-to-noise ratio(SNR)as the priori conditions,which greatly reduces the algorithm adaptability in multi-user detection.Therefore,an algorithm based on cross validation aided structured sparsity adaptive orthogonal matching pursuit(CVA-SSAOMP)is proposed to realize multi-user detection in dynamic change communication scenario of channel state information(CSI).The proposed algorithm transforms the structured sparsity model into a block sparse model,and without the priori conditions above,the cross validation method in the field of statistics and machine learning is used to adaptively estimate the sparsity of active user through the residual update of cross validation.The simulation results show that,compared with the traditional orthogonal matching pursuit(OMP)algorithm,subspace pursuit(SP)algorithm and cross validation aided block sparsity adaptive subspace pursuit(CVA-BSASP)algorithm,the proposed algorithm can effectively improve the accurate estimation of the sparsity of active user and the performance of system bit error ratio(BER),and has the advantage of low-complexity.