Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems

Hybrid massive MIMO structures with lower hardware complexity and power consumption have been considered as a potential candidate for millimeter wave (mmWave) communications. Channel covariance information can be used for designing transmitter precoders, receiver combiners, channel estimators, etc. However, hybrid structures allow only a lower-dimensional signal to be observed, which adds difficulties for channel covariance matrix estimation. In this paper, we formulate the channel covariance estimation as a structured low-rank matrix sensing problem via Kronecker product expansion and use a low-complexity algorithm to solve this problem. Numerical results with uniform linear arrays (ULA) and uniform squared planar arrays (USPA) are provided to demonstrate the effectiveness of our proposed method

Matrix Completion-Based Channel Estimation for MmWave Communication Systems With Array-Inherent Impairments

Hybrid massive MIMO structures with reduced hardware complexity and power consumption have been widely studied as a potential candidate for millimeter wave (mmWave) communications. Channel estimators that require knowledge of the array response, such as those using compressive sensing (CS) methods, may suffer from performance degradation when array-inherent impairments bring unknown phase errors and gain errors to the antenna elements. In this paper, we design matrix completion (MC)-based channel estimation schemes which are robust against the array-inherent impairments. We first design an open-loop training scheme that can sample entries from the effective channel matrix randomly and is compatible with the phase shifter-based hybrid system. Leveraging the low-rank property of the effective channel matrix, we then design a channel estimator based on the generalized conditional gradient (GCG) framework and the alternating minimization (AltMin) approach. The resulting estimator is immune to array-inherent impairments and can be implemented to systems with any array shapes for its independence of the array response. In addition, we extend our design to sample a transformed channel matrix following the concept of inductive matrix completion (IMC), which can be solved efficiently using our proposed estimator and achieve similar performance with a lower requirement of the dynamic range of the transmission power per antenna. Numerical results demonstrate the advantages of our proposed MC-based channel estimators in terms of estimation performance, computational complexity and robustness against array-inherent impairments over the orthogonal matching pursuit (OMP)-based CS channel estimator.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Extreme Learning Machine Based Non-Iterative and Iterative Nonlinearity Mitigation for LED Communications

This work concerns receiver design for light emitting diode (LED) communications where the LED nonlinearity can severely degrade the performance of communications. We propose extreme learning machine (ELM) based non-iterative receivers and iterative receivers to effectively handle the LED nonlinearity and memory effects. For the iterative receiver design, we also develop a data-aided receiver, where data is used as virtual training sequence in ELM training. It is shown that the ELM based receivers significantly outperform conventional polynomial based receivers; iterative receivers can achieve huge performance gain compared to non-iterative receivers; and the data-aided receiver can reduce training overhead considerably. This work can also be extended to radio frequency communications, e.g., to deal with the nonlinearity of power amplifiers

New approach to improve the performance of fringe pattern profilometry using multiple triangular patterns for the measurement of objects in motion

Fringe pattern profilometry using triangular patterns and intensity ratios is a robust and computationally efficient method in three-dimensional shape measurement technique. However, similar to other multiple-shot techniques, the object must be kept static during the process of measurement, which is a challenging requirement for the case of fast-moving objects. Errors will be introduced if the traditional multiple-shot techniques are used directly in the measurement of a moving object. A new method is proposed to address this issue. First, the movement of the object is measured in real time and described by the rotation matrix and translation vector. Then, the expressions are derived for the fringe patterns under the influence of the two-dimensional movement of the object, based on which the normalized fringe patterns from the object without movement are estimated. Finally, the object is reconstructed using the existing intensity ratio algorithm incorporating the fringe patterns estimated, leading to improved measurement accuracy. The performance of the proposed method is verified by experiments

Spatial shift unwrapping for digital fringe profilometry based on spatial shift estimation

An approach is presented to solve the problem of spatial shift wrapping associated with spatial shift estimation-based fringe pattern profilometry (FPP). This problem arises as the result of fringe reuses (that is, use of fringes with periodic light intensity variance), and the spatial shift can only be identified without ambiguity within the range of a fringe width. It is demonstrated that the problem is similar to the phase unwrapping problem associated with the phase-detection-based FPP, and the proposed method is inspired by the existing ideas of using multiple images with different wavelengths proposed for phase unwrapping. The effectiveness of the proposed method is verified by comparing experimental results against several objects, with the last object consisting of more complex surface features. We conclude by showing that our method is successful in reconstructing the fine details of the more complex object

Thermodynamic model of coherent island formation on vicinal substrate

A thermodynamic model has been proposed to address the formation of coherent island on the vicinal substrate. The morphological transition from square based island to elongated based one with various substrate misorientations is described. The initial stage of nucleation and growth process of islands in Stranski-Krastanow system is studied by taking into account the elastic deformations and the change of energy in the case of two-dimensional growth mode. The theoretical analysis shows the minimum nucleation barrier of island is on the decrease with increment of substrate misorientation, which means the nucleation of island on vicinal substrate is more favorable than that on flat substrate. By using the fitting data of experimental results done by Persichetti et al., [Phys. Rev. Lett. 104, 036104 (2010) and Phys. Rev. B 82, 121309(R) (2010)], we provide a meaningful explanation of the experimental observations

The fourier spectrum analysis of optical feedback self-mixing signal under weak and moderate feedback

The spectrum characteristics of self-mixing signals observed in optical feedback self-mixing interferometry (OFSMI) is studied in this paper. The purpose is to provide guidance for the design of pre-processing techniques for eliminating noise or disturbance. The influence of two important parameters of the OFSMI system on the spectrum, that is, the optical feedback factor and the linewidth enhancment factor, are measured by means of Discrete Fourier transform (DFT). The simulated results show that, at a weak feedback, the OFSMI signals are strictly band limited in nature, with the cut-off frequencies being the vibration frequency and the fringe frequency respectively. Also increasing broadens the bandwidth but has little influence on the bandwidth of the signal. At moderate feedback, the OFSMI signals are still band limited with much higher cut-off frequencies, and there is a considerable spectrum spread over a very wide range in the high frequency end. The presented analysis provides sufficient information for applying signal processing to OFSMI signals such as the filter design

Transition Analysis for Moderate Feedback Self-Mixing Interferometry

We present a theoretical analysis on the locations of transition points in moderate feedback self-mixing signal which is a fundamental issue to be addressed in preprocessing experimentally acquired data. Locations for the start and end points for upward and downward switchings are calculated based on the Lang-Kobayashi model and discussions are given, which provides guidance in achieving more accurate signal normalization

Three-dimensional measurement of object surfaces with complex shape and color distribution based on projection of color fringe patterns

A challenging issue associated with three-dimensional (3D) fringe patterns profilometry (FPP) is the unwrapping of phase maps resulting from color object surfaces. This paper proposes a new colorprojection-based 3D FPP, making use of the three primary color channels [i.e., red, green, and blue (RGB)] associated with digital projectors. One channel (e.g., red) is used for projecting sinusoidal fringes required by phase shift profilometry (PSP); the other two channels are employed for generating binary stripe patterns. In order to achieve reliable phase unwrapping, each fringe of the sinusoidal patterns is identified by a unique binary sequence. These sequences are then encoded by a channel-encoding scheme used in the area of communication. The encoded sequences are embedded in the binary coding stripe images, which are projected together with the sinusoidal patterns. The three image patterns are reflected by the object surface and captured by an RGB 3-CCD camera. The reflected sinusoidal patterns are employed to yield a wrapped phase map, and the binary stripe patterns are used to retrieve the encoded sequences, which are then decoded to yield the original binary sequences for phase unwrapping. Compared with existing color-encoded algorithms, the proposed approach uses binary codes instead of fringe color to identify the fringes, which are less sensitive to the disturbances caused by object surface color and illumination noises. Furthermore, use of the channel-coding scheme provides extra resistance to the disturbances caused by object surface color and illumination noises. Experimental results are presented to confirm the effectiveness of the proposed technique

The height variance range for one frequency fringe pattern profilometry

The upper limit on the deepest step of the surface shape that can be accurately determined is an important performance measure associated with the fringe projection profilometry. This metric is evaluated as the variance of height between two adjacent pixels on a fringe patterns reflected from the object surface. This paper presents novel results on this metric based on the Nyquist sampling theorem originally developed in the area of communication theory. Compared to existing results, we indicate that the fringe width and digital image resolution also affect the height variance range significantly. This new result could be used to increase the measurement range for projection system