11 results about "Semi blind" patented technology

The present invention provides a multi-RIS-assisted semi-blind joint channel estimation and symbol detection method and system. The solution includes establishing a multi-RIS-assisted MIMO communication system model; establishing a signal received by a base station as a parallel factor tensor model; converting the channel estimation and symbol detection problem into an iterative optimization problem of a cost function based on a tensor expansion; and solving the cost function through ALS. The solution solves the problem of excessively high dimensionality of received signals due to the multiplication of the number of RIS reflection elements in multi-RIS-assisted communication scenarios, making it difficult to accurately and quickly obtain channel state information. Compared with the pilot-assisted ALS algorithm and the KAKF semi-blind receiver in single-RIS-assisted communication scenarios, the method can effectively improve estimation accuracy and reduce bit error rate and pilot overhead.

The application discloses a LFMCW radar Keystone transformation distance walking correction and semi-blind speed effect elimination method and device. In view of the energy defocusing and Doppler tearing problems of the semi-blind speed area caused by Sinc interpolation truncation when the conventional Keystone transformation processes high-speed maneuvering targets, a double-path parallel architecture is adopted. A conventional branch extracts a safe area spectrum; a blind speed branch constructs a time domain compensation factor containing a radar frequency modulation slope and a fast time variable, substitutes high calculation power interpolation by pure physical phase rotation, and realizes extreme focusing of target energy; then, based on a target absolute Doppler index, a point-to-point coordinate mapping mechanism is adopted to seamlessly recombine the focused main lobe into a basic spectrum. The application recovers the coherent accumulation loss caused by interpolation truncation, eliminates the ghost false peaks and speed measurement blind bias at the Doppler cross-border, greatly reduces the consumption of underlying hardware resources, and meets the real-time detection demand.

The invention relates to a semi-blind phase search method based on target planning in a probabilistic shaping CO-OFDM system. According to the method, a convergence area is set by taking an original constellation point after probability shaping as a center, and a hierarchical target planning strategy is adopted: a first layer takes maximization of signal points in the convergence area as a target, and a second layer takes minimization of a difference degree of probability distribution of a compensated signal and the original constellation point as a target. Meanwhile, test phases are selected by combining a staged test phase estimation strategy in the two-stage blind phase search algorithm, and the common phase noise is compensated by comparing the test phases. Simulation experiments show that compared with a traditional algorithm, the method can effectively suppress common phase noise of various constellation diagrams in different shapes under 16-QAM and 64-QAM modulation, the bit error rate performance is improved under the same signal-to-noise ratio, and meanwhile the spectrum utilization rate is remarkably improved.

This invention discloses a semi-blind OFDM receiving method that combines channel estimation, phase noise compensation, and signal detection. The method first constructs a constrained objective function for joint channel estimation, phase noise compensation, and signal detection based on phase noise modulo-1 constraints and the mapping constraint of the signal to be detected. Then, given the phase noise and the signal to be detected, the optimal channel estimate is obtained, and this estimate is brought back to the original optimization objective to obtain an updated objective function. Subsequently, by introducing a penalty term, a penalty factor, and auxiliary variables, an augmented Lagrangian function of the optimization objective is constructed, and the corresponding optimization problem is solved using the cross-direction multiplier method (ADMM) and the minimization-maximization (MM) algorithm. When the iteration termination condition is met, the joint estimate of the channel, phase noise, and transmitted signal is obtained. This invention ensures optimal performance from the optimization objective and can effectively save pilot overhead, thereby improving spectral efficiency.

The application belongs to the technical field of image copyright confirmation and information security guarantee, and particularly relates to a semi-blind watermarking method and system based on a sound-image watermark synchronous embedding algorithm of SWT, which comprises the following steps: based on a phase truncation algorithm and a complex function algorithm, sound-image watermarks are synchronously embedded into a host image to be embedded with watermarks to obtain a watermark embedding image; the sound-image watermarks embedded in the watermark embedding image are synchronously extracted to obtain the embedded sound-image watermarks, thereby realizing the synchronous extraction of the sound-image watermarks. The application realizes the functions of sound-image watermark synchronous embedding and extraction, and guarantees the invisibility and robustness of the watermark system.

The application discloses a noise adaptive video denoising method based on semi-blind estimation. The method comprises the following steps: (1) constructing a semi-blind noise analysis neural network module based on a physical noise model; (2) constructing a video dataset containing heterodistribution noise, and pre-training the semi-blind noise analysis neural network module; (3) constructing a cyclic time large-span video denoising neural network module; (4) cascading the semi-blind noise analysis neural network module and the video denoising neural network module, and performing end-to-end training on the cascaded module using the video dataset containing heterodistribution noise. The application is based on the semi-blind noise analysis module, and the distribution parameter analysis and estimation of the heterodistribution noise are performed, and the distribution parameter is used to guide the video denoising module to process different camera heterodistribution noise, so that the adaptability and generalization of the video denoising algorithm in different cameras are fully improved.

This invention discloses a semi-blind direct localization method for thermal noise communication systems, comprising: based on the frequency domain received signal model of the thermal noise communication system, utilizing the statistical characteristics of the received signal to construct a maximum likelihood estimation problem concerning the mobile station position and channel fading coefficient, obtaining an objective function containing logarithmic determinant terms and trace function terms of a matrix; the objective function simultaneously includes a contribution from pilot power and an expected contribution from the power of the received data signal; using an optimization minimization algorithm framework, alternately solving for the mobile station position and channel fading coefficient until a preset convergence condition is met, obtaining the localization result; wherein, by constructing a substitution function containing the statistical characteristics of blind pilots and data, a closed-form solution for the channel parameters is derived in each iteration, and the mobile station position is updated through a two-dimensional grid search. This invention mines the statistical information of the data portion, effectively improving the utilization rate of the received signal and increasing the localization accuracy under low signal-to-noise ratio conditions.

The invention belongs to the technical field of image copyright confirmation and information security guarantee, and particularly relates to a semi-blind watermarking method and system of a sound-image watermark synchronous embedding algorithm based on SWT, and the method comprises the steps: synchronously embedding a sound-image watermark into a host image to be embedded with the watermark based on a phase truncation algorithm and a complex function algorithm, and obtaining a watermark embedded image; and performing sound-image watermark synchronous extraction on the watermark embedded image to obtain an embedded sound-image watermark, thereby realizing the synchronous extraction of the sound-image watermark. According to the method, a sound-image watermark synchronous embedding and extracting function is realized, and invisibility and robustness of a watermark system are ensured.

The invention provides an RIS-assisted semi-blind joint channel estimation and symbol detection method for estimating a four-dimensional data signal. The method comprises the following steps: firstly, constructing an RIS-assisted MIMO communication system model, and converting a signal received by a base station end into a tensor form; the estimation process is divided into the following two stages: in a direct link stage, a KRF algorithm is utilized to convert a channel estimation problem into an approximate value approximation problem, and a high-quality approximation result is obtained by means of a left and right dominant singular value comparison process; and entering an RIS auxiliary link stage, further converting the problem into an iterative optimization problem of a cost function according to PARAFAC nested decomposition and a TALS algorithm principle, and obtaining a more accurate threshold result along with the increase of the number of iterations. According to the method and the device, the problem that the channel state information is difficult to quickly and accurately acquire due to the fact that the dimension of the received signal is too high in an RIS-assisted communication scene is successfully solved. Compared with an ALS algorithm based on pilot assistance, a TALS semi-blind receiver and a KAKF semi-blind receiver which are widely applied in the same communication scene, the method disclosed by the invention shows remarkable advantages in the aspects of improving the estimation precision, reducing the bit error rate and reducing the pilot overhead.

The invention relates to a channel estimation algorithm based on a fourth-order nested PARAFAC model, and provides a KRD-LiSe-TALS receiver algorithm, which comprises the following steps of: in a first stage, obtaining estimations U (1) and Grd of U (1) and Grd by using a LiSe-TALS algorithm according to a first-layer tensor y; in the second stage, according to a second-layer tensor y and a known coding matrix C2, a KRD algorithm is used to obtain an estimator of the sum V (1) and the sum V (1); in the third stage, according to the tensor v of the third layer, using the LiSe-TALS algorithm to obtain estimators Z (1) and Gsr of Z (1) and Gsr; and in the fourth stage, the KRD algorithm is used according to the innermost tensor and the known coding matrix C1 to obtain the estimator of the sum S, and on the premise of reducing the number of iterations and reducing the operation time of the algorithm, the improved algorithm can obtain the estimation performance equivalent to that of C-ALS. Compared with LS and TST receiver algorithms, the semi-blind estimation algorithm provided by the invention obtains better estimation performance and lower BER compared with a comparison algorithm on the premise of reducing pilot frequency overhead.

Systems and methods for multiband linearization using kernel regression are provided. In some embodiments, a method includes, for each band of the multiband transmitter: transforming a group of input signals from one or more bands into a constructed input vector space to provide transformed input signals; predistorting the transformed input signals to provide a respective group of predistorted input signals in accordance with a Radial Basis Function (RBF) kernel regression; and transmitting the respective group of predistorted input signals. In this way, some advantages include a semi blind approach as one need not to account for the non-linearity order as in Volterra-based DPD for example, only the memory depth is needed to be incorporated to the input vector space. The computational complexity of DPD is reduced compared to Volterra-based DPD. Implementation complexity is relaxed by means of using a 1D Lookup Table implementation regardless of the number of bands.