320 results about "Orthogonalization" patented technology

A wireless communication system including receiving and base stations. The receiving station includes a detector that measures a downlink channel correlation matrix for multiple antennas of a base station. The detector computes an antenna weight increment vector normal to an antenna weight vector for multiple beams from the multiple antennas of the base station. The detector quantizes the antenna weight increment vectors to produce a respective quantized antenna weight increment vector. The receiving station includes a transmitter that sends the quantized antenna weight increment vectors to the base station. The base station includes a beamformer selector that receives from the receiving station and re-orthogonalizes the quantized antenna weight increment vector for each of the multiple beams. The base station includes a weight vector modifier that modifies the antenna weight vector for the multiple beams by adding an increment proportional to the respective re-orthogonalized quantized antenna weight increment vector.

Techniques for deriving eigenvectors based on steered reference and used for spatial processing. A steered reference is a pilot transmission on one eigenmode of a MIMO channel per symbol period using a steering vector for that eigenmode. The steered reference is used to estimate both a matrix Σ of singular values and a matrix U of left eigenvectors of a channel response matrix H. A matrix Ũ with orthogonalized columns may be derived based on the estimates of Σ and U, e.g., using QR factorization, minimum square error computation, or polar decomposition. The estimates of Σ and U (or the estimate of Σ and the matrix Ũ) may be used for matched filtering of data transmission received via a first link. The estimate of U or the matrix Ũ may also be used for spatial processing of data transmission on a second link (for reciprocal first and second links).

A data transmission method for a base station to acquire transmission beam diversity in a wireless communication system is provided. The data transmission method includes selecting at least two transmission beams to be used for data transmission from among multiple transmission beams corresponding to transmission beam information, if receiving the transmission beam information regarding the multiple transmission beams from a terminal, and transmitting data encoded with a predetermined orthogonalization code to the terminal via the selected at least two transmission beams.

A DSP checks the traffic on a control channel transmitted to each terminal, and obtains a total of traffic on the control channel for each remote radio unit. The DSP transforms a correlation matrix calculated in an analysis section to a partial orthogonal matrix subjected to partial orthogonalization. The DSP divides one or more remote radio units into the groups in accordance with the sequence of rows or columns of the partial orthogonal matrix so that the total traffic for each group in which the total of traffic is added for one or more remote radio units within the group may be less than or equal to a predetermined threshold, and stores the identification number of the remote radio unit for each group in a memory.

For eigenmode transmission with minimum mean square error (MMSE) receiver spatial processing, a transmitter performs spatial processing on N_S data symbol streams with steering vectors to transmit the streams on N_S spatial channels of a MIMO channel. The steering vectors are estimates of transmitter steering vectors required to orthogonalize the spatial channels. A receiver derives a spatial filter based on an MMSE criterion and with an estimate of the MIMO channel response and the steering vectors. The receiver (1) obtains N_R received symbol streams from N_R receive antennas, (2) performs spatial processing on the received symbol streams with the spatial filter to obtain N_S filtered symbol streams, (3) performs signal scaling on the filtered symbol streams with a scaling matrix to obtain N_S recovered symbol streams, and (4) processes the N_S recovered symbol streams to obtain N_S decoded data streams for the N_S data streams sent by the transmitter.

The invention relates to an automatic-adaptive multi-user beam shaping method based on zero defection broadening, which comprises the following steps: a plurality of sets of direction of arrival, i.e. a DOA angle combination is selected, and each set of direction of arrival includes DOA angles of N users; the orthogonalization is carried out after the transmission weights of the N users of each set is carried out by using a zero defection broadening arithmetic to obtain the final transmission weight of each user, the final transmission weights are stored as a codebook, and N is the number of the users reusing the same resource, and is not smaller than 2; when the beam is shaped, the base station receives an uplink signal, and the DOA angle corresponding to the position of each user is estimated; the N users satisfying the restrictive condition of group division are put into one user group; for each user group, the closest DOA angle combination is matched from the DOA angle combination which is previously selected according to the DOA angles of the N users in the user group, and the transmitting weights of the N users corresponding to the DOA angle combination in the code book are used. The automatic-adaptive multi-user beam shaping method enables at least two users to utilize the same time frequency and code resources and reuse system resources.

The invention discloses a self-adaptation compression reconstruction method based on energy effectiveness observation in a cognitive sensor network. The self-adaptation compression reconstruction method based on the energy effectiveness observation in the cognitive sensor network comprises the steps that (1) a node carries out local detection and compression measurement on data which are actually sensed through an analog transcriber according to the characteristic that power consumption of the node of a cognitive sensor is limited, (2) a space-time relevance structure of sensing signals is used, sensing data are mapped to a wavelet orthogonal basis cascading dictionary to carry out sparse conversion and to carry out self-adaptation observation through a weighting energy subset function, appropriate observation values are obtained in an energy effectiveness mode, orthogonalization is carried out on selected observation vectors to construct a measurement matrix, (3) the sensing data after compression measurement are fed back to an aggregation node through a report channel, the aggregation node carries out self-adaptation reconstruction on the sensing data by using a gradient projection sparse reconstruction Barzilai-Borwein method based on a convex relaxation method, and effective compromise between reconstruction performance and energy consumption of the node is achieved. The self-adaptation compression reconstruction method based on the energy effectiveness observation in the cognitive sensor network can carry out accurate reconstruction on the sensing signals, ensures energy effectiveness of the sensing node, and has actual application significance.

The invention provides a pre-coding method for a multi-user MIMO (multi-input multi-output) system. The method comprises the following steps of: acquiring a channel matrix of each user of the system by feedback or TDD (time division duplex) system channel reciprocity; acquiring a channel pseudo-inverse matrix of each user of the system according to the least square error criterion; acquiring an orthogonal vector base matrix according to a channel pseudo-inverse sentence of each user of the system; acquiring a pre-coding merging matrix of each user of the system according to the channel matrixof each user of the system and the channel pseudo-inverse orthogonal vector base matrix by combining a max signal to leakage and noise ratio criterion; and acquiring a pre-coding matrix of each user of the system according to the orthogonal vector base matrix of each user of the system and the optimal merging matrix. The scheme can effectively reduce the calculation complexity of the scheme at the same time of keeping the performance of the original MSLNR (max signal to leakage and noise ratio) criterion scheme, the performance of the scheme is superior to that of the traditional diagonal scheme, and the scheme has lower calculation complexity and reduces the operating complexity of a base station.

The invention discloses a mixed media access control method of a wireless network. System channels are of time slot, and time slots with fixed cycle are distributed to non-competitive business nodes, non-competitive business data frame is transmitted in the mode of time division multiple access. Competitive business nodes transmit competitive business data frame in the competitive time slots by using the method of random competitive access. After the competitive business data frames conflict, the competitive business nodes send the competitive business data frame again under the condition that the estimated gain value of the channels is more than or equal to a given threshold. Or else the competitive business data is forwarded by a relay node; an access point buffers the signals received before, and realizes the data frame separation by methods of serial interference cancellation and minimum mean-square error detection. At the same time, a superimposed pilot channel estimation method is used by the competitive business data, no additional time slot is needed in the method, thus being convenient for orthogonal design. The method is suitable for the unexpected properties of competitive businesses and the cyclical properties of non-competitive businesses, and the mixed transmission of the two businesses can be supported.

The invention provides a data preprocessing based covariance matrix orthogonalization wave-beam forming method aiming at solving the problem that the conventional covariance matrix based GS (Gram-Schmidt) orthogonalization (RGS) algorithm can not be directly used for training snapshot and contains desired signal information and belonging to the technical field of adaptive wave-beam forming. The data preprocessing based covariance matrix orthogonalization wave-beam forming method comprises the following steps of: firstly preprocessing training snapshot, and rejecting a desired signal; then estimating the covariance matrix by utilizing preprocessed data, and forming an interference subspace by carrying out GS orthogonalization on lines of the covariance matrix; and finally carrying out orthogonal projection on a corresponding static weight vector towards the interference subspace to obtain an adaptive weight vector. In the invention, in order to more accurately estimate the interference subspace, an adaptive threshold of orthogonalization is corrected on the basis of preprocessing; and when the training snapshot is mixed with the desired signal, the data preprocessing based covariance matrix orthogonalization wave-beam forming method provided by the invention can greatly enhance the anti-interference property of an array.

The invention relates to an overlapping community discovering method based on spectral clustering and fuzzy sets. The overlapping community discovering method comprises the steps that 1, data sets ofa social network are read to generate a network structure graph, and the attribute information of nodes in the network is acquired; 2, the Jaccard coefficient and the attribute information of the nodes in the network are combined to calculate the similarity value among the nodes in the network; 3, a similarity matrix is built based on the similarity value among the nodes, and accordingly the normalized Laplacian matrix is built; 4, the feature vector and the feature value of each node are calculated, and a new feature vector is generated by utilizing methods of iteration and compression; 5, the new feature vector is orthogonalized, the membership grade is calculated, and the nodes with a plurality of high community membership grade values are subjected to division of overlapping communities; 6, the community division meeting the highest modularity requirement is selected according to the modularity divided each time; and 7, the final community division result is output. The overlappingcommunity discovering method can efficiently and accurately discover and divide the overlapping structures in the complex network.

A method for selecting an antenna in an orthogonalized spatial multiplexing system. Upon receipt of at least one symbol from a transmitter via multiple receive antennas, a receiver decodes each of the received symbols; determines a rotation angle between the received symbols, and selects an optimal subset of transmit antennas using a distance between vectors of the decoded symbols; generates feedback information including the determined rotation angle and the selected optimal subset, and transmits the generated feedback information to the transmitter. Upon receipt of the feedback information, the transmitter beam-forms an antenna corresponding to the optimal subset depending on the received feedback information, and transmits a data symbol to the receiver. The receiver detects each of data symbols received from the transmitter.

The invention relates to a satellite attitude determination method and an attitude determination error analytical method, in particular to a satellite attitude determination method and an attitude determination error analytical method based on two star sensors, and aims at solving the problems that the existing measuring error in the star sensor optical axis direction is large and presently no attitude determination error analytical method exists. The first scheme is that the component of the optical axis vector of each star sensor in an inertial system is calculated according to measuring output of the two star sensors, the component of the optical axis vector of each star sensor in a satellite body system is calculated according to an installation matrix of each star sensor, the gesture of the satellite body system relative to the inertial system is calculated, and a gesture matrix is subjected to unit orthogonalization processing. The second scheme is that an attitude determination error matrix C* in the satellite gesture matrix and not subjected to unit orthogonalization is separated; the expression of the attitude determination error matrix C* is evaluated according to the star sensor installation matrixes; and a satellite attitude determination error matrix delta C subjected to unit orthogonalization is gained. The satellite attitude determination method and the attitude determination error analytical method are used for satellite attitude determination and attitude determination error analyzing.

The invention relates to an automatic power distribution network single line diagram drawing method based on an improved gravitation repulsion model and belongs to the technical field of electric power system dispatching automation. According to the method, firstly, all devices and connection relations which belong to one feeder line are read from a power grid public information model; all the read devices are abstracted into nodes, the connection relations between the devices are abstracted into lines, and a foundation network structure chart is completed; then, the device nodes are replaced with 8-node rectangular frames, and layout adjustment is performed on the structure chart by using the improved gravitation repulsion model; a final layout is generated through orthogonalization, intersection removal and connecting line contraction; finally, information including node positions, device types, device names and electrical attributes of the devices in the final layout are output to a single line diagram file, device diagrams replace the 8-node rectangular frames, and drawing of a power distribution network single line diagram is completed. The single line diagram drawn with the method has attractive and compact layout and lines do not intersect and overlap.

The invention discloses a large-scale power distribution network integral model simplification method applicable to electromagnetic transient simulation. The large-scale power distribution network integral model simplification method comprises the following steps of: dividing a large-scale intelligent power distribution system into two parts, i.e., an external system and a research system; connecting the external system and the research system through a plurality of branches; establishing electromagnetic transient simulation models of the external system and the research system respectively; setting a low-dimension system model order q (q is less than n) according to a simulation actual demand and computing resource, wherein n represents order of the original external system model; selecting a base calculation method corresponding to the number of columns of a matrix B input in an external system state equation; performing re-orthogonalization processing on a base V by using a re-orthogonalization method; calculating that A' is equal to VTAV, B' is equal to VTB, C' is equal to CV and D' is equal to D to obtain a low-dimension simplified system model; and performing simulation computation in linkage with a detailed model of the research system in place of the original external system model to obtain a detailed transient process in the research system. According to the large-scale power distribution network integral model simplification method, the simulation calculation efficiency is increased, large-scale system analysis simulation is oriented, and inevitable choice of operation requirements under various on-line application scenes is met.

This invention provides a method for exploiting precoder optimization gains and multi-user diversity gains with interference alignment in general MIMO wireless networks including multiple users. Specifically, two embodiments exploit either a gradient-based search or iteratively orthogonalizing inference. The method can achieve near-optimal performance at a low complexity. Furthermore, a scheduling criterion is provided for wireless networks comprised of a large number of mobile stations in each cell. The criterion can be done independently in each cell to significantly reduce information exchanged between base stations in different cells compared to the methods that perform joint scheduling over all cells. The two embodiments can be utilized in a spectrally efficient communications network equipped with relaying nodes.

The invention belongs to the technical field of wireless communication and discloses a standard-orthogonalization-based hybrid pre-coding method for a large-scale MIMO system. Analog pre-coding design is based on equal-gain transmission. The phase of a main diagonal element of a baseband equivalent channel matrix is set to zero to obtain the maximum antenna array gain so as to reduce the total energy consumption and complexity of a transmitter. The design of a digital pre-coding matrix is based on standard orthogonalization and singular value decomposition. By mapping a desired user to other user null space, the interference between users is completely eliminated and the maximum spectral efficiency is obtained. A numerical result shows that the performance of the hybrid pre-coding method, when equipped with a small number of radiofrequency links, approaches that of an all-digital pre-coding solution that requires the same number of radiofrequency links as the antennas, and can obtain high spectral efficiency with low implementation complexity.

A wireless communication system comprises a base station (4) and terminals (1)-(3). The base station (4) and the terminals (1)-(3) perform a space division multiplex wireless transmission. Each of the base station (4) and the terminals (1)-(3) comprises a multi-beam antenna for a space division multiplex. A beam pattern formed by the multi-beam antenna of the base station (4) is orthogonalized based on transfer function values of a radio-wave-propagation characteristic formed between antenna elements of the multi-beam antenna of the base station (4) and antenna elements of multi-beam antenna of the terminals (1)-(3).

An improved multi-user selecting method based on block diagonalization multiple-input multiple-output system of norm is provided, firstly selecting a maximum user of the channel Frobenius norm, then adding the maximum user of the equivalent channel Frobenius norm sum acquired by multiplying channels of all selected user with corresponding precoding matrix in a backup user collection in turn, until the maximum number of users can be supported by the system synchronously. The invention reduces the calculation complexity from two sides: adopting an heuristic Gram-Schmidt orthogonalization method to simplify the design flow of the precoding matrix; after selceting a user every time, updating the backup user collection to make users of the collelction and users of the selected user collection satisfy the orthogonality, thereby reducing the searching range selected by users at next time.

The invention relates to a gear fault diagnosis method based on the orthogonal match between multiple parallel dictionaries. According to the method, gear vibration signals are expressed in the mode of linear superposition of simple and sparse atoms of the multiple parallel dictionaries. As for the multiple parallel dictionaries, Fourier dictionaries and impact time frequency dictionaries are selected to form the multiple dictionaries according to the characteristics of the gear vibration signals, matched atoms are selected in parallel in all sub-dictionaries with a genetic algorithm, coefficients of all orders are compared to obtain a most matched atom, Gram-Schmidt orthogonalization is performed on the atom, and then a new atom library is formed. Analysis signals are projected to the atom library, and the projections are subtracted from the signals to form residual signals to be decomposed the next time. The decomposition process is completed after the iteration end conditions are met, the matched atoms and the matching coefficient are extracted, the matched atoms based on the impact time frequency dictionaries are reconstructed, corresponding impact components can be obtained, and then fault information of the gear vibration signals is demodulated and extracted for fault diagnosis.