Nokia Corporation

Nokia Technologies Oy

David Guevorkian

Aki Launiainen

Petri Liuha

Kim Rounioja

Jan Westmeijer

Ville Lappalainen

Aki Juhana Launiainen

A method for scheduling different combinations of jobs simultaneously running on a shared hardware platform is disclosed. Schedules may be created while executing the current set of jobs, for one or more possible sets of jobs that may occur after a change in the current set of jobs. In at least one embodiment, the present invention may be implemented in a SDR system where the jobs may correspond to radios in the SDR system. The possible combinations of radios that may occur after a change in the set of currently running radios may be determined at run time by adding or removing one radio at a time from the set of currently running radios.

Method for job scheduling with prediction of upcoming job combinations

The present invention relates to a method for performing calculation operations using a pipelined calculation device comprising a group of at least two pipeline stages. The pipeline stages comprise at least one data interface for input of data and at least one data interface for output of data. In the method, data for performing calculation operations is input to the device. Selective data processing is performed in the calculation device, wherein between at least one input data interface and at least one output data interface a selection is performed to connect at least one input data interface to at least one output data interface for routing data between at least one input data interface and at least one output data interface and for processing data according to the selection. The invention further relates to a system and a device in which the method is utilized.

Method and system for performing calculation operations and a device

A signal processing method, receiver and equalizing method are provided. The receiver comprises an estimator estimating a channel coefficient matrix from a received signal, a first calculation unit determining a channel correlation matrix based on the channel coefficient matrix a converter converting the channel correlation matrix into a circulant matrix. A second calculation unit determines equalization filter coefficients by applying a first transform to the real parts of a first subset of the terms in the first column of the circulant matrix and by applying a second transform to the imaginary parts of a second subset of the terms in the first column of the circulant matrix. An equalizer equalizes the received signal by using the determined equalization filter coefficients.

Signal processing method, receiver and equalizing method in receiver

A current video block of a frame to be encoded comprises a set of first data values, and at least one other video block of another frame comprises a set of second data values. Data value pairs are formed of data values from said set of first data values and equal number of corresponding data values from said set of second data values. A combined comparison value is formed by defining comparison values, each of which is defined by using data values of one data value pair of said data value pairs. Said data value pairs are divided into at least two sub-sets of data value pairs each sub-set comprising equal number of data value pairs. The calculation of the comparison values is interlaced such that the calculation of comparison values of one sub-set of data value pairs is initiated in a time after initiating and before completing the calculation of comparison values of another sub-set of data value pairs.

Method for performing motion estimation in video encoding, a video encoding system and a video encoding device

A method for performing video motion estimation in video encoding, in which a video signal consists of frames comprising blocks. In the method a combined comparison value is calculated between a current video block of a frame to be encoded and at least one other video block of another frame. The current video block of the frame to be encoded comprises a set of first data values, and the at least one other video block of another frame comprises a set of second data values. Data value pairs are formed of data values from the set of first data values and equal number of corresponding data values from the set of second data values. The combined comparison value is formed by defining comparison values, each of which is defined by using data values of one data value pair of the data value pairs. Further, at least one threshold value is defined, and it is determined whether the process for defining the combined comparison value can be terminated.

A microprocessor structure for performing a discrete wavelet transform operation, said discrete wavelet transform operation comprising decomposition of an input signal comprising a vector of r&#xd7;kinput samples, r, k and m being non-zero positive integers, over a specified number of decomposition levels j, where j is an integer in the range 1 to J, starting from a first decomposition level and progressing to a final decomposition level, said microprocessor structure having a number of processing stages, each of said number of processing stages corresponding to a decomposition level j of the discrete wavelet transform operation and being implemented by a number of basic processing elements, the number of basic processing elements implemented in each of said processing stages decreasing by a factor of k from a decomposition level j to a decomposition level j+1.

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Tampere, Finland

David Guevorkian