Ceva D.s.p. Ltd.

Zeev Kaplan

Jeffrey Allan (Alon) Jacob (Yaakov)

Noam Dvoretzki

Gideon Shlomo Kutz

Hagay Rozin

Jeffrey Allan Jacob

Tal Shalev

Kfir Bezalel

David Levy

Eitan Hai

Alexander Yufit

Omri Isaacs

Jacob Jeffrey Allan

Noam Dovretzki

Joint demodulation of a desired transmission and an interfering transmission received from an interfering cell with an unknown combination of transmission parameters is performed. For each subcarrier, an exhaustive search for the serving cell symbols and projection for the interfering cell symbols is performed for tested hypotheses of the interfering cell, by minimizing a whitened noise parabola for each combination of searched hypothesis and hyper constellation point of the serving cell. A constellation point for the interfering cell that is closest to the minimum point of the parabola is selected, where coefficients of the parabola are calculated once for each subgroup of four modulation types of the interfering cell. A measure of likelihood for each of the tested hypotheses is calculated. A cumulative measure of likelihood for each of the tested hypotheses is calculated, and the most likely hypothesis is selected based on the cumulative measure of likelihood.

System and method for blind detection of transmission parameters of an interfering cell

A system and method for cell synchronization suitable for a wireless signal including substantially identical synchronization signals that repeat in predetermined time intervals, the synchronization signals including a plurality of substantially identical symbols. For a plurality of candidate synchronization points: dividing the wireless signal into a plurality of signal segments, each equal or longer than the time interval, and each including a plurality of sub-segments having substantially same length as the symbol; performing symbol-length cross-correlations between an expected symbol and the sub-segments; performing segmented symbol-wise correlations between the cross-correlation results; calculating a cost function based on the results of the symbol-wise correlations; accumulating the cost functions across a plurality of signal segments; and selecting a coarse synchronization point from the plurality of candidate synchronization points based on the accumulated cost function; Estimating synchronization parameters e.g. time and frequency offset based on the selected synchronization point.

System and method for radio cell synchronization

A system and method for MIB estimation including generating a signal model for rank=2, based on the reference signals of a received wireless signal; converting the signal model to a four-parameter representation; determining, for values of parameters derived from the four-parameter representation, whether mutual information per bit (MIB) values depend on a single parameter or on a plurality of parameters; if the MIB values depend on the single parameter, calculating MIB values based on the single parameter; and if the MIB values depend on the plurality of parameters, calculating MIB values based on the plurality of parameters. Calculating MIB values based on the single parameter, determining, whether MIB values depend on a single parameter or on a plurality of parameters and, calculating MIB values based on the plurality of parameters, are performed using a machine learning algorithm.

System and method for selecting transmission parameters

Systems and methods for adaptive demodulation of cellular device communications signals are provided. Cellular communications over a Long Term Evolution network can involve determining a demodulations scheme based on a service cell transmission mode, an interfering cell transmission mode, a modulation order (QAM) of interferer and an interference-to-noise ratio of cellular communications signals.

System and method for adaptive demodulation of cellular device communications

Device and method for writing Discrete Fourier transform (DFT) samples in a memory in a reorder stage, the memory includes memory banks, each having a dedicated address generator. The method includes: dividing the DFT samples into R(reorder) equally sized segments, where R(reorder) is the radix value of the reorder stage of the DFT; checking whether a number of butterfly computations per cycle of a reorder stage of the DFT operation times R(reorder), denoted as P, is not larger than the number of segments; if P is larger than the number of segments: further dividing the segments or sub-segments into X equally sized sub-segments, where X is a radix value of a next stage of the DFT operation until P is not larger than the number of sub-segments; and mapping the sub-segments to the memory, each in a separate row, with an offset that includes segment offset and sub-segment offset.

System and method for zero contention memory bank access in a reorder stage in mixed radix discrete fourier transform

A method and system for soft output multiple-input-multiple-output (MIMO) decoding may include generating a tree-graph based on: MIMO rank, number of bits per layer, and type of modulation, wherein the tree-graph comprises a root node, leaf nodes, nodes, and branches connecting the nodes; performing sphere decoding by determining a radius covering a subset of nodes within said tree-graph; managing, based on the sphere decoding, tables comprising metrics and counter metrics usable for log likelihood ratio (LLR) generation; predicting, based on a specified prediction scheme, counter metrics for paths in the tree-graph that comprise nodes and branches out of the determined radius; and updating the tables comprising the counter metrics with the predicted counter metric, in a case that the predicted counter metrics are better in maximum likelihood terms than the determined counter metrics.

System and method for tree-search enhancement by metric prediction based on incomplete paths in soft output MIMO decoder

A decoder to search a tree graph to decode a received signal. The tree graph may have a plurality of levels, each level having a plurality of nodes and each node representing a different value of an element of a candidate transmit signal corresponding to the received signal. The decoder may include a first module to execute a branch prediction at each branch node to select one of a plurality of candidate nodes stemming from the branch node that has a smallest distance increment, and a second module, running in parallel to the first module, to evaluate the branch prediction made by the first module at each branch node by computing an accumulated distance of the selected node. If the accumulated distance of the selected node is greater than or equal to a search radius, the first module may override the branch prediction and select an alternative candidate node.

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Karmiel, Israel

Zeev Kaplan