Telefonaktiebolaget Lm Ericsson (Publ)

Chinese Academy of Sciences

Qi Qin

Huaisong Zhu

Christian Skärby

Jie Yang

Cong Shi

Nanjian Wu

Xitian Long

A method and an apparatus for uplink transmission control are disclosed. According to an embodiment, a base station determines a channel metric for indicating uplink channel condition between the base station and a terminal device. The base station determines an uplink transmission format that is to be used for an initial transmission from the terminal device, based on the channel metric such that a spectrum efficiency for the initial transmission can be maximized.

Method and apparatus for uplink transmission control

A method performed by a network node, for handling link adaption (LA) of a channel. The network node obtains a channel quality value for each Transmission Time Interval (TTI) in a set of TTIs. The network node estimates a probability that a specific channel quality will occur from the obtained channel quality values for the set of TTIs based on a distribution of channel quality values. The network node further determines a set of transmission parameters which optimizes a target function of LA, based on the estimated probability for the channel quality, wherein each set of transmission parameters is mapped to a channel quality which is required for a successful reception.

Method and network node, for handling link adaption of a channel

The present invention proposes a dynamically reconfigurable multi-level parallel single instruction multiple data array processing system which has a pixel level parallel image processing element array and a row-parallel array processor. The PE array mainly implements a linear operation which is adapted to be executed in parallel in the low and middle levels of image processing and the RP array implements an operation which is adapted to execute in row-parallel in the low and middle levels of image processing or more complex nonlinear operations. In particularly, such a system can be dynamically reconfigured as an SOM neural network at a low cost of area, and the neural network supports high level of image processing such as a high speed online neural network training and image feature recognition, and completely overcomes a defect that a high level of image processing can't be done by pixel-level parallel processing array in the existing programmable vision chips and parallel vision processors, and facilitates an intelligent and portable real time on-chip vision image system with a complete function at low device cost and low power consumption.

Dynamically reconstructable multistage parallel single instruction multiple data array processing system

Growing community of inventors

Beijing, China

Qi Qin