Abstract: A system and method for removing bias from a frequency estimate. A simulation is used to predict, for various values of the signal to noise ratio, a bias in a raw frequency estimate produced by a frequency estimation algorithm. A straight line is fit to simulated frequency offset estimates as a function of true frequency offset, and the reciprocal of the slope of the line is stored, as a multiplicative bias removal term, in a lookup table, for the simulated signal to noise ratio. In operation, the raw frequency estimate is multiplied by a multiplicative bias removal term, obtained from the lookup table, to form a corrected frequency offset estimate.

Abstract: A method is provided. The method includes selecting a neural network model, wherein the neural network model includes a plurality of layers, and wherein each of the plurality of layers includes weights and activations; modifying the neural network model by inserting a plurality of quantization layers within the neural network model; associating a cost function with the modified neural network model, wherein the cost function includes a first coefficient corresponding to a first regularization term, and wherein an initial value of the first coefficient is pre-defined; and training the modified neural network model to generate quantized weights for a layer by increasing the first coefficient until all weights are quantized and the first coefficient satisfies a pre-defined threshold, further including optimizing a weight scaling factor for the quantized weights and an activation scaling factor for quantized activations, and wherein the quantized weights are quantized using the optimized weight scaling factor.

Abstract: An apparatus and a method. The apparatus includes a channel estimation (CE) module, including a first input for receiving pilot resource element (RE) observations, a second input for receiving data RE observations, a third input for receiving log-likelihood ratios (LLRs), and an output; a detector, including a first input connected to the output of the CE module, a second input for receiving data RE observations, and an output connected to the third input of the CE module; and a decoder, including an input connected to the third input of the CE module, and an output.

Abstract: A method of displaying an image is provided, the method including displaying an item for providing content or information regarding the content and a pointed location corresponding to a received input; determining a distance from the pointed location to the item; determining an amount or a type of information corresponding to the item to display, based on the determined distance; and displaying information corresponding to the item, based on the determined amount or type of information.

Abstract: A system and method for characterizing an interference demodulation reference signal (DMRS) in a piece of user equipment (UE), e.g., a mobile device. The UE determines whether the serving signal is transmitted in a DMRS-based transmission mode; if it is, the UE cancels the serving DMRS from the received signal; otherwise the UE cancels the serving data signal from the received signal. The remaining signal is then analyzed for the amount of power it has in each of four interference DMRS candidates, and hypothesis testing is performed to determine whether interference DMRS is present in the signal, and, if so, to determine the rank of the interference DMRS, and the port and scrambling identity of each of the interference DMRS layers.

Abstract: Disclosed herein is convolutional neural network (CNN) system for generating a classification for an input image. According to an embodiment, the CNN system comprises a sequence of neural network layers configured to: derive a feature map based on at least the input image; puncture at least one selection among the feature map and a kernel by setting the value of one or more elements of a row of the at least one selection to zero according to a pattern and cyclic shifting the pattern by a predetermined interval per row to set the value of one or more elements of the rest of the rows of the at least one selection according to the cyclic shifted pattern; convolve the feature map with the kernel to generate a first convolved output; and generate the classification for the input image based on at least the first convolved output.

Abstract: A system and method for characterizing an interference demodulation reference signal (DMRS) in a piece of user equipment (UE), e.g., a mobile device. The UE determines whether the serving signal is transmitted in a DMRS-based transmission mode; if it is, the UE cancels the serving DMRS from the received signal; otherwise the UE cancels the serving data signal from the received signal. The remaining signal is then analyzed for the amount of power it has in each of four interference DMRS candidates, and hypothesis testing is performed to determine whether interference DMRS is present in the signal, and, if so, to determine the rank of the interference DMRS, and the port and scrambling identity of each of the interference DMRS layers.

Abstract: A system and method for characterizing an interference demodulation reference signal (DMRS) in a piece of user equipment (UE), e.g., a mobile device. The UE determines whether the serving signal is transmitted in a DMRS-based transmission mode; if it is, the UE cancels the serving DMRS from the received signal; otherwise the UE cancels the serving data signal from the received signal. The remaining signal is then analyzed for the amount of power it has in each of four interference DMRS candidates, and hypothesis testing is performed to determine whether interference DMRS is present in the signal, and, if so, to determine the rank of the interference DMRS, and the port and scrambling identity of each of the interference DMRS layers.

Abstract: A system and method for removing bias from a frequency estimate. A simulation is used to predict, for various values of the signal to noise ratio, a bias in a raw frequency estimate produced by a frequency estimation algorithm. A straight line is fit to simulated frequency offset estimates as a function of true frequency offset, and the reciprocal of the slope of the line is stored, as a multiplicative bias removal term, in a lookup table, for the simulated signal to noise ratio. In operation, the raw frequency estimate is multiplied by a multiplicative bias removal term, obtained from the lookup table, to form a corrected frequency offset estimate.

Abstract: Apparatuses and methods of manufacturing same, systems, and methods for performing network parameter quantization in deep neural networks are described. In one aspect, multi-dimensional vectors representing network parameters are constructed from a trained neural network model. The multi-dimensional vectors are quantized to obtain shared quantized vectors as cluster centers, which are fine-tuned. The fine-tuned and shared quantized vectors/cluster centers are then encoded. Decoding reverses the process.

Abstract: Apparatuses and methods of manufacturing same, systems, and methods for performing network parameter quantization in deep neural networks are described. In one aspect, diagonals of a second-order partial derivative matrix (a Hessian matrix) of a loss function of network parameters of a neural network are determined and then used to weight (Hessian-weighting) the network parameters as part of quantizing the network parameters. In another aspect, the neural network is trained using first and second moment estimates of gradients of the network parameters and then the second moment estimates are used to weight the network parameters as part of quantizing the network parameters. In yet another aspect, network parameter quantization is performed by using an entropy-constrained scalar quantization (ECSQ) iterative algorithm. In yet another aspect, network parameter quantization is performed by quantizing the network parameters of all layers of a deep neural network together at once.

Abstract: A method of obtaining identification information, and based on the obtained identification, wirelessly transmitting content between apparatuses, and a content transmission apparatus are provided. The method obtains the identification information on a content reception apparatus or a content backup apparatus by using an affordance function of a content transmission apparatus or a content providing apparatus. The method and the content transmission apparatus include obtaining identification information on a second apparatus by using a first apparatus; outputting confirmation information on the second apparatus from the first apparatus, based on the obtained identification information on the second apparatus; and wirelessly transmitting the content from the first apparatus to the second apparatus, so as to enable the content to be conveniently transmitted between the apparatuses and to provide easy accessibility to a content reception apparatus.

Abstract: A method of displaying an image is provided, the method including displaying an item for providing content or information regarding the content and a pointed location corresponding to a received input; determining a distance from the pointed location to the item; determining an amount or a type of information corresponding to the item to display, based on the determined distance; and displaying information corresponding to the item, based on the determined amount or type of information.

Abstract: An apparatus and a method. The apparatus includes a channel estimation (CE) module, including a first input for receiving pilot resource element (RE) observations, a second input for receiving data RE observations, a third input for receiving log-likelihood ratios (LLRs), and an output; a detector, including a first input connected to the output of the CE module, a second input for receiving data RE observations, and an output connected to the third input of the CE module; and a decoder, including an input connected to the third input of the CE module, and an output.

Abstract: Provided are a method and apparatus for displaying contents-related items. The method includes using a correlation between a first attribute and a second attribute to determine values of the second attribute, wherein the first attribute is one of a plurality of attributes of the contents-related items, the second attribute is one of a plurality of attributes of a plurality of blocks which is a part or a region of a screen, and each one of the plurality of blocks corresponds to each one contents-related item; and displaying the one or more contents-related items by displaying each corresponding block having the determined value of the second attribute on the screen, wherein the first attribute and the second attribute can be quantitatively represented.

Abstract: A computing system includes: an inter-device interface configured to receive receiver signal for communicating serving content through a communication channel; a communication unit, coupled to the inter-device interface, configured to: calculate a weighting set corresponding to a modular estimation mechanism, and generate a channel estimate based on the weighting set for characterizing the communication channel for recovering the serving content.

Abstract: A display system, a display apparatus, a remote control apparatus, and a method for controlling the same are provided. The display system according to the exemplary embodiment: a display apparatus; and a remote control apparatus sensing a motion and transmitting the sensed motion information to the display apparatus. The display apparatus displays a UI element when receiving motion information of the remote control apparatus and displays image contents when receiving a power on command from the remote control apparatus while the UI element is displayed.