Abstract:
A method of operation of a wireless communication system includes: tuning a receiver front end for receiving a radio-frequency signal; correcting, with an in-phase/quadrature (I/Q) compensation module, an I/Q imbalance from the receiver front end including estimating by a linear minimum mean-square error (LMMSE) module; and processing by a base band receiver for digitizing an output of the I/Q compensation module for generating a receiver data.
Abstract:
A concatenated encoder is provided that includes an outer encoder, a symbol interleaver and a polar inner encoder. The outer encoder is configured to encode a data stream using an outer code to generate outer codewords. The symbol interleaver is configured to interleave symbols of the outer codewords and generate a binary stream. The polar inner encoder is configured to encode the binary stream using a polar inner code to generate an encoded stream. A concatenated decoder is provided that includes a polar inner decoder, a symbol de-interleaver and an outer decoder. The polar inner decoder is configured to decode an encoded stream using a polar inner code to generate a binary stream. The symbol de-interleaver is configured to de-interleave symbols in the binary stream to generate outer codewords. The outer decoder is configured to decode the outer codewords using an outer code to generate a decoded stream.
Abstract:
A computing system includes: a sensor configured to receive an input observation including a sample count for processing an original content; and a control unit, coupled to the sensor, configured to: generate a covariance estimate based on the input observation for identifying the original content associated with the input observation for implementing a linear estimation mechanism, and calculate a weight combination based on the covariance estimate for identifying the original content.
Abstract:
A communication system includes: a covariance module configured to calculate a joint-covariance based on a receiver signal for communicating a communication content in a transmitter signal with an interference signal using subcarriers based on a space-frequency block-coding scheme; a preparation module, coupled to the covariance module, configured to generate a joint-whitener with a control unit based on the joint-covariance for randomizing the interference signal; a joint whitening module, coupled to the preparation module, configured to generate a joint-whitening output based on the receiver signal and the joint-whitener; a message processing module, coupled to the joint whitening module, configured to determine a joint-estimation feedback based on the joint-whitening output; and a cancellation module, coupled to the message processing module, configured to cancel the joint-estimation feedback from the receiver signal for communicating the communication content with a device.
Abstract:
A wireless communication system includes: a control module configured to calculate a maximum throughput to represent a spectral efficiency; a storage module, coupled to the control module, configured to store the maximum throughput in a throughput table; and a communication module, coupled to the control module, configured to transmit a channel quality indicator as a feedback, selected from the throughput table, based on a largest value of the maximum throughput.
Abstract:
Methods and devices are provided for performing federated learning. A global model is distributed from a server to a plurality of client devices. At each of the plurality of client devices: model inversion is performed on the global model to generate synthetic data; the global model is on an augmented dataset of collected data and the synthetic data to generate a respective client model; and the respective client model is transmitted to the server. At the server: client models are received from the plurality of client devices, where each client model is received from a respective client device of the plurality of client devices; model inversion is performed on each client model to generate a synthetic dataset; the client models are averaged to generate an averaged model; and the averaged model is trained using the synthetic dataset to generate an updated model.
Abstract:
An electronic device is provided. The electronic device includes a memory and a processor operatively connected to the memory, wherein the processor may obtain a maximum allowable bit rate of the electronic device, determine a maximum quantization value for encoding an image composed of at least one frame, obtain a first bitrate by encoding a first frame set of the image with a quantization value equal to or less than the maximum quantization value, increase the maximum quantization value in response to the obtained first bitrate exceeding the maximum allowable bitrate, decrease the maximum quantization value in response to the obtained first bitrate being less than or equal to the maximum allowable bitrate, obtain a second bitrate by encoding a second frame set subsequent to the first frame set of the image based on the increased or decreased maximum quantization value, increase the maximum quantization value in response to the obtained second bitrate exceeding the maximum allowable bitrate, and decrease the maximum quantization value in response to the obtained second bitrate being less than or equal to the maximum allowable bitrate.
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.