Abstract:
Techniques are disclosed for the use of Crest Factor Reduction (CFR) algorithm that performs oversampling of an input signal and a cancellation pulse, and detects a set of peak samples in the upsampled input signal that exceed a predetermined threshold value. The peak samples are clustered such that a subset of the oversampled signal peaks are used to compute gain factors for the generation of a scaled truncated upsampled cancellation pulse. Several scaled truncated upsampled cancellation pulses are applied in parallel to perform peak cancellation of the highest peak in each cluster as part of an initial peak cancellation process. Any remaining peaks are canceled by iterative gain factors computation process. A final cancellation pulse is then generated by multiplying a cancellation pulse by the computed gain factors.
Abstract:
Millimeter wave (mmWave) technology, apparatuses, and methods that relate to transceivers, receivers, and antenna structures for wireless communications are described. The various aspects include co-located millimeter wave (mmWave) and near-field communication (NFC) antennas, scalable phased array radio transceiver architecture (SPARTA), phased array distributed communication system with MIMO support and phase noise synchronization over a single coax cable, communicating RF signals over cable (RFoC) in a distributed phased array communication system, clock noise leakage reduction, IF-to-RF companion chip for backwards and forwards compatibility and modularity, on-package matching networks, 5G scalable receiver (Rx) architecture, among others.
Abstract:
A digital-to-analog converter is provided. The digital-to-analog converter includes a first plurality of digital-to-analog converter cells configured to generate a first analog signal. Further, digital-to-analog converter includes a second plurality of digital-to-analog converter cells configured to generate a second analog signal. The first analog signal and the second analog signal form a differential signal pair. Further, the digital-to-analog converter includes a transmission line transformer comprising a first input node coupled to the first plurality of digital-to-analog converter cells, a second input node coupled to the second plurality of digital-to-analog converter cells, and a first output node. The transmission line transformer is configured to present a first impedance at the first and second input nodes and to present a second impedance at the first output node.
Abstract:
A digital-to-analog conversion system is provided. The digital-to-analog conversion system includes a digital-to-analog converter configured to receive a pre-distorted digital signal from a digital circuit, and to generate an analog signal based on the pre-distorted digital signal. Further, the digital-to-analog conversion system includes a feedback loop for providing a digital feedback signal to the digital circuit. The feedback loop includes an analog-to-digital converter configured to generate the digital feedback signal based on the analog signal, and wherein a sample rate of the analog-to-digital converter is lower than a sample rate of the digital-to-analog converter.
Abstract:
A digital-to-analog converter is provided. The digital-to-analog converter includes a first plurality of digital-to-analog converter cells configured to generate a first analog signal. Further, digital-to-analog converter includes a second plurality of digital-to-analog converter cells configured to generate a second analog signal. The first analog signal and the second analog signal form a differential signal pair. Further, the digital-to-analog converter includes a transmission line transformer comprising a first input node coupled to the first plurality of digital-to-analog converter cells, a second input node coupled to the second plurality of digital-to-analog converter cells, and a first output node. The transmission line transformer is configured to present a first impedance at the first and second input nodes and to present a second impedance at the first output node.
Abstract:
Software Digital Front End (SoftDFE) signal processing techniques are provided. One or more digital front end (DFE) functions are performed on a signal in software by executing one or more specialized instructions on a processor to perform the one or more digital front end (DFE) functions on the signal, wherein the processor has an instruction set comprised of one or more of linear and non-linear instructions. A block of samples comprised of a plurality of data samples is optionally formed and the digital front end (DFE) functions are performed on the block of samples. The specialized instructions can include a vector convolution function, a complex exponential function, an xk function, a vector compare instruction, a vector max( ) instruction, a vector multiplication instruction, a vector addition instruction, a vector sqrt( ) instruction, a vector 1/x instruction, and a user-defined non-linear instruction.
Abstract:
Maximum likelihood bit-stream generation and detection techniques are provided using the M-algorithm and Infinite Impulse Response (IIR) filtering. The M-Algorithm is applied to a target input signal X to perform Maximum Likelihood Sequence Estimation on the target input signal X to produce a digital bit stream B, such that after filtering by an IIR filter, the produced digital stream Y produces an error signal satisfying one or more predefined requirements. The predefined requirements comprise, for example, a substantially minimum error. In an exemplary bit detection implementation, the target input signal X comprises an observed analog signal and the produced digital stream Y comprises a digitized output of a receive channel corresponding to a transmitted bit stream. In an exemplary bit stream generation implementation, the target input signal X comprises a desired transmit signal and the produced digital stream Y comprises an estimate of the desired transmit signal.
Abstract:
Methods and apparatus are provided for direct synthesis of RF signals using maximum likelihood sequence estimation. An RF digital RF input signal is synthesized by performing maximum likelihood sequence estimation on the digital RF input signal to produce a digital stream, such that after filtering by a prototype filter the produced digital stream produces a substantially minimum error. The substantially minimum error comprises a difference between a digital output of the prototype filter and the digital RF input signal. The digital stream is substantially equal to the input digital RF signal. The digital stream can be applied to an analog restitution filter, and the output of the analog restitution filter comprises an analog RF signal that approximates the digital RF input signal.
Abstract:
A processor is provided having an instruction set with a sliding window non-linear convolution function. A processor obtains a software instruction that performs a non-linear convolution function for a plurality of input delayed signal samples. In response to the software instruction for the non-linear convolution function, the processor generates a weighted sum of two or more of the input delayed signal samples, wherein the weighted sum comprises a plurality of variable coefficients defined as a sum of one or more non-linear functions of a magnitude of the input delayed signal samples; and repeats the generating step for at least one time-shifted version of the input delayed signal samples to compute a plurality of consecutive outputs. The software instruction for the non-linear convolution function is optionally part of an instruction set of the processor. The non-linear convolution function can model a non-linear system with memory, such as a power amplifier model and/or a digital pre-distortion function.
Abstract:
Methods and apparatus are provided for non-linear modeling of a physical system using look-up tables with polynomial interpolation. A non-linear function is evaluated for a complex input value by obtaining at least one look-up table with polynomial interpolation that represents the non-linear function, wherein entries in the look-up table comprise polynomial coefficients of at least degree two for different segments of the non-linear function; obtaining a point from the look-up table that is near a magnitude of the complex input value; and generating a complex output value by evaluating the polynomial coefficients at the point to perform a Taylor Series expansion from said point. The non-linear function characterizes, for example, a power amplifier or an inverse of a power amplifier and the look-up tables can be used, for example, to implement digital pre-distortion.