Abstract: Techniques are disclosed for the use of Crest Factor Reduction (CFR) technique that utilizes a cancellation pulse signal having a reduced length. The CFR technique may be applied to a signal to be transmitted, which may comprise a composite signal having one or more carrier signals. Each carrier signal of the composite signal may be filtered via a respective channel filter and then recombined to form the signal to be transmitted, on which the CFR operations are then applied. The length of the cancellation pulse signal is less than the number of taps of the channel filter with the largest number of taps. This reduction in cancellation pulse signal length significantly reduces the processing power required to perform the CFR operations while maintaining regulatory emissions compliance.

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: A vector processor is provided having an instruction set with a vector convolution function. The disclosed vector processor performs a convolution function between an input signal and a filter impulse response by obtaining a vector comprised of at least N1+N2-1 input samples; obtaining N2 time shifted versions of the vector (including a zero shifted version), wherein each time shifted version comprises N1 samples; and performing a weighted sum of the time shifted versions of the vector by a vector of N1 coefficients; and producing an output vector comprising one output value for each of the weighted sums. The vector processor performs the method, for example, in response to one or more vector convolution software instructions having a vector input. The vector can comprise a plurality of real or complex input samples and the filter impulse response can be expressed using a plurality of coefficients that are real or complex.

Abstract: A method and system for canonical channel estimation in the Long Term Evolution uplink where a multi-frequency signal is generated and then converted to frequency spectrum which is then convolved in the frequency domain with a truncated window function to obtain a time domain channel impulse response. The time domain channel impulse response can be then transformed to a frequency domain to produce a down sampled user channel response, which can be then linearly interpolated to provide a channel estimate for a plurality of subcarriers. Such an approach achieves channel estimation within Long Term Evolution at only canonical locations to reduce complexity without loss in channel entropy.

Abstract: A method and system for canonical channel estimation in the Long Term Evolution uplink where a multi-frequency signal is generated and then converted to frequency spectrum which is then convolved in the frequency domain with a truncated window function to obtain a time domain channel impulse response. The time domain channel impulse response can be then transformed to a frequency domain to produce a down sampled user channel response, which can be then linearly interpolated to provide a channel estimate for a plurality of subcarriers. Such an approach achieves channel estimation within Long Term Evolution at only canonical locations to reduce complexity without loss in channel entropy.