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Jim Shima

Jim Shima has a BSEE and MSEE, specializing in signal and image processing from the University of Florida.

He has been a signal processing practitioner, HW designer, and algorithm developer for over 30 years - leveraging DSP on everything from missile tracking to hearing aids.

He has developed several innovations in the field and even designed and implemented one of the first software-defined radios back in 1993.

Jim has held positions at TI, Qualcomm, Symmetricom, Ball Aerospace, and Trimble.

He is currently a technical fellow at BAE Systems, leading efforts on RF signal processing with AI, adaptive beamforming, and digital communications.

In his free time, Jim has also developed several real-time audio signal processing solutions vetted by Skywalker Sound and has even collaborated with legendary sound designer Ben Burtt on an audio-based physics engine for real-time sound effects synthesis.

Efficient DDC Implementation for Analytic Signal Processing

Status: Not yet available - Stay tuned!

Abstract: Most sampled systems rely on real-valued ADC data that is then converted to complex-valued (analytic) signals for processing. Examples include comm demodulators, channelizers, adaptive beamforming, phase interferometry, etc. Since conversion to complex-valued (I/Q) happens at the native sample rate post ADC, it uses an everly increasing number of MACs (multiply accumulates) per sec. This equates to more power draw for a given system, and efficient implementations bear the most fruit in mitigating computational load.

Description: Recall, analytic signals can be created using a Hilbert transform or using the modulation property of a half-complex mixer. Digital down converters are heavily used in SDRs and direct-sampled RF digital systems to mix signals to baseband, create analytic signals from real-valued inputs, and reduce the bandwidth of said signals (via resampling) to a more usable sample rate. Efficient filters such as the Hogenauer (CIC) were developed decades ago to help mitigate the use of multiplications during resampling. This talk goes over a very efficient implementation of a specific DDC that performs 2x decimation, does not use any multiplications for the mix operation, and only requires one FIR filter to create I/Q samples from real-valued inputs. This results in 4-8x reduction in computations compared to brute-force classical techniques.

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