Software Releases

The following software has been developed by the Embedded Signal Processing Laboratory at UT Austin. The software releases are freely distributable.

Antenna Selection - Channel Estimation - Handover (Band Switching) - Resolution Adaptive - Signal Compression - Statistical Interference Models - Two-Stage Analog Beamforming - User Scheduling - Complex Block Floating Point

Antenna Selection for Millimeter Wave (mmWave) Cellular Systems (New Radio)

  1. Jinseok Choi and Brian L. Evans, "Antenna Selection for Large-Scale MIMO Systems with Low-Resolution ADCs with Online Training of the Quantizer Model", Version 2.0 (February 16, 2018). Variation on the Version 1.0 release for the ICASSP 2018 paper below. The MMSE quantizer model is updated at each transmission and selection.
  2. Jinseok Choi and Brian L. Evans, "Antenna Selection for Large-Scale MIMO Systems with Low-Resolution ADCs with Offline Training of the Quantizer Model", Version 2.0 (February 16, 2018). Variation on the Version 1.0 release for the ICASSP 2018 paper below. The MMSE quantizer model is updated only once for the given simulation environment.
  3. Jinseok Choi and Brian L. Evans, "Antenna Selection for Large-Scale MIMO Systems with Low-Resolution ADCs", MATLAB code to accompany a paper of the same title in the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing. Version 1.0 (October 27, 2017).

Channel Estimation for Millimeter Wave (mmWave) Cellular Systems (New Radio)

  1. Junmo Sung, Jinseok Choi and Brian L. Evans, "Narrowband Channel Estimation for Hybrid Beamforming Millimeter Wave Communication Systems with One-Bit Quantization", MATLAB code to accompany a paper of the same title in the 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing. Version 1.0 (October 27, 2017).
  2. Junmo Sung, Jinseok Choi and Brian L. Evans, "Wideband Millimeter Wave Channel Estimation Algorithms", MATLAB code for wideband channel estimation algorithms for hybrid beamforming millimeter wave communication systems with low-resolution analog-to-digital converters (ADCs). Version 1.0 (October 13, 2017).

Handover for Millimeter Wave (mmWave) Cellular Systems (New Radio)

  1. Faris Mismar and Brian L. Evans, "Deep Learning Predictive Band Switching in Wireless Networks", Python code for predictive machine learning algorithms that switch between a lower (e.g. 3.5 GHz) band and a millimeter waveband (e.g. 28 GHz) by learning the spatial and spectral correlation between the radio frequency signals in the different bands based on knowledge of the user equipment location. Version 1.0 (Sept. 29, 2019)

Resolution-Adaptive Hybrid MIMO Architectures

  1. Jinseok Choi and Brian L. Evans, "Resolution-Adaptive Hybrid MIMO Architectures for Millimeter Wave Communications", MATLAB code to accompany a paper of the same title in the IEEE Transactions on Signal Processing, vol. 65, no. 23, pp. 6201-6216, Dec. 2017, DOI 10.1109/TSP.2017.2745440. Software release is version 1.0 (Nov. 15, 2018).

Signal Compression for Basestations

  1. Jinseok Choi and Brian L. Evans, "Space-Time Baseband LTE Compression Software", copyright © 2016 by The University of Texas. This MATLAB release implements algorithms to compress uplink baseband cellular LTE signals received by an antenna array. Software release accompanies the paper "Space-Time Fronthaul Compression of Complex Baseband Uplink LTE Signals" in the 2016 IEEE International Conference on Communications. Version 1.0 (April 4, 2016).
  2. Karl F. Nieman, Marcel Nassar, Jing Lin and Brian L. Evans, "Approximate Message Passing (AMP) Receiver". Release contains an AMP algorithm for decoding complex-valued orthogonal frequency division multiplexing (OFDM) signals. The algorithm estimates the impulsive noise observed on the null tones at the receiver to subtract out an estimate of the impulsive noise in the current OFDM frame. The AMP algorithm models the impulsive noise using a two-term Gaussian mixture model. Version 1.0 (June 5, 2013) contains two components:

Statistical Models for Co-Channel Interference

  1. Kapil Gulati, Marcel Nassar, Aditya Chopra, Nnaemeka Ben Okafor, Marcus R. DeYoung, Navid Aghasadeghi, Arvind Sujeeth, and Brian L. Evans, "Radio Frequency Interference Modeling and Mitigation Toolbox in MATLAB", copyright © 2006-2011 by The University of Texas. This toolbox provides a simulation environment for generating radio frequency interference (RFI) and quantifying the performance of algorithms for parameter estimation and interference mitigation. Release includes 56 files with 10,280 lines and 430 kB of Matlab code. Version 1.6 (April 1, 2011).

Two-Stage Analog Beamforming

  1. Jinseok Choi and Brian L. Evans, "Two-Stage Analog Beamforming", MATLAB code to accompany a paper entitled "Two-Stage Analog Combining in Hybrid Beamforming Systems with Low-Resolution ADCs" in the IEEE Transactions on Signal Processing, vol. 67, no. 9, May 1, 2019, pp. 2410-2425, DOI 10.1109/TSP.2019.2904931. Version 1.0 (July 27, 2019)

User Scheduling for Millimeter Wave (mmWave) Cellular Communications (New Radio)

  1. Jinseok Choi and Brian L. Evans, "User Scheduling Algorithms for Millimeter Wave MIMO Systems", MATLAB code to accompany a paper of the same title in the 2018 IEEE International Conference on Communications. Version 1.0 (October 13, 2017).

Complex Block Floating Point Formats for IQ Samples

  1. Yeong Choo and Brian L. Evans, "Complex Block Floating-Point Format with Box Encoding For Wordlength Reduction in Communication Systems", MATLAB code to accompany a paper for the 2017 Asilomar Conferenece Signals, Systems and Computers, Version 1.0 (October 16, 2017).

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