Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, Apr. 15-20, 2018, Calgary, Alberta, Canada.

Narrowband Channel Estimation for Hybrid Beamforming Millimeter Wave Communication Systems with One-Bit Quantization

Junmo Sung, Jinseok Choi, and Brian L. Evans

Department of Electrical and Computer Engineering, Wireless Networking and Communications Group, The University of Texas at Austin, Austin, TX 78712 USA - -

Paper Draft - Poster - Software Release

Related journal paper:
"Resolution-Adaptive Hybrid MIMO Architectures for Millimeter Wave Communications" (2018)

Related conference paper:
"ADC Bit Optimization for Spectrum- and Energy-Efficient Millimeter Wave Communications" (2007)

Related poster: "ADC Bit Allocation under a Power Constraint for MmWave Massive MIMO Communication Receivers"

Multiantenna Communications Project


Millimeter wave (mmWave) spectrum has drawn attention due to its tremendous available bandwidth. The high propagation losses in the mmWave bands necessitate beamforming with a large number of antennas. Traditionally each antenna is paired with a high-speed analog-to-digital converters (ADC), which results in high power consumption. A hybrid beamforming architecture and one-bit resolution ADCs have been proposed to reduce power consumption. However, analog beamforming and one-bit quantization make channel estimation more challenging. In this paper, we propose a narrowband channel estimation algorithm for mmWave communication systems with one-bit ADCs and hybrid beamforming based on generalized approximate message passing (GAMP). We show through simulation that
  1. GAMP variants with one-bit ADCs have better performance than do least-squares estimation methods without quantization,
  2. the proposed one-bit GAMP algorithm achieves the lowest estimation error among the GAMP variants, and
  3. exploiting more frames and RF chains enhances the channel estimation performance.

Questions & Answers

Q1) Why does the NMSE increase after a certain point in SNR?
A1) It is like the dithering effect. When SNR is too high, the thermal noise becomes too negligible to cause the dithering effect, which leads to degrading performance.

Q2) Why are other quantization bits, e.g. 2, 3 and 4 bits, not considered?
A2) The proposed modified one-bit GAMP is specialized for one-bit quantizers. It is not tested or verified for higher quantization resolution.

Q3) Why are analog beamformers randomly configured?
A3) With high probability, the randomly configured beamformers is expected to satisfy the restricted isometry property condition. Since it is not always true, however, I am working on optimal configuration of hybrid beamformers rather than random one.

Q4) Why GAMP?
A4) Since GAMP has both linear and non-linear steps in each iteration, it matches our system model where low-resolution quantizers cause great non-linear distortion.

COPYRIGHT NOTICE: All the documents on this server have been submitted by their authors to scholarly journals or conferences as indicated, for the purpose of non-commercial dissemination of scientific work. The manuscripts are put on-line to facilitate this purpose. These manuscripts are copyrighted by the authors or the journals in which they were published. You may copy a manuscript for scholarly, non-commercial purposes, such as research or instruction, provided that you agree to respect these copyrights.

Last Updated 06/02/18.