TR2018-074

Massive MIMO Channel Estimation using Signed Measurements with Antenna-Varying Thresholds

    •  Liu, F., Zhu, H., Li, J., Wang, P., Orlik, P.V., "Massive MIMO Channel Estimation using Signed Measurements with Antenna-Varying Thresholds", IEEE Statistical Signal Processing Workshop (SSP), DOI: 10.1109/​SSP.2018.8450804, June 2018, pp. 188-192.
      BibTeX TR2018-074 PDF
      • @inproceedings{Liu2018jun,
      • author = {Liu, Fangqing and Zhu, Heng and Li, Jian and Wang, Pu and Orlik, Philip V.},
      • title = {Massive MIMO Channel Estimation using Signed Measurements with Antenna-Varying Thresholds},
      • booktitle = {IEEE Statistical Signal Processing Workshop (SSP)},
      • year = 2018,
      • pages = {188--192},
      • month = jun,
      • doi = {10.1109/SSP.2018.8450804},
      • url = {https://www.merl.com/publications/TR2018-074}
      • }
  • MERL Contacts:
  • Research Areas:

    Communications, Signal Processing

Abstract:

This paper investigates angular-domain channel estimation for massive multiple-input multiple-output (MIMO) systems using signed measurements with antenna-varying thresholds. We derive the Cramer-Rao bounds (CRBs) for estimating angles-of-arrival (AoAs), angles-of-departure (AoDs) and associated path gains and compare them with their counterparts of using time-varying and zero thresholds. We then introduce the maximum likelihood (ML) method to estimate the massive MIMO channel parameters. Since the ML estimator is computationally prohibitive, we also consider a relaxation based cyclic algorithm, referred to as one-bit RELAX, for massive MIMO channel estimation. Numerical results are provided to compare the performances of using different thresholding schemes to obtain signed measurements and to verify the effectiveness of the one-bit RELAX algorithm for channel estimation.