Accurate Angular Inference for 802.11ad Devices Using Beam-Specific Measurements

Haichuan Ding*, Kang G. Shin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Due to their sparsity, 60GHz channels are characterized by a few dominant paths. Knowing the angular information of their dominant paths, we can develop various applications, such as the prediction of link performance and the tracking of 802.11ad devices. Although they are equipped with phased arrays, the angular inference for 802.11ad devices is still challenging due to their limited number of RF chains and limited phase control capabilities. Considering the beam sweeping operation and the high communication bandwidth of 802.11ad devices, we propose variation-based angle estimation (VAE), called VAE-CIR, by utilizing beam-specific channel impulse responses (CIRs) measured under different beams and the directional gains of the corresponding beams to infer the angular information of dominant paths. Unlike state-of-the-arts, VAE-CIR exploits the variations between different beam-specific CIRs for angular inference and provides a performance guarantee in the high signal-to-noise-ratio regime. To evaluate VAE-CIR, we generate the beam-specific CIRs by simulating the beam sweeping of 802.11ad devices with the beam patterns measured on off-the-shelf 802.11ad devices. The 60GHz channel is generated via a ray-tracing-based simulator and the CIRs are extracted via channel estimation based on Golay sequences. Through extensive experiments, VAE-CIR is shown to achieve more accurate angle estimation than existing schemes.

Original languageEnglish
Pages (from-to)822-834
Number of pages13
JournalIEEE Transactions on Mobile Computing
Volume21
Issue number3
DOIs
Publication statusPublished - 1 Mar 2022

Keywords

  • IEEE 802.11ad
  • angular inference
  • mmWave communications

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Ding, H., & Shin, K. G. (2022). Accurate Angular Inference for 802.11ad Devices Using Beam-Specific Measurements. IEEE Transactions on Mobile Computing, 21(3), 822-834. https://doi.org/10.1109/TMC.2020.3015936