Channel estimation and hybrid precoding for millimeter wave cellular systems

Ahmed Alkhateeb, Omar El Ayach, Geert Leus, Robert W. Heath

Research output: Contribution to journalArticlepeer-review

1294 Scopus citations

Abstract

Millimeter wave (mmWave) cellular systems will enable gigabit-per-second data rates thanks to the large bandwidth available at mmWave frequencies. To realize sufficient link margin, mmWave systems will employ directional beamforming with large antenna arrays at both the transmitter and receiver. Due to the high cost and power consumption of gigasample mixed-signal devices, mmWave precoding will likely be divided among the analog and digital domains. The large number of antennas and the presence of analog beamforming requires the development of mmWave-specific channel estimation and precoding algorithms. This paper develops an adaptive algorithm to estimate the mmWave channel parameters that exploits the poor scattering nature of the channel. To enable the efficient operation of this algorithm, a novel hierarchical multi-resolution codebook is designed to construct training beamforming vectors with different beamwidths. For single-path channels, an upper bound on the estimation error probability using the proposed algorithm is derived, and some insights into the efficient allocation of the training power among the adaptive stages of the algorithm are obtained. The adaptive channel estimation algorithm is then extended to the multi-path case relying on the sparse nature of the channel. Using the estimated channel, this paper proposes a new hybrid analog/digital precoding algorithm that overcomes the hardware constraints on the analog-only beamforming, and approaches the performance of digital solutions. Simulation results show that the proposed low-complexity channel estimation algorithm achieves comparable precoding gains compared to exhaustive channel training algorithms. The results illustrate that the proposed channel estimation and precoding algorithms can approach the coverage probability achieved by perfect channel knowledge even in the presence of interference.

Original languageEnglish (US)
Article number6847111
Pages (from-to)831-846
Number of pages16
JournalIEEE Journal on Selected Topics in Signal Processing
Volume8
Issue number5
DOIs
StatePublished - Oct 1 2014
Externally publishedYes

Keywords

  • Millimeter wave cellular systems
  • adaptive compressed sensing
  • hybrid precoding
  • sparse channel estimation

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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