IMDEA Networks Institute Publications Repository

Speeding Up mmWave Beam Training through Low-Complexity Hybrid Transceivers

Palacios, Joan and De Donno, Danilo and Giustiniano, Domenico and Widmer, Joerg (2016) Speeding Up mmWave Beam Training through Low-Complexity Hybrid Transceivers. In: The 27th Annual IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (IEEE PIMRC 2016), 4-7 September 2016, Valencia, Spain.

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Millimeter wave (mmWave) wireless technologies are expected to become key enablers of multi-gigabit wireless access in next-generation cellular and local area networks. Due to unfavorable radio propagation, mmWave systems will exploit large-scale MIMO and adaptive antenna arrays at both the transmitter and receiver to realize sufficient link margin. Unfortunately, power and cost requirements in mmWave radio frontends make the use of fully-digital beamforming very challenging. In this paper, we focus on hybrid analog-digital beamforming and address two relevant aspects of the initial access procedure at mmWave frequencies. First, we propose a beam training protocol which effectively accelerates the link establishment by exploiting the ability of mobile users to simultaneously receive from multiple directions. Second, we deal with practical constraints of mmWave transceivers and propose a novel, geometric approach to synthesize multi-beamwidth beam patterns that can be leveraged for simultaneous multi-direction scanning. Simulation results show that the proposed hybrid codebooks are able to shape beam patterns very close to those attained by a fully-digital beamforming architecture, yet require lower complexity hardware compared with the state of the art. Furthermore, the reduced duration of the beam training phase, in turn enabled by the multi-beam characteristics of our hybrid codebooks, provides a 25% to 70% increase in spectral efficiency compared to existing sequential scanning strategies.

Item Type: Conference or Workshop Papers (Paper)
Uncontrolled Keywords: Millimeter wave systems, hybrid beamforming, beam training, channel estimation, antenna patterns.
Depositing User: Danilo De Donno
Date Deposited: 10 Jun 2016 11:04
Last Modified: 06 Nov 2020 12:58

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