Hybrid MIMO Architectures for Millimeter Wave Communications: Phase Shifters or Switches?

Roi Mendez-Rial, Cristian Rusu, Nuria Gonzalez-Prelcic, Ahmed Alkhateeb, Robert W. Heath

Research output: Contribution to journalArticle

322 Scopus citations

Abstract

Hybrid analog/digital multiple-input multiple-output architectures were recently proposed as an alternative for fully digital-precoding in millimeter wave wireless communication systems. This is motivated by the possible reduction in the number of RF chains and analog-to-digital converters. In these architectures, the analog processing network is usually based on variable phase shifters. In this paper, we propose hybrid architectures based on switching networks to reduce the complexity and the power consumption of the structures based on phase shifters. We define a power consumption model and use it to evaluate the energy efficiency of both structures. To estimate the complete MIMO channel, we propose an open-loop compressive channel estimation technique that is independent of the hardware used in the analog processing stage. We analyze the performance of the new estimation algorithm for hybrid architectures based on phase shifters and switches. Using the estimate, we develop two algorithms for the design of the hybrid combiner based on switches and analyze the achieved spectral efficiency. Finally, we study the tradeoffs between power consumption, hardware complexity, and spectral efficiency for hybrid architectures based on phase shifting networks and switching networks. Numerical results show that architectures based on switches obtain equal or better channel estimation performance to that obtained using phase shifters, while reducing hardware complexity and power consumption. For equal power consumption, all the hybrid architectures provide similar spectral efficiencies.

Original languageEnglish (US)
Article number7370753
Pages (from-to)247-267
Number of pages21
JournalIEEE Access
Volume4
DOIs
StatePublished - Jan 1 2016
Externally publishedYes

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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