Uplink Achievable Rate Maximization for Reconfigurable Intelligent Surface Aided Millimeter Wave Systems with Resolution-Adaptive ADCs

Yue Xiu, Jun Zhao, Ertugrul Basar, Marco Di Renzo, Wei Sun, Guan Gui, Ning Wei

Research output: Contribution to journalArticleScientificpeer-review

25 Citations (Scopus)

Abstract

In this letter, we investigate the uplink of a reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) multi-user system. In the considered system, however, problems with hardware cost and power consumption arise when massive antenna arrays coupled with power-demanding analog-to-digital converters (ADCs) are employed. To account for practical hardware complexity, we consider that the access point (AP) is equipped with resolution-adaptive analog-to-digital converters (RADCs). We maximize the achievable rate under hardware constraints by jointly optimizing the ADC quantization bits, the RIS phase shifts, and the beam selection matrix. The formulated problem is non-convex. To efficiently tackle this problem, a block coordinated descent (BCD)-based algorithm is proposed. Simulations demonstrate that an RIS can mitigate the hardware loss due to the use of RADCs, and that the proposed BCD-based algorithm outperforms state-of-the-art algorithms.

Original languageEnglish
Article number9390351
Pages (from-to)1608-1612
Number of pages5
JournalIEEE Wireless Communications Letters
Volume10
Issue number8
DOIs
Publication statusPublished - Aug 2021
Externally publishedYes
Publication typeA1 Journal article-refereed

Keywords

  • Block coordinated descent algorithm
  • millimeter-wave communication
  • reconfigurable intelligent surface
  • resolution-adaptive analog-to-digital converter

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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