IEEE Transactions on Signal Processing, submitted April 10, 2017.

Resolution-Adaptive Hybrid MIMO Architectures for Millimeter Wave Communications

Jinseok Choi (1), Brian L. Evans (1) and Alan Gatherer (2)

(1) Department of Electrical and Computer Engineering, Wireless Networking and Communications Group, The University of Texas at Austin, Austin, TX 78712 USA
jinseokchoi89@gmail.com - bevans@ece.utexas.edu

(2) Huawei Technologies, Plano, Texas USA

Paper Draft - Archive Page

Related paper: "Space-Time Fronthaul Compression of Complex Baseband Uplink LTE Signals" (2016)

Related poster: "ADC Bit Allocation under a Power Constraint for MmWave Massive MIMO Communication Receivers"

Multiantenna Communications Project

Abstract

Hybrid analog-digital beamforming architectures with low-resolution analog-to-digital converters (ADCs) reduce hardware cost and power consumption in multiple-input multiple-output (MIMO) millimeter wave (mmWave) communication systems. In this paper, we propose a hybrid architecture with resolution-adaptive ADCs for mmWave receivers with large antenna arrays. We adopt array response vectors for the analog combiners and derive ADC bit allocation (BA) algorithms. The two proposed BA algorithms minimize the mean square quantization error of received analog signals under a total ADC power constraint. It is beneficial to assign more bits to the ADC with a larger channel gain on the corresponding radio frequency (RF) chain, and the optimal number of ADC bits is logarithmically proportional to the RF chain’s signal-to-noise ratio raised to the 1/3 power. Contributions of this paper include
  1. an ADC bit allocation algorithm to improve communication performance of a hybrid MIMO receiver,
  2. a revised ADC bit allocation algorithm that is robust to additive noise, and
  3. a worst-case analysis of the ergodic rate of the proposed MIMO receiver that quantifies system tradeoffs and serves as the lower bound.
Simulation results validate the ergodic rate formula and demonstrate that the proposed BA algorithms outperform a fixed-ADC approach in both spectral and energy efficiency. For a power constraint equivalent to that of fixed 4-bit ADCs, the revised BA algorithm makes the quantization error negligible while achieving 22% better energy efficiency. Having negligible quantization error allows existing state-of-the-art digital beamforming techniques to be readily applied to the proposed system.


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Last Updated 04/11/17.