skip to main content


Title: Efficient modeling of low‐resolution millimeter‐wave transceivers for massive MIMO wireless communications systems
Abstract

We present a high‐fidelity measurement‐based nonlinear model of low‐complexity millimeter‐wave transmit and receive circuits for design and analysis of 1‐bit on‐off‐key (OOK) massive MIMO wireless communications systems. The receive model is based upon a fabricated 38 GHz energy detector, representative of state‐of‐the‐art OOK millimeter‐wave receivers. The model is validated with measurements and includes nonlinear noise modeling. Performance of a large‐scale massive MIMO system is predicted with the model, and predictions are compared against a 4‐transmit‐element, N‐receive‐element testbed. Finally, we compute the channel capacity of several OOK massive MIMO systems, exploring tradeoffs in power consumption and number of transmit and receive cells. Results indicate a 1‐bit OOK array with low power pre‐amplifiers can achieve similar capacity to a classical linear receiver with less than one tenth the power consumption. The 1‐bit array compensates for the per‐cell simplicity by increasing the total number of cells while maintaining low overall power consumption.

 
more » « less
Award ID(s):
1731056 2132700
NSF-PAR ID:
10453956
Author(s) / Creator(s):
 ;  ;  ;  ;  
Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Microwave and Optical Technology Letters
Volume:
63
Issue:
4
ISSN:
0895-2477
Page Range / eLocation ID:
p. 1134-1140
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Power consumption of multiuser (MU) precoding is a major concern in all-digital massive MU multiple-input multiple-output (MIMO) basestations with hundreds of antenna elements operating at millimeter-wave (mmWave) frequencies. We propose to replace part of the linear Wiener filter (WF) precoding matrix by a Finite-Alphabet WF Precoding (FAWP) matrix, which enables the use of low-precision hardware that consumes low power and area. To minimize the performance loss of our approach, we present methods that efficiently compute mean-square error (MSE)-optimal FAWP matrices. Our results show that FAWP matrices are able to approach infinite-precision error-rate and error vector magnitude performance with only 3-bit precoding weights, even when operating under realistic mmWave propagation conditions. Hence, FAWP is a promising approach to substantially reduce power consumption and silicon area in all-digital mmWave massive MU-MIMO systems. 
    more » « less
  2. Full-duplex (FD) wireless communication refers to a communication system in which both ends of a wireless link transmit and receive data simultaneously and on the same frequency band. One of the major challenges of FD communication is self-interference (SI), which refers to the interference caused by transmitting elements of a radio to its own receiving elements. Fully digital beamforming is a technique used to conduct beamforming and has been recently repurposed to also reduce SI. However, the cost of fully digital systems (e.g., base stations) dramatically increases with the increase in the number of antennas as these systems use a separate Tx-Rx RF chain for each antenna element. Hybrid beamforming systems use a much smaller number of RF chains to feed the same number of antennas, and hence can significantly reduce the deployment cost. In this paper, we aim to quantify the performance gap between these two radio architectures in terms of SI cancellation and system capacity in FD multi-user MIMO setups. We first obtained over-the-air channel measurement data on two outdoor massive MIMO deployments over the course of three months. We next study two state-of-the-art transmit beamforming based FD systems for fully digital and hybrid architectures. We show that the hybrid beamforming system can achieve 80-97% of the fully digital system capacity, depending on the number of clients. 
    more » « less
  3. All-digital massive multiuser (MU) multiple-input multiple-output (MIMO) at millimeter-wave (mmWave) frequencies is a promising technology for next-generation wireless systems. Low-resolution analog-to-digital converters (ADCs) can be utilized to reduce the power consumption of all-digital basestation (BS) designs. However, simultaneously transmitting user equipments (UEs) with vastly different BS-side receive powers either drown weak UEs in quantization noise or saturate the ADCs. To address this issue, we propose high dynamic range (HDR) MIMO, a new paradigm that enables simultaneous reception of strong and weak UEs with low-resolution ADCs. HDR MIMO combines an adaptive analog spatial transform with digital equalization: The spatial transform focuses strong UEs on a subset of ADCs in order to mitigate quantization and saturation artifacts; digital equalization is then used for data detection. We demonstrate the efficacy of HDR MIMO in a massive MU-MIMO mmWave scenario that uses Householder reflections as spatial transform. 
    more » « less
  4. null (Ed.)
    Spatial ΣΔ sampling has recently been proposed to improve the performance of massive MIMO systems with low-resolution quantization for cases where the users are confined to a certain angular sector, or the array is spatially oversampled. We derive a linear minimum mean squared error (LMMSE) channel estimator for the ΣΔ array based on an element-wise Bussgang decomposition that reformulates the nonlinear quantizer operation using an equivalent linear model plus quantization noise. Both the case of one- and two-bit quantization is considered. We then evaluate the achievable rate of the ΣΔ system assuming that a linear receiver based on the LMMSE channel estimate is used to decode the data. Our numerical results demonstrate that ΣΔ architecture is able to achieve superior channel estimates and sum spectral efficiency compared to conventional low-resolution quantized massive MIMO systems. 
    more » « less
  5. Millimeter wave (mmW) communications is viewed as the key enabler of 5G cellular networks due to vast spectrum availability that could boost peak rate and capacity. Due to increased propagation loss in mmW band, transceivers with massive antenna array are required to meet a link budget, but their power consumption and cost become limiting factors for commercial systems. Radio designs based on hybrid digital and analog array architectures and the usage of radio frequency (RF) signal processing via phase shifters have emerged as potential solutions to improve radio energy efficiency and deliver performances close to the conventional digital antenna arrays. In this paper, we provide an overview of the state-of-the-art mmW massive antenna array designs and comparison among three array architectures, namely digital array, partially-connected hybrid array (sub-array), and fully-connected hybrid array. The comparison of performance, power, and area for these three architectures is performed for three representative 5G downlink use cases, which cover a range of pre-beamforming signal-to-noise-ratios (SNR) and multiplexing regimes. This is the first study to comprehensively model and quantitatively analyze all design aspects and criteria including: 1) optimal linear precoder, 2) impact of quantization error in digital-to-analog converter (DAC) and phase shifters, 3) RF signal distribution network, 4) power and area estimation based on state-of-the-art mmW circuits including baseband digital precoding, digital signal distribution network, high-speed DACs, oscillators, mixers, phase shifters, RF signal distribution network, and power amplifiers. Our simulation results show that the fully-digital array architecture is the most power and area efficient compared against optimized designs for sub-array and hybrid array architectures. Our analysis shows that digital array architecture benefits greatly from multi-user multiplexing. The analysis also reveals that sub-array architecture performance is limited by reduced beamforming gain due to array partitioning, while the system bottleneck of the fully-connected hybrid architecture is the excessively complicated and power hungry RF signal distribution network. 
    more » « less