Abstract
In this letter, we compare the capacity of a massive multiple-input multiple-output (MIMO) system using a low-resolution analog-to-digital converter (ADC) and a linear detector against a conventional MIMO system with higher order modulation and near maximum likelihood (ML) detection. We show that in the low-signal-to-noise ratio (SNR) regime, the quantized massive MIMO system can outperform the conventional large MIMO system; however, for high SNR, the conventional MIMO system with a near ML detector can outperform the extreme 1-bit quantized massive MIMO system. An analytical framework that derives the achievable rate of a linear minimum mean-squared error (MMSE)-based detector in a massive MIMO configuration, with the assumptions that the front-end is limited to a low-resolution ADC and channel estimation is imperfect, is presented.
Original language | English (US) |
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Article number | 8481691 |
Pages (from-to) | 2599-2602 |
Number of pages | 4 |
Journal | IEEE Communications Letters |
Volume | 22 |
Issue number | 12 |
DOIs | |
State | Published - Dec 2018 |
Keywords
- detection
- MMSE
- Quantized massive MIMO
ASJC Scopus subject areas
- Modeling and Simulation
- Computer Science Applications
- Electrical and Electronic Engineering