Reducing Quantizer Distortion Due to Insufficient Resolution in Massive MIMO Receivers
| Autor: | Laurence Mailaender, Xiao-Feng Qi, Arkady Molev-Shteiman |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Beamforming
Computer science Orthogonal frequency-division multiplexing Quantization (signal processing) MIMO 020206 networking & telecommunications Data_CODINGANDINFORMATIONTHEORY 02 engineering and technology Multiplexing Computer Science Applications Signal-to-noise ratio Modulation Modeling and Simulation Frequency domain Distortion 0202 electrical engineering electronic engineering information engineering Bit error rate Electrical and Electronic Engineering Algorithm Quadrature amplitude modulation Computer Science::Information Theory |
| Zdroj: | IEEE Communications Letters. 24:2599-2603 |
| ISSN: | 2373-7891 1089-7798 |
| DOI: | 10.1109/lcomm.2020.3009196 |
| Popis: | Use of low-resolution (1-4 bits) Analog-to-Digital Converters (ADCs) can reduce power consumption in Massive Multiple-Input, Multiple-Output (MIMO) receivers. Ordinary linear beamforming may suffice for low-resolution ADCs under conditions on the Signal-to-Noise Ratio (SNR) and number of antennas that may be called low but sufficient resolution. However, if the SNR increases or number of antennas decreases, an error floor will typically occur. We introduce three low-complexity iterative algorithms to reduce quantization noise in such low but insufficient resolution cases. These algorithms process the raw quantizer outputs prior to detection, achieving up to two orders-of-magnitude reduction in Bit Error Rate (BER). Our algorithms are based on the new ‘equivalent model’ for quantizers developed in our prior work. These algorithms can be applied to any number of bits and any modulation format. We focus on Orthogonal Frequency-Division Multiplexing (OFDM) to show that quantizer distortion can be corrected without going to the frequency domain. |
| Databáze: | OpenAIRE |
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