Abstract
Due to the heavy reliance of millimeter-wave (mmWave) wireless systems on directional links, beamforming (BF) with high-dimensional arrays is essential for cellular systems in these frequencies. Thus, performing the array processing in a power-efficient manner is a fundamental challenge. Analog and hybrid BF require few analog-to-digital and digital-to-analog converters (ADCs and DACs), but can only communicate in a small number of directions at a time, limiting directional search, spatial multiplexing, and control signaling. Digital BF enables flexible spatial processing but must be operated at a low quantization resolution to stay within reasonable power levels. This decrease in quantizer resolution distorts the received as well as the transmitted signal. To assess the effect of coarse quantization at the receiver, this paper presents a system level analytic framework based on a simple additive quantization noise model (AQNM). The analysis verified through extensive simulations reveals that at moderate resolutions (3-4 bits per ADC), there is negligible loss in downlink cellular capacity from quantization. In essence, the low resolution ADCs limit the high SNR, where cellular systems typically do not operate. For the transmitter, it is shown that DACs with 4 or more bits of resolution can support high order modulations, and do not violate the adjacent carrier leakage limit set by 3rd Generation Partnership Project (3GPP) New Radio (NR) standards for cellular operations. In fact, our findings suggest that low resolution digital BF architectures can be a power-efficient alternative to analog or hybrid BF for both transmitters and receivers at millimeter-wave.
Original language | English (US) |
---|---|
Article number | 8883297 |
Pages (from-to) | 756-770 |
Number of pages | 15 |
Journal | IEEE Transactions on Wireless Communications |
Volume | 19 |
Issue number | 2 |
DOIs | |
State | Published - Feb 2020 |
Keywords
- 5G cellular
- Low resolution quantizers
- Millimeter wave
- digital beamforming
ASJC Scopus subject areas
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics