Massive MIMO systems keep speed over limited digital signals and links
Spectral Efficiency Analysis of Massive MIMO-OFDM Systems with Double Quantization
Information Theory
Summary
Systems with many antennas can send data faster but need lots of power and data connections. The study looks at using limited-precision converters and data links that simplify signals by rounding numbers twice, which saves power and bandwidth but can cause errors. The authors show how to estimate these errors and calculate how fast data can be sent accurately. They find that the lower precision at either stage mostly limits speed, and using about six bits of precision works almost as well as perfect signals.
What this means in practice
- •For wireless network engineers: Improve uplink design for massive MIMO by balancing converter resolution and fronthaul data rates to sustain spectral efficiency efficiently.
- •For wireless hardware developers: Develop low-power ADC and fronthaul quantization solutions that optimize precision and system performance in wideband MIMO-OFDM radio equipment.$Commercial implications: Enables new radios with lower energy use and reduced data transport costs for telecom providers.
Authors
Bengu Bilgic Keskin, A. Oguz Kislal, Ali Gorcin, Özlem Tuğfe Demir
Abstract
Massive multiple-input multiple-output (MIMO) achieves a high spectral efficiency (SE) by employing a large number of receive antennas in the uplink. Employing many receive antennas requires a large number of analog-to-digital converters (ADCs) and a high fronthaul data rate. Low-resolution ADCs can reduce power consumption and cost, while fronthaul quantization can reduce the required fronthaul data rate, at the expense of quantization distortion at both stages. In wideband orthogonal frequency-division multiplexing systems, ADC quantization is performed in the time domain, while fronthaul quantization may be applied after the discrete Fourier transform to transmit only active subcarriers. In this study, we investigate the achievable uplink SE over fronthaul links under double quantization and imperfect channel estimation. We derive a linear minimum mean-squared error channel estimator from the double-quantized pilot observations and obtain an achievable SE using the use-and-then-forget bound. Numerical results demonstrate that the ADC and fronthaul quantization resolutions have comparable impacts on the achievable SE. When the two resolutions differ, the lower resolution becomes the dominant factor limiting the SE. Furthermore, our numerical results show that six-bit ADC and fronthaul quantization achieve more than 90% of the SE attained in the ideal case.