Finite-Alphabet MMSE Equalization for All-Digital Massive MU-MIMO mmWave Communication
arXiv:2009.02747
Abstract
We propose finite-alphabet equalization, a new paradigm that restricts the entries of the spatial equalization matrix to low-resolution numbers, enabling high-throughput, low-power, and low-cost hardware equalizers. To minimize the performance loss of this paradigm, we introduce FAME, short for finite-alphabet minimum mean-square error (MMSE) equalization, which is able to significantly outperform a naive quantization of the linear MMSE matrix. We develop efficient algorithms to approximately solve the NP-hard FAME problem and showcase that near-optimal performance can be achieved with equalization coefficients quantized to only 1-3 bits for massive multi-user multiple-input multiple-output (MU-MIMO) millimeter-wave (mmWave) systems. We provide very-large scale integration (VLSI) results that demonstrate a reduction in equalization power and area by at least a factor of 3.9x and 5.8x, respectively.
arXiv commentAppeared in the IEEE Journal on Selected Areas in Communications
References in corpus (6)
- Massive MIMO for Next Generation Wireless Systems
- Capacity Analysis of One-Bit Quantized MIMO Systems with Transmitter Channel State Information
- Throughput Analysis of Massive MIMO Uplink with Low-Resolution ADCs
- Large-Scale MIMO Detection for 3GPP LTE: Algorithms and FPGA Implementations
- A Field Guide to Forward-Backward Splitting with a FASTA Implementation
- Performance, Power, and Area Design Trade-offs in Millimeter-Wave Transmitter Beamforming Architectures