VLSI design of a nonparametric equalizer for massive MU-MIMO

Abstract

Linear minimum mean-square error (L-MMSE) equalization is among the most popular methods for data detection in massive multi-user multiple-input multiple-output (MU-MIMO) wireless systems. While L-MMSE equalization enables near-optimal spectral efficiency, accurate knowledge of the signal and noise powers is necessary. Furthermore, corresponding VLSI designs must solve linear systems of equations, which requires high arithmetic precision, exhibits stringent data dependencies, and results in high circuit complexity. This paper proposes the first VLSI design of the NOnParametric Equalizer (NOPE), which avoids knowledge of the transmit signal and noise powers, provably delivers the performance of L-MMSE equalization for massive MU-MIMO systems, and is resilient to numerous system and hardware impairments due to its parameter-free nature. Moreover, NOPE avoids computation of a matrix inverse and only requires hardware-friendly matrix-vector multiplications. To showcase the practical advantages of NOPE, we propose a parallel VLSI architecture and provide synthesis results in 28 nm CMOS. We demonstrate that NOPE performs on par with existing data detectors for massive MU-MIMO that require accurate knowledge of the signal and noise powers.

ADMM-Based Infinity-Norm Detection for Massive MIMO: Algorithm and VLSI Architecture

“…Gauss-Seidel (GS) approximate inversion based detection algorithm is also a popular choice for implementation and can be found in [9]. Several other iterative variants have been proposed, such as conjugate gradient (CG) [10], coordinate descent (CD) [11], mismatched approximate message passing [12], and stair matrix based massive MIMO detection [13]. We refer interested readers to [14] for more details on massive MIMO detection techniques.…”

“…In [12], a VLSI architecture for NOnParametric Equalizer (NOPE) massive MIMO detector is presented. The architecture is presented for 16 users and 64 BS antennas.…”