Abstract

The use of low-resolution data converters in the radio-frequency (RF) chains of all-digital massive multiple-input multiple-output (MIMO) basestations promises significant reductions in power consumption, hardware costs, and interconnect bandwidth. We propose a quantization-aware data-detection algorithm which mitigates the performance loss of 1-bit quantized massive MIMO orthogonal frequency-division multiplexing (OFDM) systems. Since the system performance heavily depends on the quality of channel estimates, we also develop a nonlinear 1-bit channel estimation algorithm that builds upon the proposed data detection algorithm. We show that the proposed algorithms significantly outperform linear data detectors and channel estimators in terms of bit error rate. For the proposed nonlinear data detection algorithm, we develop a very large scale integration (VLSI) architecture and present implementation results on a Xilinx Virtex-7 field programmable gate array (FPGA). Our implementation results are, to the best of our knowledge, the first for 1-bit massive MU-MIMO-OFDM systems and demonstrate comparable hardware efficiency with respect to state-of-the-art linear data detectors designed for systems with high-resolution data converters, while achieving lower bit error rate.

Highlights

  • M ASSIVE multi-user multiple-input multiple-output (MU-MIMO) is one of the core technologies of fifth-generation (5G) wireless systems as it promises significant improvements in spectral efficiency and link reliability, compared to traditional, small-scale MIMO [2], [3]

  • CONTRIBUTIONS We propose a new data detection algorithm and develop a corresponding very large scale integration (VLSI) design specialized for 1-bit massive MU-MIMO-orthogonal frequencydivision multiplexing (OFDM) systems operating over frequencyselective channels

  • We have proposed a quantization-aware data detection algorithm, called 1-Bit OFDM boX (1BOX), for massive MU-MIMO-OFDM systems operating over frequency-selective channels with

Read more

Summary

INTRODUCTION

M ASSIVE multi-user multiple-input multiple-output (MU-MIMO) is one of the core technologies of fifth-generation (5G) wireless systems as it promises significant improvements in spectral efficiency and link reliability, compared to traditional, small-scale MIMO [2], [3]. A. RELATED PREVIOUS WORK Linear channel estimation and data detection algorithms for 1-bit massive MU-MIMO systems, such as maximum-ratio combining (MRC) and linear minimum mean square error (L-MMSE), have been studied in [8], [14]–[16] for systems operating in frequency-flat channels. Our simulations and FPGA implementation results show that our design achieves comparable hardware efficiency but (often significantly) lower error rate compared to data detectors that have been designed for systems with high-resolution ADCs. MIRFARSHBAFAN et al.: ALGORITHM AND VLSI DESIGN FOR 1-BIT DATA DETECTION IN MASSIVE MIMO-OFDM.

SYSTEM MODEL
LINEAR-QUANTIZED DATA DETECTION
ARCHITECTURE AND FPGA IMPLEMENTATION
Findings
CONCLUSION
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call