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Open-source End-to-End Digital Beamforming System Modeling

Jose Guajardo, Ali Niknejad

TL;DR

This work tackles the challenge of designing power-efficient digital beamforming systems for massive MIMO by providing an open-source, end-to-end MATLAB model that simulates uplink performance with multiple UEs, a large BS, and potential strong interference. It combines a behavioral model with an equation-based SNDR/SQNR degradation framework to analyze how interferers and ADC resolution affect system performance, especially in low-resolution regimes. The key contributions include the open-source end-to-end model with GUI, the SNDR/SQNR degradation equations validated against the behavioral model, the SIR_min heuristic for tolerable interference, and insights into ADC resolution requirements (e.g., 3–4 bits generally suffice, with one-bit ADCs viable in large arrays). The results illuminate practical guidelines for beamforming system design, demonstrating how interference, ADC choice, and array size interact to determine feasible operation and enabling reliable design-space exploration for future 6G scenarios.

Abstract

Digital beamforming forms the foundation for massive MIMO in 6G wireless communications. At their core, digital beamforming architectures provide key benefits such as faster beam search, interference nulling via zero-force beamforming, higher spectral capacity, and more increased flexibility. However, they generally tradeoff power consumption due to the large number of ADCs in such systems. This paper introduces an open-source MATLAB-based behavioral hardware model of a general digital beamforming system. More specifically, it models an end-to-end uplink between an arbitrary number of user elements (UEs) and an arbitrarily large base station (BS) with and without a strong interferer. This paper also presents and validates an equation-based model for the effects of interference on thermal and quantization noise. The behavioral model presented in this paper aims to deepen understanding of such digital beamforming systems to enable system designers to make optimizations. The results presented in this paper primarily center on implementations with low-resolution ADCs and, thus, focus on the effects of system parameters, including interferer strength, on quantization noise.

Open-source End-to-End Digital Beamforming System Modeling

TL;DR

This work tackles the challenge of designing power-efficient digital beamforming systems for massive MIMO by providing an open-source, end-to-end MATLAB model that simulates uplink performance with multiple UEs, a large BS, and potential strong interference. It combines a behavioral model with an equation-based SNDR/SQNR degradation framework to analyze how interferers and ADC resolution affect system performance, especially in low-resolution regimes. The key contributions include the open-source end-to-end model with GUI, the SNDR/SQNR degradation equations validated against the behavioral model, the SIR_min heuristic for tolerable interference, and insights into ADC resolution requirements (e.g., 3–4 bits generally suffice, with one-bit ADCs viable in large arrays). The results illuminate practical guidelines for beamforming system design, demonstrating how interference, ADC choice, and array size interact to determine feasible operation and enabling reliable design-space exploration for future 6G scenarios.

Abstract

Digital beamforming forms the foundation for massive MIMO in 6G wireless communications. At their core, digital beamforming architectures provide key benefits such as faster beam search, interference nulling via zero-force beamforming, higher spectral capacity, and more increased flexibility. However, they generally tradeoff power consumption due to the large number of ADCs in such systems. This paper introduces an open-source MATLAB-based behavioral hardware model of a general digital beamforming system. More specifically, it models an end-to-end uplink between an arbitrary number of user elements (UEs) and an arbitrarily large base station (BS) with and without a strong interferer. This paper also presents and validates an equation-based model for the effects of interference on thermal and quantization noise. The behavioral model presented in this paper aims to deepen understanding of such digital beamforming systems to enable system designers to make optimizations. The results presented in this paper primarily center on implementations with low-resolution ADCs and, thus, focus on the effects of system parameters, including interferer strength, on quantization noise.
Paper Structure (34 sections, 29 equations, 22 figures)

This paper contains 34 sections, 29 equations, 22 figures.

Table of Contents

  1. Introduction
  2. Background and Model Overview
  3. Background: Complex Envelope Representation
  4. Model Overview, Variable Names and Definitions
  5. Tunable Model Variables (Sweep Variables):
  6. Boolean Model Variables:
  7. Model Outputs for Plotting
  8. Modeling Transmitting User Elements
  9. Modeling Receiving Base Station
  10. Modeling MIMO Channel and Beamforming Operation
  11. Measurement Blocks
  12. Measuring SNDR
  13. Computing ENOB for QAM Signals
  14. A New Heuristic: $\mathbf{SIR_{min}}$
  15. Effective Array Gain
  16. ...and 19 more sections

Figures (22)

  • Figure 1: Overview of the Digital Beamforming Behavioral Model Implemented in MATLAB
  • Figure 2: Transmitter Block Diagram
  • Figure 3: Receiver Block Diagram
  • Figure 4: MIMO Channel Block Diagram
  • Figure 5: Single-User, Single-Element Uplink
  • ...and 17 more figures