# Towards Massive MIMO 2.0: Understanding spatial correlation, interference suppression, and pilot contamination

arXiv: https://arxiv.org/abs/1904.03406 · HTML: https://mlsanity.com/paper/1904.03406/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Apr 2019.

## Built on by (most cited first, 8 of 8)

- [Pay Less But Get More: A Dual-Attention-based Channel Estimation Network for Massive MIMO Systems with Low-Density Pilots](https://mlsanity.com/paper/2303.00986/) (2023)
- [Towards Optimally Efficient Search with Deep Learning for Large-Scale MIMO Systems](https://mlsanity.com/paper/2101.02420/) (2021)
- [Mitigating Pilot Contamination and Enabling IoT Scalability in Massive MIMO Systems](https://mlsanity.com/paper/2310.03278/) (2023)
- [Smart Pilot Assignment for IoT in Massive MIMO Systems: A Path Towards Scalable IoT Infrastructure](https://mlsanity.com/paper/2404.10188/) (2024)
- [An Efficient Network with Novel Quantization Designed for Massive MIMO CSI Feedback](https://mlsanity.com/paper/2405.20068/) (2024)
- [Learning to Perform Downlink Channel Estimation in Massive MIMO Systems](https://mlsanity.com/paper/2109.02463/) (2021)
- [Pilot Contamination in Massive MIMO Systems: Challenges and Future Prospects](https://mlsanity.com/paper/2404.19238/) (2024)
- [Lightweight Deep Learning-Based Channel Estimation for RIS-Aided Extremely Large-Scale MIMO Systems on Resource-Limited Edge Devices](https://mlsanity.com/paper/2507.09627/) (2025)

## Abstract (arXiv)

Since the seminal paper by Marzetta from 2010, Massive MIMO has changed from being a theoretical concept with an infinite number of antennas to a practical technology. The key concepts are adopted in 5G and base stations (BSs) with M=64 full-digital transceivers have been commercially deployed in sub-6,GHz bands. The fast progress was enabled by many solid research contributions of which the vast majority assume spatially uncorrelated channels and signal processing schemes developed for single-cell operation. These assumptions make the performance analysis and optimization of Massive MIMO tractable but have three major caveats: 1) practical channels are spatially correlated; 2) large performance gains can be obtained by multicell processing, without BS cooperation; 3) the interference caused by pilot contamination creates a finite capacity limit, as M→∞. There is a thin line of papers that avoided these caveats, but the results are easily missed. Hence, this tutorial article explains the importance of considering spatial channel correlation and using signal processing schemes designed for multicell networks. We present recent results on the fundamental limits of Massive MIMO, which are not determined by pilot contamination but the ability to acquire channel statistics. These results will guide the journey towards the next level of Massive MIMO, which we call ``Massive MIMO 2.0''.