Massive MIMO-OFDM Channel Acquisition with Time-Frequency Phase-Shifted Pilots

2025-05-08

IEEE Transactions on Communications

AI Summary

Channel acquisition in massive MIMO-OFDM systems faces three key challenges: severe multi-user interference, excessive pilot overhead, and high estimation complexity. To address these, this paper proposes a time-frequency phase-shifted pilot (TFPSP) design and a three-beam (TB) tensor channel model, enabling joint spatial-frequency-temporal modeling. We innovatively develop an information-geometric tensor estimation algorithm (IGA) and devise its low-complexity implementation along with an efficient pilot scheduling strategy. The proposed approach achieves high estimation accuracy while significantly reducing pilot overhead and computational cost: in multi-user scenarios, it attains over 8 dB lower normalized mean square error (NMSE) than state-of-the-art methods, effectively mitigating inter-user interference. This work pioneers the deep integration of time-frequency cooperative pilot design and tensor-based information-geometric estimation, establishing an efficient and scalable new paradigm for massive MIMO-OFDM channel acquisition.

Technology Category

• Machine Learning: Matrix & Tensor Methods
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: State Estimation

Application Category

• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization
• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

In this paper, we propose a channel acquisition approach with time-frequency phase-shifted pilots (TFPSPs) for massive multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. We first present a triple-beam (TB) based channel tensor model, allowing for the representation of the space-frequency-time (SFT) domain channel as the product of beam matrices and the TB domain channel tensor. By leveraging the specific characteristics of TB domain channels, we develop TFPSPs, where distinct pilot signals are simultaneously transmitted in the frequency and time domains. Then, we present the optimal TFPSP design and provide the corresponding pilot scheduling algorithm. Further, we propose a tensor-based information geometry approach (IGA) to estimate the TB domain channel tensors. Leveraging the specific structure of beam matrices and the properties of TFPSPs, we propose a low-complexity implementation of the tensor-based IGA. We validate the efficiency of our proposed channel acquisition approach through extensive simulations. Simulation results demonstrate the superior performance of our approach. The proposed approach can effectively suppress inter-UT interference with low complexity and limited pilot overhead, thereby enhancing channel estimation performance. Particularly in scenarios with a large number of UTs, the channel acquisition method outperforms existing approaches by reducing the normalized mean square error (NMSE) by more than 8 dB.

Problem

• Develops time-frequency phase-shifted pilots for massive MIMO-OFDM channel acquisition
• Proposes tensor-based approach to estimate space-frequency-time domain channels efficiently
• Reduces inter-user interference and pilot overhead with low-complexity implementation

Innovation

• Time-frequency phase-shifted pilots for MIMO-OFDM
• Tensor-based information geometry channel estimation
• Low-complexity triple-beam domain channel modeling