Optimal Power Allocation and AI Receiver Design for Superimposed DMRS and Data Transmission

2026-08-13

AI Summary

This study addresses the challenges of power allocation and receiver design in superimposed pilot transmission for OFDM-MIMO systems. We propose an iterative error analysis framework to optimize the power ratio between pilots and data, alongside a novel Transformer-based AI-ICED receiver architecture. By integrating iterative channel estimation and detection with deep learning mechanisms, this approach effectively mitigates superimposed interference. Simulation results demonstrate that, compared to conventional non-superimposed pilot schemes, the proposed system significantly enhances spectral efficiency while maintaining robust estimation accuracy. Consequently, this work offers a promising solution for achieving high spectral efficiency in next-generation communication systems by synergizing model-driven signal processing with data-driven intelligence.

Abstract

In this paper, we consider transmissions with superimposed (SI) demodulation-reference-symbol (DMRS) and data in orthogonal frequency-division multiplexing (OFDM) based multiple-input multiple-output (MIMO) systems. First, we derive an analytical framework to characterize the iterative behavior between the mean-square errors (MSEs) of channel estimation (CE) and MIMO detection (MD) within an iterative CE and detection (ICED) process. This framework is subsequently utilized to optimize power allocation and pilot patterns between the DMRS and data symbols for SI-DMRS transmission. Second, we design an artificial intelligence (AI) based receiver built upon Transformer encoders for SI-DMRS transmissions, which incorporates an iterative CE and detection (ICED) structure. Simulation results demonstrate that the proposed AI-ICED receiver, combined with SI-DMRS, effectively increases spectral efficiency (SE) compared to conventional systems using non-overlapped DMRS and data symbols.

Problem

• Superimposed DMRS
• Power Allocation
• AI Receiver Design
• Spectral Efficiency
• MIMO-OFDM

Innovation

• Superimposed DMRS
• AI Receiver
• Transformer Encoder
• Iterative CE and Detection
• Power Allocation