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

• URL: http://arxiv.org/abs/2608.13809v1
• Date: Thu, 13 Aug 2026 22:42:42 GMT
• Title: Optimal Power Allocation and AI Receiver Design for Superimposed DMRS and Data Transmission
• Abstract summary: We consider transmissions with superimposed (SI) demodulation-reference-symbol (DMRS) and data in OFDM based multiple-input multiple-output (MIMO) systems.<n>We derive an analytical framework to characterize the iterative behavior between the mean-square errors (MSEs) of channel estimation.<n>We design an artificial intelligence (AI) based receiver built upon Transformer encoders for SI-DMRS transmissions.
• Score: 2.4493299476776778
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• 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.

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