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Polar Codes for Decomposed Multi-Input Multi-Output Gaussian Broadcast Channels
Muhammed Yusuf Şener1,2, Gerhard Kramer1, Shlomo Shamai Shitz3
1Institute for Communications Engineering, School of Computation, Information and Technology, Technical University of Munich, 80333 Munich, Germany.
Entropy (Basel, Switzerland)
|July 28, 2026
Summary
Dirty paper coding (DPC) enhances multi-input multi-output (MIMO) broadcast channels by decomposing channels and applying novel coding techniques. This method achieves significant rate and power gains over linear precoding.
Area of Science:
- Wireless communication systems engineering
- Information theory and coding
Background:
- Multi-input multi-output (MIMO) broadcast channels are crucial for modern wireless systems.
- Additive Gaussian noise and the need for efficient data transmission pose significant challenges.
- Existing linear precoding techniques have limitations in maximizing spectral efficiency.
Purpose of the Study:
- To apply Dirty Paper Coding (DPC) to MIMO broadcast channels.
- To enhance achievable data rates and power efficiency.
- To compare DPC performance against traditional linear precoding methods.
Main Methods:
- Decomposition of MIMO channels into parallel scalar channels.
- Application of modulo operators, amplitude-shift keying (ASK), and probabilistic shaping.
- Utilizing truncated Gaussian shaping, large ASK alphabets, and large modulo intervals.
Main Results:
- Achievable rate tuples cover all points within the capacity region.
- Simulations demonstrate significant rate and power gains using DPC.
- DPC maintains comparable encoding and decoding complexity to linear precoding.
Conclusions:
- Dirty Paper Coding offers a superior approach for MIMO broadcast channels.
- The proposed DPC scheme effectively improves spectral efficiency and power usage.
- This method provides a practical enhancement over linear precoding in wireless communications.
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