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Spatial and Directional Modulation Systems for Near-Field Secure Transmission.
Ji Liu1,2, Yuan Zhong3, Yong Wang1
1School of Telecommunications Engineering, Xidian University, Xi'an 710126, China.
Sensors (Basel, Switzerland)
|February 13, 2026
Summary
This study introduces a new secure communication framework for 6G near-field environments. The spatial and directional modulation with artificial noise (SDMN-AN) enhances security and spectral efficiency against eavesdropping.
Area of Science:
- Wireless communication and signal processing.
- Information security and cryptography.
Background:
- The 6G era, with its massive antenna arrays, intensifies near-field effects, posing significant security risks.
- Existing communication systems struggle to address the unique security challenges in these complex near-field environments.
Purpose of the Study:
- To propose a novel artificial noise-aided spatial and directional modulation (SDMN-AN) framework for secure near-field communications.
- To enhance both spectral efficiency and communication security in 6G near-field environments.
Main Methods:
- Integration of legitimate receiver indices, modulation symbols, and artificial noise (AN) into the SDMN-AN framework.
- Confining artificial noise to the null space of legitimate channels to mask transmissions.
- Investigating two precoding strategies: maximum-ratio transmission (MRT) and zero-forcing (ZF).
Main Results:
- The SDMN-AN framework demonstrates superior performance in mitigating eavesdropping threats.
- Significant improvements in spectral efficiency were observed.
- Analytical derivations of bit error rate (BER) bounds align with simulation results, validating the framework's effectiveness.
Conclusions:
- The proposed SDMN-AN framework offers a robust solution for secure near-field communications in 6G.
- The trade-offs between MRT and ZF precoding strategies provide flexibility for different hardware and detection requirements.
- This framework is a compelling advancement for next-generation secure wireless networks.
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