Intelligent Reflecting Surface Assisted Multi-User Robust Secret Key Generation for Low-Entropy Environments.

Area of Science:

• Wireless Communication
• Information Security
• Metamaterials

Background:

• Channel secret key generation (CSKG) is crucial for secure wireless communication.
• Intelligent Reflecting Surfaces (IRS) offer a novel approach to enhance communication systems.
• Low-entropy communication scenarios with adjacent multi-users present challenges in key generation efficiency due to channel similarity.

Purpose of the Study:

• To investigate key extraction methods in IRS-aided low-entropy communication for multi-user environments.
• To address the challenge of low key generation efficiency caused by high channel similarity among users.
• To enhance the reliability and robustness of the key generation process.

Main Methods:

• A joint user allocation and IRS reflection parameter adjustment scheme is proposed.
• Analysis of key capability expressions in IRS-aided communication systems.
• Optimization of IRS reflection matrix and user allocation to minimize channel similarity and ensure robustness.

Main Results:

• The proposed scheme effectively minimizes channel similarity between users.
• The reliability of information exchange during key generation is maintained.
• Simulation results demonstrate significant performance gains in key generation.

Conclusions:

• The developed joint optimization scheme enhances the efficiency and robustness of CSKG in IRS-aided multi-user systems.
• IRS technology, combined with intelligent resource allocation, shows great potential for secure wireless communications.
• This research contributes to advancing secure communication protocols in complex wireless environments.