IRS-Assisted Covert Wireless Networks
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Solution Overview
Problem
Conventional covert communication techniques for intelligent reflecting surface (IRS)-assisted wireless networks have limitations in optimizing transmission probability and achieving secure data transmission, as they assume a fixed transmission probability of 0.5, which does not effectively maximize the achievable data rate while ensuring covertness from adversaries.
Innovation Solution
A novel methodology that jointly optimizes the transmission probability, transmit power, and IRS reflection matrix to maximize the achievable data rate at a client while ensuring covertness, using one-dimensional line search methods and channel statistics to minimize detection error probability, without requiring instantaneous channel information to the adversary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If transmission probability is fixed to 0.5, then the communication system is simple to implement, but the achievable data rate cannot be maximized while ensuring covertness
Solution Approach 1:
The patent applies parameter changes by optimizing the transmission probability λ as a variable parameter rather than fixing it to 0.5. The system dynamically adjusts λ along with transmit power P and IRS reflection matrix Θ to maximize the achievable data rate while satisfying the covertness constraint, thereby resolving the contradiction between productivity and device complexity
Solution Approach 2:
The patent implements dynamics by making the transmission probability λ dynamically adjustable rather than static. The optimization problem allows λ to vary based on channel conditions and covertness requirements, enabling the system to adaptively maximize data rate while maintaining covertness, thus resolving the contradiction between achieving higher productivity and managing complexity
2Productivity
If transmission probability optimization is implemented, then the achievable data rate can be maximized, but the computational complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the joint optimization problem into manageable components. The optimization is performed over discrete transmission probability values and transmit power levels separately from the IRS reflection matrix configuration, reducing the computational complexity while still achieving the maximum achievable data rate
Solution Approach 2:
The patent implements feedback mechanisms where the system uses channel statistics and detection error probability information to adjust transmission probability and power levels. This feedback approach enables the system to maximize data rate while maintaining covertness without requiring exhaustive search through all possible parameter combinations, thus reducing computational complexity
3Reliability
If instantaneous channel information to adversary is used, then the detection error probability can be minimized, but the system requires more information and processing resources
Solution Approach 1:
The patent applies preliminary action by using channel statistics that are obtained in advance or continuously updated, rather than requiring real-time instantaneous channel information to the adversary. This preliminary knowledge of channel characteristics enables the system to minimize detection error probability while reducing the information processing burden, thus resolving the contradiction between reliability and information loss
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the achievable data rate at the client, ensures secure transmission, and reduces computational complexity, providing a secure covert communication link with low computational overhead and near-optimal performance.
Implementation Method 1
providing an intelligent reflecting surface (IRS) to reflect wireless radio frequency (RF) communication signals transmitted from the agent device to the client device
Data Source
AI summary
We disclose a novel methodology for wireless networks that optimizes the transmission probability, transmit power at an agent, and the reflection matrix of an IRS for covert RF communications. Key features include: (1) An exact closed-form expression for the expected detection error probability (DEP) at an adversary is provided considering the transmission probability at the agent; and (2) a novel method to optimize the transmission probability, transmit power at the agent and the reflection matrix of the IRS with the goal of maximizing the achievable rate at a client while ensuring a covertness constraint is developed. More specifically, the method may require only one-dimensional line search schemes, achieves near-optimal performance, and exhibits enhanced achievable data rate when compared to the conventional technique without the transmission probability optimization.