MIMO Artificial Signal Generation for Capacity and Secrecy
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Solution Overview
Problem
MIMO transmission systems with analog, codebook-based, or hybrid beamforming face capacity reduction and secrecy issues due to mismatches between pre-determined precoder/combiner matrices and actual channel conditions, allowing eavesdroppers to intercept signals easily.
Innovation Solution
The system generates artificial signals through convex optimization to minimize errors between information and received signals, selecting precoding/combining matrix pairs based on estimated channel coefficients, and uses power-limited artificial signals to maximize channel capacity and secrecy without modifying receivers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If pre-determined precoder/combiner matrices from a codebook are used, then device complexity is reduced and ease of operation is improved, but channel capacity is reduced and communication secrecy is compromised
Solution Approach 1:
The patent performs preliminary channel decomposition to obtain singular values and eigenvectors before transmission. These channel characteristics are used to generate optimized precoding matrices that are tailored to the specific channel conditions, rather than selecting from pre-determined codebook entries. This preliminary channel analysis enables the system to achieve higher capacity while maintaining operational simplicity.
Solution Approach 2:
The patent changes the parameters of the precoding matrices by incorporating channel-specific singular values and eigenvectors into the matrix design. Instead of using fixed codebook entries, the precoding matrices are adapted to match the actual channel characteristics, thereby increasing channel capacity while maintaining the benefits of predetermined structures.
2Ease of operation
If pre-determined precoder/combiner matrices from a codebook are used, then device complexity is reduced and ease of operation is improved, but communication secrecy is compromised
Solution Approach 1:
The patent performs preliminary channel decomposition to obtain singular values and eigenvectors before transmission. These channel characteristics are used to generate optimized precoding matrices that are tailored to the specific channel conditions, rather than selecting from pre-determined codebook entries. This preliminary channel analysis enables the system to achieve higher capacity while maintaining operational simplicity.
Solution Approach 2:
The patent changes the parameters of the precoding matrices by incorporating channel-specific singular values and eigenvectors into the matrix design. Instead of using fixed codebook entries, the precoding matrices are adapted to match the actual channel characteristics, thereby increasing channel capacity while maintaining the benefits of predetermined structures.
3Loss of information
If channel decomposition to singular values is performed, then channel capacity is maximized, but device complexity and computational requirements increase
Solution Approach 1:
The patent performs preliminary channel decomposition to obtain singular values and eigenvectors before transmission. These channel characteristics are used to generate optimized precoding matrices that are tailored to the specific channel conditions, rather than selecting from pre-determined codebook entries. This preliminary channel analysis enables the system to achieve higher capacity while maintaining operational simplicity.
Data Source
AI summary
A system and method for increasing the capacity of a Multiple-Input Multiple-Output (MIMO) system at desired user's locations and reducing the capacity at locations, other than that of the desired user, while also providing secrecy. Knowing the channel coefficient between each transmitter and receiver antenna pair at the transmitter, the method of the present invention calculates the artificial signal that minimizes the Euclidean distance between the desired and received data symbols if the precoding/combining matrix pair from the set that has the minimum Euclidean distance to the singular value decomposition (SVD) of the channel matrix is used for transmission and reception. The artificial signal may be fed to the precoder, instead of the actual desired data symbols, or may be transmitted directly to reduce computational complexity, power consumption and processing delay if the hardware configuration allows.


