Polarization Pre-coding for Single-Carrier NLOS Systems
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Solution Overview
Problem
Polarized signals in Non-Line-Of-Sight (NLOS) communication systems face challenges due to atmospheric conditions and environmental changes, leading to signal rotation and reduced polarization quality, which affects communication throughput and reliability.
Innovation Solution
A method is introduced to dynamically adjust the polarization of polarized single-carrier transmissions based on feedback from the receiver, using a rotation matrix and Singular Value Decomposition (SVD) to optimize signal quality and channel characteristics, ensuring optimal polarization alignment and data distribution between polarizations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If polarized transmission is used in NLOS conditions, then communication capacity is improved, but signal quality deteriorates due to atmospheric conditions and environmental changes causing polarization rotation
Solution Approach 1:
The system dynamically adjusts the polarization basis by estimating the channel matrix H and computing the optimal rotation matrix W through singular value decomposition. This allows the polarization basis to adapt in real-time to changing atmospheric conditions and environmental factors, maintaining signal quality while preserving communication capacity in NLOS conditions
Solution Approach 2:
The receiver estimates the channel matrix H from received signals and feeds back channel state information to the transmitter. This feedback enables the transmitter to adjust its polarization basis accordingly, resolving the contradiction between maintaining fixed polarization for capacity and adapting to changing conditions for reliability
2Device complexity
If fixed polarization basis is used, then system complexity is reduced, but adaptability to changing environmental conditions deteriorates
Solution Approach 1:
The system changes the polarization basis parameters by computing the rotation matrix W from the channel matrix H. Instead of using a fixed polarization basis, the system dynamically adjusts the basis vectors based on channel conditions, achieving adaptability while maintaining manageable complexity through mathematical transformations
3Measurement precision
If polarization rotation compensation is implemented, then signal reception quality is improved, but computational complexity increases
Solution Approach 1:
The system replaces physical polarization adjustment mechanisms with mathematical transformations. By using singular value decomposition and rotation matrices to compensate for polarization rotation, the system achieves signal reception quality improvement through computational methods rather than mechanical adjustments, balancing complexity and performance
Data Source
AI summary
A method for optimizing reception of a polarized single-carrier transmission, including transmitting a polarized single-carrier transmission to a receiver, receiving feedback from the receiver of a figure of merit of the polarized single-carrier transmission, and electronically changing polarization of the polarized single-carrier transmission based on the feedback. A single-carrier communication transmitter including a source for a polarized single-carrier transmission signal, a circuit for receiving feedback from a receiver describing a figure of merit of a received polarized single-carrier transmission, and a circuit for changing polarization of the polarized single-carrier transmission signal, based on the feedback. Related apparatus, systems and methods are also described.