Adaptive Precoding Parameters for Hardware-Impaired Wireless Transmission
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Solution Overview
Problem
Existing wireless communication systems face performance degradation due to hardware impairments such as power amplifier nonlinearities and oscillator phase noise, which are not adequately addressed by current linear precoding algorithms.
Innovation Solution
Adaptive precoding methods that account for hardware impairments by determining distortion indications and using precoding parameters to compensate for these impairments, employing machine learning techniques and codebook-based or non-codebook-based approaches to optimize precoder selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If linear precoding algorithms are used, then device complexity is reduced, but signal quality deteriorates due to uncorrected hardware impairments
Solution Approach 1:
The system performs preliminary characterization of hardware impairments by transmitting test signals and measuring distortion at the receiver. These measured distortion parameters are stored and used later to configure distortion compensation matrices, allowing the precoder to pre-compensate for known hardware defects before actual data transmission occurs.
Solution Approach 2:
The precoding algorithm dynamically adjusts its parameters based on measured distortion characteristics. By changing the precoding matrix to include distortion compensation components, the system adapts to actual hardware conditions while maintaining computational feasibility through parameter optimization rather than complete algorithm redesign.
2Reliability
If distortion compensation is implemented, then signal quality is improved, but device complexity increases due to additional processing requirements
Solution Approach 1:
The system implements partial distortion compensation by focusing on the dominant distortion components identified through measurement. Rather than attempting to compensate for all possible hardware imperfections, the precoder applies compensation matrices that address the most significant distortion sources, achieving substantial quality improvement with moderate complexity increase.
Solution Approach 2:
The receiver creates a digital model or copy of the hardware distortion characteristics by measuring the actual distortion introduced by power amplifiers and oscillators. This distortion model is then transmitted back to the transmitter, where it is used to construct compensation matrices that replicate the inverse of the measured distortion, effectively canceling it out without requiring direct modification of the physical hardware.
3Device complexity
If hardware impairments are not corrected, then device complexity remains low, but communication performance deteriorates in multi-network scenarios
Solution Approach 1:
The system establishes a feedback loop where the receiver measures distortion introduced by transmitter hardware and sends this information back to the transmitter. This feedback enables the transmitter to adapt its precoding parameters to compensate for hardware impairments, improving communication performance in multi-network scenarios without requiring complex hardware modifications.
Data Source
AI summary
Methods and apparatus are provided. In an example aspect, a method in a wireless communication device of precoding symbols for transmission is provided. The method includes determining an indication of distortion of symbols transmitted by transmission apparatus of the wireless communication device or an indication of a correction for the distortion, determining precoding parameters based on the indication of distortion or the indication of the correction, and precoding symbols to be transmitted based on the precoding parameters.