Wireless Signal Equalization Through Reference-Component Interpolation
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Solution Overview
Problem
The increasing data rates and capacity requirements in wireless communication systems, coupled with the need for sustainability and power consumption reductions, necessitate more efficient solutions in terms of computational complexity, memory use, and data transfers, particularly in the context of equalization processes.
Innovation Solution
An apparatus and method for deriving equalization coefficients by selecting reference data components in a radio frequency signal and interpolating these coefficients along the time or frequency domain to estimate non-reference data components, reducing computational complexity while maintaining link performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If equalization coefficients are computed for all components of the radio frequency signal, then the accuracy of signal processing is improved, but the computational complexity increases
Solution Approach 1:
The radio frequency signal components are segmented into reference data components and non-reference data components. Equalization coefficients are computed only for the reference data components, while coefficients for non-reference components are derived through interpolation. This segmentation reduces the number of computations required while maintaining adequate signal processing accuracy.
Solution Approach 2:
Instead of computing equalization coefficients directly for all components, the method computes coefficients for reference components and then copies/interpolates these coefficients to derive coefficients for non-reference components. This copying approach significantly reduces computational complexity while providing sufficient accuracy for signal processing.
2Reliability
If equalization coefficients are computed for all components of the radio frequency signal, then the quality of interference rejection is improved, but the power consumption increases
Solution Approach 1:
The signal processing is segmented into computing equalization coefficients only for reference data components, which are the critical components for interference rejection. The remaining non-reference components use interpolated coefficients, reducing the overall computational load and power consumption while maintaining adequate interference rejection quality.
Solution Approach 2:
The method applies partial action by computing equalization coefficients only for the necessary reference data components rather than all components. This partial computation approach reduces power consumption while providing sufficient interference rejection quality for practical applications.
3Measurement precision
If equalization coefficients are computed for all components of the radio frequency signal, then the accuracy of equalization is improved, but the memory use increases
Solution Approach 1:
Memory resources are optimized by segmenting the equalization process. Only reference data components store computed equalization coefficients, while non-reference components derive coefficients through interpolation operations. This segmentation significantly reduces memory usage while maintaining adequate equalization accuracy.
Data Source
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AI summary
The present subject matter relates to a method comprising: receiving a radio frequency signal, the radio frequency signal comprising components, wherein each component is associated with a time unit and a frequency unit; selecting components of the radio frequency signal, the selected components comprising reference data; computing, for the selected components, equalization coefficients, referred to as initial equalization coefficients; deriving the equalization coefficients for non-reference data components of the radio frequency signal by interpolating, along at least one of time domain or frequency domain, the initial equalization coefficients.