Multipath Selection via Segmented Noise Thresholds
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Solution Overview
Problem
Conventional methods for differentiating signal and noise in multipath components in wireless communication systems often result in reduced selection accuracy and Signal to Noise Ratio (SNR) due to the use of a unified threshold, leading to incorrect judgments if the threshold is set too high or too low.
Innovation Solution
A multipath selection method that divides the power spectrum of a correlation sequence into distinct areas using different noise thresholds, allowing for the accurate identification of valid multipath component signals by setting specific criteria based on the average noise power, thereby improving selection accuracy and SNR.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a unified threshold is used to differentiate signal and noise in multipath components, then the operation is simple, but the selection accuracy and SNR are reduced
Solution Approach 1:
The patent segments the power spectrum into multiple areas (first power spectrum area and second power spectrum area) and applies different noise thresholds to each area. This segmentation allows the system to use area-specific thresholds rather than a unified threshold, thereby improving selection accuracy while maintaining operational simplicity through automated area identification and threshold assignment.
Solution Approach 2:
The patent implements local quality by assigning different noise thresholds to different power spectrum areas based on their local characteristics. The first noise threshold is applied to the first power spectrum area and the second noise threshold to the second power spectrum area, allowing each region to be evaluated with the appropriate threshold for its specific signal conditions, thus improving overall selection accuracy.
2Measurement precision
If the threshold is set too low, then more signals are detected, but noise is incorrectly identified as signal
Solution Approach 1:
The patent applies different noise thresholds to different power spectrum areas based on their local characteristics. The first noise threshold is applied to the first power spectrum area and the second noise threshold to the second power spectrum area, allowing each region to be evaluated with the appropriate threshold for its specific signal conditions, thus improving overall selection accuracy.
Solution Approach 2:
The patent changes the threshold parameter based on the power spectrum area being evaluated. By dynamically selecting different noise thresholds (first noise threshold vs. second noise threshold) according to the specific area and signal characteristics, the system adapts the detection parameters to local conditions, improving both detection accuracy and reliability.
Data Source
AI summary
Disclosed are a multipath selection method and device, and a storage medium. The method includes that: a correlation sequence between a received signal and a local reference signal is acquired by means of a correlation calculation method; a power spectrum of the correlation sequence and an average noise power of the received signal are acquired; according to the average noise power of the received signal, the power spectrum of the correlation sequence is divided into at least one first multipath component area and a second multipath component area according to a pre-set dividing rule; the at least one first multipath component area is searched according to a pre-set first noise threshold, so as to acquire a valid multipath component signal in the at least one first multipath component area; and the second multipath component area is searched according to a pre-set second noise threshold, so as to acquire a valid multipath component signal in the second multipath component area.