LLTF SINR Estimation Accounting for Inter-Symbol Interference
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing SINR estimation methods fail to account for Inter Symbol Interference (ISI) in Wi-Fi systems, particularly in recent generations like Wi-Fi 6 and Wi-Fi 7, leading to performance degradation due to short guard intervals.
Innovation Solution
A method for SINR estimation that involves extracting groups of transmission symbols from the LLTF, constructing fragmented symbols, and calculating Sum of Squared Magnitudes (SSM) to estimate SINR, accounting for ISI by determining SSM of signal, noise, and ISI, using equations to calculate the correct SINR.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If short guard intervals are used in Wi-Fi 6 and Wi-Fi 7 systems, then spectral efficiency and data rate are improved, but Inter Symbol Interference (ISI) increases causing performance degradation
Solution Approach 1:
The LLTF is segmented into multiple groups of transmission symbols (first group, second group, third group) with different ISI characteristics. By dividing the training field into segments, the system can selectively process symbols with different ISI contamination levels separately, allowing accurate SINR estimation despite the presence of ISI in short guard interval configurations
Solution Approach 2:
The method extracts and identifies specific transmission symbols from the LLTF that are affected by ISI from previous symbols. By taking out and separately analyzing these ISI-affected symbols, the system can calculate their contribution to the received signal and subtract it from the total SINR measurement, thereby isolating the true signal quality metric
2Device complexity
If existing SINR estimation methods are used without accounting for ISI, then estimation complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent introduces an intermediary calculation step that computes the SSM of ISI-affected symbols separately. This intermediary value serves as a mediator between the raw received signal and the final SINR estimation, allowing the system to account for ISI effects without requiring complex iterative algorithms or advanced signal processing techniques
Solution Approach 2:
The method performs preliminary identification and extraction of ISI-affected transmission symbols before conducting the main SINR estimation. By pre-processing the LLTF to identify which symbols are contaminated by ISI from previous symbols, the system can apply simplified correction calculations rather than complex post-processing algorithms
Data Source
AI summary
Signal to Interference and Noise Ratio (SINR) estimation, and more specifically providing SINR estimation during Legacy Long Training Field (LLTF) accounting for Inter Symbol Interference (ISI) may be provided. SINR estimation may include receiving a Physical Layer Protocol Data Unit (PPDU) including a LLTF and extracting groups of transmission symbols from the LLTF. Next, groups of fragmented symbols may the groups of transmission symbols. One or more Sum of the Squared Magnitudes (SSM) may be determined, such as an SSM of the total signal, an SSM of the signal without ISI and/or noise, an SSM of ISI, an SSM of noise. Finally, SINR may be estimated using one or more SSMs (e.g., the SSM of noise, the SSM of signal, and the SSM of ISI).