LTE-SSS Ghost Cell Detection via Signature Filtering
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Solution Overview
Problem
Cell search operations in LTE and 5G networks often result in false alarms due to the detection of non-existent 'ghost cells' caused by noise and interference, leading to inaccurate cell identification and impaired UE performance.
Innovation Solution
The implementation of signature-based filtering, which correlates M-sequences to generate correlations and combines them to form a likelihood of a SSS sequence, allowing for the comparison of a known signature to eliminate false alarm peaks during cell detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cell searching is performed using PSS and SSS detection, then synchronization and cell identification are achieved, but false alarms occur due to noise and interference causing ghost cell detection
Solution Approach 1:
The patent introduces an intermediary verification mechanism using SSS sequence signature checking. After initial cell detection through PSS/SSS correlation, the detected SSS sequence is verified against expected signature patterns. This intermediary step acts as a filter between the initial detection and final cell identification, eliminating ghost cells caused by noise and interference while preserving valid cell detections.
Solution Approach 2:
The patent implements feedback by using the detected SSS sequence to generate an expected signature and comparing it against the actual received signal characteristics. This feedback loop allows the system to verify detections and correct false alarms by identifying inconsistencies between expected and actual signal properties, thereby improving detection reliability.
2Reliability
If signature-based filtering is applied to eliminate false alarms, then ghost cell detection is reduced, but detection procedure complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing signature patterns for all possible SSS sequences before the actual cell detection process. During detection, the system simply compares received signals against these pre-computed signatures rather than performing complex real-time analysis. This shifts computational complexity from the detection phase to the initialization phase, reducing real-time processing requirements.
Solution Approach 2:
The patent uses copying by creating signature representations of expected SSS sequence characteristics and comparing these copies against actual received signals. Instead of performing complex direct analysis of the received signal, the system generates simplified signature copies that capture essential characteristics, making the filtering process more computationally efficient while maintaining detection accuracy.
Data Source
AI summary
Disclosed are example embodiments of cell detection in a mobile communications network. An example method includes performing a detection procedure in the mobile communications network, the detection procedure including correlating two M-sequences to generate two correlations, and combining the two correlations, each correlation expressed as a likelihood of a cyclic shift, combining the two correlations to form a likelihood of a SSS sequence; and performing a signature-based filtering to eliminate a cell detection false alarm peak, the signature-based filtering including comparing a known signature of a specific secondary synchronization signal SSS sequence going through the detection procedure.