LTE Cell Search with Adaptive Peak Selection for Large Frequency Offset
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Solution Overview
Problem
LTE cell search faces challenges with large frequency offsets due to its vulnerability to Carrier Frequency Offset (CFO), which affects synchronization performance and requires adaptive methods to reduce candidates and adjust parameters like the number of tries and threshold for peak selection, especially in low SNR conditions.
Innovation Solution
The solution involves a UE that divides received signals into multiple frequency bins, performs FFT and IFFT, and uses adaptive multi-try based peak selection to reduce candidates, with the number of tries and threshold adjusted based on channel conditions, and non-coherent accumulation adjusted based on SNR, along with fractional frequency offset estimation to select fine bin candidates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional PSS design is used for cell search, then the design is simple and works at low frequency offset, but synchronization performance deteriorates with large frequency offset up to 25 ppm
Solution Approach 1:
The patent segments the frequency offset compensation process into multiple stages: coarse frequency bin search with adaptive peak selection, followed by fine frequency offset estimation. This segmentation allows the system to handle large frequency offsets (up to 25 ppm) by breaking down the search space into manageable frequency bins, progressively refining the synchronization accuracy from coarse to fine levels.
2Measurement precision
If small coarse frequency bin with bandwidth smaller than 3.75 kHz is used, then frequency offset resolution is improved, but the number of candidates and computational complexity increases
Solution Approach 1:
The patent implements dynamic adaptive peak selection where the number of tries and threshold are adaptively adjusted based on channel conditions and SNR. This dynamic approach allows the system to maintain high frequency bin resolution while reducing the number of candidates in practice by adapting the search depth and threshold based on actual signal quality, rather than using a fixed exhaustive search.
Solution Approach 2:
The patent changes parameters such as the number of non-coherent accumulations and peak selection threshold based on SNR conditions. In low SNR conditions, more accumulations are performed to improve detection reliability, while in high SNR conditions, fewer accumulations are needed, thus adapting the computational complexity to the actual channel conditions rather than using a fixed high-complexity approach.
3Reliability
If higher number of non-coherent accumulation is performed, then detection reliability in low SNR is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent dynamically adjusts the number of non-coherent accumulations based on SNR measurements. In low SNR conditions, a higher number of accumulations is performed to improve detection reliability. In high SNR conditions, fewer accumulations are sufficient, thus maintaining processing speed. This dynamic adaptation resolves the contradiction by matching the processing complexity to the actual signal quality requirements.
Data Source
AI summary
Methods and devices for LTE cell search with large frequency offset are disclosed. In one embodiment of the invention, a UE divides the received signals into multiple frequency bins and transforms the signals into frequency domain through FFT. The UE performs correlating measures between the received signals and reference signals. The UE then performs an adaptive multi-try based peak selection such that the number of candidate is reduced. In one embodiment of the invention, the multi-try number is adaptively adjusted based on the channel condition. In one embodiment of the invention, the threshold of the peak selection is adaptively adjusted. In other embodiments of the invention, the UE performs non-coherent accumulation and selects a predefined number of coarse bin candidates. The number of non-coherent accumulation is adaptively adjusted. In another embodiment of the invention, the UE performs fractional frequency offset estimation and selects a fine bin candidate.