ZC Sequence Group Detection Windows for High-Speed Random Access
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Solution Overview
Problem
In very-high-speed movement scenarios, the LTE system faces challenges in correctly detecting the round trip delay (RTD) of random access signals due to high frequency deviations, leading to difficulties in ensuring proper network access for user equipment.
Innovation Solution
A method is introduced that selects a ZC sequence group based on cell type and a cyclic shift parameter, sets multiple detection windows for each ZC sequence, and determines an estimated RTD value by correlating the random access sequence with the ZC sequences, ensuring accurate timing adjustment for user equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single detection window is used for RTD detection, then the detection process is simple, but the RTD detection accuracy deteriorates in high-speed scenarios with large frequency deviations
Solution Approach 1:
The detection process is segmented into multiple detection windows (first detection window, second detection window, third detection window, etc.) instead of using a single detection window. Each window is assigned to detect specific peak values corresponding to different frequency deviation ranges. This segmentation allows the system to accurately detect RTD across a wide frequency deviation range while maintaining manageable complexity through structured multi-window processing.
2Measurement precision
If multiple detection windows are used to improve RTD detection accuracy, then the detection precision improves, but the processing complexity increases
Solution Approach 1:
Each detection window is optimized for specific local conditions (frequency deviation ranges). The first detection window detects peak values in a first frequency deviation range, the second detection window detects peak values in a second frequency deviation range, and so on. This local optimization allows each window to be tuned for its specific frequency range, improving overall detection accuracy while keeping the complexity of each individual window manageable.
Solution Approach 2:
The system dynamically selects which detection window to use based on the detected frequency deviation. When a peak value is detected in a specific frequency deviation range, the corresponding detection window is activated. This dynamic adaptation allows the system to handle varying frequency deviations efficiently without processing all windows simultaneously, thereby managing complexity while maintaining high detection accuracy across different scenarios.
3Speed
If traditional single-window detection is used, then the processing speed is fast, but the access performance deteriorates in very-high-speed scenarios
Solution Approach 1:
The system performs preliminary frequency deviation estimation before RTD detection by analyzing the received signal's frequency characteristics. Based on this preliminary estimation, the appropriate detection window is pre-selected. This preliminary action ensures that the correct detection window is used from the start, avoiding the need for exhaustive searching across all windows, thus maintaining fast processing speed while ensuring reliable access performance in very-high-speed scenarios.
Solution Approach 2:
The system uses feedback from the detected peak value's frequency deviation to determine which detection window should be used for RTD measurement. The detected frequency deviation feeds back into the decision logic that selects the appropriate detection window, creating a closed-loop system that adapts to the actual signal conditions. This feedback mechanism ensures both fast processing (by directly selecting the appropriate window) and reliable access performance (by using the correct window for the detected frequency range).
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables user equipment in high-speed scenarios to correctly access the network by accurately determining the RTD, thereby improving access performance and maintaining network connectivity.
Implementation Method 1
performing correlation processing on the random access sequence with each ZC sequence in the ZC sequence group, detecting a valid peak value in the N detection windows of each ZC sequence
Data Source
AI summary
A method for processing very-high-speed random access includes: selecting a Zadoff-Chu (ZC) sequence group according to a cell type and a first cyclic shift parameter Ncs, and setting N detection windows for each ZC sequence in the ZC sequence group, where N≥5; sending the cell type, a second Ncs, and the ZC sequence group to a user equipment (UE); receiving a random access signal sent by the UE, and obtaining the random access sequence from the random access signal; performing correlation processing on the random access sequence with each ZC sequence in the ZC sequence group, detecting a valid peak value in the N detection windows of each ZC sequence, and determining an estimated value of a round trip delay (RTD) according to the valid peak value, so that a UE in a very-high-speed scenario can normally access a network, thereby improving network access performance.