Extended Random Access Preamble Classification for Non-Standard UE
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Solution Overview
Problem
The existing approaches for classifying user equipment (UE) in Evolved Universal Terrestrial Radio Access (E-UTRA) networks face limitations in identifying non-standard UE classes due to the limited number of random access preambles, which can lead to contention issues and inadequate resource allocation.
Innovation Solution
Generating an extended set of random access preambles through cyclic shifts of root sequences to identify non-standard UE classes before the random access response, allowing for special handling and resource allocation without increasing contention on the physical random access channel (PRACH).
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of random access preambles is increased to identify more UE classes, then the ability to classify non-standard UE classes is improved, but the contention on PRACH increases beyond acceptable levels
Solution Approach 1:
The patent segments the 64 available preambles into multiple groups (Group A, Group B, and additional groups) where each group serves specific UE class identification purposes. This segmentation allows the system to identify multiple UE classes without requiring all 64 preambles to be dedicated to class identification, thereby maintaining lower contention levels on PRACH while improving adaptability for non-standard UE classes.
Solution Approach 2:
The patent makes the random access preamble system multi-functional by enabling preambles to serve dual purposes: (1) traditional random access signaling and (2) UE class identification. By encoding UE class information within the preamble selection itself rather than requiring separate dedicated preambles for each class, the system achieves versatile UE class identification capability while maintaining efficient PRACH utilization and avoiding excessive contention.
2Measurement precision
If preambles are partitioned into more groups for UE classification, then the classification precision for different UE types is improved, but the complexity of the random access procedure increases
Solution Approach 1:
The patent applies local quality by assigning specific preamble groups to specific UE class identification needs. Each preamble group is locally optimized for particular UE types (e.g., Group A for coverage-enhanced UEs, Group B for non-coverage-enhanced UEs, additional groups for non-standard UE classes). This localized assignment improves classification accuracy for each UE type while keeping the overall procedure manageable through structured organization rather than uniform complex handling for all UEs.
Solution Approach 2:
The patent performs preliminary classification of UE classes during the random access preamble selection and transmission phase, before the actual random access procedure fully commences. By identifying UE class information early through preamble group selection, the system prepares the network side to apply appropriate handling strategies in advance, reducing the complexity of subsequent processing steps and enabling more precise classification without proportionally increasing overall procedure complexity.
Data Source
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AI summary
A random access process may be performed with an extended set of random access preambles comprising a standard set and at least one additional set. The use of a preamble from the standard set or the additional set may be used to indicate whether a wireless communication device belongs to a standard class or a non-standard class, allowing a radio access node to provide special treatment to the non-standard class in a random access response.