PRACH Repetition Differentiation in Wireless Random Access
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Solution Overview
Problem
In wireless communications, the ambiguity in the number of physical random access channel (PRACH) repetitions between user equipment (UE) and the base station can lead to misalignment in the RAR window, impacting successful communication and network performance, as the UE and gNB may not be in agreement regarding the number of repetitions, resulting in potential decoding losses and resource wastage.
Innovation Solution
The proposed solution involves determining the number of PRACH repetitions based on associated resources, such as PRACH preambles or their subsets, time domain, or frequency domain locations, allowing the network entity to process and align the PRACH repetitions accordingly, ensuring optimal network performance and successful communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the UE and gNB use different methods to determine the number of PRACH repetitions, then each device can independently optimize its parameters, but misalignment occurs leading to decoding losses and resource wastage
Solution Approach 1:
The patent implements feedback mechanisms where the gNB provides configuration information to the UE regarding PRACH repetition parameters. The network entity determines the number of repetitions and communicates this to the UE, ensuring both devices use the same value. This feedback loop resolves the misalignment issue while maintaining the ability to adapt to different channel conditions through configurable parameters.
Solution Approach 2:
The patent introduces configuration messages and signaling protocols as intermediaries between the UE and gNB. These intermediaries carry the determined PRACH repetition number from the network entity to the UE, ensuring both parties agree on the parameter value. This intermediary mechanism enables coordinated operation while allowing independent optimization capabilities.
2Reliability
If the number of PRACH repetitions is increased to improve coverage and reliability, then successful access probability increases, but power consumption and delay increase
Solution Approach 1:
The patent implements dynamic determination of PRACH repetition numbers based on current channel conditions, coverage requirements, and network load. The network entity adjusts the repetition count adaptively rather than using fixed values, allowing the system to optimize between reliability and power consumption based on real-time conditions. This dynamic approach enables lower repetitions when conditions permit, reducing UE power consumption while maintaining sufficient access success probability.
Solution Approach 2:
The patent changes the PRACH repetition parameter based on determined channel quality and coverage needs. By dynamically adjusting this key parameter, the system can reduce the number of repetitions (and thus power consumption) when channel conditions are good, while increasing repetitions when coverage extension is needed. This parameter adaptation resolves the contradiction between reliability and energy consumption.
3Reliability
If the number of PRACH repetitions is increased to ensure reliable reception, then decoding success improves, but processing time and network delay increase
Solution Approach 1:
The patent implements dynamic adjustment of PRACH repetition numbers based on real-time channel conditions and network state. When channel quality is good or coverage requirements are met with fewer repetitions, the system reduces the repetition count, thereby reducing access delay. This dynamic approach maintains high decoding success rates while minimizing time loss compared to always using maximum repetitions.
Solution Approach 2:
The patent modifies the PRACH repetition parameter adaptively based on determined channel quality indicators and coverage requirements. By changing this parameter according to actual conditions rather than using fixed high values, the system achieves reliable decoding when needed while reducing delay in favorable conditions. This parameter adaptation directly addresses the time-reliability tradeoff.
Data Source
AI summary
Certain aspects of the present disclosure provide techniques for differentiating physical random access channel (PRACH) repetition numbers. An example method, performed by a network entity, includes receiving at least one physical random access channel (PRACH) repetition, of a group of PRACH repetitions, determining a number of PRACH repetitions in the group, based on at least one resource associated with the at least one PRACH repetition, and processing the group of PRACH repetitions, in accordance with the determination.