Dynamic Random Access Preamble Allocation for Mixed H2H and M2M Traffic
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Solution Overview
Problem
Current wireless communication systems face challenges in efficiently managing random access preambles for human-to-human (H2H) and machine-to-machine (M2M) communications, particularly in handling the high frequency of data connections and random access load from a large population of M2M devices, which leads to increased operational costs and inefficient resource allocation.
Innovation Solution
A method is proposed where a base station estimates the arrival rates of H2H and M2M user equipment (UE) by collecting information on the number of preambles sent during the last successfully completed random access procedure, determining a random access preamble allocation mode, and broadcasting a radio resource control (RRC) message to allocate preambles without overlap or with partial overlap based on these rates, optimizing resource allocation between H2H and M2M communications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If random access preambles are allocated without overlap between H2H and M2M UEs, then collision probability is reduced and access reliability is improved, but resource utilization efficiency deteriorates due to idle preambles
Solution Approach 1:
The patent implements dynamic preamble allocation where the base station adjusts the allocation mode between non-overlapping and partially overlapping preambles based on real-time arrival rates of H2H and M2M UEs. The system transitions from static to dynamic allocation, adapting to changing traffic conditions to optimize both reliability and resource utilization.
Solution Approach 2:
The patent changes the allocation parameters (preamble sets and allocation mode) based on estimated arrival rates of different UE types. By monitoring and responding to parameter changes in traffic patterns, the system optimizes the balance between collision avoidance and resource efficiency.
2Reliability
If more random access preambles are allocated to M2M UEs, then access success rate for M2M devices is improved, but the number of available preambles for H2H UEs is reduced
Solution Approach 1:
The system dynamically adjusts the number of preambles allocated to M2M and H2H UEs based on their respective arrival rates. When M2M traffic intensity increases, the base station allocates more preambles to M2M UEs, and vice versa, ensuring optimal distribution under varying conditions.
Solution Approach 2:
The patent modifies allocation parameters (number of preambles per UE type) based on estimated arrival rates. This parameter adaptation allows the system to respond to changing traffic demands and maintain optimal performance for both UE types.
3Measurement precision
If the base station collects detailed UE information and estimates arrival rates, then resource allocation accuracy is improved, but system complexity and signaling overhead increase
Solution Approach 1:
The base station implements a feedback mechanism where UEs report their preamble transmission history, and the base station uses this feedback to estimate arrival rates and adjust allocations. This closed-loop control improves accuracy while keeping the complexity manageable through standardized feedback procedures.
Solution Approach 2:
UEs self-report their random access behavior (number of preambles sent in last successful procedure), enabling the base station to gather necessary information without complex monitoring. The UEs serve themselves by providing the data needed for accurate estimation.
Data Source
AI summary
A method for determining a proper preamble allocation mode is provided. The method is applicable to a base station communication with a number of human to human UEs and machine to machine UEs. The base station collects information from different types of UEs to figure out arrival rates for human to human type random access attempts and machine to machine type random access attempts. The base station selects one allocation mode out of two different allocation modes. In one mode, random access preambles are dedicatedly allocated to machine to machine type UES. In the other mode, preambles are commonly allocated to different types of UEs. The base station indicates the selected allocation mode by using system information block such as SIB2.