Semi-Persistent Scheduling for Private 5G Networks
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Solution Overview
Problem
Traditional scheduling schemes in communication networks, particularly in private and local 5G networks, face challenges in supporting numerous users with frequent short messages, leading to high latency and unreliability due to complex system procedures and inadequate instantaneous resource allocation.
Innovation Solution
A semi-persistent scheduling (SPS) scheme is introduced, where a minimum SPS period consists of multiple sub-frames, allowing user equipment to use reserved wireless resources for immediate uplink transmissions without frequent re-scheduling, and utilizing stochastic geometry to optimize modulation and coding schemes based on expected channel states for improved reliability and data rate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional scheduling schemes are used to allocate wireless resources according to users' data requirements and channel states, then resource allocation can be adapted to instantaneous channel conditions, but the complex system procedures incur significant delay and reduce reliability for time-sensitive communications
Solution Approach 1:
The patent applies preliminary action by pre-configuring semi-persistent scheduling parameters and pre-establishing scheduling templates before actual data transmission occurs. The base station pre-calculates and signals scheduling parameters to user equipment in advance, allowing the UE to prepare transmission buffers and resources ahead of time, thereby eliminating the need for complex real-time scheduling procedures and reducing latency while maintaining reliability
Solution Approach 2:
The patent implements dynamics by introducing flexible scheduling parameters that can be dynamically adjusted based on channel conditions and data requirements. The semi-persistent scheduling mechanism allows for dynamic reconfiguration of scheduling parameters without requiring complete re-negotiation of the scheduling agreement, enabling the system to adapt to changing conditions while maintaining low latency operation
2Adaptability or versatility
If frequent scheduling updates are conducted to adapt to changing wireless environments, then scheduling can respond to channel variations, but the frequency of updates increases system overhead and processing time
Solution Approach 1:
The patent applies periodic action by establishing a semi-persistent scheduling framework where scheduling parameters are updated periodically rather than continuously or frequently. The base station and user equipment agree on a scheduling period that balances the need for adaptability to channel changes with the desire to reduce processing frequency. This periodic update mechanism maintains scheduling effectiveness while significantly reducing system overhead and processing complexity compared to frequent re-scheduling
3Productivity
If numerous users with massive frequent short messages are supported using traditional scheduling, then user coverage can be expanded, but the system overhead and signal processing time increase significantly
Solution Approach 1:
The patent applies preliminary action at scale by pre-establishing scheduling parameters and transmission templates for multiple users in advance. The base station pre-configures scheduling parameters for numerous users, allowing them to transmit data without requiring individual real-time scheduling processing. This approach enables the network to support a large number of users with frequent short messages while maintaining low signal processing time per user, as the heavy lifting of scheduling parameter determination is completed beforehand
Data Source
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AI summary
A method for semi-persistent scheduling (SPS) based resource allocation in a private 5G network comprises receiving location data of a plurality of user equipment (UEs) in the private 5G network in a last subframe of respective current communication periods of the UEs and determining distance distribution of the UEs in a subsequent communication period of a candidate UE of the plurality of UEs, based on the respective location data of the UEs. The method further comprises determining signal to noise ratio expectation of the UEs for the subsequent communication period, solving an optimization problem optimizing an expectation of data to be carried by each of the one or more SPS channels in the subsequent communication period, to obtain scheduling result for each of the one or more SPS channels and generating resource allocation data for the candidate UE based on the scheduling result.