Wireless Uplink Prescheduling to Reduce Wasted-Grant Interference
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Solution Overview
Problem
Existing wireless communication networks face challenges in efficiently managing uplink scheduling, leading to increased latency and interference due to the difficulty in configuring parameters like preschedulingDuration and machine learning thresholds, which are not easily adjustable to account for varying load and traffic profiles.
Innovation Solution
Implementing dynamic machine learning decision thresholds and adjusting parameters such as preschedulingDuration, threshold for binary prediction, and preschedulingPeriodicity to control the aggressiveness of uplink scheduling, based on real-time load and traffic conditions, thereby reducing interference and optimizing resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If prescheduling is used to reduce latency by sending UL grants in advance, then uplink transmission speed is improved, but interference increases due to wasted grants when WDs have no data to transmit
Solution Approach 1:
The patent implements a feedback mechanism where the network node monitors whether WDs have data to transmit before sending prescheduled UL grants. The network node receives indications from WDs about their buffer status and adjusts prescheduling decisions based on this feedback, thereby reducing wasted grants and interference while maintaining low latency for active transmissions.
Solution Approach 2:
The patent dynamically adjusts the prescheduling behavior based on real-time network conditions and WD data availability. Instead of static prescheduling, the system adapts the granting of UL resources dynamically by monitoring WD buffer status and traffic patterns, optimizing the balance between transmission speed and interference reduction.
2Object-generated harmful factors
If preschedulingDuration parameter is decreased to reduce wasted UL grants and interference, then interference is reduced, but latency increases as prescheduling becomes less aggressive
Solution Approach 1:
The patent enables the system to self-adjust the prescheduling aggressiveness by automatically monitoring WD data availability and dynamically controlling prescheduling behavior. The network node serves itself by making intelligent decisions about when to apply prescheduling based on observed traffic patterns, eliminating the need for manual parameter tuning while optimizing both interference and latency performance.
Solution Approach 2:
The patent dynamically changes the effective preschedulingDuration parameter based on real-time conditions. Instead of using a fixed parameter value, the system adjusts the prescheduling window length dynamically according to WD buffer status and traffic characteristics, allowing optimal performance across varying network conditions without manual intervention.
3Object-generated harmful factors
If manual configuration of preschedulingDuration parameter is used to control prescheduling aggressiveness, then interference can be controlled, but the system becomes complex and difficult to tune for varying load and traffic profiles
Solution Approach 1:
The patent implements self-service by enabling the network node to automatically monitor WD data availability and dynamically control prescheduling behavior without manual parameter configuration. The system serves itself by making intelligent decisions about prescheduling based on observed traffic patterns, eliminating the need for complex manual tuning while optimizing both interference and latency performance.
Solution Approach 2:
The patent replaces static manual parameter configuration with dynamic adaptive control. The system automatically adjusts prescheduling behavior in real-time based on WD buffer status and traffic conditions, transforming a complex manual tuning problem into an automated dynamic optimization process that adapts to varying network conditions.
4Measurement precision
If scheduling requests (SR) and buffer-status-reports (BSR) are used to inform the network node of data availability, then accurate scheduling decisions can be made, but latency increases due to the periodic nature of SR resources
Solution Approach 1:
The patent applies preliminary action by having WDs continuously monitor and maintain information about their data buffer status, and by having the network node maintain prescheduling information in advance. When data arrives at the WD, the scheduling decision can be made immediately using pre-prepared information, eliminating the need to wait for periodic SR opportunities and reducing latency while maintaining accurate buffer status reporting.
Data Source
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AI summary
A method implemented in a network node for scheduling uplink communications from a wireless device is provided. The method includes receiving, at the network node from a WD, a plurality of UL responses associated with UL scheduling. For each received UL response from the plurality of UL responses, a type of the received UL response is determined based at least in part on contents of the received UL response, including a regular UL grant and a wasted UL grant. For each received UL response from the plurality of UL responses, a UL scheduling aggressiveness parameter to control UL scheduling of the WD is determined. The UL scheduling aggressiveness parameter is based at least in part on the determined type of UL response. The method includes, optionally, performing UL scheduling of the WD based on the updated UL scheduling aggressiveness parameter.