Beam Duration Prediction for Wireless Latency Reduction
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Solution Overview
Problem
Current wireless networking technologies face inefficiencies due to high latency and increased signaling overhead caused by sweeping multiple beams during initial access operations, which reduces system throughput and spectral efficiency.
Innovation Solution
User equipment predicts durations for which channel quality will satisfy a quality threshold using neural networks, such as recurrent neural networks, based on previous measurements and location data, and reports these predictions to the uplink node, allowing the node to select optimal beams for communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple beams are swept during initial access operations, then beam quality and coverage are improved, but latency and signaling overhead increase
Solution Approach 1:
The system performs preliminary measurements of channel qualities for multiple beams before actual data transmission. Based on these pre-measured channel qualities and predicted durations, the network node determines which beams will satisfy quality thresholds for sufficient time periods, allowing selective scheduling that avoids unnecessary beam sweeping during data transmission.
Solution Approach 2:
The system dynamically adjusts beam selection based on predicted beam durations. The network node schedules data transmission on beams that are predicted to maintain quality thresholds for at least a minimum duration, adapting beam usage to real-time channel conditions and mobility patterns rather than using fixed beam sweeping procedures.
2Reliability
If multiple beams are swept during initial access operations, then beam quality and coverage are improved, but system throughput decreases
Solution Approach 1:
The system performs preliminary measurements of channel qualities for multiple beams before actual data transmission. Based on these pre-measured channel qualities and predicted durations, the network node determines which beams will satisfy quality thresholds for sufficient time periods, allowing selective scheduling that avoids unnecessary beam sweeping during data transmission.
Solution Approach 2:
The system dynamically adjusts beam selection based on predicted beam durations. The network node schedules data transmission on beams that are predicted to maintain quality thresholds for at least a minimum duration, adapting beam usage to real-time channel conditions and mobility patterns rather than using fixed beam sweeping procedures.
3Reliability
If multiple beams are swept during initial access operations, then beam quality and coverage are improved, but spectral efficiency decreases
Solution Approach 1:
The system performs preliminary measurements of channel qualities for multiple beams before actual data transmission. Based on these pre-measured channel qualities and predicted durations, the network node determines which beams will satisfy quality thresholds for sufficient time periods, allowing selective scheduling that avoids unnecessary beam sweeping during data transmission.
Solution Approach 2:
The system dynamically adjusts beam selection based on predicted beam durations. The network node schedules data transmission on beams that are predicted to maintain quality thresholds for at least a minimum duration, adapting beam usage to real-time channel conditions and mobility patterns rather than using fixed beam sweeping procedures.
Data Source
AI summary
A method performed by a user equipment can include predicting, for at least one beam received from an uplink node, at least one duration for which a channel quality will satisfy a quality threshold; and reporting the at least one duration to the uplink node.