Dynamic Transmission Gap Configuration for Wireless Latency and Distortion
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Solution Overview
Problem
Current wireless communication technologies, such as LTE and NR, face challenges in optimizing transmission gaps for efficient communication, particularly in configuring parameters like sounding reference signals, numerology, and antenna settings, which affect latency and network coverage, especially in high-demand mobile broadband scenarios.
Innovation Solution
The method involves determining and configuring a transmission gap for a set of transmissions based on parameters such as sounding reference signal, numerology, and antenna settings, allowing for dynamic adjustment of transmission gaps to optimize communication efficiency and reduce distortion, thereby enhancing network coverage and latency performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If transmission gap is reduced to improve latency, then communication speed improves, but signal distortion increases
Solution Approach 1:
The patent implements dynamic transmission gap configuration where the gap duration is adjusted based on real-time channel conditions, signal quality metrics, and traffic requirements. This allows the system to optimize the trade-off between latency and signal distortion by adapting the gap size to current operational needs rather than using fixed gap values.
Solution Approach 2:
The system changes key parameters including transmission gap duration, power levels, and modulation schemes based on channel conditions and service requirements. By dynamically adjusting these parameters, the system can reduce latency when conditions permit while maintaining signal quality through appropriate parameter selection.
2Area of stationary object
If transmission resources are increased to improve network coverage, then coverage area expands, but resource utilization efficiency decreases
Solution Approach 1:
The patent employs dynamic resource allocation where transmission resources such as power, bandwidth, and time slots are adjusted in real-time based on channel conditions, user density, and service requirements. This dynamic approach ensures that resources are allocated efficiently across the coverage area, expanding coverage where needed while maintaining high utilization efficiency by avoiding waste in well-covered areas.
Solution Approach 2:
The system applies different transmission parameters and resource allocation strategies to different geographic locations and service types within the network. Edge regions receive enhanced resources for coverage extension, while central regions with good coverage maintain efficient resource utilization. This localized optimization resolves the contradiction between coverage expansion and resource efficiency.
Data Source
AI summary
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment may determine a transmission gap for a set of transmissions including a first type of transmission and a second type of transmission based at least in part on at least one of a sounding reference signal parameter, a numerology parameter, or an antenna parameter. In some aspects, the user equipment may transmit at least one transmission, the set of transmissions, in accordance with the transmission gap for the set of transmissions based at least in part on determining the transmission gap for the set of transmissions. Numerous other aspects are provided.