5G Uplink Packet Sizing for Low-Latency AR Streaming
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Solution Overview
Problem
Existing wireless communication systems face challenges in reducing latency and increasing bandwidth for bandwidth-intensive applications like augmented reality (AR) and virtual reality (VR) due to congestion and inefficient packet sizing in wireless uplink connections, leading to increased network overhead and underutilization of available resources.
Innovation Solution
Implementing a system that dynamically adjusts packet sizes based on real-time performance characteristics and network conditions, using edge cloud server equipment to optimize packet sizes for wireless uplinks, thereby reducing latency and improving throughput by selecting smaller packet sizes in congested conditions and maintaining efficient resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If larger packet sizes are used for uplink transmissions, then bandwidth efficiency is improved, but latency increases and network congestion worsens
Solution Approach 1:
The patent implements dynamic packet size adjustment where the packet size is not fixed but changes based on real-time network conditions. The system monitors uplink transmission performance and adapts packet sizes accordingly, making the transmission parameters dynamic rather than static to optimize both bandwidth efficiency and latency under varying network conditions
Solution Approach 2:
The system changes the transmission parameter (packet size) based on network conditions. By adjusting packet size as a variable parameter rather than using a fixed size, the system can optimize bandwidth efficiency when using larger packets while reducing latency when using smaller packets, depending on current network state
2Loss of time
If smaller packet sizes are used for uplink transmissions, then latency is reduced, but bandwidth efficiency decreases and network overhead increases
Solution Approach 1:
The system dynamically adjusts packet size based on real-time network conditions rather than using a fixed small packet size. This allows the system to use smaller packets when latency is critical while switching to larger packets when bandwidth efficiency is more important, optimizing both parameters under different conditions
Solution Approach 2:
The transmission system changes packet size as a controllable parameter based on network state. By making packet size adjustable, the system can reduce latency using smaller packets when needed while maintaining bandwidth efficiency through larger packets when appropriate
3Device complexity
If fixed packet sizes are used, then device complexity is reduced, but adaptability to network conditions worsens
Solution Approach 1:
The system implements self-service by automatically monitoring network conditions and adjusting packet sizes without requiring complex external control. The wireless device itself performs the adaptation based on observed transmission performance, reducing the need for complex network-side control mechanisms
Solution Approach 2:
The system uses feedback from uplink transmission performance to adjust packet sizes. By monitoring transmission outcomes and using this feedback to adapt packet size selections, the system achieves adaptability to network conditions through a relatively simple feedback-driven mechanism
4Adaptability or versatility
If dynamic packet size adjustment is implemented, then adaptability to network conditions is improved, but device complexity increases
Solution Approach 1:
The system achieves adaptability through self-service mechanisms where the device autonomously monitors its own transmission performance and adjusts packet sizes based on observed conditions. This self-monitoring and self-adjusting approach provides adaptability while keeping the control mechanism relatively simple
Solution Approach 2:
The system implements a feedback loop where transmission performance is monitored and used to guide packet size adjustments. This feedback-driven adaptation achieves network condition adaptability through a straightforward monitor-adjust cycle rather than complex predictive algorithms
Data Source
AI summary
The technologies described herein are generally directed to modeling radio wave propagation in a fifth generation (5G) network or other next generation networks. For example, a method described herein can include, for a network application, identifying, by a system comprising a processor, a characteristic value of a performance characteristic associated with an uplink connection enabled via a network of a user equipment to application server equipment hosting the network application. The method can further include, based on the characteristic value and a criterion, selecting, by the system, a first packet size for the uplink connection. The method can further include communicating, by the system, to the user equipment, the first packet size for use with the uplink connection.