Wireless Network Congestion Management via Dynamic Bitrate Scheduling
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Solution Overview
Problem
In wireless communications networks, a simple uplink bitrate cap is sub-optimal as it does not account for varying distances of devices from the base station, leading to inefficient bandwidth usage and potential abuse, as devices closer to the base station can utilize excess bandwidth at the expense of others, while devices farther away are limited.
Innovation Solution
Implementing a congestion management mechanism that measures and prioritizes scheduling based on congestion levels, using a processor to adjust scheduling weights according to measured congestion, packet drops, and ECN markings, allowing devices to adapt their bitrates dynamically and ensuring fair resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If an uplink bitrate cap is applied per device, then individual devices are limited to prevent excessive bandwidth usage, but devices closer to the base station cannot utilize their excess capacity while devices farther away are unfairly limited
Solution Approach 1:
The patent applies different bitrate caps to different devices based on their local conditions, specifically their distance from the base station. Devices closer to the base station receive higher bitrate caps since they have better channel conditions and can utilize the excess capacity, while devices farther away receive lower caps appropriate to their channel limitations. This localized differentiation resolves the contradiction by making the bitrate allocation fair and efficient simultaneously.
Solution Approach 2:
The patent implements dynamic bitrate caps that adjust based on real-time congestion measurements and device performance. Rather than static caps, the system continuously adapts the bitrate allocation to current network conditions, device locations, and congestion levels. This dynamic approach allows the system to optimize both fairness and overall utilization by responding to changing conditions.
2Reliability
If a simple bitrate cap is enforced, then network congestion is controlled, but LEDBAT applications cannot achieve high bitrates during low network activity
Solution Approach 1:
The patent implements a feedback mechanism where the network monitors congestion levels and dynamically adjusts bitrate caps in response. LEDBAT applications can achieve high bitrates during low activity periods because the system responds to actual congestion conditions rather than imposing static limits. When congestion is detected, the feedback loop reduces the bitrate caps to maintain control, otherwise allowing high performance.
Solution Approach 2:
The system transitions from static bitrate caps to dynamic, condition-based caps that adapt to real-time network state. This allows LEDBAT applications to benefit from high available bandwidth during low activity while the network maintains congestion control when needed, resolving the contradiction between control and performance.
3Reliability
If congestion management requires modification to every node, then comprehensive congestion control is achieved, but implementation becomes very difficult in existing networks
Solution Approach 1:
The patent extracts the complex congestion management functionality from individual network nodes and consolidates it in the base station. Rather than requiring modifications to every node in the network, the base station performs centralized congestion measurement and bitrate cap management. This extraction maintains comprehensive control while dramatically simplifying deployment in existing networks.
Solution Approach 2:
The base station acts as an intermediary that coordinates congestion management across the network. It measures congestion, determines appropriate bitrate caps, and communicates these to devices without requiring other network nodes to be modified. This intermediary approach achieves comprehensive congestion control through a single point of management.
Data Source
AI summary
A wireless communications network for communicating with wireless communications devices, the wireless communications network comprising a processor arranged to: measure congestion for each wireless communication link between a plurality of the wireless communications devices and the wireless communications network; and prioritize scheduling of communications with the plurality of wireless communications devices dependent upon the measured congestion.