Wireless Link State Transition Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data transmission technologies experience delays due to link state transitions, particularly in wireless networks, leading to poor user experience and increased network strain, as users wait for link states to transition between active and idle states during sequential requests, which is not effectively addressed by increasing infrastructure or developing faster network technologies.
Innovation Solution
An optimization system comprising four modules: the activity, environment, and load monitor module; the state transition control module; the channel state influencer module; and the policy and preference handler module, which monitor and manage link-layer activity, influence state transitions based on user equipment type, battery life, spectral cost, and network load, and control transitions using policy and preferences to minimize waiting times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the link layer state transitions out of active state due to inactivity, then energy consumption is reduced, but user experience deteriorates due to delays when transitioning back to active state
Solution Approach 1:
The system performs preliminary actions by sending keep-alive messages or pings before the inactivity timer expires, preventing the link from transitioning to idle state. This maintains the link in active state, eliminating transition delays when users need to access additional pages while consuming minimal extra energy compared to the user experience degradation.
Solution Approach 2:
The system dynamically adjusts link state transition behavior based on application type, user equipment characteristics, and network conditions. For example, it applies different strategies for web browsing versus video streaming, and adapts to whether the device is battery-powered or connected to AC power, optimizing the balance between energy consumption and response time for each scenario.
2Productivity
If infrastructure is increased to provide more bandwidth, then network capacity is improved, but cost increases
Solution Approach 1:
The system enables networks to self-optimize by automatically monitoring link state transitions and application performance, then dynamically adjusting state transition thresholds and behaviors. This self-service capability improves network capacity and user experience without requiring manual infrastructure expansion or additional human intervention, thereby avoiding the costs associated with building more cell towers.
3Speed
If link state transitions are accelerated, then responsiveness is improved, but energy consumption increases
Solution Approach 1:
The system sends keep-alive messages or pings preliminarily before the inactivity timer would trigger a state transition. This preliminary action maintains the link in active state without requiring rapid transitions, achieving responsiveness by preventing the transition rather than accelerating recovery from it, thus avoiding excessive energy consumption.
4Loss of time
If the link remains in active state longer, then user experience is improved, but radio resource contention increases
Solution Approach 1:
The system applies different link state management strategies to different applications and user equipment based on their specific characteristics. For example, it may maintain active state longer for latency-sensitive applications like video streaming or online gaming, while allowing faster transitions for less time-critical applications. This localized optimization improves waiting time for critical applications without causing excessive radio resource contention across the entire network.
Data Source
AI summary
A system for optimizing communications on a radio network by altering transitions between different link states that includes several modules. The activity, environment, and load module monitor monitors the link layer based on spectral-load metrics and radio-link metrics. The state transition control module determines when user equipment transitions between different states based on the type of user equipment, user equipment battery life, whether the user equipment is connected to an alternating current outlet, a spectral cost, and a backhaul cost. The channel state influencer module uses any of direct messages, ping messages, and keep-alive messages to influence the link state. The policy and preference handler enables or disables transitions based on the bearer technology type, the type of user equipment, the user's subscription plan, and the load level on the network.


