Dynamic Network Capacity Estimation for Wireless Off-Peak Utilization
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Solution Overview
Problem
Wireless broadband network service providers face challenges in efficiently utilizing network capacity, leading to underloaded networks during off-peak times, which can result in inefficient resource usage and inaccurate capacity determination.
Innovation Solution
The system dynamically estimates future network usage to identify excess capacity and offers time slots for data service during unused periods, allowing customers to access unlimited data without counting against their monthly limit, thereby optimizing network utilization and determining actual capacity under loaded conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the network operates with predetermined data usage limits, then customers are cautious in using high bandwidth applications, but network capacity remains underutilized during off-peak times
Solution Approach 1:
The patent applies dynamics by transitioning from static predetermined data usage limits to dynamic estimation of excess network capacity. The system continuously monitors network conditions and adjusts capacity allocation in real-time, allowing the network to adapt to changing demand patterns. This enables the network to dynamically identify and utilize excess capacity during off-peak times while maintaining appropriate limits during peak periods, thereby improving overall network utilization without compromising service quality.
Solution Approach 2:
The patent implements parameter changes by modifying the data usage limit parameter from a fixed predetermined value to a dynamically estimated excess capacity value. The system changes this parameter based on real-time network conditions, historical usage patterns, and predicted demand. This allows the network to optimize utilization by allowing higher usage during periods of excess capacity while maintaining control during peak times, effectively resolving the contradiction between utilization and capacity waste.
2Measurement precision
If the network operates with predetermined data usage limits, then service providers can manage capacity planning, but inaccurate capacity determination prevents optimal resource allocation
Solution Approach 1:
The patent applies feedback by implementing a continuous monitoring and estimation loop that tracks actual network usage, compares it with predetermined limits, and uses this information to refine excess capacity estimates. The system incorporates historical usage data and real-time network conditions into its estimation process, creating a feedback mechanism that progressively improves capacity determination accuracy. This accurate measurement enables optimal resource allocation by providing reliable data for capacity planning and decision-making.
Solution Approach 2:
The patent implements preliminary action by using historical usage data and predictive algorithms to estimate excess capacity in advance of actual network conditions. The system performs preliminary analysis of usage patterns and network performance to proactively identify periods of excess capacity before they occur. This advance preparation enables more accurate capacity determination and allows the system to optimize resource allocation proactively rather than reactively, improving both measurement precision and productivity.
3Quantity of substance
If customers are charged for exceeding data plan limits, then service providers can generate additional revenue, but customers avoid high bandwidth applications even when network capacity is available
Solution Approach 1:
The patent applies partial or excessive action by allowing customers to exceed their predetermined data limits when excess network capacity is available. Instead of strictly enforcing hard limits, the system permits partial overage usage during periods of underutilized capacity, effectively utilizing otherwise wasted network resources. This approach increases overall data usage volume and network utilization while maintaining appropriate limits during peak times, resolving the contradiction between revenue generation and resource efficiency.
Solution Approach 2:
The patent implements self-service by enabling the network system to automatically identify excess capacity and dynamically adjust data limit allocations without requiring manual intervention or customer awareness. The system autonomously monitors network conditions, estimates excess capacity, and modifies usage permissions accordingly. This self-adjusting mechanism increases data usage volume during periods of excess capacity while maintaining service quality, improving network utilization without complex customer management overhead.
Data Source
AI summary
A method may include determining a capacity metric for sectors in a network, estimating a usage metric for each of the sectors for periods of time and determining a number of user devices that can access data services based on the capacity metric and the usage metric. The method may also include storing information identifying the determined number of user devices, receiving a request from a first user device for access to data services during a first period of time and accessing the stored information to determine whether the number of user devices that can access data services for the first period of time is greater than zero. The method may further include providing access via the wireless network to the first user device during the first period of time, in response to determining that the number of user devices that can access data services is greater than zero.