WiFi Transmit Power Scheduling in Mixed 5G/IoT Coverage
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Solution Overview
Problem
Existing IoT networks face challenges in developing efficient power-saving methods for managing connectivity and transmissions across multiple devices due to the complexity of 5G and Wi-Fi technologies, leading to high energy consumption and interference.
Innovation Solution
A dynamic transmit-power control (DTPC) mechanism using a transmission energy manager that incorporates a transmission sensing component, central compute engine, and transmission scheduling engine to analyze transmission metadata, apply machine learning models, and adjust transmission modes based on energy consumption profiles to minimize power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple connectivity options (5G and Wi-Fi) are provided for IoT devices, then communication reliability and coverage are improved, but energy consumption increases
Solution Approach 1:
The system dynamically adjusts transmit power levels and switches between 5G and Wi-Fi connectivity based on real-time channel conditions and energy constraints. The base station continuously monitors device status and adapts transmission parameters to maintain reliable communication while minimizing energy consumption.
Solution Approach 2:
The patent changes key transmission parameters including power level, modulation scheme, and connectivity mode (5G vs Wi-Fi) based on channel quality and device energy status. These parameter adjustments optimize the balance between communication reliability and energy consumption for each device.
2Reliability
If transmit power is increased to improve communication quality, then signal reliability is improved, but interference to other devices increases
Solution Approach 1:
The system applies different transmit power levels to different devices based on their specific channel conditions, distance from base station, and interference environment. This localized power control ensures each device receives adequate signal quality without unnecessarily increasing interference to other devices in the network.
Solution Approach 2:
The base station continuously receives feedback from devices about signal quality and channel conditions, then adjusts transmit power accordingly. This closed-loop control prevents excessive power transmission that would cause interference while maintaining sufficient signal reliability for each device.
3Measurement precision
If manual power management is implemented for each device, then energy control precision is improved, but system complexity increases
Solution Approach 1:
The base station acts as an intermediary that centralizes power management decisions. Instead of each device independently managing its power consumption, the base station collects channel information and device status, then makes optimized power control decisions for all devices, reducing individual device complexity while maintaining precise energy control.
Solution Approach 2:
The base station performs multiple functions including power control, connectivity management, and channel optimization simultaneously. This universal approach consolidates complex management tasks into a single entity, avoiding the need for complex power management logic in each individual IoT device.
Data Source
AI summary
In one embodiment, a method can receive transmission metadata associated with a plurality of devices within an Internet of Things (IoT) network. The method can use a transmission sensing component (TSC) to measure transmission energy cost for each of the plurality of devices over a time period using the transmission metadata. The method can use a central compute engine (CCE) and the transmission energy cost for each of the plurality of devices to determine a plurality of transmission features associated with the plurality of devices having a transmission energy cost that is minimized. The method can use a transmission scheduling engine (TSE) and the plurality of transmission features to generate a transmission mode schedule to reduce a transmission energy cost for the plurality of devices within the IoT network. The method can adjust a transmission mode associated with the plurality of devices based on the transmission mode schedule.