Network Node Micro Sleep for High Speed Train Power Management
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Solution Overview
Problem
High-speed train communication networks face challenges in power consumption due to the inefficiency of existing power saving schemes, which are too slow to adapt to the rapid entry and exit of user equipment, leading to missed power saving opportunities and increased operational costs.
Innovation Solution
Implementing a dynamic power saving scheme that predicts the arrival and departure of user equipment, allowing for timely adjustments in power management, such as sleep modes and capacity changes, through mobility detection and communication between network nodes, enabling efficient power saving without compromising service quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional power saving schemes are deployed in HST networks, then power consumption is reduced during low demand periods, but the schemes are too slow to adapt to high-speed train movement causing missed power saving opportunities
Solution Approach 1:
The system performs preliminary actions by receiving advance information about incoming UEs before they actually enter the service area. The network node proactively adjusts power management settings in anticipation of the UE arrival, rather than reacting after the UEs are already present. This allows the power saving scheme to be activated early enough to handle high-speed movement while still capturing power saving opportunities.
Solution Approach 2:
The power management system transitions from static, slow-adjusting schemes to dynamic, real-time adaptation. The network node continuously monitors UE movement patterns and dynamically adjusts power saving parameters based on the actual speed and trajectory of incoming UEs, enabling the system to keep pace with high-speed train movement while optimizing energy consumption.
2Loss of energy
If power saving features are activated in HST networks, then operational costs are reduced, but large activation and deactivation time margins are required which result in losing power saving opportunities
Solution Approach 1:
The system eliminates time margin losses by performing power management adjustments in advance, based on predicted UE arrival times. The network node receives information about incoming UEs and proactively configures power saving parameters before the UEs actually enter the service area, ensuring that power saving opportunities are captured without requiring large activation margins.
Solution Approach 2:
The system implements feedback mechanisms where the network node continuously monitors actual UE arrival times and movement patterns, comparing these against predictions. Based on this feedback, the system refines its power management strategies to minimize both activation time margins and power saving opportunities lost, optimizing the balance between rapid response and energy efficiency.
3Loss of energy
If base stations remain in sleep mode to save power, then power consumption and overheating are reduced, but service quality may be compromised when UEs need rapid access
Solution Approach 1:
The system maintains service quality during sleep mode by performing preliminary wake-up actions and configuration adjustments before UEs actually need service. The network node anticipates UE arrival and pre-configures necessary parameters, ensuring that when UEs enter the service area, the base station can immediately provide quality service without requiring full-power operation throughout the entire service period.
Solution Approach 2:
The system dynamically adjusts the sleep-wake cycle based on real-time UE movement patterns and service requirements. Rather than remaining in a static sleep state, the base station transitions to an active state only when and where needed, optimizing the balance between power savings and service quality through continuous monitoring and adaptive response.
Data Source
AI summary
In one aspect, a network node receives a message indicating that UEs that require service are expected to enter a service area of the network node. The network node determines, based on the message, that a change in power management for radio equipment corresponding to the service area is required. The network node determines a timing for initiating the change in power management for the radio equipment, taking into account a predicted time for when the UEs are expected to enter the service area, and triggers the change in power management for the radio equipment, based on the determined timing. In another aspect, the network node predicts a departure time from the first service area for the UEs. The network node then sends to another network node, prior to the predicted departure time, an indication that the UEs are expected to enter a service area of the other network node.