Small Node Activation Control for Cellular Network Power Optimization
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Solution Overview
Problem
Existing solutions for managing small node activation and deactivation in heterogeneous cellular networks are inefficient, leading to frequent switching, instability, and high maintenance costs, and are not adapted to handle dynamic conditions caused by high-density small nodes.
Innovation Solution
A method that dynamically manages small node activation and deactivation based on historical and current traffic load conditions, using a three-module algorithm to identify candidate time snapshots for deactivation and activation, and a power consumption model to optimize radio resource allocation, thereby reducing power consumption while maintaining traffic load satisfaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If small nodes are frequently activated and deactivated to optimize power consumption, then power consumption is reduced, but network stability deteriorates and maintenance costs increase
Solution Approach 1:
The system performs preliminary evaluation of traffic load conditions and predicts future network states before making activation/deactivation decisions. By analyzing historical traffic patterns and current load conditions, the system determines optimal timing for node state changes, avoiding frequent switching that would compromise network stability while still achieving power consumption reduction goals.
2Productivity
If multiple small nodes are deployed to handle high traffic load, then network capacity increases, but power consumption increases
Solution Approach 1:
The system dynamically adjusts the operational state of small nodes based on real-time traffic load conditions. Instead of keeping all nodes continuously active, the system monitors traffic patterns and activates or deactivates nodes as needed, enabling the network to maintain high capacity when required while reducing power consumption during low-traffic periods.
Solution Approach 2:
The system changes the operational parameters of small nodes by transitioning them between active and deactivated states based on traffic load thresholds. This parameter change approach allows the network to optimize the balance between capacity and power consumption by adjusting node states according to actual network demands rather than maintaining fixed operational parameters.
3Loss of energy
If small nodes are deactivated to reduce power consumption, then power consumption is reduced, but traffic load handling capability deteriorates
Solution Approach 1:
The system continuously monitors traffic load conditions and uses this feedback to make informed decisions about node activation and deactivation. By implementing feedback mechanisms that track network performance and traffic patterns, the system ensures that nodes are deactivated only when traffic load is sufficiently low, thereby maintaining traffic handling capability while achieving power consumption reduction.
Data Source
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AI summary
A method (200) for managing a cellular network (100) is proposed. The cellular network (100) comprises a plurality of macro nodes (105 i ) defining respective macro cells (105 ci ) and a plurality of small nodes (110 i,j ) within said macro cells (105 ci ). The method (200) comprises, at each current time snapshot of a plurality of time snapshots and for each macro cell (105 ci ), the following steps: providing (205), according to a history traffic load (H i,k ) of the cellular network (100), an overload probability (Ο i,k ) in a first configuration of the cellular network (100) with only macro nodes (105 i ) activated; identifying (305-310), among said plurality of time snapshots, first candidate time snapshots (LM i ) for small nodes (110 i,j ) deactivation, in each first candidate time snapshot (LM i ) the overload probability (O i,k ) being lower than a threshold overload probability (O THj ); and, if (435) the current time snapshot is one among the first candidate time snapshots (LM), deactivating (440) each small node (110 i,j ) having (430) a current number (N PRBi,j ) of allocated radio resources lower than a threshold number (N PRB,THi,j ) and being (420) within a macro cell (105 ci ) currently having no macro (105 i ) or small (110 i,j ) nodes in overload condition.