Cell-less RAN Energy Efficiency via Dynamic Radio Unit Sleep Modes
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Solution Overview
Problem
Current cell-less radio access network architectures face challenges in energy efficiency due to high power consumption, especially in scenarios with varying traffic loads, and existing solutions are not well-adapted to the unique characteristics of cell-less designs where user equipment views radio resources as a common pool, leading to inefficient energy use and potential performance degradation.
Innovation Solution
The proposed energy-efficient sleep mode scheme, referred to as 3×E, introduces intelligent control over access points in a cell-less RAN architecture, implementing two-step sleep modes (non-conditional and conditional) to dynamically manage radio unit activation and interference, optimizing network energy efficiency across different user density scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all access points remain active to serve user equipment, then network coverage and service availability are maintained, but energy consumption increases significantly
Solution Approach 1:
The patent implements dynamic sleep mode management where access points transition between active and sleep states based on real-time traffic conditions. The RAN controller dynamically determines which access points should be in sleep mode versus active mode, allowing the system to adapt its energy consumption profile to actual network demand while maintaining service availability through selective activation of access points.
2Use of energy by moving object
If access points enter sleep mode to reduce energy consumption, then energy efficiency improves, but network coverage and service quality may deteriorate
Solution Approach 1:
The patent employs feedback mechanisms where the RAN controller continuously monitors traffic conditions, user equipment locations, and network performance metrics. Based on this feedback, the controller makes informed decisions about which access points should enter sleep mode and which should remain active, ensuring that service quality is maintained even as energy consumption is reduced. The system can adjust sleep mode assignments in response to changing network conditions.
3Use of energy by moving object
If sleep mode management is implemented without considering interference, then energy efficiency improves, but network performance degrades due to unmanaged interference
Solution Approach 1:
The patent introduces the RAN controller as an intermediary that coordinates sleep mode management across the network. The controller receives interference condition information from access points and uses this information to make centralized decisions about sleep mode assignments. This intermediary role allows the system to balance energy efficiency with performance by considering interference conditions that individual access points cannot assess alone.
4Use of energy by moving object
If traditional cell-based sleep mode solutions are applied to cell-less architectures, then energy efficiency may improve, but performance degradation occurs due to lack of adaptation to cell-less characteristics
Solution Approach 1:
The patent modifies the sleep mode management approach specifically for cell-less architectures by changing key parameters such as how access points are grouped, how traffic conditions are evaluated, and how sleep mode decisions are made. Instead of traditional cell-based boundaries, the system uses access point pools and collective traffic evaluation metrics that are appropriate for cell-less architectures, thereby maintaining performance while achieving energy efficiency.
Data Source
AI summary
A radio access network (RAN) operates by: determining an initial RU/UE association that allocates the plurality of UEs among the plurality of RUs via reference signal received power (RSRP) data received from the plurality of RUs; receiving RU conditions data corresponding to a set of RU conditions associated with the plurality of RUs; receiving RU constraint data associated with the plurality of RUs; assigning, via at least one iterative RU sleeping loop and based on the initial RU/UE association, the RU conditions data and the RU constraint data, an active mode to a first subset of the plurality of RUs and a sleep mode to a second subset of the plurality of RUs; and updating a dynamic RU/UE association based on the first subset of the plurality of RUs and the second subset of the plurality of RUs.