CoMP Radio Clustering with Elastic Scheduler Reallocation
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Solution Overview
Problem
The increasing demand on telecommunications networks, particularly in CoMP deployments, is leading to increased energy usage, computing resource consumption, and infrastructure complexity, with scheduler compute capacity being a limiting factor in network performance and capacity.
Innovation Solution
Dynamic clustering of radio devices and corresponding scheduler instances based on network utilization, allowing for aggregation during low demand and disaggregation during high demand, with virtualized scheduler instances being powered up or down as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static overprovisioning of scheduler compute capacity is deployed to cope with peak network demand, then network reliability is improved, but energy consumption and computing resource usage increase
Solution Approach 1:
The patent implements dynamic clustering where radio devices are reassigned between clusters based on real-time utilization conditions. Scheduler instances are activated or deactivated dynamically to match actual network demand, transforming the static overprovisioned system into a dynamic one that adapts to varying load conditions, thereby maintaining reliability while reducing energy consumption during low-demand periods
Solution Approach 2:
The system changes the operational parameters of scheduler instances by transitioning them between active and deactivated states based on utilization thresholds. This parameter change allows the network to maintain peak capacity when needed while operating at reduced capacity during low-demand periods, resolving the contradiction between reliability and energy consumption
2Productivity
If static overprovisioning of scheduler compute capacity is deployed to cope with peak network demand, then network capacity is improved, but computing resource usage increases
Solution Approach 1:
The patent creates a dynamic resource allocation system where the number of active scheduler instances fluctuates based on network utilization. During peak demand, sufficient scheduler instances are active to maintain network capacity, while during low-demand periods, instances are deactivated to reduce computing resource usage, thus resolving the contradiction between maintaining capacity and reducing resource consumption
3Reliability
If static overprovisioning of network infrastructure is deployed to cope with peak network demand, then network reliability is improved, but device complexity increases
Solution Approach 1:
The patent makes scheduler instances universal by designing them to be movable between clusters and reusable across different cluster configurations. Instead of having dedicated static infrastructure for each potential cluster, the same scheduler instances can serve multiple clusters at different times, reducing overall infrastructure complexity while maintaining the ability to handle peak demand reliably
4Loss of energy
If dynamic re-clustering of radio devices is performed based on utilization conditions, then energy efficiency is improved, but device complexity increases
Solution Approach 1:
The patent implements a self-service mechanism where the system automatically monitors utilization conditions and triggers re-clustering operations based on predefined thresholds, without requiring complex external control. The scheduler instances and radio devices adapt to changing conditions through automated decision-making embedded in the system, improving energy efficiency while keeping the control complexity manageable through rule-based automation
Data Source
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AI summary
A computer-implemented method for performing dynamic clustering of radio devices in a Cooperative Multi-Point network, the network comprising a plurality of radio devices, one or more clusters of radio devices of the plurality of radio devices, one or more scheduler instances each associated with a cluster of the one or more clusters, and a controller, the method comprising: determining that a re-clustering condition associated with utilisation of one or more radio devices in a given cluster is satisfied, wherein radio devices in a given cluster are operable to be scheduled by a same scheduler instance; in response to determining that the re-clustering condition is satisfied: signalling a scheduler instance associated with the given cluster to remove the one or more radio devices from the given cluster; changing a processing resource allocation allocated for executing the one or more scheduler instances; and signalling a second scheduler instance to adopt the one or more radio devices.