MU-MIMO Resource Allocation via Historical Scheduling Data
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Solution Overview
Problem
Existing MU-MIMO technologies face challenges in maximizing massive MIMO gain due to limitations in channel measurement and resource allocation, particularly when dealing with a large number of users with varying traffic demands.
Innovation Solution
A method and base station implementation that utilize historical scheduling characteristic information to reserve and allocate resources for MU-MIMO users, enhancing resource utilization and fairness among users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If dynamic resource allocation is used for MU-MIMO users, then resource utilization efficiency is improved, but fairness among users with varying traffic demands deteriorates
Solution Approach 1:
The patent applies preliminary action by reserving resources in advance for MU-MIMO users based on historical scheduling characteristics. The base station determines the number of CCE candidates and PRBs to be reserved before actual scheduling occurs, ensuring that users with varying traffic demands receive fair treatment while maintaining high resource utilization efficiency.
2Ease of operation
If resources are reserved based on historical scheduling characteristics, then user fairness is improved, but resource allocation flexibility deteriorates
Solution Approach 1:
The patent applies dynamics by making the resource reservation amount adjustable based on current system conditions. The base station determines the number of CCE candidates and PRBs to reserve dynamically, balancing between fairness to users and flexibility in resource allocation according to varying traffic demands and system state.
3Productivity
If the number of CCE candidates and PRBs is increased for MU-MIMO, then cell throughput is improved, but signaling overhead deteriorates
Solution Approach 1:
The patent applies parameter changes by optimizing the number of CCE candidates and PRBs allocated to MU-MIMO users. The base station determines appropriate values for these parameters based on historical scheduling characteristics and current system conditions, achieving high cell throughput while controlling signaling overhead through parameter optimization rather than simply increasing all resources.
Data Source
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AI summary
A method and a base station are disclosed for multi-user multiple input multiple output (MU-MIMO). According to an embodiment, a base station obtains historical scheduling characteristic information. The base station reserves resources for MU-MIMO users based at least on the historical scheduling characteristic information. The base station allocates the reserved resources to the MU-MIMO users.