Automated MIMO Stream Distribution Analysis for Distributed Antenna Systems
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Solution Overview
Problem
Distributed antenna systems face challenges in providing uniform MIMO coverage due to the need for multiple co-located remote units, which increases complexity and cost, while existing solutions struggle to optimize MIMO communications services without extensive infrastructure changes.
Innovation Solution
The implementation of automated analysis for MIMO communications stream distribution in distributed communication systems, allowing for interleaved MIMO configurations where adjacent remote units with non-overlapping coverage areas receive separate MIMO streams, enabling efficient MIMO cell bonding and reducing the number of required remote units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple co-located remote units are deployed to provide uniform MIMO coverage, then MIMO coverage uniformity is improved, but system complexity and cost increase
Solution Approach 1:
The system segments the MIMO coverage area into multiple zones, each served by a single remote unit. Instead of requiring multiple co-located remote units per coverage area, the patent divides the overall coverage region into distinct segments that can be independently served, reducing the number of remote units needed while maintaining coverage uniformity through automated stream distribution analysis.
Solution Approach 2:
The patent transitions from a spatial co-location approach (multiple units at the same location) to a dimensional distribution approach (single unit serving segmented areas). By analyzing stream distribution across multiple dimensions including coverage area, signal strength, and client device locations, the system determines optimal remote unit placement and stream assignment without requiring physical co-location.
2Reliability
If multiple co-located remote units are deployed to provide uniform MIMO coverage, then MIMO coverage uniformity is improved, but cost increases
Solution Approach 1:
The patent segments the coverage area and uses automated analysis to determine the minimum number of remote units required for each segment. This segmentation approach prevents over-provisioning of remote units and reduces total system cost while maintaining uniform MIMO coverage through optimized stream distribution across the segmented areas.
Solution Approach 2:
The system implements automated analysis that self-determines the optimal configuration of MIMO stream distribution and remote unit assignment. This self-service capability eliminates the need for manual planning and deployment of multiple co-located units, reducing both cost and complexity while achieving uniform coverage through algorithmic optimization.
3Quantity of substance
If existing infrastructure is used without changes to optimize MIMO services, then infrastructure cost is reduced, but MIMO optimization capability is limited
Solution Approach 1:
The patent implements a universal automated analysis framework that can optimize MIMO services across diverse existing infrastructure configurations. The system performs multi-functionality by analyzing various parameters (signal strength, coverage area, client locations) and adapting its optimization strategy to different infrastructure types without requiring physical modifications, thereby maintaining cost efficiency while enhancing MIMO capability.
Solution Approach 2:
The system optimizes MIMO services by changing operational parameters rather than physical infrastructure. It adjusts stream distribution parameters, remote unit assignment parameters, and configuration parameters through automated analysis, enabling MIMO optimization on existing infrastructure without costly physical changes while maintaining full adaptability.
Data Source
AI summary
Distributed communications systems (DCSs) supporting automated analysis of MIMO communications stream distribution to remote units in a distributed communication system (DCS) to support configuration of interleaved MIMO communications services are disclosed. In this regard, MIMO analysis circuits can be employed to determine the actual routing of MIMO communications signals and locations of the remote units to automatedly determine any MIMO cell bonding between the remote units to determine the configured interleaved MIMO configuration in effect in the DCS. The determined interleaved MIMO configuration of the DCS infrastructure is used to determine other possible interleaved MIMO configurations and their associated performance, along with the associated configurations and changes needed to realize such possible interleaved MIMO configurations. These possible interleaved MIMO communications service configurations can then be presented to a technician or customer to determine if any of the possible interleaved MIMO communication service configurations should be deployed in the DCS.