SAS Interference Mitigation via Census Tract Frequency Allocation
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Solution Overview
Problem
Current spectrum sharing systems face challenges in mitigating interference between mobile network operators, especially in dense urban areas with irregular census tract boundaries and non-cooperative infrastructure, where existing coordination mechanisms fail to effectively manage interference in shared frequency bands.
Innovation Solution
The implementation of an interference metric system that aggregates information from infrastructure components to optimize frequency allocation and activation coordination, using techniques such as time slot assignment, to mitigate interference between Citizens Broadband Service Devices (CBSDs), Base Stations (BS), and evolved NodeBs (eNBs), thereby addressing spectral efficiency, information sharing, and complexity concerns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If spectrum sharing is implemented in dense urban areas with irregular census tract boundaries, then spectrum utilization efficiency is improved, but interference between mobile network operators increases
Solution Approach 1:
The system segments the service area into census tracts with irregular boundaries that conform to geographic and demographic characteristics. Each census tract is further divided into frequency slots that can be independently allocated to different mobile network operators, allowing fine-grained control of spectrum allocation and interference management at the tract level
Solution Approach 2:
The system implements location-specific frequency slot allocation where different census tracts can have different frequency assignments based on local interference conditions, population density, and geographic characteristics. This allows optimal spectrum utilization in each local area while managing interference through localized frequency planning
2Object-affected harmful factors
If coordination mechanisms are implemented to manage interference, then interference mitigation is improved, but system complexity increases
Solution Approach 1:
The system enables mobile network operators to autonomously determine their frequency slot assignments based on publicly available census tract data and interference metrics. Operators independently optimize their frequency allocations without requiring complex real-time coordination mechanisms, reducing system complexity while maintaining effective interference mitigation
Solution Approach 2:
The system incorporates interference metric calculations that provide feedback on the interference levels between adjacent census tracts. This feedback mechanism allows operators to adjust their frequency slot assignments to minimize interference while maintaining spectrum utilization efficiency, achieving coordination through information feedback rather than complex control mechanisms
3Productivity
If frequency slot allocation is optimized for spectral efficiency, then spectral efficiency is improved, but information sharing requirements increase
Solution Approach 1:
The system uses universal census tract data that serves multiple purposes: defining service area boundaries, determining frequency slot allocations, and calculating interference metrics. This multi-functional use of publicly available geographic data eliminates the need for operators to share sensitive network information while achieving optimized frequency allocation and interference management
Data Source
AI summary
Various embodiments to enable Spectrum Access System (SAS) interference mitigation options are disclosed herein. In one embodiment, an apparatus is provided. The apparatus includes a memory to store a data sequence, and one or more processing devices coupled to the memory. The processing devices to generate an interference metric associated with a first group and a second group of infrastructure nodes of a Long-Term Evolution (LTE) network infrastructure based on measurement information. The measurement information comprises measurements related to the transmission of data sequences associated with the first group and the second group. Thereupon, configuration settings are determined for infrastructure nodes of the first group and second group based on the generated interference metric. Each configuration setting represents a frequency band and transmission power level for a corresponding infrastructure node to access data in the LTE network infrastructure.