UAV-BS Clustering for MU-MISO Interference Reduction
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Solution Overview
Problem
Unmanned aerial vehicle (UAV)-based communication systems face challenges such as signal interference, attenuated signals, and pilot contamination due to their mobility, which affect the efficiency and quality of broadband data transfer in areas where traditional infrastructure is damaged or non-existent.
Innovation Solution
The implementation of multi-user (MU), massive multiple-input single-output (MISO) communication, combined with a clustering approach and the use of an inter-cluster coordinator, optimizes the placement and signal transmission of UAV-base stations (UAV-BSs) to minimize interference and maximize network throughput and coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If UAV-BSs are deployed to deliver broadband connectivity in areas without fixed infrastructure, then network coverage and accessibility are improved, but signal interference and pilot contamination increase
Solution Approach 1:
The patent divides the network into multiple clusters, each managed by a cluster head UAV-BS. This segmentation allows localized coordination of pilot sequences and resource allocation, reducing pilot contamination and interference between distant UAV-BSs while maintaining broad network coverage through the distributed cluster structure.
Solution Approach 2:
Cluster head UAV-BSs act as intermediaries that coordinate pilot sequence allocation and resource management within their respective clusters. This intermediary layer reduces direct interference between all UAV-BS pairs by organizing them into managed groups, thereby reducing pilot contamination while maintaining extensive network coverage.
2Productivity
If UAV-BSs use multiple antennas to maximize data transmission efficiency, then data transfer rate is improved, but device complexity and coordination requirements increase
Solution Approach 1:
The patent segments the multi-antenna system into multiple UAV-BS clusters, each with its own cluster head managing the antennas. This segmentation reduces the coordination complexity by dividing the large-scale multi-antenna system into smaller, manageable clusters, while still achieving high data transfer rates through coordinated beamforming and resource allocation within each cluster.
Solution Approach 2:
The patent introduces a spatial dimension by deploying UAV-BSs in three-dimensional space rather than ground-based two-dimensional deployment. This dimensional change allows angular domain user separation using multi-antenna arrays, achieving high data transfer rates through spatial multiplexing while reducing the complexity of ground-based coordinated management.
3Loss of time
If UAV-BSs are rapidly deployed for public safety communications, then response time is improved, but network planning time is reduced leading to higher interference
Solution Approach 1:
The patent establishes preliminary cluster structures and assigns cluster heads in advance, even during rapid deployment. This preliminary organization of UAV-BSs into clusters with designated coordinators enables quick deployment for public safety communications while maintaining structured pilot sequence allocation and resource management from the outset, reducing interference despite the rapid deployment timeline.
4Area of stationary object
If UAV-BSs are positioned to maximize coverage area, then network capacity is improved, but signal attenuation increases
Solution Approach 1:
The patent utilizes the third dimension (altitude) by deploying UAV-BSs in the air rather than on the ground. This dimensional change allows coverage area to be maximized at higher altitudes while maintaining signal strength through proximity to users and line-of-sight propagation, thereby reducing signal attenuation compared to ground-based deployments that must cover the same area from lower positions.
Data Source
AI summary
Methods, apparatuses, and systems for organizing data delivering unmanned aerial vehicles (UAVs) are provided. Inter-cluster coordinators can organize data delivering unmanned aerial vehicle base stations (UAV-BSs). Various beamforming techniques (e.g., LZFBF and ZFBF) can be incorporated, and the inter-cluster coordinator can operate on a base station that serves as a controlling network node.