Beam-Aware Cell Reselection for Lower Handover Overhead
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Solution Overview
Problem
Existing mobile networks struggle to efficiently manage handovers and throughput in beamforming scenarios due to varying beam configurations and mobility types of user devices, leading to suboptimal cell reselection and increased network overhead.
Innovation Solution
A system and method that utilizes a server to generate beam priority tables based on device location, mobility type, and beam identifiers, enabling informed selection of receiving base stations with appropriate beam configurations to optimize throughput and reduce handover frequency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a base station uses a greater number of beams, then each beam is narrower which improves throughput for devices in the center, but it increases the complexity of cell reselection and handover management
Solution Approach 1:
The system pre-generates beam priority tables that rank beams based on device characteristics (mobility type, location, throughput requirements) before handover decisions are needed. This preliminary organization of beam information allows the device to quickly identify optimal beams without complex real-time analysis during handover events.
Solution Approach 2:
The patent introduces beam priority tables as an intermediary structure between the base station's multiple beams and the user device. These tables act as a pre-processed index that simplifies the matching process between device requirements and available beams, reducing the computational complexity during cell reselection.
2Productivity
If the beamwidth is narrow to improve throughput, then the device is more likely to be in the center of the beam, but it reduces the coverage area and increases handover frequency
Solution Approach 1:
The system dynamically adjusts beam selection based on device mobility characteristics. For high-mobility devices, the beam priority tables prioritize wider beams or beams with more overlap to maintain connectivity during movement. For low-mobility devices, narrower beams are selected to maximize throughput. This dynamic adaptation resolves the contradiction between narrow beam throughput benefits and coverage duration requirements.
Solution Approach 2:
The patent changes the parameter of beam selection from a static configuration to a dynamic one based on device mobility type, location, and throughput requirements. By adjusting which beam is prioritized according to these parameters, the system can optimize for either throughput or coverage duration depending on the specific device context.
3Ease of operation
If the system selects base stations based on most energy in signals to simplify handover, then it ignores beam configurations and mobility types, but this leads to suboptimal cell reselection and reduced throughput
Solution Approach 1:
The system pre-calculates and stores beam priority tables that incorporate device mobility type, location, and throughput requirements. This preliminary action allows the handover process to remain simple (just selecting from pre-ranked beams) while achieving optimal throughput by considering all relevant parameters in advance.
Solution Approach 2:
The patent replaces the simple signal energy comparison mechanism with a more sophisticated beam priority ranking system. Instead of directly comparing signal energies during handover, the system uses pre-computed priority tables that substitute complex multi-parameter analysis with a simpler lookup and selection process.
4Productivity
If the system increases the number of beams per base station to improve throughput, then each beam becomes narrower which improves center-region performance, but it increases network overhead for beam management
Solution Approach 1:
The system extracts only the essential beam information needed for cell reselection decisions from the complete set of beam configurations. By generating beam priority tables that contain only the relevant ranking information rather than full beam configuration details, the system reduces network overhead while maintaining throughput optimization.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, receiving, from the serving base station, beam information including a beam bitmap for each base station in a group of base stations in proximity to the serving base station; determining a density of beams for the group of base stations based on the beam bitmap; modifying a neighbor list for the serving base station to include the density of beams for each base station in the group of base stations; and instructing, in response to receiving a handover request for a communication device, the serving base station to hand over the communication device based on the neighbor list. Other embodiments are disclosed.