RIS Beam Allocation for Target Sensing Zone Coverage
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Solution Overview
Problem
RIS-based sensing systems face challenges in efficiently determining the minimum number of reflection beams required to cover a target sensing zone, leading to excessive radio resource consumption and latency due to brute-force beam-sweeping methods.
Innovation Solution
A network device provides information about a target sensing zone and requested beamforming gain to a RIS, allowing the RIS to determine and report the minimum number of reflection beams needed to cover the zone, optimizing radio resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If brute-force beam-sweeping methods are used to determine the minimum number of reflection beams, then the sensing zone can be covered, but radio resource consumption increases and latency increases
Solution Approach 1:
The network device pre-calculates and provides the RIS with information about the target sensing zone and requested beamforming gain before the actual sensing operation. This preliminary action allows the RIS to determine the minimum number of reflection beams in advance, avoiding the need for exhaustive beam-sweeping during runtime, thus reducing both radio resource consumption and latency while ensuring reliable sensing zone coverage.
2Reliability
If brute-force beam-sweeping methods are used to determine the minimum number of reflection beams, then the sensing zone can be covered, but latency increases
Solution Approach 1:
The network device pre-calculates and provides the RIS with information about the target sensing zone and requested beamforming gain before the actual sensing operation. This preliminary action allows the RIS to determine the minimum number of reflection beams in advance, avoiding the need for exhaustive beam-sweeping during runtime, thus reducing both radio resource consumption and latency while ensuring reliable sensing zone coverage.
3Reliability
If more RIS beams are used to cover the sensing zone, then coverage reliability improves, but radio resource consumption increases
Solution Approach 1:
The system changes the parameter of beamforming gain to optimize the number of reflection beams. By adjusting the beamforming gain parameter, the RIS can achieve the required sensing zone coverage with the minimum necessary number of beams, thereby improving radio resource utilization efficiency while maintaining coverage reliability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces radio resource consumption and latency by ensuring efficient coverage of the sensing zone with minimal beam usage, enhancing the cost-effectiveness of RIS-assisted sensing.
Implementation Method 1
reconfigurable intelligent surface (RIS)-based sensing system
Implementation Method 2
requested beamforming gain for RIS beams
Data Source
AI summary
Disclosed are systems, apparatuses, processes, and computer-readable media for wireless communications. For example, a reconfigurable intelligent surface (RIS) can receive a first message comprising information of a target sensing zone and can receive a second message comprising a requested beamforming gain for RIS beams. The RIS can determine a minimum quantity of the RIS beams based on the information of the target sensing zone and the requested beamforming gain for the RIS beams. The RIS can transmit a reporting message comprising at least one of the minimum quantity of the RIS beams for sensing the target sensing zone or a configuration failure alert.


