Adaptive Waveform Selection for Integrated Communications and Sensing
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Solution Overview
Problem
Existing wireless communication networks struggle to find a waveform that is suitable for both communication and sensing applications, particularly due to hardware imperfections and differing performance requirements between communication and sensing tasks.
Innovation Solution
The method involves selecting a waveform for an Integrated Communications and Sensing (ICS) signal that is adapted based on the hardware capabilities of nodes involved in sensing applications and defined sensing key performance indicators, as well as the extent to which data is to be embedded for communication applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If CP-OFDM waveform is used for communication, then communication performance is acceptable with low complexity, but sensing performance deteriorates due to hardware imperfections
Solution Approach 1:
The system dynamically selects waveforms based on the sensing application requirements and hardware capabilities. Different waveforms (CP-OFDM, FMCW, chirp) are chosen adaptively for different sensing scenarios, allowing the system to optimize sensing performance while maintaining communication functionality.
Solution Approach 2:
The patent changes waveform parameters such as modulation type, frequency structure, and time-frequency characteristics to suit sensing applications. By adjusting these parameters, the system overcomes the limitations of fixed CP-OFDM waveform for sensing while preserving its communication advantages.
2Reliability
If FMCW chirp waveform is used for sensing, then sensing performance is improved, but communication capability deteriorates
Solution Approach 1:
The system segments the waveform selection process into different modes: communication-optimized modes and sensing-optimized modes. This allows the network to switch between waveform types based on whether the primary function is communication or sensing, resolving the contradiction by separating the two functional requirements.
Solution Approach 2:
The patent develops universal waveform designs that can serve both communication and sensing functions. By designing waveforms with dual functionality or creating a unified waveform family that covers both application domains, the system eliminates the need to choose between specialized waveforms for each function.
3Adaptability or versatility
If waveform is adapted based on hardware capabilities and sensing requirements, then sensing coverage and diversity improve, but system complexity increases
Solution Approach 1:
The system implements feedback mechanisms where nodes report their hardware capabilities and sensing requirements to the network. Based on this feedback, the network makes informed waveform selection decisions, balancing adaptability with manageable complexity through structured information exchange.
Solution Approach 2:
The patent performs preliminary waveform selection and configuration before actual sensing operations begin. By pre-configuring waveforms based on known hardware capabilities and application requirements, the system reduces real-time decision complexity while maintaining high adaptability.
4Productivity
If waveform is optimized for data embedding in communication, then communication performance improves, but sensing performance deteriorates
Solution Approach 1:
The system dynamically adjusts waveform characteristics based on the primary function required. When communication is the priority, waveforms are optimized for data embedding; when sensing is prioritized, waveforms are optimized for sensing performance. This dynamic adaptation resolves the contradiction by allowing context-dependent optimization.
Data Source
AI summary
Some embodiments of the present disclosure relate to the selection of a waveform for an integrated communications and sensing (ICS) signal, where the waveform is suitable for both communication applications and sensing applications. In view of the sensing applications, the waveform selection can be, at least in part, adapted based on capabilities of hardware of nodes involved in the sensing applications. In view of the communication applications, the waveform selection can be, at least in part, adapted based on the extent to which data is to be embedded.