Computation Offloading for Integrated Sensing and Communication
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Solution Overview
Problem
In integrated sensing and communication technologies, the interference between sensing beams and communication beams, combined with terminal mobility and dynamic channel conditions, complicates computation offloading, making it difficult to process data efficiently and reduce energy consumption.
Innovation Solution
A computation offloading method is established using an associated model that trains on to-be-computed tasks, uplink communication channel gains, sensing pulse responses, and angle differences between communication and sensing beams to obtain offloading parameters, including decisions for task offloading and radio frequency transmission power, utilizing reinforcement learning modules like Multi-DQN and TD3 to optimize offloading strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If computation offloading is implemented in integrated sensing and communication, then terminal energy consumption is reduced, but beam interference between sensing and communication becomes more difficult to manage
Solution Approach 1:
The patent changes the parameter of beam separation angle to resolve the contradiction. By dynamically adjusting the angle difference between sensing beam and communication beam based on channel conditions and task requirements, the system reduces beam interference while maintaining effective computation offloading, thus managing interference complexity without sacrificing energy efficiency
Solution Approach 2:
The patent applies dynamics by making the computation offloading decision adaptive rather than static. The system dynamically adjusts offloading decisions based on real-time beam interference conditions, channel state, and terminal mobility, allowing the system to manage interference complexity adaptively while maintaining energy efficiency
2Use of energy by moving object
If computation offloading is implemented in integrated sensing and communication, then terminal energy consumption is reduced, but handling terminal mobility and dynamic channel conditions becomes more difficult
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors channel conditions, terminal mobility state, and beam interference levels, then uses this feedback to dynamically adjust computation offloading decisions. This closed-loop control enables the system to adapt to mobility and channel changes effectively while maintaining energy efficiency
Solution Approach 2:
The system transitions from static to dynamic computation offloading by continuously adapting decisions based on real-time channel conditions and terminal mobility. This dynamic approach ensures the system remains adaptable to changing environments while achieving energy savings through selective offloading
3Object-affected harmful factors
If beam separation is increased to reduce interference, then beam interference is reduced, but system complexity and difficulty in realizing computation offloading increase
Solution Approach 1:
The patent changes the beam separation parameter dynamically rather than using a fixed large separation. By adjusting the angle difference between sensing and communication beams based on actual interference levels and task requirements, the system reduces beam interference while avoiding the excessive complexity that would result from always using maximum beam separation
Data Source
AI summary
A computation offloading method includes: establishing an associated model of a terminal for computation offloading; training the associated model by taking a to-be-computed task of the terminal, an uplink communication channel gain, a sensing pulse response and an angle difference between a communication beam and a sensing beam as input, to obtain an offloading parameter of the terminal for the to-be-computed task, wherein the to-be-computed task comprises to-be-computed communication data and to-be-computed sensing data, and the offloading parameter comprises a decision for offloading a computing task and a decision for offloading radio frequency transmission power; and offloading the to-be-computed task to an edge side according to the offloading parameter.