Non-Coherent Gradient Modulation for CSI-Free Federated Learning
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Solution Overview
Problem
Analog over-the-air federated learning in wireless communication systems faces challenges due to the unavailability of channel state information (CSI) at user equipment (UE) and limited transmit power, which complicates channel pre-compensation.
Innovation Solution
User equipment (UE) transmits gradient updates using a non-coherent orthogonal modulation scheme, allowing network nodes to receive and accumulate gradient updates without CSI, and update the machine learning model based on received power from multiple UEs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If channel pre-compensation is performed in analog over-the-air federated learning, then gradient update transmission can be achieved, but it requires unavailable channel state information (CSI) at UE and additional transmit power
Solution Approach 1:
The patent extracts the channel pre-compensation step from the transmission process, eliminating the need for CSI at the UE. Instead of compensating for channel effects at the transmitter, the system uses non-coherent orthogonal modulation that is inherently robust to channel variations, thereby removing the complex pre-compensation operation while maintaining reliable gradient transmission
Solution Approach 2:
The patent changes the modulation parameter from coherent modulation (requiring CSI and precise phase control) to non-coherent orthogonal modulation. This parameter change allows the system to achieve reliable gradient transmission without requiring channel state information or additional transmit power for pre-compensation, directly resolving the technical contradiction
2Ease of operation
If non-coherent orthogonal modulation scheme is used, then CSI is not required at UE, but transmit power is limited
Solution Approach 1:
The non-coherent orthogonal modulation scheme is self-service in nature, as it does not require external assistance from channel state information or complex power control mechanisms. The system achieves reliable communication through the inherent properties of the modulation scheme itself, making it operationally simple while naturally accommodating limited transmit power constraints
3Measurement precision
If coherent modulation is used for gradient transmission, then transmission accuracy is improved, but it requires CSI which is unavailable at UE
Solution Approach 1:
Instead of using coherent modulation that requires CSI to achieve high transmission accuracy, the patent inverts the approach by using non-coherent orthogonal modulation. This inversion allows the system to achieve sufficient transmission accuracy without requiring CSI, thereby adapting to the condition of unavailable channel state information at the UE
Data Source
AI summary
A UE may identify, in at least one round of a federated learning procedure, at least one gradient update based on local data and a local copy of a machine learning model associated with the federated learning procedure. The UE may transmit, in the at least one round of the federated learning procedure, for a network node, an indication of the at least one gradient update based on a sign of the at least one gradient update and a non-coherent orthogonal modulation scheme. The network node may identify, in at least one round of the federated learning procedure, an accumulated sign of the at least one gradient update based on a first received power associated with the at least one first resource and a second received power associated with the at least one second resource.