AirComp Pulse-Position Modulation for Federated Edge Learning
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Solution Overview
Problem
Federated edge learning (FEEL) faces communication bottlenecks due to the need for transmitting large model parameters over wireless networks, and existing over-the-air computation (AirComp) schemes require channel state information (CSI), which can lead to overhead and unreliable aggregation, especially in mobile wireless networks.
Innovation Solution
A novel AirComp method using pulse-position modulation (PPM) and discrete Fourier transform (DFT)-spread orthogonal frequency division multiplexing (OFDM) that eliminates the need for CSI at edge devices and servers, enabling coherent detection of majority votes without channel inversion, and reduces peak-to-mean envelope power ratio (PMEPR) by encoding information in pulse positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If channel state information (CSI) is used for coherent superposition in AirComp, then aggregation reliability is improved, but communication overhead and system complexity increase
Solution Approach 1:
The patent extracts and removes the CSI requirement from the AirComp system. By using pulse-position modulation where pulses are transmitted at different time positions to represent different values, the system achieves coherent superposition without needing channel state information, thus eliminating the overhead and complexity associated with CSI acquisition and management
Solution Approach 2:
The patent replaces the traditional mechanism of using CSI for coherent superposition with a pulse-position based mechanism. Instead of adjusting transmission based on channel conditions, the system uses temporal positioning of pulses to encode information, substituting the CSI-based control mechanism with a simpler time-domain encoding approach
2Measurement precision
If truncated-channel inversion (TCI) is applied to reverse multipath channel effects, then signal quality is improved, but transmission bandwidth and complexity increase
Solution Approach 1:
The patent removes the TCI processing step from the transmission chain. By using pulse-position modulation where information is encoded in the temporal position rather than amplitude or frequency, the system becomes immune to multipath effects without requiring channel inversion, thus eliminating the bandwidth overhead and computational complexity of TCI
Solution Approach 2:
The patent converts the potentially harmful multipath channel effects into a beneficial feature. The temporal spreading of pulses due to multipath propagation can be directly exploited to resolve pulse positions in the time domain, turning channel impairment into a mechanism that preserves rather than degrades information
3Reliability
If beamforming with large number of antennas is used to reduce channel impact, then aggregation reliability is improved, but device complexity and hardware requirements increase
Solution Approach 1:
The patent replaces the hardware-intensive beamforming mechanism with a signal-processing-based pulse-position modulation approach. Instead of using multiple antennas to create directional beams and combat channel effects, the system uses temporal encoding that is inherently robust to channel variations, substituting complex hardware requirements with simpler signal processing
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 enhances test accuracy in fading channels for both independent and identically distributed (IID) and non-IID data, reduces PMEPR, and is compatible with time-varying channels, eliminating the need for CSI and channel inversion, thus improving communication efficiency in mobile networks.
Implementation Method 1
One of the promising solutions to this issue is to perform the aggregation by utilizing the signal-superposition property of a wireless multiple access channel, i.e., over-the-air computation (AirComp)
Data Source
AI summary
An over-the-air computation (AirComp) scheme is proposed for federated edge learning (FEEL) without channel state information (CSI) at the edge devices (EDs) or edge server (ES). The proposed scheme adopts the majority vote (MV) principle and uses pulse-position modulation (PPM) symbols constructed with discrete Fourier transform (DFT)-spread orthogonal frequency division multiplexing (OFDM) (DFT-s-OFDM) as votes from EDs. By taking the delay spread and synchronization errors into account, we show how to eliminate the need for truncated-channel inversion (TCI) at the EDs and detect MV at the ED with a non-coherent detector. The proposed method naturally reduces the peak-to-mean envelope power ratio (PMEPR) of the signal as it inherits the properties of the single-carrier (SC) waveform. An alternative proposed scheme also adopts the majority vote (MV) principle but further defines multiple subcarriers and orthogonal frequency division multiplexing (OFDM) symbols for voting options, which reduces to frequency-shift keying (FSK) over OFDM subcarriers as a special case. Since the votes from EDs are separated on orthogonal resources, the proposed scheme eliminates the need for truncated-channel inversion (TCI) at the EDs and allows the ES to detect MV with a non-coherent detector. We also mitigate the peak-to-mean envelope power ratio (PMEPR) of the synthesized signals by using randomization symbols. Through simulations, we show that the proposed schemes provide high test accuracy in fading channels for both independent and identically distributed (IID) and non-IID data while resulting in lower PMEPR symbols as compared to one-bit broadband digital aggregation (OBDA) with quadrature amplitude modulation (QAM).