What is digital pre-distortion?
It applies the inverse of a power amplifier's non-linear transfer characteristic to the signal before amplification, so that the amplifier's own distortion cancels it and the output is closer to the intended waveform.
Digital pre-distortion with adaptive algorithms that model non-linear behaviour across multiple power amplifiers. The adaptive part matters: an amplifier's characteristic drifts with temperature, ageing and drive level, so a fixed correction is right once and increasingly wrong afterwards.
A power amplifier is non-linear near saturation. Feed it a signal and what emerges is a distorted version, with the distortion spilling energy into adjacent channels and degrading the constellation the receiver has to decode.
Digital pre-distortion characterises that non-linearity and applies its inverse before amplification, so the amplifier's own distortion cancels it. Done well, the amplifier can be driven substantially harder for the same spectral compliance.
The difficulty is that the characteristic is not fixed. It moves with junction temperature, with supply, with drive level and with ageing, and in a multi-amplifier system each device differs. Adaptive algorithms track those changes rather than assuming a factory characterisation holds for the deployment's life, and the model spans multiple amplifiers rather than treating each in isolation.
| Parameter | Detail |
|---|---|
| Function | Digital pre-distortion of the transmit signal |
| Approach | Adaptive algorithms tracking amplifier characteristic over temperature, drive and ageing |
| Coverage | Models non-linear behaviour across multiple power amplifiers |
| Result | Improved adjacent channel leakage ratio at higher drive levels |
| Availability | Separate core, or integrated within the 5G digital front end |
| Typical markets | RAN, satellite, broadcast |
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It applies the inverse of a power amplifier's non-linear transfer characteristic to the signal before amplification, so that the amplifier's own distortion cancels it and the output is closer to the intended waveform.
Because the amplifier's characteristic moves with junction temperature, supply, drive level and ageing. A fixed correction derived at factory characterisation is right once and progressively wrong afterwards.
In a multi-chain system such as massive MIMO, each amplifier has its own characteristic and its own drift. The model spans them rather than treating each in isolation.
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