ET-DPD for outphasing PAs is the synergistic application of envelope tracking and digital predistortion to a Chireix-outphasing amplifier. In a LINC transmitter, a variable-envelope signal is decomposed into two constant-envelope, phase-modulated vectors. The nonlinear power combiner, essential for efficiency, introduces severe AM-AM and AM-PM distortion. ET-DPD jointly addresses this by modulating the supply voltage of the branch PAs to enhance combiner efficiency while using a dual-input behavioral model to linearize the composite nonlinear response.
Glossary
ET-DPD for Outphasing PAs

What is ET-DPD for Outphasing PAs?
ET-DPD for outphasing PAs is a hybrid linearization and efficiency enhancement technique that combines dynamic supply modulation with digital predistortion to correct the nonlinearities of a LINC (Linear Amplification using Nonlinear Components) transmitter architecture.
The primary challenge is the complex, multi-dimensional distortion surface created by the interaction of the outphasing angle, the dynamic supply voltage, and the non-isolating combiner. A specialized 3D look-up table or an augmented Volterra model indexed by instantaneous signal magnitude and supply voltage is required. This approach compensates for supply-dependent gain compression and the combiner's load-pulling effects, enabling the transmitter to meet stringent 5G NR spectral mask and EVM requirements while operating near peak theoretical efficiency.
Key Characteristics of ET-DPD for Outphasing
Envelope tracking digital predistortion for outphasing power amplifiers addresses the unique nonlinearities arising from the interaction of dynamic supply modulation with the signal decomposition and power combining process inherent to LINC architectures.
Non-Isolating Combiner Distortion
Unlike ideal isolating combiners, practical outphasing combiners (e.g., Chireix combiners) are non-isolating, meaning the two branch PAs see a load impedance that varies with the outphasing angle. This load modulation creates significant AM-AM and AM-PM distortion that is compounded when envelope tracking dynamically varies the supply voltage. ET-DPD must linearize a system where the PA's nonlinearity is a function of both instantaneous supply voltage and the time-varying load impedance presented by the combiner.
Signal Component Separation
The outphasing transmitter decomposes a variable-envelope input signal into two constant-envelope, phase-modulated signals (S1 and S2). This signal component separator (SCS) creates a unique distortion mechanism: any bandwidth expansion or AM-PM distortion in the branch PAs is translated through the combiner into amplitude distortion at the output. ET-DPD must pre-distort the phase signals to account for how supply-dependent nonlinearities in each branch manifest after vector recombination.
Chireix Compensation Elements
Chireix outphasing combiners use shunt compensation reactances (+jX and -jX) to maximize efficiency at a specific back-off power level. These reactive elements create a frequency-dependent, non-linear impedance environment. When envelope tracking is applied, the varying drain capacitance of the PAs interacts with these compensation elements, shifting the optimal combiner tuning. ET-DPD models must capture this supply-dependent impedance detuning to maintain linearity across the ET voltage range.
Branch Imbalance Correction
Outphasing relies on perfect symmetry between the two amplifier branches. In practice, gain and phase mismatches between the two PAs, their supply modulators, and the RF paths create incomplete cancellation at the combiner, resulting in residual AM distortion. ET-DPD for outphasing must simultaneously correct for the individual nonlinearities of each branch while compensating for the differential errors that corrupt the vector summation at the output.
Dual-Input Dual-Branch Modeling
A complete ET-DPD model for outphasing requires a multi-input behavioral framework. The model must accept the two outphasing phase signals and the dynamic supply voltage as inputs to predict the combined output. This often necessitates a dual-input Volterra or neural network structure that captures the cross-coupling between the two RF paths and the supply modulation, accounting for the nonlinear interaction of all three variables at the combiner.
Efficiency-Linearity Trade-Off Optimization
The primary advantage of combining ET with outphasing is the potential for very high efficiency across a wide dynamic range. However, the deepest efficiency enhancement often occurs at operating points where the combiner's nonlinearity is most severe. ET-DPD must be co-optimized with the shaping function and the outphasing angle mapping to find the Pareto-optimal front where the DPD can successfully linearize the system while preserving the efficiency gains from both techniques.
Enabling Efficiency, Speed & Accuracy
Intelligent Analysis, Decision & Execution
We build AI systems for teams that need search across company data, workflow automation across tools, or AI features inside products and internal software.
Talk to Us
Search across company data
Give teams answers from docs, tickets, runbooks, and product data with sources and permissions.
Useful when people spend too long searching or get different answers from different systems.

Automate internal workflows
Use AI to route work, draft outputs, trigger actions, and keep approvals and logs in place.
Useful when repetitive work moves across multiple tools and teams.

Add AI to products and internal tools
Build assistants, guided actions, or decision support into the software your team or customers already use.
Useful when AI needs to be part of the product, not a separate tool.
Frequently Asked Questions
Addressing the most common technical questions about combining envelope tracking with outphasing power amplifier architectures for enhanced efficiency and linearity.
ET-DPD for outphasing PAs is a combined efficiency and linearization technique where envelope tracking (ET) dynamically modulates the supply voltage of the constituent power amplifiers in an outphasing architecture, while digital predistortion (DPD) corrects the resulting nonlinearities. In a standard outphasing (LINC) system, a constant-envelope input signal is decomposed into two phase-modulated signals, amplified by highly efficient saturated PAs, and recombined. By applying ET, the supply voltage to these branch PAs is reduced during low instantaneous envelope periods, preventing the combiner from dissipating excess power as heat and dramatically improving the system's back-off efficiency. However, this dynamic supply modulation introduces complex supply-dependent AM-AM and AM-PM distortions that interact with the outphasing angle. The DPD block, typically placed in the digital baseband before the signal component separator, pre-distorts the input to invert these compounded nonlinearities, ensuring the final recombined output meets linearity specifications.
Related Terms
Key concepts for understanding the integration of envelope tracking with outphasing power amplifier architectures.
Outphasing (LINC) Architecture
A transmitter technique where a variable-envelope signal is decomposed into two constant-envelope, phase-modulated signals. These signals drive two highly efficient, nonlinear PAs. The original amplitude modulation is restored by vector summing the PA outputs in a non-isolating power combiner. The combiner's reactive loading causes the PAs to see time-varying impedances, creating a unique nonlinear distortion profile that ET-DPD must correct.
Chireix Power Combiner
A non-isolating combiner topology used in outphasing systems that includes shunt reactive compensation elements. These elements are tuned to maximize efficiency at a specific outphasing angle, creating an efficiency peak at back-off power levels. However, this compensation also introduces a strongly nonlinear, signal-dependent reactive load to the PAs, which is a primary source of the distortion requiring ET-DPD linearization.
Load Modulation Distortion
The primary nonlinear mechanism in outphasing PAs. As the outphasing angle changes, the instantaneous impedance seen by each PA's drain varies dynamically. This load-pull effect modulates the PA's gain and phase response. When combined with envelope tracking, the supply voltage variation adds a second dimension to this load modulation, creating a complex, two-dimensional nonlinearity that requires a dual-input behavioral model.
Multi-Level LINC (ML-LINC)
An advanced outphasing architecture that combines envelope tracking with the LINC concept. Instead of using purely constant-envelope signals, the input is decomposed into signals with a discrete number of amplitude levels. The supply voltage is then switched between corresponding discrete levels. This reduces the required outphasing angle range, improving combiner efficiency and reducing reactive loading, but introduces supply-switching transients that DPD must handle.
Asymmetric Multilevel Outphasing (AMO)
A highly efficient variant where both the outphasing angle and the discrete supply voltages of the two PAs are controlled independently. This breaks the symmetry of traditional LINC, allowing for more degrees of freedom to maximize power-added efficiency (PAE) across the entire dynamic range. The resulting distortion surface is highly complex and non-separable, demanding a sophisticated ET-DPD joint model for linearization.
Signal Component Separator (SCS)
The digital signal processing block that decomposes the baseband input signal into the phase-modulated component signals for the two outphasing paths. The SCS computes the outphasing angle from the instantaneous signal amplitude. In ET-DPD for outphasing, the SCS must work in concert with the shaping function to coordinate the phase signals and the dynamic supply voltage, ensuring a coherent drive profile at the combiner.

About the author
Prasad Kumkar
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
Partnered with leading AI, data, and software stack.
How We Work
Custom AI workflows for your Business
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
01
Review the use case
We understand the task, the users, and where AI can actually help.
Read more02
Pick the right approach
We define what needs search, automation, or product integration.
Read more03
Build the first useful version
We implement the part that proves the value first.
Read more04
Improve from there
We add the checks and visibility needed to keep it useful.
Read moreThe first call is a practical review of your use case and the right next step.
Talk to Us