The Importance of Input Linearity for Optimizing RF Receiver Designs

Linearity of a receiver plays an important role in the overall performance of the system. It affects system-level parameters like link budget and receiver sensitivity. Designing high-performance RF receivers involves navigating the classic tug-of-war between two critical specifications: Noise Figure (NF) and input linearity, typically expressed as input third-order intercept point (IIP3). Lower NF improves sensitivity but often requires higher Gain. Conversely, high IIP3 supports better tolerance to interference but usually comes at the cost of reducing Gain.

This article explores the interaction between these specifications and how receiver linearity performance is critical to the overall system performance. We'll also cover key concepts in intermodulation distortion, the difference in linearity optimization for transmitters versus receivers, and how tools like Error Vector Magnitude (EVM) can simplify the overall system-level trade-offs.

A Brief Review of Linearity

Linearity is the ability of the amplifier to produce an output signal that is a linear representation of the input signal. Having a good linear signal helps maintain signal integrity. Non-linearity can lead to distortion, intermodulation products and spectral regrowth – all of which can lead to a degraded signal quality in the system. Linearity performance is measured at medium signal levels, i.e., the system is not driven into compression, but intermodulation distortion is generated.

Second- and Third-Order Intercept & IMD Products

The second and third-order intercept-point (IP2 and IP3) products are widely used to benchmark the linear performance of an RF system. IIP3 refers to the hypothetical input power level where the power of third-order intermodulation products (IMD) equals the power of the fundamental output signal. To fully understand IP3, it's important to know the difference between Input IP3 (IIP3) and Output IP3 (OIP3).

IIP3 is the signal power going into the device at the intercept point, while OIP3 is the signal power coming out of the device at that same point. Both values help us understand how an RF device performs when dealing with different input signal levels. Understanding the relationship between Input IP3 (IIP3) and Output IP3 (OIP3) can provide invaluable insights into the behavior of RF devices and systems. OIP3 can be calculated using the formula:

OIP3(dBm) = Gain(dB) + IIP3(dBm)

Before the IP3 point is reached, the device usually hits saturation. This means it can’t increase its output power in a straight linear line anymore, no matter how much you raise the input. The result is signal compression and distortion. See Figure 1.

Figure 1: IP2, IP3 and P1dB

Two-tone tests shown in Figure 2 can be performed to measure IP2 and IP3. Two closely spaced sinusoidal signals (Fundamental Tones) with equal power level input power (Pin) at frequencies f1 and f2 are applied, and the level of the second order IMD (IM2) at frequencies |f2 – f1|, 2f1 and 2f2 is then observed as Pin increases. For third-order intermodulation products, the two-tone frequencies are chosen such that the IM products fall inside the received signal band. For IP3, the IM3 components at |2f1−f2| and |2f2−f1| are observed as Pin increases.

Figure 2: Fundamental, IMD products.

The IP3 is a result of third-order IMD products, specifically |2f1 – f2| and |2f2 – f1| as shown above. The third-order intercept is a figure of merit that characterizes an RF receiver’s tolerance when subjected to multiple RF signals within the desired passband. These IMD products apply to both transmit and receive sides of the RF system. But optimizing each end of the system requires slightly different approaches.

As shown in Figure 3 below, the graph illustrates two distinct slopes that represent different regions of amplifier behavior. In the initial linear region, the output power increases proportionally with input power at a 1:1 slope, reflecting the ideal, distortion-free operation of the device where the fundamental signal dominates. This region indicates that the amplifier operates within its linear dynamic range, preserving signal integrity.

However, as the input power continues to rise, the device transitions into a non-linear region where intermodulation distortion products, particularly third-order (IMD3), begin to emerge. In this region, these distortion components increase at a much faster rate than the fundamental, with a characteristic slope of 3:1. This means that for every 1 dB increase in input power, the IMD3 components grow by 3 dB, quickly surpassing the desired signal and degrading overall performance. Understanding these two regions and their respective slopes is essential for accurately characterizing the linearity of RF components and for predicting how they will perform under real-world signal conditions.

Figure 3: IP3 with input power versus output power slopes.

Optimizing the Receiver via IIP3

Designing RF receivers with a focus on output linearity can be misleading, as it often focuses on Gain that ultimately compromises receiver performance.

While higher output Gain helps maximize output linearity (like one would do for a transmitter), it simultaneously degrades input linearity by making the system more susceptible to compression from smaller input signals, as shown in Figure 4. The data shows that optimal receiver performance requires a careful balance between input-referenced linearity and NF. Lower NF is achieved with higher front-end Gain, but this comes at the cost of reduced input linearity. Conversely, maximizing input linearity calls for lower overall Gain, which can raise the NF. Therefore, effective receiver design demands trade-offs between these parameters, so neither parameter is sacrificed excessively. Designers must avoid the transmitter-oriented mindset that more Gain is inherently better and instead select a Gain profile that optimally balances NF and IIP3 for the intended application.

Figure 4: Cascaded RF receiver parameter data comparison.

But why is the receiver linearity IIP3 so important? It is because it directly impacts the receiver’s ability to handle multiple signals and prevent IMD. A high IIP3 in a receiver design indicates the receiver is more linear and therefore can better separate designed signals from unwanted IMD products.

It is important for system designers to understand the influencing factors such as Gain, NF, OIP3 and IIP3. Balancing the trade-offs between these parameters is critical to ensuring the overall system is optimized.

EVM and the Bathtub Curve Explained

 The manifestation of Error Vector Magnitude (EVM) (a measure of the difference between an ideal signal and the actual received signal in digital communication systems) can come from many different sources. The EVM figure of merit is typically a combination of noise and distortion. As shown in Figure 5, at lower power levels, noise tends to dominate, and the EVM increases as we lower the power. At high power levels, distortion tends to dominate, and we observe increased EVM as we increase power levels. In the middle, we often see the minimum EVM, and so the overall shape resembles a bathtub curve. As such, the EVM bathtub curve becomes an essential visualization tool for system-level optimization, offering a comprehensive view of how different impairments jointly impact overall performance.

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Figure 5: Bathtub EVM curve (EVM vs. Operating Power).

While most frequency devices exhibit low phase noise below 2 GHz, this advantage diminishes at higher frequencies and wider signal bandwidths, where integrated phase noise can increase substantially and degrade system performance. This challenge is particularly acute in millimeter wave (mmWave) systems operating above 20 GHz, where elevated phase noise directly contributes to higher EVM.

To address this, system-level design often begins with cascade analysis, using low-level performance metrics of individual components to estimate overall system behavior. In these situations, EVM serves as a highly practical system-level performance metric, enabling engineers to consolidate the effects of multiple impairments, such as noise, non-linearities and phase noise, into a single optimization target. Rather than tuning several individual parameters, designers can focus on minimizing the root-mean-square (rms) EVM value for an efficient and effective design process. This optimization is visually aided by the EVM bathtub curve.

The System Advantages of Optimized Receiver Linearity

High linearity in an RF receiver is critical for maintaining robust system performance in the presence of strong or closely spaced signals. One of the primary benefits of high receiver linearity is an expanded spurious-free dynamic range (SFDR), which quantifies the usable signal range before intermodulation products rise above the noise floor. SFDR is directly proportional to the IIP3 and inversely proportional to the noise floor (No), with the relationship defined by this formula.

SFDR = (2/3) × (IIP3 − No)

A higher IIP3 indicates better tolerance to interference, as third-order intermodulation (3IM) spurs decrease by approximately 2 dB for every 1 dB increase in IIP3. However, achieving high linearity often comes at the expense of a higher NF, presenting a well-known design trade-off. Systems that support adjustable receiver input linearity—based on real-time assessment of incoming signal strength—offer the most flexibility. In RF environments with low interference, higher receiver Gain can be used to minimize NF, even though this reduces input linearity. Conversely, in high-interference scenarios, reducing Gain improves input linearity, allowing the receiver to better tolerate strong unwanted signals. For receivers, it's important to focus on input linearity rather than output metrics like OIP3, as high OIP3 can misleadingly suggest good receiver performance while input signal handling capability may be poor.

Conclusion

In summary, optimizing RF receiver performance demands a careful balancing act between input linearity and NF, as both parameters critically influence system sensitivity, interference tolerance and overall signal fidelity. While conventional design approaches may prioritize output metrics like OIP3 or default to maximizing Gain, this can lead to suboptimal trade-offs, particularly in dynamic RF environments. A focus on IIP3, supported by tools like EVM analysis and cascade modeling, enables more accurate predictions of receiver system behavior and better-informed design choices. Whether operating in low-interference conditions that favor higher Gain and lower NF or in high-interference scenarios that require improved linearity through Gain reduction, adaptive receiver architectures that dynamically adjust to their signal environment offer the greatest design flexibility. By embracing a system-level perspective that accounts for all impairments, including intermodulation, compression, noise and phase distortion, engineers can achieve receiver designs that are both robust and efficient across a wide range of use cases.

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About the Authors

Our authors bring a wealth of technical expertise in developing and optimizing high-performance RF receiver solutions and systems. With a deep understanding of customer needs and industry trends, they collaborate closely with our design teams to drive innovation and deliver cutting-edge solutions that support industry-leading products.

Thank you to our main contributors of this article: David Corman (Chief Systems Architect) and David Schnaufer (Corporate, Technical Marketing Manager) for their contributions to this blog post, ensuring our readers stay informed with expert knowledge and industry trends.