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Simplifying 5G Transceiver Design and Evaluation

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by Hamed M. Sanogo, End-Market Specialist, Analog Devices

With wireless communication standards such as LTE and 5G, the emphasis on higher data rates and spectral efficiency has driven wireless original equipment manufacturers to adopt new transmission formats such as orthogonal frequency division multiplexing (OFDM). However, these signals, with large fluctuations in their envelopes, are especially vulnerable to nonlinear power amplifier distortion due to their high peak-to-average power ratios (PAPR). With such a high PAPR, power amplifier nonlinearity can produce substantial signal distortion that increases bit error rates (BERs) and decreases the signal-to-noise ratio. This article reviews PAPRs, where they originate, how they can break down the RF components of the transmit line-up, and how to get rid of them or at least mitigate their effects on the signal chain.

The newer modulation formats, such as OFDM and various forms of quadrature amplitude modulation (QAM), have large fluctuations in their signal envelopes. This creates a high PAPR in the signal. Playing a high PAPR signal on a nonlinear power amplifier generates spectral regrowth, which refers to new frequencies caused by gain compression and not in the original input. The high PAPR causes in-band distortion, degrading the system’s BER performance. We will discuss a solution to help find the suitable system trade-off between efficiency and linearity using digital predistortion (DPD) and crest factor reduction (CFR) engines.

OFDM Modulation

In LTE and 5G systems, carrier aggregation, transmitting several carriers in parallel, increases bandwidth and data rate. These networks leverage OFDM modulation, a proficient and widely used multicarrier transmission technique that enables better spectral efficiency and reduces the impact of multipath reflections on the receiver’s ability to demodulate the signal. With OFDM, the final waveform is an orthogonal summation of subcarriers that carry information, where each subcarrier has its own center frequency and modulation scheme.

In the time domain, these subcarriers’ peaks can sometimes align to produce an aggregate large OFDM waveform peak. A unique feature of OFDM is that the subcarrier waveforms are orthogonally combined so that one subcarrier’s null (or zero amplitude) coincides with the peak of other subcarriers, as shown in Figure 1. This provides a relatively efficient use of the channel bandwidth, resulting in improved spectral efficiency compared to traditional single-carrier modulation.

Figure 1: Multicarrier OFDM subcarrier waveforms

OFDM has several other benefits, including its robustness against multipath fading. However, one of the significant problems with OFDM modulation is that the transmitting waveforms suffer from a high PAPR. Figure 2 shows the PAPR of various mobile technologies or modulation types. The typical PAPR has steadily increased as new standards or modulation technologies have emerged.

Figure 2: Typical PAPR for various modulation technologies

PAPR in OFDM Signals

As noted, carrier aggregation, enabled by OFDM modulation, increases the bandwidth and data rate in 5G systems. OFDM also results in a signal whose envelope is nonconstant, which can lead to high PAPR, contributing to system damage. If the RF power components in the RF signal line-up, primarily the power amplifier, are not suitably specified to manage the expected voltage peaks, these components can fail.

A large PAPR reduces the power amplifier efficiency by driving it deep into saturation, its nonlinear operating region. This leads to distortion that results in the signal’s spectral spreading. Power amplifier linearity has always been a critical design issue for nonconstant-envelope digital modulation schemes. Figure 3 shows a time-domain LTE 64-QAM signal captured at the output of the Analog Devices ADRV9040 transceiver SoC.

Figure 3: An illustration of orthogonal summation of subcarriers causing large peaks

Complementary Cumulative Distribution Function (CCDF)

Due to its form, an OFDM signal requires a statistical approach for proper measurement. The CCDF is used to evaluate the PAPR reduction performance in an RF signal chain. Figure 4a shows the transmitted waveform of an LTE downlink with 10 MHz of bandwidth and 64 QAM subcarrier modulation signal. The CCDF in Figure 4b shows that the signal power exceeds the average by at least 7.4 dB for 0.01% of the time. The theoretical maximum peak occurs at 0% probability, which is undefined in this plot. The trace intersects the X-axis (0.01%, or a probability of 104) at a PAPR of about 7.4 dB. This would indicate that one sample out of every 10,000 would be expected to exceed the average power by more than 7.4 dB.

Figure 4: CCDF of an LTE downlink with 10 MHz bandwidth and 64 QAM subcarrier modulation

Upon looking at the CCDF graph, observe that the Y-axis is cumulative probability and is usually plotted on a log scale. The X-axis is power plotted in decibels. The graph displays the probability or the percentage of time a signal power is at or above the average power. The CCDF plot depicts the time the signal spends above the average power level for each power level. As the CCDF curve moves to the right, the ratio of our peak power to the average power increases.

The CCDF plot verifies linear operation and is more often measured immediately after a power amplifier. It can give a more accurate depiction of signal compression compared to the commonly used method of tracking changes in gain at differing power levels. The statistical analysis of crest factor occurrence makes it a valuable tool for designers to assess the impact of amplifier compression on the system’s BER and error vector magnitude (EVM).

Why PAPR is So Important

RF power amplifiers are nonlinear in nature and exhibit a trade-off between linearity and efficiency. The common nonlinear problems are gain compression and phase distortion, including in-band and out-of-band distortions. Each of these factors degrades the system’s BER performance and creates out-of-band spectral regrowth, which leads to adjacent channel interference and violates out-of-band emissions standards mandated by regulatory bodies.

While testing an amplifier, the input amplitude gradually increases until the measured ratio decreases by 1 dB, representing 1 dB gain compression. The 1 dB compression point is a crucial figure of merit that provides RF designers with assumptions about their amplifier’s performance. Essentially, an amplifier’s 1 dB compression point is defined as the output power at which the device’s gain drops by 1 dB from its small-signal value. This parameter is commonly used as a reference point for the beginning of amplifier nonlinearity and is approximately equal to the maximum usable peak output power for the amplifier.

This is why many RF designers estimate their amplifier’s maximum operating output power to be a few decibels lower than its 1 dB compression point. Finding the 1 dB compression point is crucial so that a signal with a high PAPR is never allowed to saturate the amplifier. Another name for PAPR is the crest factor. Figure 5 shows the AM-AM curve with the 1 dB compression point shown.

Figure 5: The AM-AM curve with the 1 dB compression point

Now that the designer has evaluated the amplifier and identified its 1 dB compression point, they need to operate it in its linear region with an input power back-off (for example, operate it at a lower power within the linear portion of its operating curve) to avoid the spectral growth.

However, while backing off the input, far from the amplifier’s saturation point, can undoubtedly help avoid all the nonlinear problems discussed, it results in very low efficiencies and increases heat dissipation. Solving this low-efficiency problem by increasing the system’s power consumption is not a viable trade-off. As seen in Figure 2, as the standards bodies got innovative with new modulation schemes to use the existing spectrum better, this has resulted in signals with higher and higher levels of crest factor.

So, a back-off implementation strategy would not work overall. The following sections of this article will discuss two implementation strategies that, when combined, will operate the amplifier up to its saturation point while maintaining high linearity and significantly increasing its efficiency. The first uses an amplitude clipping technique for PAPR reduction and the second method is to linearize the nonlinear response of an amplifier over its intended power range.

Features of a Successful Digital Front-End Solution

In a wireless digital front-end (DFE), a broad range of subsystems are covered, including DPD, digital upconversion (DUC), digital downconversion (DDC), and CFR. Other essential areas include DC-offset calibration, pulse-shaping, image rejection, digital mixing, delay/gain/imbalance compensation, error correction, and other relevant blocks. The DPD circuit utilizes the data captured at the output of the amplifier to linearize its output. DPD improves system linearity by allowing the amplifiers to operate more efficiently, while CFR helps limit signal PAPR. The DPD engine is used after using CFR to reduce the signal’s dynamic range and allows the amplifier to be operated above the linear region. While each block covers key features of the DFE, this section of the article will only focus on the CFR and DPD blocks.

Crest Factor Reduction

Most of the input signal of an OFDM waveform will be within the linear range of the amplifier. However, as previously shown, the signal has peaks that may exceed its linear operating range, which invites long-term reliability concerns due to their contribution to system damage. Again, driving the amplifier at the highest possible input power is highly desirable without having it saturate. CFR is used to avoid saturation due to the peaks, where instead of attenuating the whole signal, only the portions of the signal above the amplifier’s linear range are attenuated. In short, CFR assists in keeping it linear.

When peaks are suppressed, this results in a constant output power, ensuring the signal remains within the amplifier’s linear range. Although CFR is not a linearization technique, it is an efficiency improvement scheme. With its most effective implementation, CFR eliminates the peaks of the transmit signal to reduce the PAPR while complying with the desired spectral emission mask, adjacent channel power ratio, and EVM specifications. Figure 6 shows detected signal peaks above a threshold level. The magnitude of the peaks is reduced to below some target value. This is usually followed by filtering to reshape the signal spectrum.

Figure 6: Detected signal peaks above the threshold level are reduced

A downside of CFR is that clipping leads to in-band signal distortion, resulting in BER performance degradation and out-of-band radiation, which imposes out-of-band interference signals to adjacent channels. In short, the consequence of clipping is poor signal ACLR and EVM. Filtering the clipped signal is often used to reduce out-of-band radiation at the cost of peak regrowth.

Digital Predistortion

With DPD, an amplifier can operate up to the saturation region without compromising its linear characteristics. DPD allows RF designers to operate their systems in the efficient yet nonlinear region of an amplifier while retaining the transmit signal linearity required of the OFDM modulation. In other words, with DPD, the linear region is extended. The DPD engine produces predistorter coefficients by modeling the amplifier’s inverse AM-AM and AM-PM characteristics. Essentially, DPD focuses on improving the signal quality that the amplifier produces when operating at peak efficiency. DPD aims to introduce inverse nonlinearities that compensate for the amplifier’s gain. This technique improves the linearity of a nonlinear amplifier by introducing precise anti-distortion into the input waveform that compensates for in-band nonlinear products. Figure 7 shows the concept of DPD for linearizing a response.

Figure 7: Generic concept of DPD for linearizing the PA response: (a) typical AM-AM curve showing the overall linear region is in green, (b) basic concept of DPD and how it improves power amplifier efficiency

It works on the principle of predistorting the transmitted data in the digital domain to cancel the distortion caused by compression in the analog domain. The approach to DPD can range from simple solutions such as a basic lookup table (LUT) to a more complex real-time signal processing approach. DPD implementations can be classified into memoryless models and models with memory.

Memoryless DPD

Memoryless DPD corrects the amplitude and phase of the IQ samples based on the current sample only. Amplifiers that are strictly memoryless can be characterized by their AM-AM and AM-PM conversions. This instantaneous nonlinearity is usually characterized by the amplifier’s AM-AM and AM-PM responses, where the output signal amplitude and phase deviation are given as functions of the amplitude of its current input.

Therefore, a memoryless amplifier can be characterized by its AM-AM and AM-PM responses. These measurements create LUT data that relates every input power/phase combination to the power/phase required to produce the desired linear output. The advantage of memoryless DPD is that it can be implemented in a relatively straightforward way as a lookup table. Figures 7a and 7b show the AM-AM response of an amplifier with and without DPD correction applied to a 2 x 100 MHz, 400 MHz bandwidth 4096 sample dataset.

DPD with Memory

Amplifiers will exhibit memory effects as the transmit signal bandwidth gets wider. These are nonuniform frequency responses in specific components like the biasing network, decoupling capacitors, and power supply circuitry, or they can be attributed to the thermal constants of the active devices. As a result, the current output depends on the current input and past input values. When this is the case, the amplifier has become a nonlinear system with memory. DPD with memory corrects the amplitude and phase of IQ data samples based on several previous samples and their interdependencies.

The amplifier’s response generally depends not only on the current signal amplitude but also on the amplitudes of the previous samples. Thus, the digital predistorter would also need to have memory structures—the mathematical backbone of DPD. The Volterra series is the most general polynomial type of nonlinearity with memory and is used to model nonlinear systems with memory. Therefore, using the Volterra series is the most general way to introduce memory. For an elaborate discussion of the details of the math behind modeling distortion with the Volterra series, which is beyond the scope of this article, please refer to Masterson.2

Making the Design of 5G RF Signal Chains Easier

The ADRV9040 RF transceiver provides a streamlined framework for designing, implementing, and testing the RF signal chain lineup of a 5G communication system. A discrete massive MIMO system requires four chip levels in its discrete form of deployment, including an RF transceiver, DFE, FPGAs, a baseband FPGA/ASIC, and a control FPGA. As this transceiver has an integrated DFE, it eliminates the need for several FPGAs used in competitive discrete solutions where the DPD, CFR, DUC, and DDC blocks are implemented in computer code.

Figure 8: AM-AM response of an amplifier with and without DPD on a 2 x 100 MHz, 400 MHz bandwidth signal

The FPGA implementation is typically costly and power-hungry. This highly integrated RF transceiver helps eliminate such power-hungry dedicated FPGAs. In this section, we highlight this RF transceiver and a proposed framework for checking a typical amplifier gain lineup and performing a sanity check for noise limits by implementing register writes inside the device.

The ADRV9040 SoC has eight transmitters, two observation receivers for monitoring transmitter channels, eight receivers, an integrated local oscillator (LO) and clock synthesizers, and digital signal processing functions to provide a complete transceiver with digital front-end capability. The device provides the high radio performance and low power consumption demanded by cellular infrastructure applications such as small cell radio units (RUs), macro 4G/5G RUs, and massive MIMO RUs.

Figure 9: ADRV9040 high-level functional block diagram

The transceiver subsystem includes automatic and manual attenuation control, DC offset correction, quadrature error correction, and digital filtering. The transceiver has a digital front-end that supports a few key blocks, including DPD (up to 400 MHz instantaneous bandwidth), a high performance three-stage CFR engine, integrated digital downconversion and digital upconversion capable of supporting up to eight component carriers. The device is suitable for such applications as small-cell single-band, multi-band, TDD massive-MIMO, and TDD/FDD in macro-RU equipment. Figure 9 shows a high-level functional block diagram.

ZIF-Based Architecture

The transmit and receive signal paths of the ADRV9040 use a zero-IF (ZIF) architecture that provides a wide bandwidth with a dynamic range suitable for noncontiguous multicarrier RU applications. The ZIF architecture has the benefits of low power plus RF frequency and bandwidth agility and provides size, weight, and power advantages over discrete solutions. The architecture enables OEMs to design 5G massive-MIMO radios that are 40% lighter and about 10% more energy efficient. Analysis of a complete small-signal radio board shows that the ZIF architecture enables significant cost savings (per 32T32R) on an RF bill of materials versus simple derivative RUs.

The zero-IF architecture also transmits energy at the LO frequency. Quadrature and LO leakage errors (for example, carriers are not centered on LO) are introduced because of differences in IQ mixing and data paths (for example, two mixers never have the same characteristics). This is an even bigger issue in multicarrier and asymmetric-carrier applications. To reduce these undesired emissions, the transceiver has a transmit LO leakage correction algorithm, which is used both for initial calibration and followed by a tracking calibration used during runtime operation.

CFR Block

The device’s CFR assists in keeping amplifiers linear. This low-power CFR engine helps designers reduce the PAPR of the input signal, enabling higher-efficiency transmit line-ups. As mentioned previously, spectral regrowth of corrected peaks is always a concern with CFR. It is crucial to note that the ADRV9040 plays a vital role in optimizing the algorithm to ensure that the impact of the CFR block aligns with the OEM’s system specifications. The ideal CFR block has very low latency and zero missed peaks.

Figure 10 shows the results of a PAPR reduction on a 5G New Radio (5G NR) signal. The pre-CFR (left) plot shows peak compression, which is indicated by the output signal’s CCDF (yellow trace) falling off at a steeper rate than the input, Gaussian reference, CCDF (green trace) as the PAPR increases. On the other hand, the post-CFR (right) plot shows a much-improved 5G NR signal where its CCDF is like that of the Gaussian signal.

Figure 10: 5G NR signal before and after applying CFR

CFR is implemented using a variation of a pulse cancellation technique by subtracting a precomputed pulse from the detected peaks to bring the signal within the amplifier’s linear range. The CFR block consists of three copies of CFR engines, each using a detection threshold to detect the peaks and a correction threshold to which the detected peaks are attenuated. These spectrally- shaped correction pulses are subtracted from the data stream to bring the signal within the linear range.

The correction pulse must be spectrally shaped to manage the noise leakage into adjacent bands. The ADRV9040 can simultaneously hold two correction pulses corresponding to two different carrier configurations on the device. These correction pulses can be preloaded, allowing the device to switch between two carrier configurations on the fly.

DPD Block

The device includes an integrated low-power DPD engine for RF signal chain linearization applications and provides excellent DPD performance. As discussed earlier, using the Volterra series is the most general way to introduce memory. This DPD engine is based on an abbreviated implementation of generalized memory polynomial (GMP) and dynamic deviation reduction (DDR), which are generalized subsets of the well-known Volterra series. An inverse power amplifier model (PA-1) is applied to the interpolated digital baseband samples through the DPD actuator hardware. A dedicated embedded Arm® Cortex® A55 processor is used to compute the GMP coefficients. The DPD actuator is a programmable polynomial calculator. Figure 11 shows a PA-1 model applied to the interpolated digital baseband samples.

Figure 11: An inverse power amplifier applied to the interpolated digital baseband samples

This DPD algorithm supports indirect and direct learning DPD mechanisms for extracting DPD model coefficients. Indirect learning involves using the observation receiver data as a reference for predicting the input samples corresponding to the reference. In contrast, direct learning involves using the pre-DPD actuator transmit signal as a reference to minimize the error between the observed and reference data.

Figure 12: Power spectral density showing improvement in ACLR post-DPD

The difference between the two is that the indirect learning algorithm is time efficient, but the direct learning algorithm is more accurate as it requires longer converging. In a system application where DPD is unnecessary, the ADRV9040 provides a mechanism to bypass predistortion through GPIO control. Figure 12 shows ACLR’s power spectral density improvement after applying DPD for a 20 MHz LTE signal. The impairments that provoked the ACLR skirt shown on the left plot have been removed using DPD on the right plot.

Power Management Considerations

Designing the ADRV9040 with the correct power solutions is paramount to avoiding issues such as the first symbol poor EVM (for example, Cyclic prefix) at the TDD receive-to-transmit transitions and achieving optimum RF performance. ADI Silent Switcher® technology offers several differentiations, including high switching frequency, ultralow RMS noise, and spot noise. A Silent Switcher 3 power design requires fewer components, a small PCB footprint, and a faster and well-controlled transient settling time, which results in ultralow EMI emissions. Figure 13 shows a high-level block diagram of a macro base station with a few suggested power ICs, LT8627SP and ADM7172, for powering the ADRV9040 voltage rails.

Figure 13: System-level block diagram of a macro RRH with the ADRV9040 power solutions

The ADRV9040 evaluation platform facilitates the establishment of a simple and straightforward framework for evaluating the user’s design. The designer needs only to connect their equipment to the evaluation platform to capture the different plots while the ADRV9040 does the heavy lifting to find the optimal performance configuration via data byte writes into its registers.

Conclusion

The advances in telecom technologies that enable higher data rate communications and improved spectral efficiency through carrier aggregation also contribute to an increase in PAPR. However, integrating CFR and DPD capabilities into the ADRV9040 transceiver simplifies the radio design process, resulting in reduced RF bill of materials (BOM) cost, board size, weight, and power consumption compared to conventional FPGA-based implementations.

With many wireless base stations and remote units deployed globally, improved power amplifier efficiency can significantly reduce energy and cooling costs for service providers. This accelerates time-to-market, helps lower operational expenses (energy and truck rolls), and ensures compliance when deployed in networks.

References

“ADRV9040: 8T8R SoC with DFE, 400 MHz iBW RF Transceiver,” Analog Devices, Inc., 2021.

Claire Masterson, “Digital Predistortion for RF Communications: From Equations to Implementation,” Analog Dialogue, Vol. 56, No. 2, April 2022.

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