Nonlinear Amplifier Effect on High Bit Rate Modulation Techniques Used in WiFi Generation with MATLAB Simulink

Nonlinear Amplifier Effect on High Bit Rate Modulation Techniques Used in WiFi Generation with MATLAB Simulink

Fatima Faydhe Al-Azzawi* Kamal Y. Kamal Majida Saud Ibrahim Saba Dhey Abed

Institute of Technology, Middle Technical University (MTU), Baghdad 10074, Iraq

School of Engineering, University of Guelph, Guelph N1G 2W1, Ontario, Canada

Corresponding Author Email: 
fatima_faydy1981@mtu.edu.iq
Page: 
27-33
|
DOI: 
https://doi.org/10.18280/mmep.110103
Received: 
20 July 2023
|
Revised: 
2 September 2023
|
Accepted: 
10 September 2023
|
Available online: 
30 January 2024
| Citation

© 2024 The authors. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).

OPEN ACCESS

Abstract: 

High bit rate modulation is an essential aspect of next-generation WiFi and plays a crucial role in achieving high data rates and increased network capacity. high-bit rate modulation uses advanced modulation schemes, such as 4096-QAM, to increase the maximum number of bits sent over a particular frequency band. Using nonlinear amplifiers in wireless communication systems will significantly improve the performance of high bit rate modulation techniques, such as 4096-QAM. Nonlinear amplifiers can cause a range of impairments, including intermodulation, harmonic distortion, and amplitude compression, which can affect the transmitted signal quality. It is essential to minimize the effects of these impairments through proper design and optimization of the amplifier to ensure the highest quality possible of the transmitted signal. In this paper, M-QAM with nonlinear amplifier system design and implanted with MATLAB Simulink where in terms of Transmitted and Received spectrum signal and constellation diagram and calculated error vector magnitude (EVM) and modulation error ratio (MER) measurements for 1024, 2048, and 4096-QAM that used in WiFi 6, WiFi 6E, WiFi 7, respectively.

Keywords: 

high bit rate modulation, M-QAM, nonlinear amplifier, WiFi

1. Introduction

High bit rate modulation is an essential aspect of next-generation WiFi and plays a crucial role in achieving high data rates and increased network capacity. High-bit rate modulation uses advanced modulation schemes, such as 4096-QAM, to increase the number of bits sent over a particular frequency band [1, 2].

One of the key benefits of high bit rate modulation providers is that they make better use of the available spectrum, enabling more data to be sent across a given frequency band. This is crucial since the demand for wireless data is rising and straining the available spectrum [3].

Improved signal quality, enhanced robustness against interference, and dependability in noisy environments are further benefits of high bit rate modulation. This is especially crucial for applications that need to send audio or video in high definition [4, 5].

In the context of next-generation WiFi, high bit rate modulation is especially important because it makes multiple-input multiple-output (MIMO) technology possible, which boosts link capacity and increases spatial multiplexing [6, 7].

Next-generation WiFi must include high bit rate modulation in order to maximize network capacity, improve signal quality, and make better use of the spectrum's resources. Technological advancements in high bit rate modulation are necessary to meet the growing demand for wireless data [8, 9].

In wireless communication systems, high bit rate modulation schemes like 4096-QAM can perform much better when nonlinear amplifiers are used. The quality of the transmitted signal can be impacted by a number of impairments caused by nonlinear amplifiers, including as amplitude compression, harmonic distortion, and intermodulation [10, 11].

When two or more signals are mixed in a nonlinear amplifier, intermodulation takes place, producing new signals that weren't there before. This may lead to interference, lower the signal-to-noise ratio, and lower the transmitted signal's quality [12].

When an amplifier modifies the transmitted signal's structure, higher-frequency components stand out more, a phenomenon known as harmonic distortion takes place. This may result in worse signal quality and more spectrum spreading [11, 13].

When the amplifier is unable to supply the transmitted signal enough gain, the amplitude is compressed. This phenomenon is known as amplitude compression. As a result, the signal quality and signal-to-noise ratio may decrease [14-20].

These impairments can negatively impact the performance of high bit rate modulation techniques used in WiFi technologies. To minimize these effects, nonlinear amplifiers should be designed and optimized to minimize these impairments, ensuring that the transmitted signal is of the highest quality possible [21-23].

Using nonlinear amplifiers in wireless communication systems can significantly improve the performance of high bit rate modulation techniques used in WiFi. It is important to minimize the effects of these impairments through proper design and optimization of the amplifier to ensure the highest quality possible transmitted signal [24-28].

In this paper, M-QAM with nonlinear amplifier system design and implanted with MATLAB Simulink where in terms of Transmitted and Received spectrum signal and constellation diagram and calculated error vector magnitude (EVM) and modulation error ratio (MER) measurements for 1024, 2048, and 4096-QAM that used in WiFi 6, WiFi 6E, WiFi 7, respectively.

2. Nonlinear Amplifier

A nonlinear amplifier is a type of amplifier that amplifies an input signal in a nonlinear manner. Unlike linear amplifiers, which amplify the input signal proportionally, nonlinear amplifiers introduce distortions into the output signal [8, 9].

These distortions can result in intermodulation, harmonic distortion, and amplitude compression, which can negatively affect the quality of the transmitted signal. Nonlinear amplifiers are commonly used in various applications, including communication, power, and audio systems [8, 9].

Reducing the impairments caused by the nonlinear behavior while maintaining the gain and output power required for the application is one of the major problems in constructing nonlinear amplifiers.

Nonlinear amplifiers are frequently used in communication systems to supply the high power and gain needed for wireless transmission. Feedforward linearization and digital pre-distortion are two examples of linearization techniques that are frequently employed to reduce the impairments caused by nonlinear behavior.

To sum up, nonlinear amplifiers introduce distortions into the output signal via amplification of the input signal in a nonlinear manner. The transmitted signal's quality may be negatively impacted by these distortions, thus it's critical to reduce them through appropriate amplifier design and optimization.

There are two viable methods for signals with a vast dynamic range: The simplest is to utilize a programmable gain amplifier (PGA) or a variable gain amplifier (VGA). Using a closed-loop circuit that also measures the signal characteristics, such as its maximum value or RMS (root mean square) under the control of a system processor, these have their gain automatically changed. The VGA/PGA technique is effective in some applications, although it is typically not appropriate for signals with more dynamic range than roughly 10dB. The logarithmic (log) amplifier offers a solution when the dynamic range exceeds what the VGA/PGA can manage. This amplifier uses a straightforward transfer function [10, 11]:

$V_{\text {out }}=K \ln \left(V_{\text {in }}\right)$   (1)

where, K is a scaling factor.

Three fundamental topologies can be employed, starting with the most straightforward diode log amp. The fundamental voltage-current relationship is logarithmic in a diode. The voltage of inverting op-amp will be proportional to the input current in a log form if a diode is placed in the feedback channel, Figure 1.

The following equations describe the relationship between the input voltage $V_{\text {in }}$ and the output voltage $V_{\text {out }}$:

$V_{\text {out }}=-V_T \ln \left(\frac{V_{\text {in }}}{I_S R}\right)$       (2)

where, $I_S$ and $V_T$ stand for the diode's thermal voltage and saturation current, respectively.

Due to non-ideal diode characteristics, the design dynamic range is typically only 40-60dB, but if the diode is replaced with diode-connected transistor, as shown in Figure 2, the dynamic range can be increased to 120dB or more.

Figure 1. The Diode/Op-amp log amp

Figure 2. Op-amp log amp with transistor

A log amplifier must always have a positive input voltage, or $V_{i n}$, to function correctly. This can be ensured by conditioning the input signal using a filter rectifier before applying it to the input of the log amplifier. As the op-amp is in the configuration of inverting and $V_{\text {in }}$ is positive, $V_{\text {out }}$ must be negative and is sufficient to forward bias the emitter-base junction of the BJT, keeping it in the active mode of operation [12, 13]. Now:

$V_{B E}=-V_{\text {out }}$

$I_C=I_S\left(e_{V_T}^{V_{B E}}-1\right) \approx I_S e_{V_T}^{V_{B E}}$

$V_{B E}=V_T \ln \left(\frac{I_C}{I_S}\right)$     (3)

It is the emitter-base diode’s saturation current. Due to the op-amp differential input’s virtual ground [14, 15]:

$I_C=\frac{V_{\text {in }}}{R}$

$V_{\text {out }}=-V_T \ln \left(\frac{V_{\text {in }}}{I_S R}\right)$        (4)

3. M-QAM Modulation with Nonlinear Amplifier Simulink

M-QAM transceiver design and implanted using MATLAB Simulink as shown in Figure 3, where signal source block illustrated in Figure 4, starting with Random Integer block that Generate random uniformly distributed integers in the range [0, M-1], where M is the set size. Followed by M-QAM block Modulate the input signal using the rectangular quadrature amplitude modulation method. This block will receive a column vector or scalar input signal.

Figure 3. M-QAM modulation with nonlinear amplifier MATLAB Simulink

Figure 4. Signal source block

Bits or integers may be used as the input signal. The input width must be an integer multiple of the number of bits per symbol if the “Input type” parameter is set to “Bit”. After that, Raised Cosine transmits the Up-sample and filters the input signal using a regular or square root raised cosine FIR filter. K block is a slide gain block whereby Move the slider modifies the scalar gain. To observe the nonlinear effect in this design, double-click the Slider Gain block and modify the gain value while the model is running [22, 23].

Input Port in the Narrowband Amplifier Connection block from Simulink to RF Block set physical blocks. The RF Block sets physical blocks of a modeling approach using baseband equivalents. This method simulates a 1/ (Sample time) bandwidth, with the center frequency set at the desired value. This frequency value corresponds to 0Hz in the baseband-equivalent model. The block provides the option to interpret the Simulink signal as either the incident power wave to the RF system or the source voltage of the RF system. The ‘Incident power wave’ option is the most common RF modeling interpretation, while the ‘Source voltage’ option is provided for backward compatibility. If the input Simulink signal is the incident power wave, the output of the RF system is the transmitted power wave. If the input is the source voltage, the output is the load voltage.

The block controls the modeling of RF Block set, physical blocks between this block and the Output Port block using:

FIR filters to model the frequency-dependent characteristics

Look up tables to model the nonlinear behaviors

Optional guard bands can be specified as a fraction of the modeling bandwidth.

The guards’ bands are implemented by applying a Tukey window to the frequency response. Modeling delay may be added to improve the response of the FIR filters. The parameters of this block are shown in Figure 5.

Figure 5. The parameters of the input port of the Narrowband amplifier

A general amplifier block is an RF amplifier described by a data source that consists of either an object or data from a file. When there is no noise data in the data source, use the Noise Data tab to specify amplifier noise information. The Noise Data tab accepts a separate N-element vector of the corresponding frequency values for a frequency-dependent noise. When there is no non-linearity data in the data source, use the Non-linearity Data tab to specify amplifier non-linearity information. The Non-linearity Data tab accepts a separate N-element vector of the corresponding frequency values for a frequency-dependent non-linearity. When the data source contains operating condition information, use the Operating Conditions tab to select operating condition settings for the simulation. Data interpolation is used during simulation.

Output Port in Narrowband Amplifier Connection block from RF Block set physical blocks to Simulink. Several RF system characteristics, which are separated by an input port block and an output port block, can be displayed once a simulation has been conducted, including composite data, an X-Y plane, a polar plane, a Z Smith chart, a Y Smith chart, and a ZY Smith chart. as shown in Figure 6.

Figure 6. Parameters of output port

The signal sink block contains a visa-versa of the signal source, as shown in Figure 7.

Figure 7. Signal sink block

4. Simulink Results

M-QAM transceiver design and implanted using MATLAB Simulink as shown in Figure 3, where M used 1024, 20248, and 4096 in WiFi 6, WiFi 6E, and WiFi 7, respectively. When comparing the spectrums of transmitted and received signals, the spectrum regrowth at the received signal can be seen. This regrowth is due to the amplifier’s non-linearity, as shown in Figures 8-10. From these figures, the non-linearity effect on the three M-QAM modulations is equally affection on the spectrum; the percentage of growth from the main loop to the side loop is -65 to -95 dBm/Hz power spectral density in the transmitted signal to -45 to -65 dBm/Hz power spectral density in the received signal.

Figure 8. 4096-QAM transmitted and received signals spectrums

Figure 9. 2048-QAM transmitted and received signals spectrums

Figure 10. 1024-QAM transmitted and received signals spectrums

Figure 11. 4096-QAM transmitted signal constellation

Figure 12. 4096-QAM received signal constellation

Figure 13. 2048-QAM transmitted signal constellation

Figure 14. 2048-QAM received signal constellation

When comparing the constellations of transmitted and received signals, Figures 11-16 can be seen as the signal distortion of the received signal. This distortion is due to the non-linearity of the amplifier.

Display calculated error vector magnitude (EVM) and modulation error ratio (MER) measurements in Table 1, where RMS EVM increased by 0.16% at the receiver with 1024-QAM while decreasing by 0.75%, 27% for 2048, 4096-QAM, respectively. Peak EVM increased by 1.52% at the receiver with 1024-QAM, decreasing by 0.21% and 0.53% at the receiver for 2048 and 4096 QAM, respectively. Avg EVM decreased for all M-QAM by 0.06dB, 0.26dB, and 0.09dB, respectively. Peak EVM decreased by 0.31dB and 0.11dB at the receiver for 1024-QAM and 4096-QAM while increased by 0.05dB at 2024-QAM, Avg MER increased for all types of M-QAM by 1.11dB, 1.15dB, 1.16dB respectively.

Figure 15. 1024-QAM transmitted signal constellation

Figure 16. 1024-QAM received signal constellation

Table 1. Error Vector Magnitude (EVM) and Modulation Error Ratio (MER) measurements

EVM/MER

1024-QAM

2048-QAM

4096-QAM

Transmitter

Receiver

Transmitter

Receiver

Transmitter

Receiver

RMS EVM (%)

24.67

24.83

25.32

24.57

24.81

24.54

Peak EVM (%)

41.96

43.48

44.08

43.87

42.82

43.35

Avg EVM (dB)

-12.16

-12.10

-11.93

-12.19

-12.11

-12.20

Peak EVM (dB)

-7.54

-7.23

-7.11

-7.16

-7.37

-7.26

Avg MER (dB)

11.15

12.26

11.04

12.19

11.21

12.37

5. Conclusion

In this paper, M-QAM with nonlinear amplifier system design and implanted with MATLAB Simulink where in terms of Transmitted and Received spectrum signal and constellation diagram and calculated error vector magnitude (EVM) and modulation error ratio (MER) measurements for 1024, 2048, and 4096-QAM that used in WiFi 6, WiFi 6E, WiFi 7 respectively, when comparing the spectrums of transmitted and received signals it can be seen the spectrum regrowth at the received signal. This regrowth is due to the non-linearity of the amplifier. The non-linearity effect on the three M-QAM modulations is equally affection on the spectrum. The growth percentage from the main loop to the side loop is -65 to -95 dBm/Hz power spectral density in the transmitted signal to -45 to -65 dBm/Hz power spectral density in the received signal. When comparing the constellations of transmitted and received signals, the signal distortion of the received signal can be seen.

This distortion is due to the non-linearity of the amplifier. Display is the calculated error vector magnitude (EVM) and modulation error ratio (MER) measurements, where RMS EVM increased by 0.16% at the receiver with 1024 QAM while decreasing by 0.75%, 27% at the receiver for 2048, 4096-QAM, respectively. Peak EVM increased by 1.52% at the receiver with 1024 QAM, decreasing by 0.21%, and 0.53% at the receiver for 2048 and 4096 QAM, respectively. Avg EVM decreased for all M-QAM by 0.06dB, 0.26dB, and 0.09dB, respectively. Peak EVM decreased by 0.31dB and 0.11dB at the receiver for 1024 QAM and 4096 QAM while increasing by 0.05dB at 2024 QAM. Avg MER increased for all types of M-QAM by 1.11dB, 1.15dB, and 1.16dB, respectively. From above, the use of nonlinear amplifiers in wireless communication systems can significantly impact the performance of high bit rate modulation techniques, such as 4096-QAM. Nonlinear amplifiers can cause a range of impairments, including intermodulation, harmonic distortion, and amplitude compression, which can affect the quality of the transmitted signal. It is essential to minimize the effects of these impairments through proper design and optimization of the amplifier to ensure that the transmitted signal is of the highest quality possible.

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