AGC

Adaptively adjust gain for constant signal-level output

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Libraries:
Communications Toolbox / RF Impairments Correction

Description

The automatic gain controller (AGC) block adaptively adjusts its gain to achieve a constant signal level at the output.

This icon shows the AGC block with the optional Px port.

Examples

Adjust Received Signal Power by Using AGC

The doc_agc_received_signal_amplitude model uses an AGC block to adjust the received signal power to approximately 1 watt.

A constellation diagram displays the signal before and after the signal level is adjusted by the AGC block. Random integer-valued symbols are QPSK modulated and then the signal level is scaled down by using a Gain block. The AGC block adjusts the signal to achieve a desired power level of 1 W. A constellation diagram displays the signal input to and output from the AGC block.

Run the model and display the constellation diagram to show the signal level adjustments performed by the AGC block.

Adjust Receive Signal by Using Different AGC Step Sizes

This model uses AGC blocks with different step size settings to adjust the received signal power.

A time scope plots the effect of step size on AGC performance. Random integer-valued symbols are QPSK modulated and then the signal level is scaled down by using a Gain block. Three signal branches flow to a time scope to plot the received signal magnitude with no AGC, AGC with step size set to 0.0001, and AGC with step size set to 0.001.

Run the model and display the time scope to show the signal level adjustments performed by the AGC blocks.

Compare AGC Performance for Different Maximum Gains

This model uses AGC blocks with different maximum gain settings to adjust the received signal power.

A time scope plots the effect of maximum gain on AGC performance. The maximum gain setting affects the ability of the AGC to reach its target output power. Random integer-valued symbols are QPSK modulated and then the signal level is scaled down by using a Gain block. Three signal branches flow to a time scope to plot the received signal magnitude with no AGC, AGC with maximum gain set to 30 dB, and AGC with maximum gain set to 24 dB.

Run the model and display the time scope to show the signal level adjustments performed by the AGC blocks.

Ports

Input

In — Input signal

column vector

Input signal, specified as a column vector.

Data Types: single | double | int | uint
Complex Number Support: Yes

Output

y — Output signal

N_S-element column vector

Output signal, returned as an N_S-element column vector. N_S is the length of the input signal. The output signal is the same data type as the input signal.

Px — Power level estimate

N_S-element column vector

Power level estimate, returned as an N_S-element column vector. N_S is the length of the input signal. You can use powerlevel as an energy detector output.

Dependencies

To enable this port, select the Enable output of estimated input power parameter.

Parameters

To edit block parameters interactively, use the Property Inspector. From the Simulink^® Toolstrip, on the Simulation tab, in the Prepare gallery, select Property Inspector.

Step size — Step size for gain updates

0.01 | positive scalar

Step size for gain updates, specified as a positive scalar. Increasing the step size enables the AGC to respond more quickly to changes in the input signal level but increases variation in the output signal level after reaching steady-state operation. For more information, see AGC Performance Criteria.

Desired output power (W) — Target output power level

1 | positive scalar

Target output power level, specified as a positive scalar. The power level is measured in watts referenced to 1 ohm.

Averaging length — Length of averaging window

100 | positive integer

Length of the averaging window in samples, specified as a positive integer. For more information on how the averaging length influences the variance of the AGC output signal in steady-state operation and the execution speed, see Tips.

Maximum power gain (dB) — Maximum power gain

60 (default) | positive scalar

Maximum power gain in decibels, specified as a positive scalar. Large gain adjustments can cause clipping when a small input signal power suddenly increases. Use this property to avoid large gain adjustments by limiting the gain that the AGC applies to the input signal. For an example, see Compare AGC Performance for Different Maximum Gains.

Enable output of estimated input power — Option to output estimated input power

off (default) | on

Select this check box to provide an output port, Px, that returns an estimate of the input signal power.

Simulate using — Type of simulation to run

Interpreted execution (default) | Code generation

Type of simulation to run, specified as Interpreted execution or Code generation.

• Interpreted execution — Simulate the model by using the MATLAB^® interpreter. This option requires less startup time, but the speed of subsequent simulations is slower than with the Code generation option. In this mode, you can debug the source code of the block.

• Code generation — Simulate the model by using generated C code. The first time you run a simulation, Simulink generates C code for the block. The model reuses the C code for subsequent simulations unless the model changes. This option requires additional startup time, but the speed of the subsequent simulations is faster than with the Interpreted execution option.

For more information, see Interpreted Execution vs. Code Generation (Simulink).

Block Characteristics

Data Types	double | single
Multidimensional Signals	no
Variable-Size Signals	yes

More About

Logarithmic-Loop AGC

The AGC implementation uses a logarithmic feedback loop. As this figure of the logarithmic-loop AGC algorithm shows, the output signal is the product of the input signal and the exponential of the loop gain. The error signal is the difference between the reference level and the product of the logarithm of the detector output and the exponential of the loop gain. After multiplying by the step size, the AGC passes the error signal to an integrator.

The logarithmic-loop AGC performs well for a variety of signal types, including amplitude modulation. The AGC Detector is applied to the input signal, which improves convergence times, but increases signal power variation at the detector input. Large signal variation at the detector input is acceptable for floating-point systems.

Mathematically, the algorithm is summarized as

$$\begin{array}{l}y(n)=x(n)\cdot e^{(g(n-1))}\text{,}\\ z(n)=Detector(x(n))\cdot e^{(2g(n-1))}\text{,}\\ err(n)=A-\ln (z(n))\text{, and }\\ g(n)=g(n-1)+K\cdot err(n),\end{array}$$

where:

• x is the input signal.

• y is the output signal.

• g is the loop gain.

• Detector(•) is the detector function.

• z is the detector output.

• A is the reference value.

• err is the error signal.

• K is the step size.

AGC Detector

The AGC detector output, z, computes a square law detector given by

$$z(m)=\frac{1}{N}{\displaystyle {\sum }_{n=mN}^{(m+1)N-1}{\left|y(n)\right|}^2},$$

where N is the update period. The square law detector produces an output proportional to the square of the input signal y.

AGC Performance Criteria

Increasing the step size decreases the attack time and decay times, but it also increases gain pumping.

• Attack time — The duration taken for the AGC to respond to an increase in the input amplitude

• Decay time — The duration taken for the AGC to respond to a decrease in the input amplitude

• Gain pumping — The variation in the gain value during steady-state operation

Tips

• This block is designed for streaming applications.

• If the signal amplitude does not change within the frame, you can simulate an ideal AGC by calculating the average gain desired for a frame of samples. Then, apply the gain to each sample in the frame.

• If you use the AGC with higher order QAM signals, you might need to reduce the variation in the gain during steady-state operation. Inspect the constellation diagram at the output of the AGC during steady-state operation. You can increase the averaging length to avoid frequent gain adjustments. An increase in averaging length reduces execution speed.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.

Version History

Introduced in R2013a