基于MATLAB的QPSK通信系统
http://www.mathworks.com/examples/matlab-communications/mw/comm_product-commQPSKTransmitterReceiver-qpsk-transmitter-and-receiver
QPSK Transmitter and Receiver
This example shows a digital communications system using QPSK modulation. The example uses Communications System objects to simulate the QPSK transceiver. In particular, this example illustrates methods to address real-world wireless communications issues like carrier frequency and phase offset, timing recovery and frame synchronization.
Contents
- Implementations
- Introduction
- Initialization
- Code Architecture for the System Under Test
- Description of the Individual Components
- System Under Test
- Execution and Results
- Alternate Execution Options
- Summary
- Appendix
- References
Implementations
This example describes the MATLAB implementation of the QPSK transceiver.
MATLAB script using System objects: commQPSKTransmitterReceiver.m.
For a Simulink® implementation using blocks, check: commqpsktxrx.slx.
Introduction
The transmitted QPSK data undergoes impairments that simulate the effects of wireless transmission such as addition of Additive White Gaussian Noise (AWGN), introduction of carrier frequency and phase offset, and timing delay. To cope with these impairments, this example provides a reference design of a practical digital receiver. The receiver includes FFT-based coarse frequency compensation, PLL-based fine frequency compensation, PLL-based symbol timing recovery, frame synchronization, and phase ambiguity resolution.
This example serves three main purposes:
- To model a general wireless communication system that is able to successfully recover a message, which was corrupted by various simulated channel impairments.
- To illustrate the use of key Communications System Toolbox™ System objects for QPSK system design, including coarse and fine carrier frequency compensation, closed-loop timing recovery with bit stuffing and stripping, frame synchronization, carrier phase ambiguity resolution, and message decoding.
- To illustrate the creation of higher level System objects that contain other System objects in order to model larger components of the system under test
Initialization
The commqpsktxrx_init.m script initializes simulation parameters and generates the structure prmQPSKTxRx.
Code Architecture for the System Under Test
This example models a digital communication system using QPSK modulation. The function runQPSKSystemUnderTest models this communication environment. The QPSK transceiver model in this script is divided into the following four main components.
1) QPSKTransmitter: generates the bit stream and then encodes, modulates and filters it.
2) QPSKChannel: models the channel with carrier offset, timing offset, and AWGN.
3) QPSKReceiver: models the receiver, including components for phase recovery, timing recovery, decoding, demodulation, etc.
4) QPSKScopes: optionally visualizes the signal using time scopes, frequency scopes, and constellation diagrams.
Each component is modeled using a System object. To see the construction of the four main System object components, refer torunQPSKSystemUnderTest.m.
Description of the Individual Components
Transmitter
This component generates a message using ASCII characters, converts the characters to bits, and prepends a Barker code for receiver frame synchronization. This data is then modulated using QPSK and filtered with a square root raised cosine filter.
Channel
This component simulates the effects of over-the-air transmission. It degrades the transmitted signal with both phase and frequency offset, a time-varying delay to mimic clock skew between transmitter and receiver, and AWGN.
Receiver
This component regenerates the original transmitted message. It is divided into six subcomponents, modeled using System objects.
1) Automatic Gain Control: Sets its output power to 1/sqrt(Upsampling Factor) (0.5) so that the input amplitude of the Coarse Frequency Compensationsubcomponent is stable and roughly one. This ensures that the equivalent gains of the phase and timing error detectors keep constant over time. The AGC is placed before the Raised Cosine Receive Filter so that the signal amplitude can be measured with an oversampling factor of four. This process improves the accuracy of the estimate.
2) Coarse frequency compensation: Uses nonlinearity and a Fast Fourier Transform (FFT) to roughly estimate the frequency offset and then compensate for it. The frequency offset is estimated by using a comm.PSKCoarseFrequencyEstimator System object and the compensation is performed by using acomm.PhaseFrequencyOffset System object.
3) Fine frequency compensation: Performs closed-loop scalar processing and compensates for the frequency offset accurately, using acomm.CarrierSynchronizer System object. The object implements a phase-locked loop (PLL) to track the residual frequency offset and the phase offset in the input signal.
4) Timing recovery: Performs timing recovery with closed-loop scalar processing to overcome the effects of delay introduced by the channel, using acomm.SymbolSynchronizer System object. The object implements a PLL to correct the symbol timing error in the received signal. The Zero-Crossing timing error detector is chosen for the object in this example. The input to the object is a fixed-length frame of samples. The output of the object is a frame of symbols whose length can vary due stuffing and stripping, depending on actual channel delays.
5) Frame Synchronization: Performs frame synchronization with the known Barker code and, meanwhile, convert the variable-length symbol inputs into fixed-length outputs, using a FrameFormation System object for examples. The step method of the object has a secondary output that is a boolean scalar indicating if the first frame output is valid.
6) Data decoder: Performs phase ambiguity resolution and demodulation. Also, the data decoder compares the regenerated message with the transmitted one and calculates the BER.
Scopes
This component provides optional visualization by plotting the following diagrams:
- a time scope showing the normalized time delay,
- a spectrum scope depicting the received signal after square root raised cosine filtering,
- constellation diagrams showing the received signal after receiver filtering, and then after carrier phase.
For more information about the system components, refer to the QPSK Transmitter and Receiver example using Simulink.
System Under Test
The main loop in the system under test script processes the data frame-by-frame. Set the MATLAB variable compileIt to true in order to generate code; this can be accomplished by using the codegen command provided by the MATLAB Coder™ product. The codegen command translates MATLAB® functions to a C++ static or dynamic library, executable, or to a MEX file, producing a code for accelerated execution. The generated C code runs several times faster than the original MATLAB code. For this example, set useCodegen to true to use the code generated by codegen instead of the MATLAB code.
The inner loop of runQPSKSystemUnderTest uses the four System objects previously mentioned. There is a for-loop around the system under test to process one frame at a time.
for count = 1:prmQPSKTxRx.FrameCount
transmittedSignal = step(hTx);
corruptSignal = step(hChan, transmittedSignal, count);
[RCRxSignal,coarseCompBuffer, timingRecBuffer,BER] = step(hRx,corruptSignal);
if useScopes
stepQPSKScopes(hScopes,RCRxSignal,coarseCompBuffer, timingRecBuffer);
end
end
Execution and Results
To run the System Under Test script and obtain BER values for the simulated QPSK communication, the following code is executed. When you run the simulations, it displays the bit error rate data, and some graphical results. The figures displayed are, respectively:
1) Constellation diagram of the Raised Cosine Receive Filter output.
2) Power spectrum of the Raised Cosine Receive Filter output.
3) Constellation diagram of the Fine Frequency Compensation output.
4) Estimated (fractional) timing error from the Timing Recovery.
Alternate Execution Options
As already mentioned in the section Run System Under Test, by using the global variables at the beginning of the example, it is possible to interact with the code to explore different aspects of System objects and coding options.
By default, the variables useScopes and printReceivedData are set to true and false, respectively. The useScopes variable enables MATLAB scopes to be opened during the example execution. Using the scopes, you can see how the simulated subcomponent behave and also obtain a better understanding of how the system functions in simulation time. When you set this variable to false, the scopes will not open during the example execution. When you set printReceivedData to true, you can also see the decoded received packets printed in the command window. The other two variables, compileIt and useCodegen, are related to speed performance and can be used to analyze design tradeoffs.
When you set compileIt to true, this example script will use MATLAB Coder™ capabilities to compile the script runQPSKSystemUnderText for accelerated execution. This command will create a MEX file (runQPSKSystemUnderTest_mex) and save it in the current folder. Once you set useCodegen to true to run the mex file, the example is able to run the system implemented in MATLAB much faster. This feature is essential for implementation of real-time systems and is an important simulation tool. To maximize simulation speed, set useScopes to false and useCodegen to true to run the mex file.
For other exploration options, refer to the QPSK Transmitter and Receiver example using Simulink.
Summary
This example utilizes several System objects to simulate digital communication over an AWGN channel. It shows how to model several parts of the QPSK system such as modulation, frequency and phase recovery, timing recovery, and frame synchronization. It measures the system performance by calculating BER. It also shows that the generated C code runs several times faster than the original MATLAB code.
Appendix
This example uses the following script and helper functions:
- runQPSKSystemUnderTest.m
- QPSKTransmitter.m
- QPSKChannel.m
- QPSKReceiver.m
- QPSKScopes.m
- QPSKBitsGenerator.m
- QPSKDataDecoder.m
- FrameFormation.m
References
1. Rice, Michael. Digital Communications - A Discrete-Time Approach. 1st ed. New York, NY: Prentice Hall, 2008.