QPSK Receiver with ADALM-PLUTO Radio

Implementations

This example describes the MATLAB implementation of a QPSK receiver with ADALM-PLUTO Radio. There is another implementation of this example that uses Simulink®.

MATLAB script using System objects: QPSKReceiverWithADALMPLUTORadioExample.

Simulink implementation using blocks: QPSKReceiverWithADALMPLUTORadioSimulinkExample.

You can also explore a no-radio QPSK Transmitter and Receiver example that models a general wireless communication system using an AWGN channel and simulated channel impairments at QPSKTransmitterAndReceiverExample.

Introduction

This example has the following motivation:

In this example, the ADALM-PLUTO System object receives data corrupted by the transmission over the air and outputs complex baseband signals which are processed by the QPSK Receiver System object. This example provides a reference design of a practical digital receiver that can cope with wireless channel impairments. The receiver includes FFT-based coarse frequency compensation, PLL-based fine frequency compensation, timing recovery with fixed-rate re-sampling and bit stuffing/skipping, frame synchronization, and phase ambiguity resolution.

Initialization

The plutoradioqpskreceiver_init.m script initializes the simulation parameters and generates the structure prmQPSKReceiver.

% Receiver parameter structure
prmQPSKReceiver = plutoradioqpskreceiver_init;
% Specify Radio ID
prmQPSKReceiver.Address = 'usb:0'

prmQPSKReceiver = 

  struct with fields:

                           Rsym: 200000
                ModulationOrder: 4
                  Interpolation: 2
                     Decimation: 1
                           Tsym: 5.0000e-06
                             Fs: 400000
                     BarkerCode: [1 1 1 1 1 -1 -1 1 1 -1 1 -1 1]
                   BarkerLength: 13
                   HeaderLength: 26
                        Message: 'Hello world'
                  MessageLength: 16
                NumberOfMessage: 100
                  PayloadLength: 11200
                      FrameSize: 5613
                      FrameTime: 0.0281
                  RolloffFactor: 0.5000
                  ScramblerBase: 2
            ScramblerPolynomial: [1 1 1 0 1]
     ScramblerInitialConditions: [0 0 0 0]
         RaisedCosineFilterSpan: 10
                   DesiredPower: 2
                AveragingLength: 50
                   MaxPowerGain: 60
         MaximumFrequencyOffset: 6000
     PhaseRecoveryLoopBandwidth: 0.0100
     PhaseRecoveryDampingFactor: 1
    TimingRecoveryLoopBandwidth: 0.0100
    TimingRecoveryDampingFactor: 1
        TimingErrorDetectorGain: 5.4000
     PreambleDetectionThreshold: 0.8000
                    MessageBits: [11200×1 double]
                        BerMask: [7700×1 double]
           PlutoCenterFrequency: 915000000
                      PlutoGain: 30
        PlutoFrontEndSampleRate: 400000
               PlutoFrameLength: 11226
                 PlutoFrameTime: 0.0281
                       StopTime: 10
                        Address: 'usb:0'

Code Architecture

The function runPlutoradioQPSKReceiver implements the QPSK receiver using the QPSK receiver System object, QPSKReceiver, and ADALM-PLUTO radio System object, comm.SDRRxPluto.

ADALM-PLUTO Receiver

This example communicates with the ADALM-PLUTO radio using the ADALM-PLUTO Receiver System object. The parameter structure prmQPSKReceiver sets the CenterFrequency, Gain, and InterpolationFactor etc.

QPSK Receiver

This component regenerates the original transmitted message. It is divided into six subcomponents, modeled using System objects. Each subcomponent is modeled by other subcomponents using System objects.

1) Automatic Gain Control: Sets its output power to a level ensuring 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 two. This process improves the accuracy of the estimate.

2) Coarse frequency compensation: Uses a correlation-based algorithm to roughly estimate the frequency offset and then compensate for it. The estimated coarse frequency offset is averaged so that fine frequency compensation is allowed to lock/converge. Hence, the coarse frequency offset is estimated using a "comm.CoarseFrequencyCompensator" System object and an averaging formula; the compensation is performed using a "comm.PhaseFrequencyOffset" System object.

3) Timing recovery: Performs timing recovery with closed-loop scalar processing to overcome the effects of mismatched sample rate between the transmitter and the receiver due to inaccuracies of crystal oscillators used in sampling clock generation, we employ a comm.SymbolSynchronizer System object. The object implements a PLL to correct the symbol timing error in the received signal. The rotationally-invariant Gardner timing error detector is chosen for the object in this example; thus, timing recovery can precede fine frequency compensation. 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 to bit stuffing and stripping, depending on actual channel delays.

4) Fine frequency compensation: Performs closed-loop scalar processing and compensates for the frequency offset accurately, using a comm.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.

5) Frame Synchronization: Detects the location of the known Barker code in the input and performs frame synchronization using a FrameSynchronizer System object. It also converts the variable-length symbol inputs into fixed-length outputs. 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.

For more information about the system components, refer to the QPSK Receiver with ADALM-PLUTO Radio in Simulink.

Execution and Results

Connect two ADALM-PLUTO Radios to the computer. Start the QPSK Transmitter with ADALM-PLUTO Radio example in one MATLAB session and then start the receiver script in another MATLAB session.

printReceivedData = false;    % true if the received data is to be printed

BER = runPlutoradioQPSKReceiver(prmQPSKReceiver, printReceivedData);

fprintf('Error rate is = %f.\n',BER(1));
fprintf('Number of detected errors = %d.\n',BER(2));
fprintf('Total number of compared samples = %d.\n',BER(3));

## Establishing connection to hardware. This process can take several seconds.
Error rate is = 0.504279.
Number of detected errors = 1036748.
Total number of compared samples = 2055900.

When you run the simulations, the received messages are decoded and printed out in the MATLAB command window while the simulation is running. BER information is also shown at the end of the script execution. The calculation of the BER value includes the first received frames, when some of the adaptive components in the QPSK receiver still have not converged. During this period, the BER is quite high. Once the transient period is over, the receiver is able to estimate the transmitted frame and the BER dramatically improves. In this example, to guarantee a reasonable execution time of the system in simulation mode, the simulation duration is fairly short. As such, the overall BER results are significantly affected by the high BER values at the beginning of the simulation. To increase the simulation duration and obtain lower BER values, you can change the SimParams.StopTime variable in the receiver initialization file.

If the message is not properly decoded by the receiver system, you can vary the gain of the source signals in the ADALM-PLUTO Transmitter and ADALM-PLUTO Receiver System objects by changing the SimParams.PlutoGain value in the transmitter initialization file and in the receiver initialization file.

Finally, a large relative frequency offset between the transmit and receive devices can prevent the receiver functions from properly decoding the message. If that happens, you can determine the offset by running the Frequency Offset Calibration (Tx) with ADALM-PLUTO Radio and the Frequency Offset Calibration (Rx) with ADALM-PLUTO Radio models, then applying that offset to the center frequency of the ADALM-PLUTO Receiver System object.

Appendix

This example uses the following script and helper functions:

References

1. Rice, Michael. Digital Communications - A Discrete-Time Approach. 1st ed. New York, NY: Prentice Hall, 2008.