OSTBC encoding for MIMO

I have this code of beam MIMO forming, It uses convolutional encoding, how can I change the encoding to OSTBC?

%% Beamforming for MIMO-OFDM Systems
% This example shows how to model a point-to-point MIMO-OFDM system with
% beamforming. The combination of multiple-input-multiple-output (MIMO) and
% orthogonal frequency division multiplexing (OFDM) techniques have been
% adopted in recent wireless standards, such as 802.11x families, to
% provide higher data rate. Because MIMO uses antenna arrays, beamforming
% can be adopted to improve the received signal to noise ratio (SNR) which
% in turn reduces the bit error rate (BER).
%
% This example requires Communications Toolbox(TM).

%   Copyright 2014-2018 The MathWorks, Inc.

%% Introduction
% The term MIMO is used to describe a system where multiple transmitters or
% multiple receivers are present. In practice the system can take many
% different forms, such as single-input-multiple-output (SIMO) or
% multiple-input-single-output (MISO) system. This example illustrates a
% downlink MISO system. An 8-element ULA is deployed at the base station as
% the transmitter while the mobile unit is the receiver with a single
% antenna.
%
% The rest of the system is configured as follows. The transmitter power is
% 8 watts and the transmit gain is -8 dB. The mobile receiver is stationary
% and located at 2750 meters away, and is 3 degrees off the transmitter's
% boresight. An interferer with a power of 1 watt and a gain of -20 dB is
% located at 9000 meters, 20 degrees off the transmitter's boresight. 

% Initialize system constants
rng(2014);
gc = helperGetDesignSpecsParameters();

% Tunable parameters
tp.txPower = 9;           % watt
tp.txGain = -8;           % dB
tp.mobileRange = 2750;    % m
tp.mobileAngle = 3;       % degrees
tp.interfPower = 1;       % watt
tp.interfGain = -20;      % dB
tp.interfRange = 9000;    % m
tp.interfAngle =   20;    % degrees
tp.numTXElements = 8;       
tp.steeringAngle = 0;     % degrees
tp.rxGain = 108.8320 - tp.txGain; % dB

numTx= tp.numTXElements;

%%
% The entire scene can be depicted in the figure below.

helperPlotMIMOEnvironment(gc, tp);

%% Signal Transmission 
% First, configure the system's transmitter. 

[encoder,scrambler,modulatorRQAM,modulatorOFDM,steeringvec,transmitter,...
    radiator,pilots,numDataSymbols,frmSz] = helperMIMOTxSetup(gc,tp);

%%
% There are many components in the transmitter subsystem, such as the
% convolutional encoder, the scrambler, the QAM modulator, the OFDM
% modulator, and so on. The message is first converted to an information
% bit stream and then passed through source coding and modulation stages to
% prepare for the radiation.

txBits = randi([0, 1], frmSz,1);
coded = encoder(txBits);
bitsS = scrambler(coded);
tx = modulatorRQAM(bitsS);

%%
% In an OFDM system, the data is carried by multiple sub-carriers that are
% orthogonal to each other. 

ofdm1 = reshape(tx, gc.numCarriers,numDataSymbols);

%%
% Then, the data stream is duplicated to all radiating elements in the
% transmitting array

ofdmData = repmat(ofdm1,[1, 1, numTx]);
txOFDM = modulatorOFDM(ofdmData, pilots);
%scale
txOFDM = txOFDM * ...
    (gc.FFTLength/sqrt(gc.FFTLength-sum(gc.NumGuardBandCarriers)-1));

% Amplify to achieve peak TX power for each channel
for n = 1:numTx
    txOFDM(:,n) = transmitter(txOFDM(:,n));
end

%%
% In a MIMO system, it is also possible to separate multiple users spatial
% division multiplexing (SDMA). In these situations, the data stream is
% often modulated by a weight corresponding to the desired direction so
% that once radiated, the signal is maximized in that direction. Because in
% a MIMO channel, the signal radiated from different elements in an array
% may go through different propagation environments, the signal radiated
% from each antenna should be propagated individually. This can be achieved
% by setting CombineRadiatedSignals to false on the phased.Radiator
% component.

radiator.CombineRadiatedSignals = false;

%%
% To achieve precoding, the data stream radiated from each antenna in the
% array is modulated by a phase shift corresponding to its radiating
% direction. The goal of this precoding is to ensure these data streams add
% in phase if the array is steered toward that direction. Precoding can be
% specified as weights used at the radiator.

wR = steeringvec(gc.fc,[-tp.mobileAngle;0]);

%% 
% Meanwhile, the array is also steered toward a given steering angle, so
% the total weights are a combination of both precoding and the steering
% weights.

wT = steeringvec(gc.fc,[tp.steeringAngle;0]);
weight = wT.* wR;

%%
% The transmitted signal is thus given by

txOFDM = radiator(txOFDM,repmat([tp.mobileAngle;0],1,numTx),conj(weight));

%%
% Note that the transmitted signal, txOFDM, is a matrix whose columns
% represent data streams radiated from the corresponding elements in the
% transmit array.


%% Signal Propagation 
% Next, the signal propagates through a MIMO channel. In general, there are
% two propagation effects on the received signal strength that are of
% interest: one of them is the spreading loss due to the propagation
% distance, often termed as the free space path loss; and the other is the
% fading due to multipath. This example models both effects.

[channel,interferenceTransmitter,toRxAng,spLoss] = ...
    helperMIMOEnvSetup(gc,tp);
[sigFade, chPathG] =  channel(txOFDM);
sigLoss = sigFade/sqrt(db2pow(spLoss(1)));

%%
% To simulate a more realistic mobile environment, next section also
% inserts an interference source. Note that in a wireless communication
% system, the interference is often a different mobile user.

% Generate interference and apply gain and propagation loss
numBits = size(sigFade,1);
interfSymbols = wgn(numBits,1,1,'linear','complex');
interfSymbols = interferenceTransmitter(interfSymbols);
interfLoss = interfSymbols/sqrt(db2pow(spLoss(2)));

%% Signal Reception
% The receiving antenna collects both the propagated signal as well as the
% interference and passes them to the receiver to recover the original
% information embedded in the signal. Just like the transmit end of the
% system, the receiver used in a MIMO-OFDM system also contains many
% stages, including OFDM demodulator, QAM demodulator, descrambler,
% equalizer, and Viterbi decoder.

[collector,receiver,demodulatorOFDM,demodulatorRQAM,...
    descrambler,decoder] = helperMIMORxSetup(gc,tp,numDataSymbols);

rxSig = collector([sigLoss interfLoss],toRxAng);

% Front-end amplifier gain and thermal noise
rxSig = receiver(rxSig);

rxOFDM = rxSig * ...
    (sqrt(gc.FFTLength-sum(gc.NumGuardBandCarriers)-1)) / (gc.FFTLength);

% OFDM Demodulation
rxOFDM = demodulatorOFDM(rxOFDM);

% Channel estimation
hD = helperIdealChannelEstimation(gc,  numDataSymbols, chPathG);

% Equalization
rxEq = helperEqualizer(rxOFDM, hD, numTx);

% Collapse OFDM matrix
rxSymbs = rxEq(:);

rxBitsS = demodulatorRQAM(rxSymbs);
rxCoded = descrambler(rxBitsS);
rxDeCoded = decoder(rxCoded);
rxBits = rxDeCoded(1:frmSz);

%% 
% A comparison of the decoded output with the original message stream
% suggests that the resulting BER is too high for a communication system.
% The constellation diagram is also shown below

ber = comm.ErrorRate;
measures = ber(txBits, rxBits);
fprintf('BER = %.2f%%; No. of Bits = %d; No. of errors = %d\n', ...
    measures(1)*100,measures(3), measures(2));

%%

constdiag = comm.ConstellationDiagram('SamplesPerSymbol', 1,...
    'ReferenceConstellation', [], 'ColorFading',true,...
    'Position', gc.constPlotPosition);
% Display received constellation
constdiag(rxSymbs);

%%
% The high BER is mainly due to the mobile being off the steering direction
% of the base station array. If the mobile is aligned with the steering
% direction, the BER is greatly improved.

tp.steeringAngle = tp.mobileAngle;

% Steer the transmitter main lobe
wT = steeringvec(gc.fc,[tp.steeringAngle;0]);

[txBits, rxBits,rxSymbs] = helperRerunMIMOBeamformingExample(gc,tp,wT);

reset(ber);
measures = ber(txBits, rxBits);
fprintf('BER = %.2f%%; No. of Bits = %d; No. of errors = %d\n', ...
    measures(1)*100,measures(3), measures(2));

%%
constdiag(rxSymbs);

%% 
% Therefore, the system is very sensitive to the steering error. On the
% other hand, it is this kind of spatial sensitivity makes SDMA possible to
% distinguish multiple users in space.

%% Phase Shifter Quantization Effect
% The discussion so far assumes that the beam can be steered toward the
% exact desired direction. In reality, however, this is often not true,
% especially when the analog phase shifters are used. Analog phase shifters
% have only limited precision and are categorized by the number of bits
% used in phase shifts. For example, a 3-bit phase shifter can only
% represent 8 different angles within 360 degrees. Thus, if such
% quantization is included in the simulation, the system performance
% degrades, which can be observed from the constellation plot.

% analog phase shifter with quantization effect
release(steeringvec);
steeringvec.NumPhaseShifterBits = 4;
wTq = steeringvec(gc.fc,[tp.steeringAngle;0]);

[txBits, rxBits,rxSymbs] = helperRerunMIMOBeamformingExample(gc,tp,wTq);

reset(ber);
measures = ber(txBits, rxBits);
fprintf('BER = %.2f%%; No. of Bits = %d; No. of errors = %d\n', ...
    measures(1)*100,measures(3), measures(2));

constdiag = comm.ConstellationDiagram('SamplesPerSymbol', 1,...
    'ReferenceConstellation', [], 'ColorFading',true,...
    'Position', gc.constPlotPosition);
constdiag(rxSymbs);

%% Summary
% This example shows a system level simulation of a point-to-point
% MIMO-OFDM system employing beamforming. The simulation models many system
% components such as encoding, transmit beamforming, precoding, multipath
% fading, channel estimation, equalization, and decoding. 

%% Reference
% [1] Houman Zarrinkoub, Understanding LTE with MATLAB, Wiley, 2014
% 
% [2] Theodore S. Rappaport et al. Millimeter Wave Wireless Communications,
% Prentice Hall, 2014