% generating error patterns using gilbert-elliot model

p_gg = 0.99;
p_bb = 0.1;
p_bg = 1 - p_bb;

pi_0 = p_bb / (2 - (p_gg + p_bb));

% freely chosen bit error probability
e_g = 10^-4;
e_b = 10^-1;

% generate random bitstream
bits_array_len = 10^6;
bits = randi([0, 1], 1, bits_array_len);

% choose beginning channel state, biased to false, 
% assume pipe dirty at start of stream
if rand() < pi_0
    channel_state = true;
else
    channel_state = false;
end

% preallocated array/vector for the resulting bits
result_stream = zeros(1, bits_array_len);

bit_error_rate_counter = 0;
gap_size_tracker = [];
current_gap_size = 0;

for it = 1 : bits_array_len
    current_bit = bits(it);

    r = rand();

    % error and channel
    if channel_state == true
        % channel selection from good state with probability p_gg
        if r < p_gg
            channel_state = 1;
        else
            channel_state = 0;
        end
        
        if r < e_g
            received_bit = 1 - current_bit;
        else 
            received_bit = current_bit;
        end
    else
        % change channel to good with probability 
        if r < p_bg
            channel_state = 1;
        else
            channel_state = 0;
        end

        if r < e_b
            received_bit = 1 - current_bit;
        else 
            received_bit = current_bit;
        end
    end

    result_stream(it) = received_bit;

    % BER and Gap
    if current_bit ~= received_bit
        bit_error_rate_counter = bit_error_rate_counter + 1;
        gap_size_tracker(end + 1) = current_gap_size;
        current_gap_size = 0;
    end

    current_gap_size = current_gap_size + 1;
end

bit_error_rate = bit_error_rate_counter / bits_array_len

% limit gap size to 500 in histogram
% for pdf, 1 - 2 sites, describe what i did and what the results were and
% are