ti_mo
82 lines
1.8 KiB
Plaintext
82 lines
1.8 KiB
Plaintext
% generating error patterns using gilbert-elliot model
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p_gg = 0.99;
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p_bb = 0.1;
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p_bg = 1 - p_bb;
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pi_0 = p_bb / (2 - (p_gg + p_bb));
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% freely chosen bit error probability
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e_g = 10^-4;
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e_b = 10^-1;
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% generate random bitstream
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bits_array_len = 10^6;
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bits = randi([0, 1], 1, bits_array_len);
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% choose beginning channel state, biased to false,
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% assume pipe dirty at start of stream
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if rand() < pi_0
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channel_state = true;
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else
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channel_state = false;
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end
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% preallocated array/vector for the resulting bits
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result_stream = zeros(1, bits_array_len);
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bit_error_rate_counter = 0;
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gap_size_tracker = [];
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current_gap_size = 0;
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for it = 1 : bits_array_len
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current_bit = bits(it);
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r = rand();
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% error and channel
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if channel_state == true
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% channel selection from good state with probability p_gg
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if r < p_gg
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channel_state = 1;
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else
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channel_state = 0;
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end
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if r < e_g
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received_bit = 1 - current_bit;
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else
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received_bit = current_bit;
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end
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else
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% change channel to good with probability
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if r < p_bg
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channel_state = 1;
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else
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channel_state = 0;
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end
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if r < e_b
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received_bit = 1 - current_bit;
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else
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received_bit = current_bit;
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end
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end
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result_stream(it) = received_bit;
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% BER and Gap
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if current_bit ~= received_bit
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bit_error_rate_counter = bit_error_rate_counter + 1;
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gap_size_tracker(end + 1) = current_gap_size;
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current_gap_size = 0;
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end
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current_gap_size = current_gap_size + 1;
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end
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bit_error_rate = bit_error_rate_counter / bits_array_len
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% limit gap size to 500 in histogram
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% for pdf, 1 - 2 sites, describe what i did and what the results were and
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% are |