hfskscenarios.m

来自「1、HSDPA； 2、LTE； 3、turbo code； 4、Mobil」· M 代码 · 共 1,460 行 · 第 1/5 页

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sim_param(record).code_configuration = 0; % Convolutional
sim_param(record).SNR = [0:4 4.2:0.1:10];
sim_param(record).SNR_type = 'Eb/No in dB';
sim_param(record).framesize = 2048;
sim_param(record).modulation = 'FSK';
sim_param(record).h = 0.32;
sim_param(record).mapping = 'dt';
sim_param(record).mod_order = 8;
sim_param(record).csi_flag = 1; % noncoherent w/ CSI
sim_param(record).channel = 'AWGN';
sim_param(record).bicm = 2; % BICM-ID
sim_param(record).demod_type = 0; % linear-log-MAP
sim_param(record).linetype = 'b:';
sim_param(record).g1 = [1 0 1 1 0 1 1
   1 1 1 1 0 0 1];
sim_param(record).pun_pattern1 = [1 1 1 1 1 1 1 0
    1 1 1 1 1 1 1 1 ];
sim_param(record).tail_pattern1 = ones(2,length(sim_param(record).g1)-1);
sim_param(record).nsc_flag1 = 1;
sim_param(record).decoder_type =  0;  % linear-log-MAP
sim_param(record).max_iterations = 8;
sim_param(record).filename = strcat( data_directory, 'CPFSK8_h032_convolutional_AWGN_dt_bicmid_8r15.mat');
sim_param(record).reset = 0;
sim_param(record).max_trials = 1e9*ones( size(sim_param(record).SNR) );
sim_param(record).minBER = BER;    
sim_param(record).max_frame_errors = num_errors*ones( size(sim_param(record).SNR) );
sim_param(record).save_rate = 100;
sim_param(record).plot_iterations = [1 8];

% BICM: Convolutionally coded (r=8/15) 8FSK modulation in AWGN: natural mapping
record = 18;
sim_param(record).comment = 'natural mapping, r=8/15 CC, K = 7, q=8, h=0.32, AWGN';
sim_param(record).legend = 'natural mapping';
sim_param(record).sim_type = 'coded';
sim_param(record).code_configuration = 0; % Convolutional
sim_param(record).SNR = [0:4 4.2:0.1:10];
sim_param(record).SNR_type = 'Eb/No in dB';
sim_param(record).framesize = 2048;
sim_param(record).modulation = 'FSK';
sim_param(record).h = 0.32;
sim_param(record).mapping = 'natural';
sim_param(record).mod_order = 8;
sim_param(record).csi_flag = 1; % noncoherent w/ CSI
sim_param(record).channel = 'AWGN';
sim_param(record).bicm = 2; % BICM-ID
sim_param(record).demod_type = 0; % linear-log-MAP
sim_param(record).linetype = 'r:';
sim_param(record).g1 = [1 0 1 1 0 1 1
   1 1 1 1 0 0 1];
sim_param(record).pun_pattern1 = [1 1 1 1 1 1 1 0
    1 1 1 1 1 1 1 1 ];
sim_param(record).tail_pattern1 = ones(2,length(sim_param(record).g1)-1);
sim_param(record).nsc_flag1 = 1;
sim_param(record).decoder_type =  0;  % linear-log-MAP
sim_param(record).max_iterations = 8;
sim_param(record).filename = strcat( data_directory, 'CPFSK8_h032_convolutional_AWGN_natural_bicmid_8r15.mat');
sim_param(record).reset = 0;
sim_param(record).max_trials = 1e9*ones( size(sim_param(record).SNR) );
sim_param(record).minBER = BER;    
sim_param(record).max_frame_errors = num_errors*ones( size(sim_param(record).SNR) );
sim_param(record).save_rate = 100;
sim_param(record).plot_iterations = [1 8];

% BICM: Convolutionally coded (r=8/15) 8FSK modulation in AWGN: reverse gray mapping
record = 19;
sim_param(record).comment = 'reverse-gray mapping, r=8/15 CC, K = 7, q=8, h=0.32, AWGN';
sim_param(record).legend = 'reverse-gray mapping';
sim_param(record).sim_type = 'coded';
sim_param(record).code_configuration = 0; % Convolutional
sim_param(record).SNR = [0:4 4.2:0.1:10];
sim_param(record).SNR_type = 'Eb/No in dB';
sim_param(record).framesize = 2048;
sim_param(record).modulation = 'FSK';
sim_param(record).h = 0.32;
sim_param(record).mapping = [0 1 3 2 7 6 4 5];
sim_param(record).mod_order = 8;
sim_param(record).csi_flag = 1; % noncoherent w/ CSI
sim_param(record).channel = 'AWGN';
sim_param(record).bicm = 2; % BICM-ID
sim_param(record).demod_type = 0; % linear-log-MAP
sim_param(record).linetype = 'g:';
sim_param(record).g1 = [1 0 1 1 0 1 1
   1 1 1 1 0 0 1];
sim_param(record).pun_pattern1 = [1 1 1 1 1 1 1 0
    1 1 1 1 1 1 1 1 ];
sim_param(record).tail_pattern1 = ones(2,length(sim_param(record).g1)-1);
sim_param(record).nsc_flag1 = 1;
sim_param(record).decoder_type =  0;  % linear-log-MAP
sim_param(record).max_iterations = 8;
sim_param(record).filename = strcat( data_directory, 'CPFSK8_h032_convolutional_AWGN_reversegray_bicmid_8r15.mat');
sim_param(record).reset = 0;
sim_param(record).max_trials = 1e9*ones( size(sim_param(record).SNR) );
sim_param(record).minBER = BER;  
sim_param(record).max_frame_errors = num_errors*ones( size(sim_param(record).SNR) );
sim_param(record).save_rate = 100;
sim_param(record).plot_iterations = [1 8];

% BICM: Convolutionally coded (r=8/15) 8FSK modulation in AWGN: gray mapping
record = 20;
sim_param(record).comment = 'gray mapping, r=8/15 CC, K = 7, q=8, h=0.32, AWGN';
sim_param(record).legend = 'gray mapping';
sim_param(record).sim_type = 'coded';
sim_param(record).code_configuration = 0; % Convolutional
sim_param(record).SNR = [0:4 4.2:0.1:10];
sim_param(record).SNR_type = 'Eb/No in dB';
sim_param(record).framesize = 2048;
sim_param(record).modulation = 'FSK';
sim_param(record).h = 0.32;
sim_param(record).mapping = 'gray';
sim_param(record).mod_order = 8;
sim_param(record).csi_flag = 1; % noncoherent w/ CSI
sim_param(record).channel = 'AWGN';
sim_param(record).bicm = 2; % BICM-ID
sim_param(record).demod_type = 0; % linear-log-MAP
sim_param(record).linetype = 'k:';
sim_param(record).g1 = [1 0 1 1 0 1 1
   1 1 1 1 0 0 1];
sim_param(record).pun_pattern1 = [1 1 1 1 1 1 1 0
    1 1 1 1 1 1 1 1 ];
sim_param(record).tail_pattern1 = ones(2,length(sim_param(record).g1)-1);
sim_param(record).nsc_flag1 = 1;
sim_param(record).decoder_type =  0;  % linear-log-MAP
sim_param(record).max_iterations = 8;
sim_param(record).filename = strcat( data_directory, 'CPFSK8_h032_convolutional_AWGN_gray_bicmid_8r15.mat');
sim_param(record).reset = 0;
sim_param(record).max_trials = 1e9*ones( size(sim_param(record).SNR) );
sim_param(record).minBER = BER;    
sim_param(record).max_frame_errors = num_errors*ones( size(sim_param(record).SNR) );
sim_param(record).save_rate = 100;
sim_param(record).plot_iterations = [1 8];

% BICM: Convolutionally coded (r=8/15, K = 4) 8FSK modulation in AWGN: mv mapping
record = 21;
sim_param(record).comment = 'reverse-dt mapping, r=8/15 CC, K = 4, q=8, h=0.32, AWGN';
sim_param(record).legend = 'reverse-dt mapping';
sim_param(record).sim_type = 'coded';
sim_param(record).code_configuration = 0; % Convolutional
sim_param(record).SNR = [0:4 4.2:0.1:10];
sim_param(record).SNR_type = 'Eb/No in dB';
sim_param(record).framesize = 2048;
sim_param(record).modulation = 'FSK';
sim_param(record).h = 0.32;
sim_param(record).mapping = 'mv';
sim_param(record).mod_order = 8;
sim_param(record).csi_flag = 1; % noncoherent w/ CSI
sim_param(record).channel = 'AWGN';
sim_param(record).bicm = 2; % BICM-ID
sim_param(record).demod_type = 0; % linear-log-MAP
sim_param(record).linetype = 'm--';
sim_param(record).g1 = [1 0 1 1
    1 1 0 1];
sim_param(record).pun_pattern1 = [1 1 1 1 1 1 1 0
    1 1 1 1 1 1 1 1 ];
sim_param(record).tail_pattern1 = ones(2,length(sim_param(record).g1)-1);
sim_param(record).nsc_flag1 = 1;
sim_param(record).decoder_type =  0;  % linear-log-MAP
sim_param(record).max_iterations = 8;
sim_param(record).filename = strcat( data_directory, 'CPFSK8_h032_convolutional_AWGN_mv_bicmid_8r15_K4.mat');
sim_param(record).reset = 0;
sim_param(record).max_trials = 1e9*ones( size(sim_param(record).SNR) );
sim_param(record).minBER = BER;    
sim_param(record).max_frame_errors = num_errors*ones( size(sim_param(record).SNR) );
sim_param(record).save_rate = 100;
sim_param(record).plot_iterations = [1 8];

% BICM: Convolutionally coded (r=8/15, K=4) 8FSK modulation in AWGN: dt mapping
record = 22;
sim_param(record).comment = 'dt mapping, r=8/15 CC, K = 4, q=8, h=0.32, AWGN';
sim_param(record).legend = 'dt mapping';
sim_param(record).sim_type = 'coded';
sim_param(record).code_configuration = 0; % Convolutional
sim_param(record).SNR = [0:4 4.2:0.1:10];
sim_param(record).SNR_type = 'Eb/No in dB';
sim_param(record).framesize = 2048;
sim_param(record).modulation = 'FSK';
sim_param(record).h = 0.32;
sim_param(record).mapping = 'dt';
sim_param(record).mod_order = 8;
sim_param(record).csi_flag = 1; % noncoherent w/ CSI
sim_param(record).channel = 'AWGN';
sim_param(record).bicm = 2; % BICM-ID
sim_param(record).demod_type = 0; % linear-log-MAP
sim_param(record).linetype = 'b--';
sim_param(record).g1 = [1 0 1 1
    1 1 0 1];
sim_param(record).pun_pattern1 = [1 1 1 1 1 1 1 0
    1 1 1 1 1 1 1 1 ];
sim_param(record).tail_pattern1 = ones(2,length(sim_param(record).g1)-1);
sim_param(record).nsc_flag1 = 1;
sim_param(record).decoder_type =  0;  % linear-log-MAP
sim_param(record).max_iterations = 8;
sim_param(record).filename = strcat( data_directory, 'CPFSK8_h032_convolutional_AWGN_dt_bicmid_8r15_K4.mat');
sim_param(record).reset = 0;
sim_param(record).max_trials = 1e9*ones( size(sim_param(record).SNR) );
sim_param(record).minBER = BER;    
sim_param(record).max_frame_errors = num_errors*ones( size(sim_param(record).SNR) );
sim_param(record).save_rate = 100;
sim_param(record).plot_iterations = [1 8];

% BICM: Convolutionally coded (r=8/15, K=4) 8FSK modulation in AWGN: natural mapping
record = 23;
sim_param(record).comment = 'natural mapping, r=8/15 CC, K = 4, q=8, h=0.32, AWGN';
sim_param(record).legend = 'natural mapping';
sim_param(record).sim_type = 'coded';
sim_param(record).code_configuration = 0; % Convolutional
sim_param(record).SNR = [0:4 4.2:0.1:10];
sim_param(record).SNR_type = 'Eb/No in dB';
sim_param(record).framesize = 2048;
sim_param(record).modulation = 'FSK';
sim_param(record).h = 0.32;
sim_param(record).mapping = 'natural';
sim_param(record).mod_order = 8;
sim_param(record).csi_flag = 1; % noncoherent w/ CSI
sim_param(record).channel = 'AWGN';
sim_param(record).bicm = 2; % BICM-ID
sim_param(record).demod_type = 0; % linear-log-MAP
sim_param(record).linetype = 'r--';
sim_param(record).g1 = [1 0 1 1
    1 1 0 1];
sim_param(record).pun_pattern1 = [1 1 1 1 1 1 1 0
    1 1 1 1 1 1 1 1 ];
sim_param(record).tail_pattern1 = ones(2,length(sim_param(record).g1)-1);
sim_param(record).nsc_flag1 = 1;
sim_param(record).decoder_type =  0;  % linear-log-MAP
sim_param(record).max_iterations = 8;
sim_param(record).filename = strcat( data_directory, 'CPFSK8_h032_convolutional_AWGN_natural_bicmid_8r15_K4.mat');
sim_param(record).reset = 0;
sim_param(record).max_trials = 1e9*ones( size(sim_param(record).SNR) );
sim_param(record).minBER = BER;    
sim_param(record).max_frame_errors = num_errors*ones( size(sim_param(record).SNR) );
sim_param(record).save_rate = 100;
sim_param(record).plot_iterations = [1 8];

% BICM: Convolutionally coded (r=8/15, K=4) 8FSK modulation in AWGN: reverse gray mapping
record = 24;
sim_param(record).comment = 'reverse-gray mapping, r=8/15 CC, K = 4, q=8, h=0.32, AWGN';
sim_param(record).legend = 'reverse-gray mapping';
sim_param(record).sim_type = 'coded';
sim_param(record).code_configuration = 0; % Convolutional
sim_param(record).SNR = [0:4 4.2:0.1:10];
sim_param(record).SNR_type = 'Eb/No in dB';
sim_param(record).framesize = 2048;
sim_param(record).modulation = 'FSK';
sim_param(record).h = 0.32;
sim_param(record).mapping = [0 1 3 2 7 6 4 5];
sim_param(record).mod_order = 8;
sim_param(record).csi_flag = 1; % noncoherent w/ CSI
sim_param(record).channel = 'AWGN';
sim_param(record).bicm = 2; % BICM-ID
sim_param(record).demod_type = 0; % linear-log-MAP
sim_param(record).linetype = 'g--';
sim_param(record).g1 = [1 0 1 1
    1 1 0 1];
sim_param(record).pun_pattern1 = [1 1 1 1 1 1 1 0
    1 1 1 1 1 1 1 1 ];
sim_param(record).tail_pattern1 = ones(2,length(sim_param(record).g1)-1);
sim_param(record).nsc_flag1 = 1;
sim_param(record).decoder_type =  0;  % linear-log-MAP
sim_param(record).max_iterations = 8;
sim_param(record).filename = strcat( data_directory, 'CPFSK8_h032_convolutional_AWGN_reversegray_bicmid_8r15_K4.mat');
sim_param(record).reset = 0;
sim_param(record).max_trials = 1e9*ones( size(sim_param(record).SNR) );
sim_param(record).minBER = BER;  
sim_param(record).max_frame_errors = num_errors*ones( size(sim_param(record).SNR) );
sim_param(record).save_rate = 100;
sim_param(record).plot_iterations = [1 8];

% BICM: Convolutionally coded (r=8/15, K=4) 8FSK modulation in AWGN: gray mapping
record = 25;
sim_param(record).comment = 'gray mapping, r=8/15 CC, K = 4, q=8, h=0.32, AWGN';
sim_param(record).legend = 'gray mapping';
sim_param(record).sim_type = 'coded';
sim_param(record).code_configuration = 0; % Convolutional
sim_param(record).SNR = [0:4 4.2:0.1:10];
sim_param(record).SNR_type = 'Eb/No in dB';
sim_param(record).framesize = 2048;
sim_param(record).modulation = 'FSK';
sim_param(record).h = 0.32;
sim_param(record).mapping = 'gray';
sim_param(record).mod_order = 8;
sim_param(record).csi_flag = 1; % noncoherent w/ CSI
sim_param(record).channel = 'AWGN';
sim_param(record).bicm = 2; % BICM-ID
sim_param(record).demod_type = 0; % linear-log-MAP
sim_param(record).linetype = 'k--';
sim_param(record).g1 = [1 0 1 1
    1 1 0 1];
sim_param(record).pun_pattern1 = [1 1 1 1 1 1 1 0
    1 1 1 1 1 1 1 1 ];
sim_param(record).tail_pattern1 = ones(2,length(sim_param(record).g1)-1);
sim_param(record).nsc_flag1 = 1;
sim_param(record).decoder_type =  0;  % linear-log-MAP
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hfskscenarios.m - 源码说明

本页面展示了「1、HSDPA； 2、LTE； 3、turbo code； 4、Mobile WiMAX； 5、LDPC」中的 hfskscenarios.m 源码文件，采用 M 编程语言编写，共 1,460 行代码。您可以在线阅读完整代码内容，也可以返回资源详情页下载完整源码包进行本地学习和开发。

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