根据lte系统中的咬尾卷积码，写一个matlab的译码程序

在LTE（Long-Term Evolution）系统中，咬尾卷积码（Tailbiting Convolutional Codes, TBCC）是一种用于前向纠错的码型，特别适合于有限长度的传输。在MATLAB中，我们可以使用Viterbi算法进行TBCC的译码。以下是一个基本的Viterbi译码器实现示例：

% 假设你有生成矩阵G、初始状态概率和转移概率数组
G = [1 1 0; 0 1 1]; % 例如一个2级卷积码的生成矩阵
initial_probabilities = [1 0]; % 初始状态概率
transition_probabilities = [1 1/2 1/2; 1/2 1 1/2]; % 转移概率

% 设定接收信号比特流和TBCC码字长
received_bits = [0 1 0 1 1 0 1 1]; % 接收的比特序列
tbcc_length = length(G)-1; % TBCC码字长度（因为是尾部连接）

% 确保接收比特流长度足够长
if mod(length(received_bits), tbcc_length) ~= 0
    error('Received bit sequence length is not a multiple of TBCC length.');
end

% Viterbi译码器
function decoded_sequence = viterbi_decode(encoded_bits, G, initial_probs, trans_probs)
    n_states = size(G, 1);
    path_memory = zeros(n_states, 1); % 存储路径信息
    path_probabilities = zeros(n_states, 1); % 存储路径概率

    % 初始化
    for state = 1:n_states
        path_memory(state) = 0;
        path_probabilities(state) = initial_probs(state);
    end
    
    % 遍历接收比特流
    for i = 1:length(encoded_bits)
        next_state_probabilities = zeros(n_states, 1);
        
        % 更新路径概率
        for j = 1:n_states
            next_state_probabilities(j) = path_probabilities(j) * trans_probs(j, encoded_bits(i)) .* path_memory(j);
        end
        
        % 更新路径记忆和路径概率
        [~, max_index] = max(next_state_probabilities);
        path_memory = circshift(path_memory, -1);
        path_memory(1) = encoded_bits(i);
        path_probabilities = next_state_probabilities;
    end
    
    % 取最大概率路径作为解码结果
    decoded_sequence = path_memory(find(path_probabilities == max(path_probabilities)));
end

decoded_sequence = viterbi_decode(received_bits, G, initial_probabilities, transition_probabilities);

注意：上述代码只是一个简化版本，实际应用可能需要对错误检测和修正、以及更复杂的TBCC参数进行调整。此外，你需要提供具体的G矩阵、初始状态概率和转移概率才能运行这个函数。