PCCC Parallel Concatenated Convolution Coding
PCCC (Parallel Concatenated Convolution Coding) is a powerful error correction coding scheme used in digital communication systems to enhance the reliability and integrity of transmitted data. It is a type of turbo coding, which is based on the principle of concatenating multiple convolutional codes together. PCCC is widely employed in various communication standards, including satellite communication, wireless communication, and deep space communication, where data accuracy and error resilience are of utmost importance.
To understand PCCC, let's first discuss the basic concepts of convolutional coding. Convolutional codes are a class of error correction codes that encode data in a sequential manner. They operate on a sliding window of input bits and generate a set of output bits based on the current input bits and the previous state of the encoder. The encoder consists of shift registers and modulo-2 adders. The output bits are generated by performing modulo-2 addition on selected bits from the shift registers. Convolutional codes are characterized by two parameters: the code rate and the constraint length. The code rate represents the ratio of output bits to input bits, while the constraint length refers to the number of shift registers in the encoder.
In PCCC, multiple convolutional codes are concatenated in parallel to form a more powerful coding scheme. The main idea behind PCCC is to exploit the complementary error patterns of different convolutional codes to improve the overall error correction capability. By combining the outputs of multiple encoders in parallel, PCCC achieves better performance compared to individual convolutional codes.
The PCCC encoder consists of multiple parallel convolutional encoders, each operating on a different set of input bits. The outputs of these encoders are combined using a bitwise modulo-2 addition, forming the encoded output. The encoded data is then transmitted over the communication channel.
At the receiver end, the received data is subjected to a decoding process to recover the original information bits. PCCC utilizes a decoding algorithm called the iterative decoding algorithm. This algorithm iteratively exchanges information between the constituent decoders to refine their estimates of the transmitted bits. The iterative process continues until a certain stopping criterion is met or a maximum number of iterations is reached. The decoded output of PCCC is then passed through a process called deinterleaving to restore the original sequence of data bits.
The performance of PCCC is evaluated using metrics such as bit error rate (BER) and frame error rate (FER). BER represents the number of erroneous bits divided by the total number of transmitted bits, while FER represents the number of erroneous frames divided by the total number of transmitted frames. PCCC typically achieves significant gains in terms of error correction performance compared to individual convolutional codes, especially in the presence of noise and interference.
PCCC has been extensively used in various communication systems and standards. In satellite communication, PCCC is employed to ensure reliable transmission of data over long distances and through challenging atmospheric conditions. In wireless communication, PCCC is utilized to combat channel impairments, such as multipath fading and interference, resulting in improved data throughput and quality of service. In deep space communication, PCCC is crucial for transmitting data from space probes and satellites, where the signal-to-noise ratio is extremely low.
In conclusion, PCCC (Parallel Concatenated Convolution Coding) is a powerful error correction coding scheme that combines multiple convolutional codes in parallel to enhance the reliability of transmitted data. By exploiting the complementary error patterns of different codes, PCCC achieves improved error correction performance compared to individual codes. PCCC is widely employed in various communication systems and standards, playing a crucial role in ensuring the accuracy and integrity of transmitted data in the face of noise, interference, and other channel impairments.