lic shift to the right of each row is applied. Unlike the LDPC codes specified in other wireless technologies, the NR LDPC codes have a rate-compatible structure, which means codewords with different rates can be generated by including a different number of parity bits, or equivalently by using a smaller subset of the full PC matrix. This is especially useful for communication systems employing HARQ-IR for retransmissions. Another advantage of this structure is that for higher rates, the PC matrix and the decoding complex- ity and latency are smaller. This is in contrast with the LTE turbo codes, which have con- stant decoding complexity and latency irrespective of the code rate [55]. The NR data channel supports two base graphs to ensure good performance and decoding latency can be achieved for the full range of code rates and information block sizes. The base graph 1 is optimized for large information block sizes and high code rates. It is designed for maximum code rate of 8/9 and may be used for code rates up to 0.95. The base graph 2 is optimized for small information block sizes and lower code rates. The lowest code rate for base graph 2 without using repetition is 1/5. This is significantly lower than that of the LTE turbo codes, which rely on repetition for code rates below 1/3. The NR LDPC codes can also achieve an additional coding gain at low-code rates, which makes them suitable for high reliability scenarios. From decoding complexity perspective, for a given number of input bits, it is beneficial to use base graph 2, since it is more com- pact and utilizes a larger lifting factor, that is, more parallelism, relative to base graph 1. The decoding latency is typically proportional to the number of non-zero elements in the base graph. Since base graph 2 has much fewer non-zero elements compared to base graph 1 for a given code rate, its decoding latency is significantly lower. In 3GPP NR, the input bit sequence is represented as c = where number of information bits to encode. The output LDPC-coded bits a