of a PC matrix. The degree of a node is the number of edges (lines) connected to it in a Tanner graph. The decoding algorithms for LDPC codes were discovered independently, and they come under different names. The most common ones are the BP algorithm, the message passing algorithm (MPA), and the sum-product algorithm. In a BP algorithm, the probabilistic mes- sages are iteratively exchanged between variable and check nodes until either a valid code- word is found or the maximum number of iterations is exceeded. The LDPC codes can be decoded using message passing or BP on the bipartite Tanner graph where, the CNDs and VNDs communicate with each other, successively passing revised estimates of the associated LLR in each decoding iteration. The bit reliability metric is defined as LLR(bi) = log p(bi = 0) - log(bi = 1) where bi denotes the ith bit in the received codeword. If LLR > 0, it implies that bi = 0 is more likely, while LLR <0 implies that bi = 1 is more probable. As an example, assume that codeword 0, 0, 0, 0, 0, 0, 0, 0, 0) is transmitted, and (0, 0, 0, 1, 0, 0, 0, 0, 0, 0) is received by decoder. Each valid 11-bit codeword C10) has the sum (modulo 2) of all bits equal to zero. The received vector does not satisfy this code constraint, indicating that there are errors present in the received codeword. Furthermore, assume that the decoder is provided with bit-level reliabil- ity metric in the form of probability (confidence in the received values) of being correct as 0.8,0.86, 0.7, 0.55, 1, 1, 0.8, ,0.98,0.68,0.99) From the soft information, it follows that bit C4 is the least reliable and should be flipped to bring the received codeword in com- pliance with code constraint. Using LLRs as messages, the hardware implementation has become much easier when compared to the message passing algorithm. The implementation complexity is further reduced by simplifying the process for updating the CNDs, which is the most complex part of the message passing algorithm. This algorithm is known as the min-sum algorithm. 