Recently, a number of LDPC decoder architectures have been proposed [3]- [8]. These architectures have implemented the widely used Sum Product Algorithm with various approaches to satisfy throughput and hardware requirements. The need for large hardware resources is a significant problem in the implementation of an LDPC decoder. Mostly, serial architectures that require lesser hardware than parallel implementations are used. In [4] and [5] a memory efficient turbo decoding algorithm for LDPC codes is proposed. In [11] the issues relating to the implementation of a min-sum LDPC decoder is explored. In [2] an offset min-sum algorithm offering tradeoff between performance and complexity is explored to save extrinsic message memory. In [1] an approximate min constraint for check node update is proposed. The approximation is exploited by the decoder to reduce hardware for check node computation units without any noticeable degradation in bit error rate performance. We observe that the bulk of hardware requirement for the serial LDPC decoder lies in the memory used for storing the extrinsic values(check to bit or bit to check) and hence attempt to reduce it. The proposed modification to the SPA explained in section III is identical to the one proposed in [1] but we implement the approximation in log-tanh domain to facilitate our serial decoder architecture. The proposed decoder stores only few bit to check messages which is very efficient when compared to architectures proposed in [6], [7] which store all the bit to check messages and also check to bit messages. When compared to the serial decoder [2] our design stores lesser number of extrinsic values and requires lesser memory to store intermediate partial sums. The proposed decoder is explained in section IV.