Structure and BER of a novel convolutional code

Channel error-correcting coding is essential to improve the communication quality. Low density parity check (LDPC) code with near Shannon limit characteristics has increasing significantcalculation complexity with the increasing code length. A convolutional encoding structure was presented through synthesizing the characteristics of both LDPC and convolutional codes, with which to construct sparse convolutional code and achieve higher decoding performance. Analysis verifies that the presented structure can achieve lower bit error rate under error rate of 10^-4 comparing with traditional convolutional code. Moreover, the simulations based on LTE-A software multi-antenna MIMO platform can realize long constraints and parallel coding, which has advantages of less complexity and small decoding delay.