SCMA decoding method based on message passing algorithm

Abstract

The invention discloses an SCMA decoding method based on a message passing algorithm. The method comprises the following steps: 1) inputting signals, and with a codebook storage unit being combined, initializing conditional probability; 2) after initialization, carrying out iterative update on posterior probability in an iterative detection receiver, wherein the iterative detection receiver comprises a user node decoder and a resource node decoder, the resource node decoder being connected with the user node decoder, and the posterior probability is subjected to joint iterative update between the user node decoder and the resource node decoder; and 3) after many times of iteration, serving information output by the user node decoder as low-density parity-check code decoding input and finishing decoding. The method not only improves convergence speed and bit error rate, but also reduces algorithm complexity.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to an SCMA decoding method based on a message passing algorithm. Background technique [0002] In mobile communication systems, Sparse Code Multiple Access (SCMA) is a multiple access technology, that is, how a base station serves and distinguishes multiple users at the same time. Multiple access technology is a necessary means to satisfy multiple users to communicate at the same time. The emergence of each generation of mobile communication systems is accompanied by the innovation of multiple access technology. The performance of the sparse code multiple access system mainly depends on the SCMA codebook design and decoder design, so a good decoder is very important. Maximum Joint Posteriori Probability (MAP) detection is the optimal multi-user joint detection, but due to the huge storage capacity and high complexity, it cannot be used in practice. Due to the struct...

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Problems solved by technology

Maximum Joint Posteriori Probability (MAP) detection is the optimal multi-user joint detection, but due to the huge storage capacity and high complexity, it cannot be used in practice. Due to the structure of low-density spread spectrum in SCMA, approximate Low-complexity message-passing algorithm based on maximum likelihood ratio (ML) detection performance. The basic principle of message-passing algorithm is to decompose a computationally difficult problem into many easy-to-calculate sub-problems. The algorithm is more complicated, and the convergence performance is not optimal. Well, the current message passing algorithm can no longer meet the actual needs. It is necessary to provide an algorithm that can not only improve the convergence speed of messages, but also reduce the complexity of the algorithm.

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