Low-complexity SCMA decoding method and device based on quantum computation

Abstract

The invention discloses a low-complexity SCMA decoding method and a low-complexity SCMA decoding device based on quantum computation. The method comprises the steps of acquiring one or multiple piecesof basic information of a received signal, a codebook and a channel state, and acquiring a factor graph corresponding to a characteristic matrix according to the characteristic matrix; setting a target function according to an information transferring algorithm MPA iteration update rule; and after VN to FN information is computed in a classical field on the factor graph according to the MPA update rule, quantum searching is performed on the target function within a quantum domain to acquire VN to FN information, and the number of iterations meets a preset number of times or reaches a preset condition, computing a posterior probability to acquire a decoded signal. According to the method provided by the invention, the iteration of the MPA algorithm is performed via quantum computation, thequantum information transferring algorithm is provided, the quantum decoder of the SCMA is designed, and thus the practicability of SCMA decoding is effectively improved, and the decoding performanceis prevented from being affected while the decoding complexity is reduced.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to a low-complexity SCMA decoding method and device based on quantum computing. Background technique [0002] The main methods of SCMA (Sparse Code Multiple Access, sparse code multiple access) decoding are MAP (Maximum A Posterior Probability, maximum a posteriori probability) and MPA (Message Passing Algorithm, information transfer algorithm) and other based on MPA algorithm. improve algorithm. Including: SCMA decoding based on Maximum Posteriori Probability (MAP), SCMA decoding based on Information Passing Algorithm (MPA), and improved algorithm with low computational complexity based on MPA. [0003] At present, the decoding has the following problems: (1) the decoding complexity is too high to be practical; (2) the complexity is greatly reduced on the basis of MAP decoding, but the decoding complexity is still exponential, and the complexity is still very high; (3) ) T...

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Problems solved by technology

[0003] At present, the decoding has the following problems: (1) the decoding complexity is too high to be practical; (2) the complexity is greatly reduced on the basis of MAP decoding, but the decoding complexity is still exponential, and the complexity is still very high; (3) ) The improved algorithm based on MPA will reduce the complexity and affect the decoding performance

[0004] In related technologies, solutions such as Sphere decoding and further improvement of complexity and decoding performance on the basis of MPA decoding are often used to solve the above problems. However, it is still necessary to sacrifice performance such as decoding accuracy in exchange for reduced complexity. In the case of low performance loss, The complexity reduction effect of the current method is not good enough

In related technologies, optimal decoding and complexity reduction cannot be considered at the same time, which needs to be solved

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