Detection method for breadth-first sphere decoding in MIMO (multiple input multiple output) system

Abstract

The invention discloses a detection method for breadth-first sphere decoding in an MIMO (multiple input multiple output) system, which comprises the following steps: a receiving end obtains a channel matrix by channel estimation, and carries out sequencing QL decomposition on the channel matrix to obtain a unitary matrix Q and a lower triangular matrix L; received signals are processed by the unitary matrix Q, and the processed signals are detected layer by layer in a sequence from 1 to NT; in the detection of a layer, firstly, the received signals in the layer are preprocessed by the signalsdetected in the previous layers, and then the process of selecting reserved paths comprises two steps: (1) selecting m1 constellations reserved in the layer according to the processed result of the layer; and (2) combining the m1 constellations reserved in the layer and m2 types of results detected in the previous layers to obtain m1*m2 candidate paths, calculating the Euclidean distances, and sending m2 paths of which the Euclidean distances are the shortest to the next layer for detection; and when the final layer of detection is finished, the path with the shortest Euclidean distance is output to obtain the MIMO detection result. The method ensures the MIMO detection performance, and simultaneously the operation complexity of the sphere decoding method at the receiving end is greatly reduced.

Description

technical field [0001] The invention relates to a multiple-input multiple-output detection method in a wireless communication system, in particular to a low-complexity breadth-first spherical decoding detection method in a MIMO system. Background technique [0002] Multiple-Input Multiple-Output (MIMO) technology is a major breakthrough in the field of wireless mobile communication. With the deepening of research on multi-antenna technology, MIMO systems have been widely used, which can bring many benefits to channel capacity, link reliability and coverage, and the detection method at the receiving end plays an important role in the realization of this advantage. important role. At present, the commonly used detection methods at the receiving end include the Zero-Forcing (ZF) algorithm, the Minimum Mean Square Error (MMSE) algorithm and the Maximum Likelihood (ML) algorithm. Among them, the ZF algorithm and the MMSE algorithm are simple to implement, but the bit error rate...

AI Technical Summary

Problems solved by technology

In this way, when the number of constellation points is relatively large, the computational complexity of the traditional K-best algorithm is still high, which greatly limits its practical application

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