Sphere decoding detection method and device

Abstract

The invention discloses a sphere decoding detection method and device. The method comprises the steps that a received signal is preprocessed, and a signal approximation estimation value Xpre of the received signal is acquired; according to the Xpre, the initial square radius D2 of sphere decoding detection is derived; according to the current signal to noise ratio of the received signal, the constellation space size l is determined; according to depth first and sphere constraint rules, and according to the constellation space size l and the initial square radius D2, a searching path is searched; nodes passed by the searching path are located in a sphere whose radius is the initial square radius; after the searching path is searched, and when the sum of the local euclidean distances of the searched searching path is less than the current square radius, the square radius is updated; in a multidimensional sphere, the searching path is searched again, wherein the received signal is the sphere center, and the updated square radius is the radius; and until the searching path cannot be searched, a candidate signal point corresponding to the searching path which is latest saved is determined as the optimal signal estimation point.

Description

technical field [0001] The invention relates to the field of mobile communication, in particular to a sphere decoding detection method and device. Background technique [0002] In recent years, a large number of researchers have conducted extensive and in-depth research on signal detection methods in wireless MIMO communication systems. These signal detection methods include: maximum likelihood detection (Maximum Likelyhood Detection, MLD), zero forcing detection (Zero Forcing, ZF), minimum mean square error (Minimum Mean Square Error, MMSE) detection, semi-definite relaxation detection (Semi-Definite Relaxation, SDR) and Sphere Decoding (Sphere Decoding, SD) detection, etc. [0003] MLD has state-of-the-art performance, but is exponentially complex and almost impossible to implement in hardware. ZF and MMSE detection, although the calculation is simple, have poor bit error performance, and semi-definite relaxation detection, because the conditions are relaxed on the basis...

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Problems solved by technology

[0005] Chinese patent application publication CN200910084580.6 discloses a sphere decoding detection method based on depth-first search. Although the complexity of the algorithm is well controlled, the maximum number of nodes for tree search is limited to M, resulting in signal distortion. There is a certain loss in performance

[0006] Chinese patent application publication CN201010515931.7 discloses a depth-first SD detection algorithm based on QR preprocessing. This method is only suitable for high signal-to-noise ratio areas and MIMO signal detection using low-order modulation. For low signal-to-noise ratio Area's Signal Detection Not Applicable

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