Lattice reduction-based multiple input multiple output (MIMO) detection soft output method

A lattice reduction, soft output technology, applied in the field of MIMO communication systems, can solve problems such as high computational complexity and difficult engineering implementation, and achieve the effect of reducing computational complexity, easy implementation, and high accuracy

Inactive Publication Date: 2010-12-15
BEIJING UNIV OF POSTS & TELECOMM +1
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Problems solved by technology

However, during stack detection, weight calculations are performed on all child nodes, resulting in high computational complexity; in additi

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  • Lattice reduction-based multiple input multiple output (MIMO) detection soft output method
  • Lattice reduction-based multiple input multiple output (MIMO) detection soft output method
  • Lattice reduction-based multiple input multiple output (MIMO) detection soft output method

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[0039] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0040] In order to facilitate the understanding of the innovations of the present application, see image 3 and Figure 4 Two detection processes of the soft output method in the prior art paper and the soft output method of the lattice-based MIMO multi-antenna detection based on the present invention are given respectively. The difference between the two can be clearly seen from these two figures: because the simple and general soft output method in the MIMO detection algorithm based on the lattice-based protocol of the present invention utilizes a sorted list, the complexity of the algorithm can be greatly reduced. In the figure, is the set of surviving vectors, is the set of surviving bits.

[0041] Below, specifically illustrate four oper...

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Abstract

The invention relates to a lattice reduction-based multiple input multiple output (MIMO) detection soft output method. The method comprises the following steps of: firstly, acquiring an ordered list of transform domain signals aiming at different transformation matrixes and storing the ordered list for inquiring during detection; secondly, when executing the lattice reduction-based MIMO detection at each time, applying the lattice reduction to a channel response matrix to obtain a lattice reduction base and the transformation matrixes and acquiring the corresponding ordered list of the transform domain signals by using the transformation matrixes; thirdly, executing QR Decomposition and M algorithm (QRM) detection by using the lattice reduction base and the ordered list of the transform domain signals to acquire survival vectors and the corresponding weight value of each survival vector; and finally, determining the soft information of each bit by using the survival vectors and the weight value of each survival vector. The method has the advantages of effectively reducing the number of nodes which need to calculate the weight values during the QRM detection by using the ordered list stored in advance, greatly reducing the complexity of the calculation, along with no need of model extension and easy implementation; and compared with a method for acquiring the set of the survival vectors through the disturbance of the optimum survival vector, the method has higher accuracy.

Description

technical field [0001] The invention relates to a soft output method for MIMO multi-antenna detection based on a grid-based protocol, and belongs to the technical field of MIMO communication systems. Background technique [0002] First introduce the multi-antenna transmission and multi-antenna reception MIMO (Multiple Input Multiple Output) system model: Assume that the spatial multiplexing MIMO system has N t root transmit antenna and N r root receiving antenna, the wireless channel is diffuse scattering and quasi-static flat fading, the fading experienced by each transmitting antenna and receiving antenna can be regarded as independent of each other, and the receiver can estimate the ideal channel, then the system transmission model can be expressed as It is: y=Hx+n; where, the received signal vector Its dimension is N r ×1; channel response matrix Its dimension is N r ×N t , where the channel gain h between transmitting antenna j and receiving antenna i ij is a c...

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Application Information

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IPC IPC(8): H04L25/06H04L25/03
Inventor 赵慧周小平王文博吴斌周玉梅
Owner BEIJING UNIV OF POSTS & TELECOMM
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