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Grid reduction assisted breadth-first tree search mimo detection method

A breadth-first, detection method technology, applied in baseband system components, diversity/multi-antenna systems, digital transmission systems, etc.

Active Publication Date: 2019-09-27
NANJING UNIV OF INFORMATION SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a lattice reduction assisted breadth-first tree search MIMO detection method with limited maximum complexity and minimum average complexity, which is used to meet the needs of large-scale, high-speed MIMO systems

Method used

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  • Grid reduction assisted breadth-first tree search mimo detection method
  • Grid reduction assisted breadth-first tree search mimo detection method
  • Grid reduction assisted breadth-first tree search mimo detection method

Examples

Experimental program
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Effect test

Embodiment 1

[0156] enter: parameter: k=1,...,2N t ,N c (=2), K m .

[0157] Output: (Send symbol vector Test results).

[0158] 1: The received signal is expressed as: Change the received signal and channel matrix into MMSE form, for convenience, still use the original symbol: namely

[0159] Pair channel matrix Perform lattice reduction to get the reduction base Unitary matrix Using LLL algorithm, δ=0.99.

[0160] 2: The complex number model is transformed into a real number model, expressed as x=As+w, where Represents the set of real numbers), Specific conversion method:

[0161] Re(·) means taking the real part of a complex number, and Im(·) means taking the imaginary part of a complex number.

[0162] The received signal is expressed in a reduced basis: Where d=U -1 s.

[0163] 3: calculation Pseudo-inverse matrix

[0164] Calculation

[0165] Correct Perform QR decomposition and reorder the row vectors in the order of V-BLAST detection: Calculation Note that R is the lower trian...

Embodiment 2

[0210] enter: parameter: ε, k=1,...,2N t ,N c (=2), K m .

[0211] Output: (Send symbol vector Test results).

[0212] 1: The received signal is expressed as: Change the received signal and channel matrix into MMSE form, for convenience, still use the original symbol to indicate: namely

[0213] Calculate the channel matrix Pseudo-inverse matrix

[0214] Pseudo-inverse matrix Perform lattice reduction to get the reduction base Unitary matrix Using the D-LLL algorithm, δ=0.99.

[0215] Calculation

[0216] 2: The complex number model is transformed into a real number model, expressed as x=As+w, where Represents the set of real numbers), Specific conversion method:

[0217] Re(·) means taking the real part of a complex number, and Im(·) means taking the imaginary part of a complex number.

[0218] The received signal is expressed in a reduced basis: Where d=U -1 s.

[0219] 3: calculation

[0220] Correct Perform QR decomposition and reorder the row vectors in the order of V...

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Abstract

The invention discloses a lattice reduction assisted breadth-first tree searching MIMO detecting method. The lattice reduction assisted breadth-first tree searching MIMO detecting method comprises the following steps: changing a receiving complex vector as shown in the specification and a complex communication channel matrix as shown in the specification into minimum mean square error modes; carrying out lattice reduction on the complex communication channel matrix to obtain a reduction basis matrix as shown in the specification, and carrying out QR disintegration on the reduction basis matrix, wherein a V-BLAST sequence is adopted during QR disintegration; after received signals are expressed by the reduction basis matrix and a figure shift vector, carrying out breadth-first tree searching on the received signals, and determining Kk retaining paths of a kth layer; repeating the steps until retaining paths of which the number is as shown in the specification of a k=2Nt layer are obtained; and selecting a symbolic vector of which the measurement is minimum and the element does not exceed a used QAM symbol value range in symbolic vectors as a detection result as shown in the specification, and if all the symbolic vectors exceed the QAM symbol value range, randomly selecting one of the symbolic vectors as a final detection result as shown in the specification. By the method, the maximum complexity is limited, the average complexity is minimum, and requirements of large-scale MIMO systems are met.

Description

Technical field [0001] The present invention relates to a signal detection method of a multiple input multiple output (MIMO) wireless communication system, in particular to a lattice reduction assisted breadth priority tree search MIMO detection method, and belongs to the technical field of wireless communication. Background technique [0002] In a multiple-input multiple-output (MIMO) wireless communication system, the detection of MIMO signals is referred to as MIMO detection. There are two important metrics to measure the pros and cons of MIMO detection methods: 1) Detection performance. Measured by symbol error rate. 2) The computational complexity can be measured by the number of floating-point operations in the detection process. [0003] Although various MIMO detection methods have been researched, it is necessary to find a detection method whose performance is the best or close to the best, and at the same time has very low complexity, and is easy to implement with large-...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04B7/0413H04B7/08H04L1/00H04L25/02H04L25/03
Inventor 刘金铸
Owner NANJING UNIV OF INFORMATION SCI & TECH
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