Lattice reduction assisted breadth-first tree searching MIMO detecting method
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A breadth-first, detection method technology, applied in space transmit diversity, shaping network in transmitter/receiver, transmission system, etc.
Active Publication Date: 2017-01-25
NANJING UNIV OF INFORMATION SCI & TECH
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[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
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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 the sake of convenience, the original symbol is still used: that is
[0159] pair channel matrix Carry out grid reduction to obtain the reduced basis Unimodular matrix Using the 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] s = Re ( s · ) Im ( s ...
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 the sake of convenience, the original symbol is still used: that is
[0213] Calculate channel matrix Pseudo-inverse of
[0214] Pseudo-inverse matrix Carry out grid reduction to obtain the reduced basis Unimodular matrix Using the D-LLL algorithm, δ=0.99.
[0215] calculate
[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] s = Re ( s · ) Im ...
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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 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-first 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, MIMO signal detection is called MIMO detection for short. The pros and cons of MIMO detection methods have two important metrics: 1) detection performance. Measured by symbol error rate. 2) 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 at present, 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 in large-scale integrated circ...
Claims
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