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Compressed Landweber detection method and architecture based on large-scale MIMO

A detection method and large-scale technology, applied in baseband systems, baseband system components, radio transmission systems, etc., can solve the problems of difficult inverse matrix calculation and high complexity

Active Publication Date: 2019-01-22
SOUTHEAST UNIV
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  • Claims
  • Application Information

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Problems solved by technology

In the specific application of 5G mobile communication, detection technology is a necessary step for massive MIMO, but as the number of antennas increases, the dimension of the channel matrix also increases, which makes the minimum mean square error (MMSE) The calculation of the filter matrix and its inverse matrix becomes extremely difficult and the complexity is extremely high
Landweber is suitable for solving large-scale MIMO problems, but after optimization, the optimized Landweber algorithm (improved Landweber detection, ILD) has good performance, but the complexity is very high

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  • Compressed Landweber detection method and architecture based on large-scale MIMO

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Embodiment Construction

[0035] In this embodiment, a massive MIMO channel model is established for simulation operation. In a massive MIMO system, the number of base station antennas is N, the number of user antennas is M, let s=[s 1 ,s 2 ,s 3 ,...,s M ] T Represents a signal vector, s contains transmission symbols generated from M users, all of which are mapped in a 64-QAM manner. H represents a channel matrix whose dimension is N×M, so the received signal vector y of the uplink base station can be expressed as

[0036] y=Hs+n

[0037] The dimension of y is N×1, and n is an additive white noise vector of N×1 dimension. Uplink signal detection is through the receiver receiving vector y=[y 1 ,y 2 ,y 3 ,...,y N ] T Estimate the original transmission signal symbol s. Assuming that H is known, its elements obey the independent and identical distribution with a mean of 0 and a variance of 1, using the minimum mean square error (MMSE) linear detection method, and the estimation of the transmitt...

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Abstract

The invention discloses a compressed Landweber detection method and a structure based on a large-scale MIMO, which comprises the following steps: (1) calculating a matrix R=IM[omega]HHH according to areceiving channel matrix H and a receiving signal vector y, where IM is the identity matrix, [omega] is the relaxation factor, and HH is the conjugate transpose of H; (2) setting initial value s (0)= [omega] HHy and iteration times k=0; (3) calculating according to the formula s (k+1) = s (k) + [omega] R 2ks (k), where s (k) denotes the value of s at the kth iteration and R2k denotes the 2k th power of the matrix; (4) k=k+1, and returning to step (3) for iteration, as that estimate of the transmit signal (img file = 'DDA0001806251210000011. TIF' wi= '58' he= '51' / ), s (k+1) at the end of thepreset iteration is reached and the complexity of the present invention is low.

Description

technical field [0001] The invention relates to the field of communication technologies, in particular to a massive MIMO-based compressed Landweber detection method and architecture. Background technique [0002] Large-scale Multiple-Input Multiple-Output (Massive MIMO), as a key technology for next-generation (5G) mobile communications, can provide better spectral efficiency and avoid interference better than traditional MIMO. In the specific application of 5G mobile communication, detection technology is a necessary step for massive MIMO, but as the number of antennas increases, the dimension of the channel matrix also increases, which makes the minimum mean square error (MMSE) The calculation of the filter matrix and its inverse matrix becomes extremely difficult and the complexity is extremely high. Landweber is suitable for solving massive MIMO problems, but after optimization, the optimized Landweber algorithm (improved Landweber detection, ILD) has good performance, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04B7/0413H04L25/02
CPCH04B7/0413H04L25/024H04L25/0242
Inventor 张川杨宇峰尤肖虎
Owner SOUTHEAST UNIV
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