Sparse estimation method of channel parameters in time-varying large-scale MIMO network

A channel parameter, large-scale technology, applied in the direction of shaping network, digital transmission system, radio transmission system, etc. in the transmitter/receiver, which can solve the problem when the MIMO network cannot be applied, the time division duplex mode is not applicable, and the network is not considered. Transgender issues

Active Publication Date: 2018-12-07
XIDIAN UNIV
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Problems solved by technology

This method can effectively reduce the overhead of channel estimation, making the time of channel estimation much shorter than the coherence time of the channel. However, this method still has the disadvantage that it is not suitable for time division duplex mode.
However, the disadvantage of this method is that the time-varying nature of the network is not considered when the physical channel matrix is ​​sparsely represented, and it cannot be applied to time-varying massive MIMO networks.

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  • Sparse estimation method of channel parameters in time-varying large-scale MIMO network
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  • Sparse estimation method of channel parameters in time-varying large-scale MIMO network

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[0045] The present invention will be further described below in conjunction with the accompanying drawings.

[0046] Refer to attached figure 1 , to further describe the specific steps of the present invention.

[0047] Step 1, construct the virtual channel sparse signal model of the signal received by the base station as follows.

[0048]

[0049] Among them, Y m Indicates the virtual channel sparse signal received by the base station in the mth time slot, τ indicates the total number of users in the cellular network cell currently communicating with the base station, Σ indicates the summation operation, and k indicates the cellular network cell users currently communicating with the base station serial number, F G Represents the normalized Fourier matrix of G×G size, G represents the number of antennas of the base station, H represents the conjugate transpose operation, diag(c k ) indicates that the diagonal element is the channel sparse parameter c of the user in the...

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Abstract

The invention discloses a sparse estimation method of channel parameters in a time-varying large-scale MIMO network. The method comprises the following steps: constructing a virtual channel sparse signal model of a base station received signal; selecting a time slot with the minimum time slot sequence number from unselected time slots; calculating a virtual channel variance value by using a Kalmanfilter; calculating a virtual channel value; calculating a virtual channel autocorrelation posteriori statistical probability of each cellular network cell user in each time slot; calculating a virtual channel mutual correlation posteriori statistical probability of each cellular network cell user in each adjacent time slot; jointly estimating a virtual channel transfer state value and a virtualchannel transfer state noise variance value of each cellular network cell user; and estimating a channel sparsity parameter of each cellular network cell user by using a low complexity search algorithm. The sparse estimation method disclosed by the invention has the advantage of being applicable to the time-varying large-scale MIMO network.

Description

technical field [0001] The invention belongs to the technical field of communication, and further relates to a method for sparsely estimating channel parameters in a time-varying large-scale multiple-input multiple-output MIMO (Multiple-Input Multiple-Output) network in the technical field of wireless communication. The invention can be used for estimating virtual channel transition state value, virtual channel transition state noise variance value and channel sparsity parameter in wireless communication channel, and the base station uses these parameters to recover the sending signal of cellular network cell users. Background technique [0002] Due to the advantages of high spectrum efficiency, large channel capacity, and strong anti-interference ability, massive MIMO networks have become the core technology to meet the capacity requirements of next-generation cellular networks. Channel state information estimation is a key link in recovering the transmitted signal at the r...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04B7/0413H04L25/02H04L25/03
CPCH04B7/0413H04L25/0222H04L25/0242H04L25/03987
Inventor 张顺张海潮李红艳马建鹏
Owner XIDIAN UNIV
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