CN105680965A - Obtaining method and apparatus for simultaneous information and power transfer type transceiver model - Google Patents

Abstract

The invention provides an obtaining method and apparatus for a simultaneous information and power transfer (SWIPT) type transceiver model. The method comprises: according to a minimum mean square error and a channel capacity of an information decoding module receiving signal of a user node, an objective function of a SWIPT type transceiver model is obtained; a transmitting power of a base station is obtained based on a transmitting signal of the base station; according to a signal sent by the base station to an energy receiving module, a receiving signal of the user node is obtained; and on the basis of the objective function, the transmitting power of the base station, and the receiving signal of the user node, a first system model of the SWIPT type transceiver is obtained. According to the provided method and apparatus, the base station and user transceiver model of the SWIPT system are obtained and optimized, thereby improving the communication quality of the SWIPT system.

Description

Method and device for obtaining wireless energy-carrying communication transceiver model

Technical Field

The invention relates to the technical field of communication, in particular to a method and a device for obtaining a wireless energy-carrying communication transceiver model.

Background

With the rapid development of wireless communication technology, the consumption of energy by devices in a wireless communication network is increasing, and because wireless energy-carrying communication (SWIPT for short) simultaneously transmits information and energy by using the same wireless carrier, nodes such as a base station and the like not only transmit information for nodes in a coverage range, but also perform microwave energy charging for user nodes under limited energy, the dependence of a mobile terminal on battery capacity can be reduced, efficient and reliable communication is realized, and thus the wireless energy-carrying communication is widely applied.

At present, a scenario of a main research of wireless energy-carrying communication is in a communication system, especially applied to a Multiple-input Multiple-Output (MIMO) system in a multi-cell, where in the current MIMO system, system channel information is mainly obtained according to a point-to-point information transmission process between user nodes, a model of a receiver and a transmitter (hereinafter, collectively referred to as a transceiver) is established according to the system channel information, and a transceiver matched with the system channel information is designed according to the model.

However, the energy is added to the receiving segment and the transmitting segment of the wireless energy-carrying communication by the transceiver, and the system channel information obtained in the current MIMO system only considers the information transmission process between user nodes and does not consider the energy transmission, so that a certain error exists between the system channel information obtained by the transceiver and the real channel information, and the communication quality of the system is reduced.

Disclosure of Invention

The invention provides a method and a device for obtaining a wireless energy-carrying communication transceiver model, which improve the communication quality of a wireless energy-carrying communication system.

The invention provides a method for obtaining a wireless energy-carrying communication transceiver model, which comprises the following steps:

obtaining an objective function of a wireless energy-carrying communication transceiver model according to the minimum mean square error and the channel capacity of a signal received by an information decoding module of a user node;

acquiring the transmitting power of a base station according to a transmitting signal of the base station;

acquiring a receiving signal of a user node according to a signal sent to an energy receiving module by the base station;

and obtaining a first system model of the wireless energy-carrying communication transceiver according to the objective function, the transmitting power of the base station and the receiving signal of the user node.

A second aspect of the present invention provides a wireless energy-carrying communication transceiver model obtaining apparatus, including:

the target function acquisition module is used for acquiring a target function of a wireless energy-carrying communication transceiver model according to the minimum mean square error and the channel capacity of the signal received by the information decoding module of the user node;

the transmission power acquisition module is used for acquiring the transmission power of the base station according to the transmission signal of the base station;

a received signal obtaining module, configured to obtain a received signal of a user node according to a signal sent by the base station to the energy receiving module;

and the first system model obtaining module is used for obtaining a first system model of the wireless energy carrying communication transceiver according to the objective function, the transmitting power of the base station and the receiving signal of the user node.

Wherein an objective function of the wireless energy-carrying communication transceiver model is as follows:

$\underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}{\mathrm{\α}}_{i_k}\left(Tr\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right);$

the first system model of the wireless energy-carrying communication transceiver is as follows:

$\begin{array}{cc}& \underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}{\mathrm{\α}}_{i_k}\left(Tr\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right)\\ s.t& Tr\[{\mathrm{Fr}}_k(\underset{i}{\overset{I_k}{\Σ}}{G}_{i_{k}k}{f}_{i_k}{f}_{i_k}^H{G}_{i_{k}k}^H+{\mathrm{\σ}}^{2}I){\mathrm{Fr}}_k^H\]\≤P_k\\ & Tr\left(D_{i_{k}k}{\mathrm{Fr}}_k\right(\underset{l}{\overset{I_k}{\Σ}}{G}_{l_{k}k}{f}_{l_k}{f}_{l_k}^H{G}_{l_{k}k}^H+{\mathrm{\σ}}^{2}I){\mathrm{Fr}}_k^H{D}_{i_{k}k}^H)\≥P_c\end{array}$

wherein,representing user sectionsPoint i_kThe signal decoding matrix of (a) is,representing user node i_kWeight coefficient of mean square error MSE, Fr_kA beamforming matrix representing a base station,the representation matrix Fr_kThe transpose of (a) is performed,representing user node i_kThe proportion of the capacity of the system channel is, representing user node i_kIs received, Tr denotes the rank of the matrix, det denotes the determinant, K denotes the base station of each cell, K is 1,2_kDenotes the ith user node, i, in base station k_k＝1,2,...,I_k，I_kRepresenting the number of user nodes comprised by the cell covered by the base station, s.t representing the constraints of said objective function,/_kDenotes the l user node, P, in base station k_kRepresenting the base station transmission power, P_cWhich represents the charging threshold of the EH,indicating the channel of the ID to the base station,representation matrixThe transpose of (a) is performed,a channel representing a base station to an ID,representation matrixThe transpose of (a) is performed,the beam-forming of the representation ID,representation matrixIs transposed, σ denotes the channelI denotes an identity matrix.

The method and the device for obtaining the wireless energy-carrying communication transceiver model provided by the embodiment of the invention provide a channel model of a multi-cell multi-input multi-output wireless energy-carrying communication system, combine the maximum channel capacity and the minimum mean square error in the wireless energy-carrying communication system, obtain and optimize a base station and a user transceiver model of the wireless energy-carrying communication system, and improve the communication quality of the wireless energy-carrying communication system.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.

Fig. 1 is a schematic structural diagram of a multi-cell mimo wireless energy-carrying communication system according to an embodiment of the present invention;

fig. 2 is a flowchart of a method for acquiring a model of a wireless energy-carrying communication transceiver according to an embodiment of the present invention;

fig. 3 is a schematic diagram of a simulation result of the minimum MSE of the system according to the embodiment of the present invention;

fig. 4 is a diagram illustrating simulation results of maximum channel capacity according to an embodiment of the present invention;

FIG. 5 is a partially enlarged schematic view of the simulation result of FIG. 4;

fig. 6 is a schematic structural diagram of a wireless energy-carrying communication transceiver model obtaining apparatus according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

A communication system generally comprises a base station, a relay, a user node, and the like, and to implement point-to-point communication between user nodes, the user node needs to first uplink a signal to the relay or the base station, and then downlink the signal to a receiver at an opposite end by the relay or the base station, a link for uplink of the user node to the relay or the base station may be referred to as an uplink, where the uplink is referred to as a downlinkThe link that relays or base stations down to the receiver may be referred to as the downlink. Fig. 1 is a schematic structural diagram of a multi-cell mimo wireless energy-carrying communication system according to an embodiment of the present invention. As shown in fig. 1, when the first node communicates with the second node, it needs to be implemented through the base station of the first cell. In the embodiment of the present invention, it is assumed that the number of cells is K, each cell has one and only one base station, and K (K is 1,2, …, K) is used instead, where each base station includes M antennas, and the covered cell includes I_kEach user node comprises an energy receiving module (EH) and an information decoding module (ID), and the user node of the kth cell is made to be i_k(i_k＝1,2,...,I_k) The EH and ID of each user node respectively comprise N_EHAnd N_IDA root antenna.

Fig. 2 is a flowchart of a method for acquiring a model of a wireless energy-carrying communication transceiver according to an embodiment of the present invention. As shown in fig. 2, a method provided in an embodiment of the present invention includes:

s201: and obtaining an objective function of the wireless energy-carrying communication transceiver model according to the minimum mean square error and the channel capacity of the signal received by the information decoding module of the user node.

The wireless energy-carrying communication transceiver model comprises an objective function:

$\underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}{\mathrm{\α}}_{i_k}\left(Tr\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right).$

in particular, according to the proportion of user nodes in the systemAnd channel capacity of user nodeThe total system capacity of the system can be determined asWherein,s represents the received signal power of the user nodeN represents the received noise power of the user node $N=\underset{j\≠k}{\mathrm{\Σ}}\underset{l}{\mathrm{\Σ}}{H}_{i_{k}j}{\mathrm{Fr}}_j{G}_{l_{j}j}{f}_{l_j}{f_{l_j}}^H{G_{l_{j}j}}^H{{\mathrm{Fr}}_j}^H{H_{i_{k}j}}^H+{\mathrm{\σ}}^2\underset{j}{\overset{K}{\mathrm{\Σ}}}{H}_{i_{k}j}{\mathrm{Fr}}_j{{\mathrm{Fr}}_j}^H{H_{i_{k}j}}^H+{{\mathrm{\σ}}_2}^{2}I.$

Will total system capacityJoining user node i_kWeighted coefficient of Mean Square Error (MSE)Then the total system capacityMay be equivalent to the following expression:

$\underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}{\mathrm{\α}}_{i_k}\left(Tr\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right)$

wherein,is a positively determined weight matrix, anAndandis irrelevant.

It should be noted that, in the embodiment of the present invention, the minimum mean square error of the signal received by the information decoding module of the user node may be referred to as a system minimum mean square error.

S202: and obtaining the transmitting power of the base station according to the transmitting signal of the base station.

Wherein, the transmitting power of the base station is: $\mathrm{Tr}\left[{\mathrm{Fr}}_k\right(\underset{i}{\overset{I_k}{\mathrm{\Σ}}}{G}_{i_{k}k}{f}_{i_k}{f}_{i_k}^H{G}_{i_{k}k}^H+{\mathrm{\σ}}^{2}I\left){\mathrm{Fr}}_k^H\right].$

specifically, the signals transmitted by the base station are:

${\mathrm{Fr}}_k(\underset{l}{\overset{I_k}{\Σ}}{G}_{i_{k}k}{f}_{i_k}{s}_{i_k}+n_{i_k})$

the transmission power of the base station obtained from the signal transmitted by the base station is:

$Tr\[{\mathrm{Fr}}_k(\underset{i}{\overset{I_k}{\Σ}}{G}_{i_{k}k}{f}_k{f}_{i_k}^H{G}_{i_{k}k}^H+{\mathrm{\σ}}^{2}I){\mathrm{Fr}}_k^H\]$

wherein,for the superposition of channel noise for all uplinks in the same cell,

s203: and obtaining a receiving signal of the user node according to the signal sent to the energy receiving module by the base station.

Wherein, the received signal of the user node is: $\mathrm{Tr}\left(D_{i_{k}k}{\mathrm{Fr}}_k\right(\underset{l}{\overset{I_k}{\mathrm{\Σ}}}{G}_{l_{k}k}{f}_{l_k}{f}_{l_k}^H{G}_{l_{k}k}^H+{\mathrm{\σ}}^{2}I\left){\mathrm{Fr}}_k^H{D}_{i_{k}k}^H\right).$

specifically, the downlink signal from the base station to the EH is:

$D_{i_{k}k}{\mathrm{Fr}}_k(\underset{1}{\overset{I_k}{\Σ}}{G}_{l_{k}k}{f}_{l_k}{s}_{l_k}+n_{i_k})$

regardless of the additive white noise of the downlink and the interference from other relays, the received signal of a single user node can be derived from the signal downlink from the base station to the EH as follows:

$Tr\left(D_{i_{k}k}{\mathrm{Fr}}_k\right(\underset{l}{\overset{I_k}{\Σ}}{G}_{l_{k}k}{f}_{l_k}{f}_{l_k}^H{G}_{l_{k}k}^H+{\mathrm{\σ}}^{2}I){\mathrm{Fr}}_k^H{D}_{i_{k}k}^H)$

s204: a first system model of the wireless energy-carrying communication transceiver is obtained based on the objective function, the transmit power of the base station, and the received signal of the user node.

The first system model of the wireless energy-carrying communication transceiver is as follows:

$\begin{array}{cc}& \underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}{\mathrm{\α}}_{i_k}\left(Tr\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right)\\ s.t& Tr\[{\mathrm{Fr}}_k(\underset{i}{\overset{I_k}{\Σ}}{G}_{i_{k}k}{f}_{i_k}{f}_{i_k}^H{G}_{i_{k}k}^H+{\mathrm{\σ}}^{2}I){\mathrm{Fr}}_k^H\]\≤P_k\\ & Tr\left(D_{i_{k}k}{\mathrm{Fr}}_k\right(\underset{l}{\overset{I_k}{\Σ}}{G}_{l_{k}k}{f}_{l_k}{f}_{l_k}^H{G}_{l_{k}k}^H+{\mathrm{\σ}}^{2}I){\mathrm{Fr}}_k^H{D}_{i_{k}k}^H)\≥P_c\end{array}$

wherein,representing user node i_kThe signal decoding matrix of (a) is,representing user node i_kWeight coefficient of mean square error MSE, Fr_kA beamforming matrix representing a base station,the representation matrix Fr_kThe transpose of (a) is performed,representing user node i_kThe proportion of the capacity of the system channel is, representing user node i_kIs received, Tr denotes the rank of the matrix, det denotes the determinant, K denotes the base station of each cell, K is 1,2_kDenotes the ith user node, i, in base station k_k＝1,2,...,I_k，I_kRepresenting the number of user nodes comprised by the cell covered by the base station, s.t representing the constraints of the objective function,/_kDenotes the l user node, P, in base station k_kRepresenting the base station transmission power, P_cWhich represents the charging threshold of the EH,indicating the channel of the ID to the base station,representation matrixThe transpose of (a) is performed,a channel representing a base station to an ID,representation matrixThe transpose of (a) is performed,the beam-forming of the representation ID,representation matrixIs transposed, σ denotes the channelI denotes an identity matrix.

In addition, i is_kDenotes the ith user node, l, in base station k_kIndicating the l-th user node in a base station k, the invention indicates a communication user node in a base station in the form of letter combinations, e.g. i_kThe subscript k denotes the base station k, and i denotes the ith user node in this base station, i.e. the ith user node in the coverage of the base station k.

The method for obtaining the wireless energy-carrying communication transceiver model provided by the embodiment of the invention obtains an objective function of the wireless energy-carrying communication transceiver model through the minimum mean square error of a system and the system capacity, obtains the transmitting power of a base station according to the transmitting signal of the base station, obtains the receiving signal of a user node according to the signal of the base station downlink to an energy receiving module, obtains a first system model of the wireless energy-carrying communication transceiver according to the objective function, the transmitting power of the base station and the receiving signal of the user node, provides a channel model of a multi-cell multi-input multi-output (MIMO) wireless energy-carrying communication system, combines the maximum channel capacity and the minimum mean square error in the wireless energy-carrying communication system, obtains and optimizes the base station and the user transceiver model of the wireless energy-carrying communication system, and improves the communication quality of the wireless energy-carrying communication system.

Further, on the basis of the embodiment shown in fig. 2, the method provided in the embodiment of the present invention further includes, before S201:

according to user nodeTo user node i_kTransmitted signalUsing a formulaAcquiring signals received by a base station

Wherein the user nodeAnd user node i_kFor different user nodes in the same cell,is a place in the same cellThere is a superposition of the channel noise of the uplink,

specifically, it is assumed that channels of EH and ID from the base station to any node are known and information transmitted from the base station is of a single stream. Then the transmit beamforming of the base station may be represented as a vectork＝1,2,...,K，i_k＝1,2,...,I_kLet us orderFor base station k to want to send to user node i_kWherein the different signals are independent and orthogonal to each other and are also orthogonal to the noise signal, that is:

$E\[s_{i_k}{s_{l_j}}^H\]=0,\∀(i,k)\≠(l,j)$

$E\[s_{i_k}{n_{l_j}}^H\]=0,\∀i_k,l_j,$ and is(Single flow)

Consider a user node in cell kTo another user node i_kTransmitting a single stream signalThe signal is transmitted to node i via base station k_kWherein the signal received by the base station k is:

obtaining user node i_kReceived signal

Wherein, ${\tilde{x}}_{i_k}=H_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}{s}_{{\tilde{i}}_k}+H_{i_{k}k}{\mathrm{Fr}}_k{n}_{{\tilde{i}}_k}+\underset{j\≠k}{\overset{K}{\Σ}}{H}_{i_{k}j}{\mathrm{Fr}}_j(\underset{l}{\overset{I_j}{\Σ}}{G}_{l_{j}j}{f}_{l_j}{s}_{l_j}+n_{l_j})+n_{io},$ representing the signal from the l-th user node in base station j,representing the signal from the l-th user node in base station j,indicating all the user nodes i_kTotal downlink noise.

Note that, base station j ≠ K denotes the number of cells covered by the base station 1, 2.

Specifically, the same user node sent by the user node of other cells can be ignored in the embodiment of the present inventionA signal, then goes down from base station k to i_kThe signal of (d) may be expressed as:

$y_{i_k}=H_{i_{k}k}{\mathrm{Fr}}_k(\underset{l}{\overset{I_k}{\Σ}}{G}_{i_{k}k}{f}_{i_k}{s}_{i_k}+n_{i_k})$

whereinIs the superposition of channel noise of all uplinks in the same cell, still white Gaussian noise, and Fr_kRepresenting the transmitter beamforming matrix for base station k.

Adding signals from other base stations and noise of downlink channels to eliminate self-interference, and then adding the noise to the signals_kWhere the received signal is ${\tilde{x}}_{i_k}=H_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}{s}_{{\tilde{i}}_k}+H_{i_{k}k}{\mathrm{Fr}}_k{n}_{{\tilde{i}}_k}+\underset{j\≠k}{\overset{K}{\Σ}}{H}_{i_{k}k}{\mathrm{Fr}}_j(\underset{l}{\overset{I_j}{\Σ}}{G}_{l_{j}j}{f}_{l_j}{s}_{l_j}+n_{l_j})+n_{io}.$

According toUsing a formulaObtaining a decoded signal

According toAndusing a formulaAnd acquiring the minimum mean square error of the system.

In particular, the decoded matrixThereafter, a decoded signal can be obtained:

${\tilde{s}}_{i_k}=g_{i_k}{H}_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}{s}_{{\tilde{i}}_k}+g_{i_k}{H}_{i_{k}k}{\mathrm{Fr}}_k{n}_{{\tilde{i}}_k}+g_{i_k}\underset{j\≠k}{\overset{K}{\Σ}}{H}_{i_{k}j}{\mathrm{Fr}}_j(\underset{l}{\overset{I_j}{\Σ}}{G}_{l_{j}j}{f}_{l_j}{s}_{l_j}+n_{l_j})+g_{i_k}{n}_{io}.$

then, a calculation formula of a system minimum mean-square-error (MSE) can be obtained:

$\begin{array}{c}{E}_{i_k}=({\tilde{s}}_{i_k}-s_{{\tilde{i}}_k}){({\tilde{s}}_{i_k}-s_{{\tilde{i}}_k})}^H\\ =g_{i_k}{H}_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{g_{i_k}}^H-g_{i_k}{H}_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}\\ -{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{g_{i_k}}^H+{\mathrm{\σ}}^2{g}_{i_k}{H}_{i_{k}k}{\mathrm{Fr}}_k{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{g_{i_k}}^H\\ +g_{i_k}\left(\underset{j\≠k}{\Σ}\underset{l}{\Σ}{H}_{i_{k}j}{\mathrm{Fr}}_j{G}_{l_{j}j}{f}_{l_j}{f_{l_j}}^H{G_{l_{j}j}}^H{{\mathrm{Fr}}_j}^H{H_{i_{k}j}}^H\right){g_{i_k}}^H\\ +{\mathrm{\σ}}^2{g}_{i_k}\left(\underset{j\≠k}{\overset{K}{\Σ}}{H}_{i_{k}j}{\mathrm{Fr}}_j{{\mathrm{Fr}}_j}^H{H_{i_{k}j}}^H\right){g_{i_k}}^H+{{\mathrm{\σ}}_2}^2{g}_{i_k}{g_{i_k}}^H+I\end{array}$

where σ and σ₂Respectively representing the standard deviation of additive noise for the ID to base station channel (uplink channel) and the base station to ID channel (downlink channel).

Further, on the basis of the embodiment shown in FIG. 2, according toAndusing a formulaAcquiring the minimum mean square error of the system comprises the following steps:

will be a formulaTo pairDerivation by formulaGet user node i_kSignal decoding matrix of ${g_{i_k}}^{MMSE}={f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}K}}^H{Z}^{-1};$

Wherein, $\begin{array}{c}Z=\underset{j\≠k}{\Σ}\underset{l}{\Σ}{H}_{i_{k}j}{\mathrm{Fr}}_j{G}_{l_{j}j}{f}_{l_j}{f_{l_j}}^H{G_{l_{j}j}}^H{{\mathrm{Fr}}_j}^H{H_{i_{k}j}}^H+{\mathrm{\σ}}^2\underset{j}{\overset{K}{\Σ}}{H}_{i_{k}j}{\mathrm{Fr}}_j{{\mathrm{Fr}}_j}^H{H_{i_{k}j}}^H\\ +{{\mathrm{\σ}}_2}^{2}I+H_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H\end{array}$

will be provided withSubstitution formulaIn the method, the minimum mean square error of the system is obtained

In particular, the fixed base station transmits a beamforming Fr_kLet us orderIt is possible to obtain:

${g_{i_k}}^{MMSE}={f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{Z}^{-1}$

i.e. the minimum MSE receiver of the ID. Wherein

$\begin{array}{c}Z=\underset{j\≠k}{\Σ}\underset{l}{\Σ}{H}_{i_{k}j}{\mathrm{Fr}}_j{G}_{l_{j}j}{f}_{l_j}{f_{l_j}}^H{G_{l_{j}j}}^H{{\mathrm{Fr}}_j}^H{H_{i_{k}j}}^H+{\mathrm{\σ}}^2\underset{j}{\overset{K}{\Σ}}{H}_{i_{k}j}{\mathrm{Fr}}_j{{\mathrm{Fr}}_j}^H{H_{i_{k}j}}^H\\ +{{\mathrm{\σ}}_2}^{2}I+H_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H\end{array}$

HandleSubstituted back toIt is possible to obtain:

$E_{i_k}=I-{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{Z}^{-1}{H}_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}$

further, in the embodiment shown in fig. 2, the method provided in the embodiment of the present invention further includes:

using a formulaObtaining user node i_kWeighted coefficient of mean square error of

Specifically, as can be seen from the above-described embodiments, $E_{i_k}=I-{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{Z}^{-1}{H}_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}.$

will be provided withAndsubstituting into the first system model, and substituting intoAndcarrying out kronecker decomposition on the later first system model, and changing the first system model into a second system model:

$\begin{array}{cc}& \underset{{\mathrm{fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}Tr\left({{\mathrm{fr}}_k}^H\right(Q_a+Q_b+Q_c){\mathrm{fr}}_k-q_a{\mathrm{fr}}_k-{{\mathrm{fr}}_k}^H{q}_b)\\ s.t.& Tr\left({\mathrm{fr}}_k^H\right((\underset{i}{\overset{I_k}{\Σ}}{G}_{i_{k}k}{f}_{i_k}{f}_{i_k}^H{G}_{i_{k}k}^H+{\mathrm{\σ}}^{2}I)\⊗I\left){\mathrm{fr}}_k\right)\≤P_k\\ & Tr\left({\mathrm{fr}}_k^H\right((\underset{l}{\overset{I_k}{\Σ}}{G}_{l_{k}k}{f}_{l_k}{f_{l_k}}^H{G_{l_{k}k}}^H+{\mathrm{\σ}}^{2}I)\⊗{D_{i_{k}k}}^H{D}_{i_{k}k}\left){\mathrm{fr}}_k\right)\≥P_c\end{array}$

wherein fr_k＝vec(Fr_k)， $Q_a={\mathrm{\α}}_{i_k}{G}_{{\stackrel{\‾}{i}}_{k}k}{f}_{{\stackrel{\‾}{i}}_k}{f_{{\stackrel{\‾}{i}}_k}}^H{G_{{\stackrel{\‾}{i}}_{k}k}}^H\⊗{H_{i_{k}k}}^H{g_{i_k}}^H{W}_{i_k}{g}_{i_k}{H}_{i_{k}k},$

$Q_b=\underset{j\≠k}{\Σ}\underset{l}{\Σ}{\mathrm{\α}}_{l_j}(G_{i_{k}k}{f}_{i_k}{f_{i_k}}^H{G_{i_{k}k}}^H\⊗{H_{l_{j}k}}^H{g_{l_j}}^H{W}_{l_j}{g}_{l_j}{H}_{l_{j}k}),Q_c=\underset{j}{\Σ}{\mathrm{\α}}_{i_j}{\mathrm{\σ}}^2(I\⊗{H_{i_{j}k}}^H{g_{i_j}}^H{W}_{i_j}{g}_{i_j}{H}_{i_{j}k}),$ $q_a={\mathrm{\α}}_{i_k}vec{\left({H_{i_{k}k}}^H{g_{i_k}}^H{W_{i_k}}^H{f_{{\stackrel{\‾}{i}}_k}}^H{G_{{\stackrel{\‾}{i}}_{k}k}}^H\right)}^H,q_b={\mathrm{\α}}_{i_k}vec\left({H_{i_{k}k}}^H{g_{i_k}}^H{W}_{i_k}{f_{{\stackrel{\‾}{i}}_k}}^H{G_{{\stackrel{\‾}{i}}_{k}k}}^H\right),$ vec denotes vectorizing the matrix.

Specifically, in the embodiment of the present invention, an iterative algorithm is adopted to decompose the objective function of the first system model into three, and the three objective functions are solved respectively.

Will find aboveAndsubstituting into the first system model, the first system model may be changed to:

$\begin{array}{cc}& \underset{{\mathrm{Fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}{\mathrm{\α}}_{i_k}\left(Tr\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right)\\ s.t& Tr\[{\mathrm{Fr}}_k(\underset{i}{\overset{I_k}{\Σ}}{G}_{i_{k}k}{f}_{i_k}{f}_{i_k}^H{G}_{i_{k}k}^H+{\mathrm{\σ}}^{2}I){\mathrm{Fr}}_k^H\]\≤P_k\\ & Tr\left(D_{i_{k}k}{\mathrm{Fr}}_k\right(\underset{l}{\overset{I_k}{\Σ}}{G}_{l_{k}k}{f}_{l_k}{f}_{l_k}^H{G}_{l_{k}k}^H+{\mathrm{\σ}}^{2}I){\mathrm{Fr}}_k^H{D}_{i_{k}k}^H)\≥P_c\end{array}$

will be provided withSubstituted into the above objective function and the variable Fr is removed_kGet:

$\begin{array}{c}\underset{{\mathrm{Fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}{\mathrm{\α}}_{i_k}\left(Tr\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right)=\\ \underset{{\mathrm{Fr}}_k}{min}\[\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}Tr({\mathrm{\α}}_{i_k}{W}_{i_k}{g}_{i_k}{H}_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\stackrel{\‾}{i}}_{k}k}{f}_{{\stackrel{\‾}{i}}_k}{f_{{\stackrel{\‾}{i}}_k}}^H{G_{{\stackrel{\‾}{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{g_{i_k}}^H-\\ {\mathrm{\α}}_{i_k}{W}_{i_k}{g}_{i_k}{H}_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\stackrel{\‾}{i}}_{k}k}{f}_{{\stackrel{\‾}{i}}_k}-{\mathrm{\α}}_{i_k}{W}_{i_k}{f_{{\stackrel{\‾}{i}}_k}}^H{f_{{\stackrel{\‾}{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{g_{i_k}}^H+\\ \underset{j\≠k}{\Σ}\underset{l}{\Σ}{\mathrm{\α}}_{l_j}{W}_{l_j}{g}_{l_j}{H}_{l_{j}k}{\mathrm{Fr}}_k{G}_{i_{k}k}{f}_{i_k}{f_{i_k}}^H{G_{i_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{l_{j}k}}^H{g_{l_j}}^H)+\\ \underset{j}{\Σ}{\mathrm{\α}}_{i_j}{\mathrm{\σ}}^2{W}_{i_j}{g}_{i_j}{H}_{i_{j}k}{\mathrm{Fr}}_k{{\mathrm{Fr}}_k}^H{H_{i_{j}k}}^H{g_{i_j}}^H)\]\end{array}$

according to the formula of the inner product of CrohnKronecker decomposition of the above formula gives:

$\underset{{\mathrm{Fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}{\mathrm{\α}}_{i_k}\left(Tr\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right)=\underset{{\mathrm{fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}Tr\left({{\mathrm{fr}}_k}^H\right(Q_a+Q_b+Q_c){\mathrm{fr}}_k-q_a{\mathrm{fr}}_k-{{\mathrm{fr}}_k}^H{q}_b)$

thus, the first system model is changed to the second system model:

$\begin{array}{cc}& \underset{{\mathrm{fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}Tr\left({{\mathrm{fr}}_k}^H\right(Q_a+Q_b+Q_c){\mathrm{fr}}_k-q_a{\mathrm{fr}}_k-{{\mathrm{fr}}_k}^H{q}_b)\\ s.t& Tr\left({\mathrm{fr}}_k^H\right((\underset{i}{\overset{I_k}{\Σ}}{G}_{i_{k}k}{f}_{i_k}{f}_{i_k}^H{G}_{i_{k}k}^H+{\mathrm{\σ}}^{2}I)\⊗I\left){\mathrm{fr}}_k\right)\≤P_k\\ & Tr\left({\mathrm{fr}}_k^H\right((\underset{l}{\overset{I_k}{\Σ}}{G}_{l_{k}k}{f}_{l_k}{f_{l_k}}^H{G_{l_{k}k}}^H+{\mathrm{\σ}}^{2}I)\⊗{D_{i_{k}k}}^H{D}_{i_{k}k}\left){\mathrm{fr}}_k\right)\≥P_c\end{array}$

it should be noted that, in the embodiment of the present invention, the first system model is changed into the second system model through the above change, and the objective function in the first system model is converted into a form of quadratic programming (QCQP) of the quadratic constraint in the convex optimization, that is, the objective function in the second system model is in the form of QCQP in the convex optimization.

Fr is obtained by adopting a semi-positive definite relaxation algorithm according to a second system model_k。

Specifically, the second system model can be solved by adopting a semi-definite relaxation (SDR) algorithm, wherein the second system model obtains the beam-forming of the ID by adopting the SDR algorithm to calculateTo pairFr can be calculated by inverse quantization_k. It should be noted that the form of QCQP and the form of solving QCQP by using SDR algorithm in the embodiment of the present invention are the same as the form of QCQP and the form of solving QCQP by using SDR algorithm in the prior art, and the embodiment of the present invention is not described herein again.

Further, in the embodiment shown in fig. 2, before S201, the method provided in the embodiment of the present invention further includes:

obtaining preset base station transmitting power P_kInformation decoding module to base station channelBase station to ID channelCharging threshold P from base station to EH_c。

Specifically, before obtaining the objective function of the wireless energy-carrying communication transceiver model according to the minimum mean square error and the system capacity of the system, the preset initial parameters in the system can be obtainedP_k、And P_c。

It should be noted that, in the present embodiment, the power P of the user node may be determined in the system according to the power P of the user node_iInitializing ID beamformingFor equal power, according to the transmitting power P of the base station_kInitializing Fr_jIs of equal power.

It should be noted that, in the embodiment of the present invention, a lagrangian algorithm may also be used for the first system model, one of the two constraint conditions is set as an equivalent condition, and then the equivalent condition is obtained through the lagrangian algorithmAnd Fr_kWherein the result is obtained by using Lagrangian algorithmAnd Fr_kIs not an optimal solution and therefore can be found using the Lagrangian algorithmAnd Fr_kReferred to as a sub-optimal solution.

The invention provides a communication model combining a multi-cell MIMO system and wireless energy carrying, and a base station charges energy for an opposite end node while realizing point-to-point communication between user nodes, thereby realizing maximization of channel capacity in the system and minimization of mean square error. Fig. 3 is a schematic diagram of a simulation result of a minimum MSE of a system according to an embodiment of the present invention, fig. 4 is a schematic diagram of a simulation result of a maximum channel capacity according to an embodiment of the present invention, and fig. 5 is a schematic diagram of a partial enlargement of the simulation result of fig. 4. As shown in fig. 3 to 5, a communication link and a communication process are simulated, and simulation analysis compares the advantages and disadvantages of the minimum MSE and the maximum channel capacity of the system obtained under three conditions of an SDR algorithm, a lagrangian algorithm and no energy-charging constraint, and as can be seen from fig. 3 to 5, the SDR optimal algorithm used in the embodiment of the invention can rapidly achieve stability with few iteration times, can well design a multi-cell MIMO wireless energy-carrying transceiver with excellent performance, can enable the maximum channel capacity and the minimum mean square error of the system to be achieved simultaneously, well balances the effectiveness and reliability of wireless communication, and simultaneously meets all energy-charging and power constraint conditions of wireless energy-carrying, and proves the feasibility of the scheme.

It should be noted that, in the embodiment of the present invention, the formula can be proved in the following manner $\underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{\min }\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{i=1}{\overset{I_k}{\mathrm{\Σ}}}{\mathrm{\α}}_{i_k}\left(\mathrm{Tr}\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right)$ And $\underset{g,\mathrm{Fr}}{\max }\underset{i}{\mathrm{\Σ}}\underset{k}{\mathrm{\Σ}}{\mathrm{\α}}_{i_k}{R}_{i_k}$ equivalently, the minimum MSE and the maximum channel capacity of the system can be achieved simultaneously under the same ID decoding matrix and base station transmit beamforming conditions.

Due to the fact thatAndis irrelevant to and fixedIn (1)It is possible to obtain:

$\underset{W}{min}\underset{i}{\Σ}\underset{k}{\Σ}{\mathrm{\α}}_{i_k}\left(Tr\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right)$

to pairCalculating a partial derivative to obtain

Will be provided with ${W_{i_k}}^{\mathrm{MMSE}}={E_{i_k}}^{-1}$ Is substituted into $\underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{\min }\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{i=1}{\overset{I_k}{\mathrm{\Σ}}}{\mathrm{\α}}_{i_k}\left(\mathrm{Tr}\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right)$ In (b), one can obtain: $\min \underset{i}{\Σ}\underset{k}{\Σ}{\mathrm{\α}}_{i_k}(I-\log \det (W_{i_k}\left)\right)=\min \underset{i}{\Σ}\underset{k}{\Σ}{\mathrm{\α}}_{i_k}(-\log \det ({E_{i_k}}^{-1}\left)\right)=\max \underset{i}{\Σ}\underset{k}{\Σ}{\mathrm{\α}}_{i_k}\left(\log \det \right({E_{i_k}}^{-1}\left)\right)$

fixing $W_{i_k}={E_{i_k}}^{-1}$ At this time $\underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{\min }\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{i=1}{\overset{I_k}{\mathrm{\Σ}}}{\mathrm{\α}}_{i_k}\left(\mathrm{Tr}\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right)$ Can be completely regarded asI.e. to find the system minimum MSE.

In the above embodiment, we have obtained $E_{i_k}=I-{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{Z}^{-1}{H}_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k},$ Finally fixing $W_{i_k}={E_{i_k}}^{-1},$ Will be provided with $E_{i_k}=I-{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{Z}^{-1}{H}_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}$ Is substituted into $\max \underset{i}{\mathrm{\Σ}}\underset{k}{\mathrm{\Σ}}{\mathrm{\α}}_{i_k}\left(\log \det \right({E_{i_k}}^{-1}\left)\right)$ In (b), one can obtain:

$\min \underset{i}{\Σ}\underset{k}{\Σ}{\mathrm{\α}}_{i_k}(I-\log \det (W_{i_k}\left)\right)=\min \underset{i}{\Σ}\underset{k}{\Σ}{\mathrm{\α}}_{i_k}\left(\log \det {\left(I-{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{Z}^{-1}{H}_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}\right)}^{-1}\right)$

according to the inversion formula of the matrix theory: (A-UD)^-1V)^-1＝A^-1+A^-1U(D-VA^-1U)^-1VA^-1And the formula: logdet (I + AB) ═ logdet (I + BA), we can find:

$\begin{array}{c}\min \underset{i}{\Σ}\underset{k}{\Σ}{\mathrm{\α}}_{i_k}(I-\log \det (W_{i_k}\left)\right)=\\ \max \underset{i}{\Σ}\underset{k}{\Σ}{\mathrm{\α}}_{i_k}\left(\log \det \right(I+{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{(Z-H_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H)}^{-1}{H}_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}))\\ =\max \underset{i}{\Σ}\underset{k}{\Σ}{\mathrm{\α}}_{i_k}\left(\log \det \right(I+{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{N}^{-1}{H}_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}))\\ =\max \underset{i}{\Σ}\underset{k}{\Σ}{\mathrm{\α}}_{i_k}\left(\log \det \right(I+H_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{N}^{-1}))\\ =\max \underset{i}{\Σ}\underset{k}{\Σ}{\mathrm{\α}}_{i_k}\left(\log \det \right(I+{\mathrm{SN}}^{-1}))\\ =\max \underset{i}{\Σ}\underset{k}{\Σ}{\mathrm{\α}}_{i_k}{R}_{i_k}\end{array}$

it can therefore be seen that, as a result, $\underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{\min }\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{i=1}{\overset{I_k}{\mathrm{\Σ}}}{\mathrm{\α}}_{i_k}\left(\mathrm{Tr}\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right)$ and $\underset{g,\mathrm{Fr}}{\max }\underset{i}{\mathrm{\Σ}}\underset{k}{\mathrm{\Σ}}{\mathrm{\α}}_{i_k}{R}_{i_k}$ is equivalent, then the system can be optimized simultaneously from both the maximum channel capacity and the system minimum MSE.

Fig. 6 is a schematic structural diagram of a wireless energy-carrying communication transceiver model obtaining apparatus according to an embodiment of the present invention. As shown in fig. 6, an apparatus provided in an embodiment of the present invention includes: an objective function obtaining module 61, a transmission power obtaining module 62, a received signal obtaining module 63 and a first system model obtaining module 64.

And the objective function obtaining module 61 is configured to obtain an objective function of the wireless energy-carrying communication transceiver model according to the minimum mean square error and the channel capacity of the signal received by the information decoding module of the user node.

And a transmission power obtaining module 62, configured to obtain the transmission power of the base station according to the transmission signal of the base station.

And a received signal obtaining module 63, configured to obtain a received signal of the user node according to a signal sent by the base station to the energy receiving module.

A first system model obtaining module 64, configured to obtain a first system model of the wireless energy-carrying communication transceiver according to the objective function, the transmission power of the base station, and the received signal of the user node.

The wireless energy-carrying communication transceiver model comprises an objective function:

$\underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}{\mathrm{\α}}_{i_k}\left(Tr\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right).$

the first system model of the wireless energy-carrying communication transceiver is as follows:

$\begin{array}{cc}& \underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}{\mathrm{\α}}_{i_k}\left(Tr\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right)\\ s.t& Tr\[{\mathrm{Fr}}_k(\underset{i}{\overset{I_k}{\Σ}}{G}_{i_{k}k}{f}_{i_k}{f}_{i_k}^H{G}_{i_{k}k}^H+{\mathrm{\σ}}^{2}I){\mathrm{Fr}}_k^H\]\≤P_k\\ & Tr\left(D_{i_{k}k}{\mathrm{Fr}}_k\right(\underset{l}{\overset{I_k}{\Σ}}{G}_{l_{k}k}{f}_{l_k}{f}_{l_k}^H{G}_{l_{k}k}^H+{\mathrm{\σ}}^{2}I){\mathrm{Fr}}_k^H{D}_{i_{k}k}^H)\≥P_c\end{array}$

wherein,representing user node i_kThe signal decoding matrix of (a) is,representing user node i_kWeight coefficient of mean square error MSE, Fr_kA beamforming matrix representing a base station,which represents the transpose of the matrix Frk,representing user node i_kChannel capacity in systemThe proportion of the active carbon in the water is, representing user node i_kIs received, Tr denotes the rank of the matrix, det denotes the determinant, K denotes the base station of each cell, K is 1,2_kDenotes the ith user node, i, in base station k_k＝1,2,...,I_k，I_kRepresenting the number of user nodes comprised by the cell covered by the base station, s.t representing the constraints of the objective function,/_kDenotes the l user node, P, in base station k_kRepresenting the base station transmission power, P_cWhich represents the charging threshold of the EH,indicating the channel of the ID to the base station,representation matrixThe transpose of (a) is performed,a channel representing a base station to an ID,representation matrixThe transpose of (a) is performed,the beam-forming of the representation ID,representation matrixIs transposed, σ denotes the channelI denotes an identity matrix.

The wireless energy-carrying communication transceiver model obtaining apparatus according to the embodiment of the present invention is used for implementing the technical solution of the method embodiment shown in fig. 2, and the implementation principle and the technical effect are similar, and are not described herein again.

Further, on the basis of the embodiment shown in fig. 6, the apparatus provided in the embodiment of the present invention further includes: and a minimum mean square error acquisition module.

A minimum mean square error acquisition module for acquiring the minimum mean square error according to the user nodeTo user node i_kTransmitted signalUsing a formulaAcquiring signals received by a base stationObtaining user node i_kReceived signalAccording toUsing a formulaObtaining a decoded signalAccording toAndusing a formulaAnd acquiring the minimum mean square error of the system.

Wherein, ${\tilde{x}}_{i_k}=H_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}{s}_{{\tilde{i}}_k}+H_{i_{k}k}{\mathrm{Fr}}_k{n}_{{\tilde{i}}_k}+\underset{j\≠k}{\overset{K}{\Σ}}{H}_{i_{k}j}{\mathrm{Fr}}_j(\underset{l}{\overset{I_j}{\Σ}}{G}_{l_{j}j}{f}_{l_j}{s}_{l_j}+n_{l_j})+n_{io},$ representing the signal from the l-th user node in base station j,representing a user node l_jChannel noise when performing uplink communication to the base station j,indicating all the user nodes i_kTotal downlink noise of, user nodeAnd user node i_kFor different user nodes in the same cell,for the superposition of channel noise for all uplinks in the same cell,

a minimum mean square error acquisition module for further using the formulaTo pairDerivation by formulaGet user node i_kSignal decoding matrix ofWill be provided withSubstitution formulaIn the method, the minimum mean square error of the system is obtained

Wherein, $\begin{array}{c}Z=\underset{j\≠k}{\Σ}\underset{l}{\Σ}{H}_{i_{k}j}{\mathrm{Fr}}_j{G}_{l_{j}j}{f}_{l_j}{f_{l_j}}^H{G_{l_{j}j}}^H{{\mathrm{Fr}}_j}^H{H_{i_{k}j}}^H+{\mathrm{\σ}}^2\underset{j}{\overset{K}{\Σ}}{H}_{i_{k}j}{\mathrm{Fr}}_j{{\mathrm{Fr}}_j}^H{H_{i_{k}j}}^H\\ +{{\mathrm{\σ}}_2}^{2}I+H_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H\end{array}.$

further, on the basis of the embodiment shown in fig. 6, the apparatus provided in the embodiment of the present invention further includes: the system comprises a weighting coefficient acquisition module, a second system model acquisition module and a calculation module.

A weighting coefficient obtaining module for adopting a formulaObtaining user node i_kWeighted coefficient of Mean Square Error (MSE)

A second system model acquisition module for acquiring the system modelAndsubstituting into the first system model, and substituting intoAndcarrying out kronecker decomposition on the later first system model, and changing the first system model into a second system model:

$\underset{{\mathrm{fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}Tr\left({{\mathrm{fr}}_k}^H\right(Q_a+Q_b+Q_c){\mathrm{fr}}_k-q_a{\mathrm{fr}}_k-{{\mathrm{fr}}_k}^H{q}_b)$

$\begin{array}{cc}s.t.& Tr\left({\mathrm{fr}}_k^H\right((\underset{i}{\overset{I_k}{\Σ}}{G}_{i_{k}k}{f}_{i_k}{f}_{i_k}^H{G}_{i_{k}k}^H+{\mathrm{\σ}}^{2}I)\⊗I\left){\mathrm{fr}}_k\right)\≤P_k\\ & Tr\left({{\mathrm{fr}}_k}^H\right((\underset{l}{\overset{I_k}{\Σ}}{G}_{l_{k}k}{f}_{l_k}{f_{l_k}}^H{G_{l_{k}k}}^H+{\mathrm{\σ}}^{2}I)\⊗{D_{i_{k}k}}^H{D}_{i_{k}k}\left){\mathrm{fr}}_k\right)\≥P_c\end{array}$

wherein fr_k＝vec(Fr_k) And vec represents the number of bits in the table, $Q_a={\mathrm{\α}}_{i_k}{G}_{{\stackrel{\‾}{i}}_{k}k}{f}_{{\stackrel{\‾}{i}}_k}{f_{{\stackrel{\‾}{i}}_k}}^H{G_{{\stackrel{\‾}{i}}_{k}k}}^H\⊗{H_{i_{k}k}}^H{g_{i_k}}^H{W}_{i_k}{g}_{i_k}{H}_{i_{k}k},$ $Q_b=\underset{j\≠k}{\Σ}\underset{l}{\Σ}{\mathrm{\α}}_{l_j}(G_{i_{k}k}{f}_{i_k}{f_{i_k}}^H{G_{i_{k}k}}^H\⊗{H_{l_{j}k}}^H{g_{l_j}}^H{W}_{l_j}{g}_{l_j}{H}_{l_{j}k}),Q_c=\underset{j}{\Σ}{\mathrm{\α}}_{i_j}{\mathrm{\σ}}^2(I\⊗{H_{i_{j}k}}^H{g_{i_j}}^H{W}_{i_j}{g}_{i_j}{H}_{i_{j}k}),$ $q_a={\mathrm{\α}}_{i_k}vec{\left({H_{i_{k}k}}^H{g_{i_k}}^H{W_{i_k}}^H{f_{{\stackrel{\‾}{i}}_k}}^H{G_{{\stackrel{\‾}{i}}_{k}k}}^H\right)}^H,q_b={\mathrm{\α}}_{i_k}vec\left({H_{i_{k}k}}^H{g_{i_k}}^H{W}_{i_k}{f_{{\stackrel{\‾}{i}}_k}}^H{G_{{\stackrel{\‾}{i}}_{k}k}}^H\right).$

a calculating module for obtaining Fr by using a semi-positive definite relaxation SDR algorithm according to the second system model_k。

Further, on the basis of the embodiment shown in fig. 6, the apparatus provided in the embodiment of the present invention further includes: and a pre-acquisition module.

A pre-obtaining module for obtaining the preset base station transmitting power P_kID to base station channelBase station to ID channelCharging threshold P from base station to EH_c。

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. A method for obtaining a wireless energy-carrying communication transceiver model, comprising:

obtaining an objective function of a wireless energy-carrying communication transceiver model according to the minimum mean square error and the channel capacity of a signal received by an information decoding module ID of a user node;

acquiring the transmitting power of a base station according to a transmitting signal of the base station;

acquiring a receiving signal of a user node according to a signal sent to an energy receiving module EH by the base station;

and obtaining a first system model of the wireless energy-carrying communication transceiver according to the objective function, the transmitting power of the base station and the receiving signal of the user node.

2. The method of claim 1, wherein the objective function of the wireless energy-carrying communication transceiver model is: $\underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{\min }\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{i=1}{\overset{I_k}{\mathrm{\Σ}}}{\mathrm{\α}}_{i_k}\left(Tr\left(W_{i_k}{E}_{i_k}\right)-\log \det \left(W_{i_k}\right)\right);$

the first system model of the wireless energy-carrying communication transceiver is as follows:

$\underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{\min }\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{i=1}{\overset{I_k}{\mathrm{\Σ}}}{\mathrm{\α}}_{i_k}\left(Tr\left(W_{i_k}{E}_{i_k}\right)-\log \det \left(W_{i_k}\right)\right);$

$\begin{array}{cc}s.t.& Tr\[{\mathrm{Fr}}_k\left(\underset{i}{\overset{I_k}{\mathrm{\Σ}}}{G}_{i_{k}k}{f}_{i_k}{f}_{i_k}^H{G}_{i_{k}k}^H+{\mathrm{\σ}}^{2}I\right){\mathrm{Fr}}_k^H\]\≤P_k\end{array}$

$Tr\left(D_{i_{k}k}{\mathrm{Fr}}_k\left(\underset{l}{\overset{I_k}{\mathrm{\Σ}}}{G}_{l_{k}k},f_{l_k}{f}_{l_k}^H{G}_{l_{k}k}^H+{\mathrm{\σ}}^{2}I\right){\mathrm{Fr}}_k^H{D}_{i_{k}k}^H\right)\≥P_c$

wherein,representing user node i_kThe signal decoding matrix of (a) is,representing user node i_kWeight coefficient of mean square error MSE, Fr_kA beamforming matrix representing a base station,the representation matrix Fr_kThe transpose of (a) is performed,representing user node i_kThe proportion of the capacity of the system channel is,representing user node i_kIs the minimum mean square error of the ID received signal, Tr representsThe rank of the matrix, det denotes the determinant, K denotes the base station of each cell, K1, 2_kDenotes the ith user node, i, in base station k_k＝1,2,...,I_k，I_kRepresenting the number of user nodes comprised by the cell covered by the base station, s.t representing the constraints of said objective function,/_kDenotes the l user node, P, in base station k_kRepresenting the base station transmission power, P_cWhich represents the charging threshold of the EH,a channel representing the information decoding module ID to the base station,representation matrixThe transpose of (a) is performed,a channel representing a base station to an ID,representation matrixThe transpose of (a) is performed,a beamforming representing the information decoding module ID,representation matrixIs transposed, σ denotes the channelI denotes an identity matrix.

3. The method of claim 2, wherein the objective function of the model of the wireless energy-carrying communication transceiver is obtained according to the minimum mean square error of the system and the system capacityBefore, still include:

according to user nodeTo user node i_kTransmitted signalUsing a formulaAcquiring signals received by a base station

Wherein the user nodeAnd user node i_kFor different user nodes in the same cell,for the superposition of channel noise for all uplinks in the same cell,

obtaining user node i_kReceived signal

Wherein, ${\tilde{x}}_{i_k}=H_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}{s}_{{\tilde{i}}_k}+H_{i_{k}k}{\mathrm{Fr}}_k{n}_{{\tilde{i}}_k}+\underset{j\≠k}{\overset{K}{\mathrm{\Σ}}}{H}_{i_{k}j}{\mathrm{Fr}}_j\left(\underset{l}{\overset{I_j}{\Σ}}{G}_{l_{j}j}{f}_{l_j}{s}_{l_j}+n_{l_j}\right)+n_{io},$ representing the signal from the l-th user node in base station j,representing a user node l_jChannel noise when performing uplink communication to the base station j,indicating all the user nodes i_kTotal downlink noise of (1);

according to the aboveUsing a formulaObtaining a decoded signal

According to the aboveAnd saidUsing a formulaAnd acquiring the minimum mean square error of the system.

4. The method of claim 3, wherein said determining is based on saidAnd saidUsing a formulaObtaining the system minimum mean square error comprises:

will be a formulaTo pairDerivation by formulaGet user node i_kSignal decoding matrix of $g_{i_k}^{\mathrm{MMSE}}={f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_k,k}}^H{Z}^{-1};$

Wherein, $\begin{array}{c}Z=\underset{j\≠k}{\mathrm{\Σ}}\underset{l}{\mathrm{\Σ}}{H}_{i_{k}j}{\mathrm{Fr}}_j{G}_{l_{j}j}{f}_{l_j}{f_{l_j}}^H{G_{l_{j}j}}^H{{\mathrm{Fr}}_j}^H{H_{i_{k}j}}^H+{\mathrm{\σ}}^2\underset{j}{\overset{K}{\mathrm{\Σ}}}{H}_{i_{k}j}{\mathrm{Fr}}_j{{\mathrm{Fr}}_j}^H{H_{i_{k}j}}^H\\ +{{\mathrm{\σ}}_2}^{2}I+H_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H\end{array}$

will be described inSubstitution formulaIn the method, the minimum mean square error of the system is obtained

5. The method of claim 4, further comprising:

using a formulaObtaining user node i_kWeighted coefficient of Mean Square Error (MSE)

Will be described inAnd saidSubstituting the first system model and substituting the first system model into the first system modelAnd saidCarrying out kronecker decomposition on the later first system model, and changing the first system model into a second system model:

$\underset{{\mathrm{fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}Tr\left({{\mathrm{fr}}_k}^H\right(Q_a+Q_b+Q_c){\mathrm{fr}}_k-q_a{\mathrm{fr}}_k-{{\mathrm{fr}}_k}^H{q}_b)$

$\begin{array}{cc}s.t.& Tr\left({\mathrm{fr}}_k^H\right(\left(\underset{i}{\overset{I_k}{\mathrm{\Σ}}}{G}_{i_{k}k}{f}_{i_k}{f}_{i_k}^H{G}_{i_{k}k}^H+{\mathrm{\σ}}^{2}I\right)\⊗I\left){\mathrm{fr}}_k\right)\≤P_k\end{array}$

$Tr\left({{\mathrm{fr}}_k}^H\right(\left(\underset{l}{\overset{I_k}{\mathrm{\Σ}}}{G}_{l_{k}k}{f}_{l_k}{f_{l_k}}^H{G_{l_{k}k}}^H+{\mathrm{\σ}}^{2}I\right)\⊗{D_{i_{k}k}}^H{D}_{i_{k}k}\left){\mathrm{fr}}_k\right)\≤P_c$

wherein fr_k＝vec(Fr_k)， $Q_a={\mathrm{\α}}_{i_k}{G}_{\stackrel{\‾}{i_k}k}{f}_{\stackrel{\‾}{i_k}}{f_{\stackrel{\‾}{i_k}}}^H{G_{\stackrel{\‾}{i_k}k}}^H\⊗{H_{i_{k}k}}^H{g_{i_k}}^H{W}_{i_k}{g}_{i_k}{H}_{i_{k}k},$ $Q_b=\underset{j\≠k}{\mathrm{\Σ}}\underset{l}{\mathrm{\Σ}}{\mathrm{\α}}_{l_j}\left(G_{i_{k}k}{f}_{i_k}{f_{i_k}}^H{G_{i_{k}k}}^H\⊗{H_{l_{j}k}}^H{g_{l_j}}^H{W}_{l_j}{g}_{l_j}{H}_{l_{j}k}\right),Q_c=\underset{j}{\mathrm{\Σ}}{\mathrm{\α}}_{i_j}{\mathrm{\σ}}^2\left(I\⊗{H_{i_{j}k}}^H{g_{i_j}}^H{W}_{i_j}{g}_{i_j}{H}_{i_{j}k}\right),$ $q_a={\mathrm{\α}}_{i_k}vec{\left({H_{i_{k}k}}^H{g_{i_k}}^H{W_{i_k}}^H{f_{\stackrel{\‾}{i_k}}}^H{G_{\stackrel{\‾}{i_k}k}}^H\right)}^H,q_b={\mathrm{\α}}_{i_k}vec\left({H_{i_{k}k}}^H{g_{i_k}}^H{W}_{i_k}{f_{\stackrel{\‾}{i_k}}}^H{G_{\stackrel{\‾}{i_k}k}}^H\right),$ vec represents vectorizing the matrix;

obtaining the Fr by adopting a semi-positive definite relaxation SDR algorithm according to the second system model_k。

6. The method according to any one of claims 1-5, wherein the objective function of the model of the wireless energy-carrying communication transceiver is obtained according to the minimum mean square error of the system and the system capacityBefore, still include:

obtaining preset base station transmitting power P_kInformation decoding module ID to base station channelBase station to ID channelCharging threshold P from base station to EH_c。

7. A wireless energy-carrying communication transceiver model obtaining apparatus, comprising:

the target function acquisition module is used for acquiring a target function of a wireless energy-carrying communication transceiver model according to the minimum mean square error and the channel capacity of the signal received by the information decoding module ID of the user node;

the transmission power acquisition module is used for acquiring the transmission power of the base station according to the transmission signal of the base station;

a received signal obtaining module, configured to obtain a received signal of a user node according to a signal sent by the base station to the energy receiving module EH;

a first system model obtaining module, configured to obtain a first system model of a wireless energy-carrying communication transceiver according to the objective function, the transmission power of the base station, and a received signal of the user node;

wherein an objective function of the wireless energy-carrying communication transceiver model is as follows: $\underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{\min }\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{i=1}{\overset{I_k}{\mathrm{\Σ}}}{\mathrm{\α}}_{i_k}\left(Tr\left(W_{i_k}{E}_{i_k}\right)-\log \det \left(W_{i_k}\right)\right);$

the first system model of the wireless energy-carrying communication transceiver is as follows:

$\underset{g_{i_k},W_{i_k},{\mathrm{Fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}{\mathrm{\α}}_{i_k}\left(Tr\right(W_{i_k}{E}_{i_k})-\log \det (W_{i_k}\left)\right)$

$\begin{array}{cc}s.t.& Tr\[{\mathrm{Fr}}_k\left(\underset{i}{\overset{I_k}{\mathrm{\Σ}}}{G}_{i_{k}k}{f}_{i_k}{f}_{i_k}^H{G}_{i_{k}k}^H+{\mathrm{\σ}}^{2}I\right){\mathrm{Fr}}_k^H\]\≤P_k\end{array}$

$Tr\left(D_{i_{k}k}{\mathrm{Fr}}_k\left(\underset{l}{\overset{I_k}{\mathrm{\Σ}}}{G}_{l_{k}k}{f}_{l_k}{f}_{l_k}^H{G}_{l_{k}k}^H+{\mathrm{\σ}}^{2}I\right){\mathrm{Fr}}_k^H{D}_{i_{k}k}^H\right)\≥P_c$

wherein,representing user node i_kThe signal decoding matrix of (a) is,representing user node i_kWeight coefficient of mean square error MSE, Fr_kA beamforming matrix representing a base station,the representation matrix Fr_kThe transpose of (a) is performed,representing user node i_kThe proportion of the capacity of the system channel is,representing user node i_kIs received, Tr denotes the rank of the matrix, det denotes the determinant, K denotes the base station of each cell, K is 1,2_kDenotes the ith user node, i, in base station k_k＝1,2,...,I_k，I_kRepresenting the number of user nodes comprised by the cell covered by the base station, s.t representing the constraints of said objective function,/_kDenotes the l user node, P, in base station k_kRepresenting the base station transmission power, P_cWhich represents the charging threshold of the EH,a channel representing the information decoding module ID to the base station,representation matrixThe transpose of (a) is performed,a channel representing a base station to an ID,representation matrixThe transpose of (a) is performed,a beamforming representing the information decoding module ID,representation matrixIs transposed, σ denotes the channelI denotes an identity matrix.

8. The apparatus of claim 7, further comprising:

a minimum mean square error acquisition module for acquiring the minimum mean square error according to the user nodeTo user node i_kTransmitted signalUsing a formulaAcquiring signals received by a base stationObtaining user node i_kReceived signalAccording to the aboveUsing a formulaObtaining decoded informationNumber (C)According to the aboveAnd saidUsing a formulaAcquiring the minimum mean square error of the system;

wherein, ${\tilde{x}}_{i_k}=H_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}{s}_{{\tilde{i}}_k}+H_{i_{k}k}{\mathrm{Fr}}_k{n}_{{\tilde{i}}_k}+\underset{j\≠k}{\overset{k}{\mathrm{\Σ}}}{H}_{i_{k}j}{\mathrm{Fr}}_j\left(\underset{l}{\overset{I_j}{\Σ}}{G}_{l_{j}j}{f}_{l_j}{s}_{l_j}+n_{l_j}\right)+n_{io,}$ representing the signal from the l-th user node in base station j,representing a user node l_jChannel noise when performing uplink communication to the base station j,indicating all the user nodes i_kTotal downlink noise of, user nodeAnd user node i_kFor different user nodes in the same cell,for the superposition of channel noise for all uplinks in the same cell,

the minimum mean square error acquisition module is also used for converting a formulaTo pairDerivation by formulaGet user node i_kSignal decoding matrix of ${g_{i_k}}^{MMSE}={f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H{Z}^{-1};$ Will be described inSubstitution formula $E_{i_k}=({\tilde{s}}_{i_k}-s_{{\tilde{i}}_k}){({\tilde{s}}_{i_k}-s_{{\tilde{i}}_k})}^H$ In the method, the minimum mean square error of the system is obtained

Wherein, $\begin{array}{c}Z=\underset{j\≠k}{\mathrm{\Σ}}\underset{l}{\mathrm{\Σ}}{H}_{i_{k}j}{\mathrm{Fr}}_j{G}_{l_{j}j}{f}_{l_j}{f_{l_j}}^H{G_{l_{j}j}}^H{{\mathrm{Fr}}_j}^H{H_{i_{k}j}}^H+{\mathrm{\σ}}^2\underset{j}{\overset{K}{\mathrm{\Σ}}}{H}_{i_{k}j}{\mathrm{Fr}}_j{{\mathrm{Fr}}_j}^H{H_{i_{k}j}}^H\\ +{{\mathrm{\σ}}_2}^{2}I+H_{i_{k}k}{\mathrm{Fr}}_k{G}_{{\tilde{i}}_{k}k}{f}_{{\tilde{i}}_k}{f_{{\tilde{i}}_k}}^H{G_{{\tilde{i}}_{k}k}}^H{{\mathrm{Fr}}_k}^H{H_{i_{k}k}}^H\end{array}.$

9. the apparatus of claim 8, further comprising:

weighting coefficient obtainingA fetch module for fetching a formulaObtaining user node i_kWeighted coefficient of Mean Square Error (MSE)

A second system model acquisition module for acquiring the system modelAnd saidSubstituting the first system model and substituting the first system model into the first system modelAnd saidCarrying out kronecker decomposition on the later first system model, and changing the first system model into a second system model:

$\underset{{\mathrm{fr}}_k}{min}\underset{k=1}{\overset{K}{\Σ}}\underset{i=1}{\overset{I_k}{\Σ}}Tr\left({{\mathrm{fr}}_k}^H\right(Q_a+Q_b+Q_c){\mathrm{fr}}_k-q_a{\mathrm{fr}}_k-{{\mathrm{fr}}_k}^H{q}_b)$

$\begin{array}{cc}s.t.& Tr\left({\mathrm{fr}}_k^H\right(\left(\underset{i}{\overset{I_k}{\mathrm{\Σ}}}{G}_{i_{k}k}{f}_{i_k}{f}_{i_k}^H{G}_{i_{k}k}^H+{\mathrm{\σ}}^{2}I\right)\⊗I\left){\mathrm{fr}}_k\right)\≤P_k\end{array}$

$Tr\left({{\mathrm{fr}}_k}^H\left(\left(\underset{l}{\overset{I_k}{\mathrm{\Σ}}}{G}_{l_{k}k}{f}_{l_k}{f_{l_k}}^H{G_{l_{k}k}}^H+{\mathrm{\σ}}^{2}I\right)\⊗{D_{i_{k}k}}^H{D}_{i_{k}k}\right){\mathrm{fr}}_k\right)\≥P_c$

wherein fr_k＝vec(Fr_k)， $Q_a={\mathrm{\α}}_{i_k}{G}_{\stackrel{\‾}{i_k}k}{f}_{\stackrel{\‾}{i_k}}{f_{\stackrel{\‾}{i_k}}}^H{G_{\stackrel{\‾}{i_k}k}}^H\⊗{H_{i_{k}k}}^H{g_{i_k}}^H{W}_{i_k}{g}_{i_k}{H}_{i_{k}k},$ $Q_b=\underset{j\≠k}{\mathrm{\Σ}}\underset{l}{\mathrm{\Σ}}{\mathrm{\α}}_{l_j}\left(G_{i_{k}k}{f}_{i_k}{f_{i_k}}^H{G_{i_{k}k}}^H\⊗{H_{l_{j}k}}^H{g_{l_j}}^H{W}_{l_j}{g}_{l_j}{H}_{l_{j}k}\right),Q_c=\underset{j}{\mathrm{\Σ}}{\mathrm{\α}}_{i_j}{\mathrm{\σ}}^2\left(I\⊗{H_{i_{j}k}}^H{g_{i_j}}^H{W}_{i_j}{g}_{i_j}{H}_{i_{j}k}\right),$ $q_a={\mathrm{\α}}_{i_k}vec{\left({H_{i_{k}k}}^H{g_{i_k}}^H{W_{i_k}}^H{f_{\stackrel{\‾}{i_k}}}^H{G_{\stackrel{\‾}{i_k}k}}^H\right)}^H,q_b={\mathrm{\α}}_{i_k}vec\left({H_{i_{k}k}}^H{g_{i_k}}^H{W}_{i_k}{f_{\stackrel{\‾}{i_k}}}^H{G_{\stackrel{\‾}{i_k}k}}^H\right),$ vec represents vectorizing the matrix;

a calculation module for obtaining the Fr by using a semi-positive definite relaxation SDR algorithm according to the second system model_k。

10. The apparatus according to any one of claims 7-9, further comprising:

a pre-obtaining module for obtaining the preset base station transmitting power P_kInformation decoding module ID to base station channelBase station to ID channelCharging threshold P from base station to EH_c。