阅读说明：本技术 一种基于量化感知的接收天线贪婪选择方法 (Receiving antenna greedy selection method based on quantization perception ) 是由 王仕果 朱敏 李琳至 刘鸿东 张文杰 于 2021-09-01 设计创作，主要内容包括：本发明公开了一种基于量化感知的接收天线贪婪选择方法,在上行链路接收端采用两轮天线选择,首先使用SMV算法,先随机选择N-(B)根天线,再通过迭代交换不断地增大被选天线矩阵的体积,进而全局优化第一轮选择的N-(B)根天线,第一轮天线选择不仅有效提高了系统的安全容量同时还缩小了第二轮天线选择的候选天线集合的大小从而减少了计算复杂度,在第二轮天线选择中综合考虑信道增益和量化误差影响来选择N-(r)-N-(B)根天线,进一步提高了系统的安全容量。(The invention discloses a receiving antenna greedy selection method based on quantization perception, which adopts two-wheel antenna selection at an uplink receiving end, firstly uses an SMV algorithm, and firstly randomly selects N B The volume of the selected antenna matrix is continuously increased through iterative exchange by the root antenna, and N selected in the first round is globally optimized B The first round of antenna selection not only effectively improves the safety capacity of the system, but also reduces the size of a candidate antenna set selected by the second round of antenna selection so as to reduce the computational complexity, and N is selected by comprehensively considering the influence of channel gain and quantization error in the second round of antenna selection r ‑N B The safety capacity of the system is further improved by the root antenna.)

1. A receiving antenna greedy selection method based on quantization perception is characterized by comprising the following steps:

the method comprises the following steps: at the receiving end, N before random selection_BRoot antenna as first round selected antenna set H_φWherein the unselected antennas areN_BThe number of the users;

step two: computingFinding the element | Q with the largest absolute value in Q_i,jL, and recording the position thereof, wherein Qi, j represents the ith row and the jth column element in Q;

step three: if | Q_i,jIf | is greater than 1, exchanging vectors of the ith row and the jth row in the channel matrix H, returning to the step two, and repeatedly executing the step two and the step three until | Q_i,j|＝1；

Step four: coupling the unselected antennaPerforming a second round of receiving antenna selection as a candidate antenna set omega;

step five: respectively calculating the channel gains c corresponding to all antennas in the candidate antenna set_kAnd quantization error d_k；

Step six: selecting c_k/d_kThe smallest antenna is deleted from the candidate antenna set;

step seven: updating relevant parameters, returning to the step six, and repeatedly executing the step six and the step seven until N remains in the candidate antenna set_r-N_BA root antenna, wherein Nr is the number of antennas to be selected;

step eight: combining the selected antenna set in the first selection round and the candidate antenna set in the second selection round to obtain the finally selected N_rRoot receiving antenna H_sel。

2. The method of claim 1, wherein N is the first random selection at the receiving end_BRoot antenna as first round selected antenna set H_φWherein the unselected antennas areThe method comprises the following steps:

at the receiving end, N before random selection_BRoot antenna as initial selected antenna set H_φ＝H(1:N_BIf the antenna is not selected, the unselected antenna isH_φAndrespectively is N_B×N_B，(N_A-N_B)×N_BWhere H is a dimension N_A×N_BUplink channel matrix, N in uplink_AIs the number of receiving antennas, N_BIs the number of users.

3. The method of claim 2, wherein the computing is performed by a computing deviceFind the best in QFor the element | Q with the largest value_i,jAnd recording its location, including:

based on the formulaCalculating Q, searching the element with the maximum absolute value in Q and recording the position [ i, j ] of the element]＝arg max(max|Q_i,j|) wherein Q has a dimension of N_A×N_B，|Q_i,jI represents the absolute value of the ith row and jth column element in Q, and i is 1,2_A，j＝1,2,...,N_B，Is H_φThe inverse matrix of (c).

4. The method of claim 3, wherein the if | Q_i,jIf | is greater than 1, exchanging vectors of the ith row and the jth row in the channel matrix H, returning to the step two, and repeatedly executing the step two and the step three until | Q_i,j1, comprising:

if | Q_i,jIf | is greater than 1, the ith and jth row vectors in H are exchanged to obtain a new larger H_φ；

Returning to the second step, and repeatedly executing the second step and the third step until the absolute value of Q is obtained_i,jGet 1, get the optimal antenna set H for the first round of selection_φ。

5. Method according to claim 4, characterized in that the non-selected antennas are assignedPerforming a second round of receiving antenna selection as a candidate antenna set ω, comprising:

based on the formulaInitializing B, wherein_ADRepresenting low resolution at the receiving endQuantization accuracy of analog-to-digital converter, P_URepresenting the transmit power, D representing the noise covariance matrix, D^-1The inverse matrix representing D is then used,representsTranspose conjugate matrix of (2), antenna not to be selectedA second round of antenna selection is performed as a candidate antenna set ω, where ω ═ 1,2_A-N_B}。

6. The method of claim 5, wherein the channel gains c corresponding to all antennas in the candidate antenna set are calculated separately_kAnd quantization error d_kThe method comprises the following steps:

based on the formulaCalculating the channel gain c corresponding to all antennas in the candidate antenna set_kBased on the formulaCalculating quantization errors d corresponding to all antennas in the candidate antenna set_kWhere k ∈ ω, c_kAnd d_kRespectively represent the channel gain and quantization error corresponding to the k-th candidate antenna,representsThe k-th row vector of (1).

7. The method of claim 6Method, characterized in that said selection is such that c_k/d_kThe smallest antenna is deleted from the candidate antenna set, and the method comprises the following steps:

selecting c according to the converted objective function_k/d_kMinimum antenna k^*Wherein k is^*Satisfy k^*＝arg min c_k/d_kAnd deleting omega-omega \ k from the candidate antenna set^*。

8. The method of claim 7, wherein the updating the correlation parameters returns to the sixth step, and the sixth and seventh steps are repeated until N remains in the candidate antenna set_r-N_BA root antenna, comprising:

based on the formulaUpdating a based on formula B ═ B + aa^HUpdate B based on formulaUpdate c_kAnd returning to the step six, and repeatedly executing the step six and the step seven until N remains in the candidate antenna set_r-N_BA root antenna, wherein,to representK of (1)^*The number of the row vectors is,denotes the kth^*The quantization error of the root candidate antenna is,denotes the kth^*Gain of root candidate antenna, a^HIndicates the rotation of aAnd (4) conjugation.

9. The method of claim 8, wherein the selected antenna set in the first round of selection and the candidate antenna set in the second round of selection are combined to obtain N of the last selection_rRoot receiving antenna H_selThe method comprises the following steps:

combining the selected antenna sets H in the first round of selection_φAnd the remaining candidate antenna sets in the second round of selectionObtaining the finally selected N_rRoot receiving antenna H_sel＝[H_φ；H_ω]。

Technical Field

The invention relates to the technical field of antenna selection, in particular to a greedy selection method for a receiving antenna based on quantization perception.

Background

Large-scale Multiple-Input Multiple-Output (MIMO) is one of core technologies of a fifth generation mobile communication system, and it implements higher system capacity and spectral efficiency by configuring a large number of antennas (tens or even hundreds) at a Base Station (BS) end. Research finds that the large-scale MIMO technology has the following advantages: (1) when the number of antennas is large enough, the influence of thermal noise and interference among users can be eliminated, so that the reliability and the effectiveness of the system are improved; (2) increasing the number of antennas at the base station end can improve the space multiplexing gain and the diversity gain, thereby improving the system capacity and the spectrum efficiency; (3) when the base station increases the number of the antennas and the transmitting power is unchanged, the energy efficiency of the system can be improved, and the requirement of green communication is met better. However, the massive MIMO technology also faces some challenges, and due to the great increase of the number of base station antennas, if each antenna is equipped with a Radio Frequency (RF) link and a pair of high-resolution analog-to-digital converters/digital-to-analog converters (ADC/DAC), the hardware cost, complexity and power consumption of the system will be greatly increased, thereby greatly increasing the difficulty of actual deployment and later maintenance of the massive MIMO system.

At present, almost all research assumes that the base station employs high resolution ADCs/DACs, which are not possible to use in a practical massive MIMO deployment. The use of a low-resolution ADC/DAC in a base station inevitably brings quantization errors, however, almost all existing antenna selection technologies do not consider quantization errors for antenna selection, which inevitably causes some performance loss, and some existing antenna selection technologies have the disadvantages of high complexity, low practicability, and the like.

Therefore, how to select the greedy receiving antenna more simply and effectively to reduce the hardware complexity, cost and power consumption of the system is an urgent problem to be solved.

Disclosure of Invention

In view of this, the invention provides a receiving antenna greedy selection method based on quantization sensing, which can effectively reduce the hardware complexity, cost and power consumption of the system.

The invention provides a receiving antenna greedy selection method based on quantization perception, which comprises the following steps:

the method comprises the following steps: at the receiving end, N before random selection_BRoot antenna as first round selected antenna set H_φWherein the unselected antennas areN_BThe number of the users;

step two: computingFinding the element | Q with the largest absolute value in Q_i，jAnd recording its position, wherein Q_i，jRepresents the ith row and jth column element in Q;

step three: if | Q_i，jIf | is greater than 1, exchanging vectors of the ith row and the jth row in the channel matrix H, returning to the step two, and repeatedly executing the step two and the step three until | Q_i，j|＝1；

Step four: coupling the unselected antennaPerforming a second round of receiving antenna selection as a candidate antenna set omega;

step five: respectively calculating the channel gains c corresponding to all antennas in the candidate antenna set_kAnd quantization error d_k；

Step six: selecting c_k/d_kThe smallest antenna is deleted from the candidate antenna set;

step seven: updating relevant parameters, returning to the step six, and repeatedly executing the step six and the step seven until N remains in the candidate antenna set_r-NB antennas, where Nr is the number of antennas to be selected;

step eight: combining the selected antenna set in the first selection round and the candidate antenna set in the second selection round to obtain the finally selected N_rRoot receiving antenna H_sel。

Preferably, the first N is randomly selected at the receiving end_BRoot antenna as first round selected antenna set H_φWherein the unselected antennas areThe method comprises the following steps:

at the receiving end, N before random selection_BRoot antenna as initial selected antenna set H_φ＝H(1∶N_B,: ) Then the unselected antenna isH_φAndrespectively is N_B×N_B，(N_A-N_B)×N_BWhere H is a dimension N_A×N_BUplink channel matrix, N in uplink_AIs the number of receiving antennas, N_BIs the number of users.

Preferably, the calculation Q ═ HH_φ ¹Finding the element | Q with the largest absolute value in Q_i，jAnd recording its location, including:

based on the formulaCalculating Q, searching the element with the maximum absolute value in Q and recording the position [ i, j ] of the element]＝arg max(max|Q_i，j|) wherein Q has a dimension of N_A×N_B，|Q_i，jI represents the absolute value of the ith row and jth column element in Q, and i is 1,2_A，j＝1，2，...，N_B，Is H_φThe inverse matrix of (c).

Preferably, the if | Q_i，jIf | is greater than 1, exchanging vectors of the ith row and the jth row in the channel matrix H, returning to the step two, and repeatedly executing the step two and the step three until | Q_i，j1, comprising:

if | Q_i，jIf | is greater than 1, the ith and jth row vectors in H are exchanged to obtain a new larger H_φ；

Go back toStep two, and repeatedly executing the step two and the step three until | Q_i，jGet 1, get the optimal antenna set H for the first round of selection_φ。

Preferably, the unselected antenna is connected to the antennaPerforming a second round of receiving antenna selection as a candidate antenna set ω, comprising:

based on the formulaInitializing B, wherein_ADRepresenting the quantization accuracy, P, of the low-resolution analog-to-digital converter at the receiving end_URepresenting the transmit power, D representing the noise covariance matrix, D^-1The inverse matrix representing D is then used,representsTranspose conjugate matrix of (2), antenna not to be selectedA second round of antenna selection is performed as a candidate antenna set ω, where ω ═ 1,2_A-N_B}。

Preferably, the channel gains c corresponding to all antennas in the candidate antenna set are calculated respectively_kAnd quantization error d_kThe method comprises the following steps:

based on the formulaCalculating the channel gain c corresponding to all antennas in the candidate antenna set_kBased on the formulaCalculating quantization errors d corresponding to all antennas in the candidate antenna set_kWhere k ∈ ω, c_kAnd d_kRespectively represent the channel gain and quantization error corresponding to the k-th candidate antenna,representsThe k-th row vector of (1).

Preferably, the selection is such that c_k/d_kThe smallest antenna is deleted from the candidate antenna set, and the method comprises the following steps:

selecting c according to the converted objective function_k/d_kMinimum antenna k^*Wherein k is^*Satisfy k^*＝arg min c_k/d_kAnd deleting omega-omega \ k from the candidate antenna set^*。

Preferably, the relevant parameters are updated, the step six is returned, and the step six and the step seven are repeatedly executed until N remains in the candidate antenna set_r-N_BA root antenna, comprising:

based on the formulaUpdating a based on formula B ═ B + aa^HUpdate B based on formulaUpdate c_kAnd returning to the step six, and repeatedly executing the step six and the step seven until N remains in the candidate antenna set_r-N_BA root antenna, wherein,to representK of (1)^*The number of the row vectors is,denotes the kth^*Root candidate dayThe quantization error of the line is determined,denotes the kth^*Gain of root candidate antenna, a^HRepresenting the transposed conjugate of a.

Preferably, the selected antenna set in the first selection round and the candidate antenna set in the second selection round are combined to obtain the last selected N_rRoot receiving antenna H_selThe method comprises the following steps:

combining the selected antenna sets H in the first round of selection_φAnd the remaining candidate antenna sets in the second round of selectionObtaining the finally selected N_rRoot receiving antenna H_sel＝[H_φ；H_ω]。

In summary, the invention discloses a greedy selection method for receiving antennas based on quantization sensing, which adopts two rounds of antenna selection at the receiving end of an uplink, firstly uses a square maximum-volume (SMV) algorithm, and firstly randomly selects N_BThe volume of the selected antenna matrix is continuously increased through iterative exchange by the root antenna, and N selected in the first round is globally optimized_BThe first round of antenna selection not only effectively improves the safety capacity of the system, but also reduces the size of a candidate antenna set selected by the second round of antenna selection so as to reduce the computational complexity, and N is selected by comprehensively considering the influence of channel gain and quantization error in the second round of antenna selection_r-N_BThe safety capacity of the system is further improved by the root antenna.

Drawings

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

FIG. 1 is a diagram of an antenna selection model for a massive MIMO system according to the present disclosure;

FIG. 2 is a flowchart of an embodiment of a method for greedy selection of receive antennas based on quantized sensing according to the present disclosure;

FIG. 3 is N_A＝130，N_B＝10，NE＝4，P_U＝3dB，α_ADWhen the signal level is 3dB, a system average safety capacity comparison graph of a receiving antenna greedy selection method based on quantization perception and the existing antenna selection method is obtained;

FIG. 4 is N_A＝128，N_r＝24，N_B＝12，N_E＝4，α_ADWhen m1 is 2 and m2 is 1, a comparison graph of the system average safety capacity of the receiving antenna greedy selection method based on the quantized sensing and the existing antenna selection method is shown;

FIG. 5 is N_A＝128，N_r＝20，N_B＝8，N_E＝3，P_UWhen m1 is 1 and m2 is 2, the invention relates to a comparison graph of average safe capacity of a system based on quantized sensing greedy selection method of receiving antennas and the existing antenna selection method.

Detailed Description

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 only a part of the embodiments of the present invention, and not all of the embodiments. 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.

As shown in fig. 1 and 2, in the uplink, a receiving antenna greedy selection method based on quantized sensing may include the following steps:

the method comprises the following steps: at the receiving end, N before random selection_BRoot antenna as first round selected antenna set H_φWherein the unselected antennas areN_BThe number of the users;

specifically, the first N is randomly selected at the receiving end_BRoot antenna as initial selected antenna set H_φ＝H(1：N_B,: ) Then the unselected antenna isH_φAndrespectively is N_B×N_B，(N_A-N_B)×N_BWhere H is a dimension N_A×N_BUplink channel matrix, N in uplink_AIs the number of receiving antennas, N_BIs the number of users.

Step two: computingFinding the element | Q with the largest absolute value in Q_i，jAnd recording its position, wherein Q_i，jRepresents the ith row and jth column element in Q;

in particular, based on formulasCalculating Q, searching the element with the maximum absolute value in Q and recording the position [ i, j ] of the element]＝arg max(max|Q_i，j|) wherein Q has a dimension of N_A×N_B，|Q_i，jI represents the absolute value of the ith row and jth column element in Q, and i is 1,2_A，j＝1，2，...，N_B，Is H_φThe inverse matrix of (c).

Step three: if | Q_i，jIf | is greater than 1, exchanging the ith row and the jth row in the channel matrix H, returning to the step two, and repeatedly executing the step two and the step three until | Q |_i，j|＝1。

Specifically, if | Q_i，jIf | is greater than 1, exchange the ith row and the jth row in H to obtain a new larger H_φ；

Returning to the second step, and repeatedly executing the second step and the third step until the absolute value of Q is obtained_i，jGet 1, get the optimal antenna set H for the first round of selection_φ。

Step four: coupling the unselected antennaPerforming a second round of receiving antenna selection as a candidate antenna set omega;

in particular, based on formulasInitializing B, wherein_ADRepresenting the quantization accuracy, P, of a receiving-side low-resolution analog-to-digital converter (ADC)_URepresents the total transmit power, D represents the noise covariance matrix (including Gaussian noise and quantization noise), D^-1The inverse matrix representing D is then used,representsTranspose conjugate matrix of (2), antenna not to be selectedA second round of antenna selection is performed as a candidate antenna set ω, where ω ═ 1,2_A-N_B}。

Step five: respectively calculating the channel gains c corresponding to all antennas in the candidate antenna set_kAnd quantization error d_k；

In particular, based on formulasCalculating the channel gain c corresponding to all antennas in the candidate antenna set_kBased onFormula (II)Calculating quantization errors d corresponding to all antennas in the candidate antenna set_kWhere k ∈ ω, c_kAnd d_kRespectively represent the channel gain and quantization error corresponding to the k-th candidate antenna,representsThe k-th row vector of (1).

Step six: selecting c_k/d_kThe smallest antenna is deleted from the candidate antenna set;

specifically, c is selected according to the converted objective function_k/d_kMinimum antenna k^*Wherein k is^*Satisfy k^*＝arg min c_k/d_kAnd deleting omega-omega \ k from the candidate antenna set^*。

Step seven: updating relevant parameters, returning to the step six, and repeatedly executing the step six and the step seven until N remains in the candidate antenna set_r-N_BA root antenna, wherein Nr is the number of antennas to be selected;

in particular, based on formulasUpdating a based on formula B ═ B + aa^HUpdate B based on formulaUpdate c_kAnd returning to the step six, and repeatedly executing the step six and the step seven until N remains in the candidate antenna set_r-N_BA root antenna, wherein,to representK of (1)^*The number of the row vectors is,denotes the kth^*The quantization error of the root candidate antenna is,denotes the kth^*Gain of root candidate antenna, a^HRepresenting the transposed conjugate of a.

Step eight: combining the selected antenna set in the first selection round and the candidate antenna set in the second selection round to obtain the finally selected N_rRoot receiving antenna

Specifically, the selected antenna sets H in the first selection round are combined_φAnd the remaining candidate antenna sets in the second round of selectionObtaining the finally selected N_rRoot receiving antenna H_sel＝[H_φ；H_ω]。

It can be seen from fig. 3 that when the number of selected receiving antennas in the uplink increases, the system security capacity of the greedy selection method for receiving antennas based on quantization sensing of the present invention is superior to that of the random antenna selection and decreasing antenna selection methods under different channel fading coefficients.

It is shown from fig. 4 that the system security capacity of the receiving antenna selection method of the present invention is always better than the random antenna selection and the decremental antenna selection methods when the transmission power is increased, whether in the presence or absence of eavesdropping.

It can be seen from fig. 5 that when the ADC quantization bit is 1dB to 8dB, the system security capacity of all antenna selection methods increases with the increase of the quantization bit, and when the ADC quantization bit is greater than 8, the system security capacity of each antenna selection method does not increase any more, which indicates that it is advisable to use a low-resolution ADC at the base station, and in this process, the system security capacity of the greedy receiving antenna selection method based on quantization sensing of the present invention is always better than that of other antenna selection methods.

In conclusion, the invention can effectively reduce the hardware complexity, cost and power consumption of the system.

The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.

Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.