CN112073100B - Millimeter wave wireless energy-carrying safe communication method and device - Google Patents

Millimeter wave wireless energy-carrying safe communication method and device Download PDF

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CN112073100B
CN112073100B CN202010928154.2A CN202010928154A CN112073100B CN 112073100 B CN112073100 B CN 112073100B CN 202010928154 A CN202010928154 A CN 202010928154A CN 112073100 B CN112073100 B CN 112073100B
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precoding
millimeter wave
rank
wireless energy
rate
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CN112073100A (en
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朱政宇
郝万明
孙钢灿
马梦园
王忠勇
刘沛佳
申凌峰
赵飞
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Zhengzhou University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention relates to a millimeter wave wireless energy-carrying safe communication method and a millimeter wave wireless energy-carrying safe communication device, which are used for maximizing the secrecy rate of a system and comprise the following steps: s1: b bit quantization phase shifters are adopted in the full-connection and sub-connection structures to realize analog pre-coding; s2: constructing a digital pre-coding vector, a power splitting rate and an artificial noise covariance matrix combined optimization problem; s3: providing an alternative optimization algorithm based on semi-definite relaxation to obtain a suboptimal solution; s4: an alternating optimization algorithm based on zero-forcing precoding is provided to reduce complexity. The invention combines millimeter waves and SWIPT, and provides a privacy rate maximization method and device based on the millimeter waves SWIPT. Millimeter waves may fill more antennas with smaller physical dimensions; in a multi-user system, the SWIPT interference power is converted into energy of a receiving end, so that the energy efficiency can be improved; with analog/digital hybrid precoding, the number of RF chains required is much smaller than the number of antennas.

Description

Millimeter wave wireless energy-carrying safe communication method and device
Technical Field
The invention relates to the technical field of communication, in particular to a millimeter wave wireless energy-carrying safe communication method and device.
Background
In recent years, millimeter wave (Mmwave) Massive Multiple Input Multiple Output (MMIMO) is considered a promising technology for future wireless communication. In previously studied MIMO systems, a dedicated Radio Frequency (RF) chain was required to connect each antenna. Therefore, the use of a large number of antennas results in immeasurable hardware loss and power consumption. Hybrid Precoding (HP) has been proposed to address this problem. There are two types of HP architectures: full connection and secondary connection. Comparing the two architectures, higher Spectral Efficiency (SE) can be achieved in the fully-connected architecture, while higher Energy Efficiency (EE) can be achieved in the sub-connected architecture.
In particular, Simultaneous Wireless Information and Power Transfer (SWIPT) has been proposed to achieve higher EE. This is a promising technique for extending the life of the battery without increasing the size of the battery. In the SWIPT system, there are two typical schemes: one is Power Splitting (PS), the receiving end implements both Information Decoding (ID) and Energy Harvesting (EH); the other is time switching, and the receiving end performs conversion between ID and EH. In recent years, some research work has considered both millimeter waves and SWIPT.
In addition, Physical Layer Security (PLS) has also been proposed to improve the security of wireless communications. In the millimeter wave system, a larger antenna array, a narrower beam, and a shorter transmission distance all result in a stronger PLS. Injecting Artificial Noise (AN) is considered as AN effective way to improve PLS, i.e. to disturb AN eavesdropper when transmitting a signal.
In a millimeter wave SWIPT system, when an Energy Receiver (ER) and an Information Receiver (IR) are in the same cell, the ER may eavesdrop on the information transmitted to the IRs. To ensure information security, some measures need to be taken to prevent emergency personnel from eavesdropping on the information. To overcome the energy shortage and achieve secure communication, both SWIPT and PLS must be considered.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a millimeter wave wireless energy-carrying safe communication method and device.
The purpose of the invention is realized as follows: a millimeter wave wireless energy-carrying safe communication method comprises
S1: b bit quantization phase shifters are adopted in the full-connection and sub-connection structures to realize analog pre-coding;
s2: constructing a digital pre-coding vector, a power splitting rate and an artificial noise covariance matrix combined optimization problem;
s3: providing an alternative optimization algorithm based on semi-definite relaxation to obtain a suboptimal solution;
s4: an alternating optimization algorithm based on zero-forcing precoding is provided to reduce complexity.
The step S1 specifically includes:
from the channel vector, maximize the array to obtain | hfk|2Obtaining an analog precoding vector, the fully concatenated analog precoding vector f of the ith elementkIs that
Figure BDA0002669194990000021
Wherein
Figure BDA0002669194990000022
Similarly, where i ═ N (k-1)SUB+1,(k-1)NSUB+2,…,kNSUBSimulating a precoding vector fkIs that
Figure BDA0002669194990000023
In the formula (I), the compound is shown in the specification,
Figure BDA0002669194990000024
the same as in (2).
The step S2 specifically includes:
the SR maximization of the system is realized by jointly optimizing the digital precoding vector, the PS ratio and the AN covariance matrix, and the optimization problem can be written as
Figure BDA0002669194990000031
Figure BDA0002669194990000032
Figure BDA0002669194990000033
||Fv||2+Tr(W)≤Pmax, (4d)
Figure BDA0002669194990000034
The step S3 specifically includes:
applying SDR to process rank 1 constraint, then introducing relaxation variable t, the original problem can be rewritten as
Figure BDA0002669194990000035
Figure BDA0002669194990000036
Figure BDA0002669194990000037
Figure BDA0002669194990000038
Tr(FVFH)+Tr(W)≤Pmax, (5e)
Figure BDA0002669194990000039
Figure BDA00026691949900000310
Figure BDA00026691949900000311
Figure BDA00026691949900000312
This convex problem can be solved with CVX, however, weIt is not known whether V is a rank 1 matrix. When the obtained V has a rank of 1, it can be written as V ═ vv by applying eigenvalue decompositionHThus obtaining the optimal v; v is recovered using gaussian randomization approximation when the rank of V is not 1.
The step S4 specifically includes:
and an algorithm based on alternating optimization of ZF precoding is provided to reduce complexity. SINR of IR can be rewritten as
Figure BDA0002669194990000041
Finally, the SR maximization problem can be reduced to
Figure BDA0002669194990000042
Figure BDA0002669194990000043
Figure BDA0002669194990000044
Figure BDA0002669194990000045
p+Tr(W)≤Pmax, (7e)
Figure BDA0002669194990000046
Figure BDA0002669194990000047
Figure BDA0002669194990000048
p≥0. (7i)
This is a convex problem that can be solved with a convex programming solver, such as CVX.
A millimeter wave wireless energy-carrying safety communication device comprises
A pre-coding module: the method is used for realizing analog precoding by adopting a B bit quantization phase shifter in a full-connection and sub-connection structure;
a modeling module: the method is used for constructing a digital pre-coding vector, a power splitting rate and an artificial noise covariance matrix joint optimization problem;
a suboptimal solving module: the method is used for solving a suboptimal solution by an alternative optimization algorithm based on semi-definite relaxation;
a zero forcing solving module: the method is used for reducing complexity by proposing an alternating optimization algorithm based on zero-forcing precoding.
The pre-coding module specifically includes:
a precoding module to maximize the array to obtain the h |, based on the channel vectork|2Obtaining an analog precoding vector, the fully concatenated analog precoding vector f of the ith elementkIs that
Figure BDA0002669194990000051
Wherein
Figure BDA0002669194990000052
Similarly, where i ═ N (k-1)SUB+1,(k-1)NSUB+2,…,kNSUBSimulating a precoding vector fkIs that
Figure BDA0002669194990000053
In the formula (I), the compound is shown in the specification,
Figure BDA0002669194990000054
the same as in (9).
The modeling module specifically comprises:
a modeling module for jointly optimizing the digital pre-coding vector, the PS ratio and the AN covariance matrix to realize the system SR maximization, and the optimization problem can be written as
Figure BDA0002669194990000055
Figure BDA0002669194990000056
Figure BDA0002669194990000057
||Fv||2+Tr(W)≤Pmax, (11d)
Figure BDA0002669194990000058
The suboptimal solving module specifically comprises:
a suboptimum solving module for applying SDR to process rank 1 constraint and then introducing a relaxation variable t, wherein the original problem can be rewritten into
Figure BDA0002669194990000059
Figure BDA0002669194990000061
Figure BDA0002669194990000062
Figure BDA0002669194990000063
Tr(FVFH)+Tr(W)≤Pmax, (12e)
Figure BDA0002669194990000064
Figure BDA0002669194990000065
Figure BDA0002669194990000066
Figure BDA0002669194990000067
This convex problem can be solved with CVX, however, we do not know if V is a rank 1 matrix. When the obtained V has a rank of 1, it can be written as V ═ vv by applying eigenvalue decompositionHThus obtaining the optimal v; v is recovered using gaussian randomization approximation when the rank of V is not 1.
The zero forcing solving module specifically comprises:
and the zero forcing solving module is used for providing an alternating optimization algorithm based on ZF precoding to reduce the complexity.
SINR of IR can be rewritten as
Figure BDA0002669194990000068
Finally, the SR maximization problem can be reduced to
Figure BDA0002669194990000069
Figure BDA00026691949900000610
Figure BDA00026691949900000611
Figure BDA00026691949900000612
p+Tr(W)≤Pmax, (14e)
Figure BDA0002669194990000071
Figure BDA0002669194990000072
Figure BDA0002669194990000073
p≥0. (14i)
This is a convex problem that can be solved with a convex programming solver, such as CVX.
The invention has the beneficial effects that: according to the technical scheme, the millimeter wave wireless energy-carrying safe communication method and device provided by the invention consider two radio frequency chain type antenna structures, and under the condition of considering nonlinear energy acquisition and maximum transmission power constraint, the combined optimization problem of the digital precoding vector, the power division rate and the artificial noise covariance matrix is provided to maximize the secrecy rate of the system.
Drawings
Fig. 1 is a schematic flow chart of a millimeter wave wireless energy-carrying secure communication method according to the present invention;
fig. 2 is a schematic structural diagram of a millimeter wave secure communication system based on SWIPT;
FIG. 3 is a schematic diagram of the structure of two sparse radio frequency chains of a base station;
FIG. 4 is a comparison graph of SR simulations of different structures in the present invention when the maximum transmission power of a base station gradually increases in a Rayleigh fading channel;
FIG. 5 is a comparison graph of SR simulations of different structures in the present invention when the maximum transmission power of a base station in a millimeter wave channel is gradually increased;
FIG. 6 is a comparison graph of SR simulations of different structures in the present invention when the number of ERs in millimeter wave channels increases;
fig. 7 is a schematic structural diagram of a millimeter wave wireless energy-carrying secure communication device according to 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 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 of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a millimeter wave wireless energy-carrying safe communication method and a millimeter wave wireless energy-carrying safe communication device. Under the condition of considering nonlinear energy acquisition and maximum transmitting power constraint, the joint optimization problem of a digital pre-coding vector, a power division rate and an artificial noise covariance matrix is provided to maximize the system secret rate. As shown in fig. 2, the method comprises the steps of:
s1: b bit quantization phase shifters are adopted in the full-connection and sub-connection structures to realize analog pre-coding;
s2: constructing a digital pre-coding vector, a power splitting rate and an artificial noise covariance matrix combined optimization problem;
s3: providing an alternative optimization algorithm based on semi-definite relaxation to obtain a suboptimal solution;
s4: an alternating optimization algorithm based on zero-forcing precoding is provided to reduce complexity.
As shown in fig. 2, the present inventionThe method described in the embodiment is applied to a millimeter wave secure communication system based on SWIPT, and we set L to be 3, including a line of sight (LOS) and two non-line of sight (NLOS) routes. Theta is formed by [0,2 pi ]]. Noise power
Figure BDA0002669194990000081
For the nonlinear EH model, a is 150, b is 0.014, and M is 24 mW. At the same time, the minimum harvesting energy
Figure BDA0002669194990000082
Let us set d λ/2, N64, NRF＝4，K＝2。
In this embodiment, the specific process of step S1 is as follows:
signals received by the user
yb＝hb(Fvx+w)+nb, (15)
Signals received by eavesdroppers
Figure BDA0002669194990000091
Figure BDA0002669194990000092
And x respectively represent a downlink channel vector, a digital precoding vector, and a transmission signal of the k-th user.
Figure BDA0002669194990000093
Is an artificial noise vector generated by the base station. n isb，
Figure BDA0002669194990000094
Is independent and identically distributed Additive White Gaussian Noise (AWGN) defined as
Figure BDA0002669194990000095
Figure BDA0002669194990000096
The representation being implemented by equipower dividers and phase shiftersA precoding matrix is simulated. w is modeled as a random vector with a circularly symmetric complex gaussian distribution,
Figure BDA0002669194990000097
for a fully connected structure, F can be represented as
Figure BDA0002669194990000098
Wherein
Figure BDA0002669194990000099
Is an analog precoding vector associated with the kth RF chain, and
Figure BDA00026691949900000910
also, for a sublinker structure, F can be represented as
Figure BDA00026691949900000911
Wherein N isUSB＝N/NRFThe number of antennas to which each RF chain is connected is the same. In addition, β1Representing the PS ratio, IR splits the signal into ID and EH components. Thus, the EH of the IR may be represented as
Figure BDA00026691949900000912
Previously, the linear model was mainly used for the SWIPT system, and the harvested energy was written as ψLr＝ηPinThe energy conversion efficiency eta is equal to [0,1 ]]。PinIs the input power of the receiver. However, the actual EH model is non-linear. So we use a non-linear model,
Figure BDA00026691949900000913
wherein psinLr(Pin) A non-linear EH function. a, b are constants determined by capacitance, resistance and circuit sensitivity. Specifically, M represents the maximum power collected by the EH circuit.
The transmission power at IR and erk can be given by:
Figure BDA0002669194990000101
Figure BDA0002669194990000102
the energy obtained at IR and ER k is
Figure BDA0002669194990000103
Figure BDA0002669194990000104
The ID signal at IR can be written as
Figure BDA0002669194990000105
Wherein the content of the first and second substances,
Figure BDA0002669194990000106
is additive noise caused by the ID. The SINR of the signal at IR and ER k can be expressed as
Figure BDA0002669194990000107
Figure BDA0002669194990000108
A widely used millimeter wave channel model is used, as shown below
Figure BDA0002669194990000109
Where L is the number of paths, αlThe complex gain of the l-th path is indicated. a (theta)l) Is the antenna array response vector. In view of the uniform linear arrays,
Figure BDA00026691949900001010
where λ represents the wavelength, d represents the antenna spacing, θ1Indicating the azimuth angle (AoD) of the ith path.
Analog precoding is achieved using B-bit quantization phase shifters. When the element is non-zero, for a fully connected architecture, F is
Figure BDA00026691949900001011
Similarly, for the sub-connection architecture, F is
Figure BDA0002669194990000111
From the channel vector, we can maximize the array to obtain | hfk|2And obtaining an analog precoding vector. The fully concatenated analog precoding vector f of this i-th elementkIs that
Figure BDA0002669194990000112
Wherein
Figure BDA0002669194990000113
Similarly, where i ═ N (k-1)SUB+1,(k-1)NSUB+2,…,kNSUBSimulating a precoding vector fkIs that
Figure BDA0002669194990000114
In the formula (I), the compound is shown in the specification,
Figure BDA0002669194990000115
the same as in (33).
In this embodiment, the specific process of step S2 is as follows:
the SR maximization of the system is realized by jointly optimizing a digital precoding vector, a PS ratio and AN AN covariance matrix, and can be written as
Figure BDA0002669194990000116
Figure BDA0002669194990000117
Figure BDA0002669194990000118
||Fv||2+Tr(W)≤Pmax, (35d)
Figure BDA0002669194990000119
(28b) And (28c) is the minimum acquisition energy constraint for IR and ER k, and (28d) is the maximum transmission power constraint for the base station. We can observe larger
Figure BDA00026691949900001110
And
Figure BDA00026691949900001111
higher transmit power is required. When in use
Figure BDA00026691949900001112
And
Figure BDA00026691949900001113
are all very large, PmaxVery little time, equation (28) may not be feasible. Therefore, when (28) for a given PmaxWhen it is not feasible, we can reduce
Figure BDA00026691949900001114
And
Figure BDA00026691949900001115
in this embodiment, the specific process of step S3 is as follows:
define an equivalent channel as
Figure 1
And introduces the auxiliary variables mu and alpha, the original SR maximization problem can be written as
Figure BDA0002669194990000122
Figure BDA0002669194990000123
Figure BDA0002669194990000124
Tr(FVFH)+Tr(W)≤Pmax, (36d)
α≥1/(1-β1), (36e)
μ≥1/β1, (36f)
rank(V)＝1, (36g)
Figure BDA0002669194990000125
(35e)
It can be observed that the original SR maximization problem is a non-convex problem. The following theorem is first applied to turn the objective function into a concave function.
Introduction 1: for function
Figure BDA0002669194990000126
When x is greater than 0, the ratio of x,
Figure BDA0002669194990000127
when x is more than 0, the optimal solution can be obtained.
According to the introduction 1, we set
Figure BDA0002669194990000128
Figure BDA0002669194990000129
Wherein
Figure BDA00026691949900001210
Also, we set
Figure BDA00026691949900001211
Figure BDA00026691949900001212
Wherein
Figure BDA0002669194990000131
According to the maximum and minimum theorem of icon, (29a) can be simplified to
Figure BDA0002669194990000132
Figure BDA0002669194990000133
"ln 2" is deleted from the optimization problem. It can be seen that for (V, W) or
Figure BDA0002669194990000134
It is convex. The fixation (V, W) is optimized
Figure BDA0002669194990000135
Can be written as
Figure BDA0002669194990000136
Figure BDA0002669194990000137
Thus, is fixed
Figure BDA0002669194990000138
The best (V, W) can be obtained.
In addition, by applying (13), psinLr(Pin) Can be expressed as
Figure BDA0002669194990000139
(36b) And (36c) can be rewritten as
Figure BDA00026691949900001310
Figure BDA00026691949900001311
According to the Schulk's theorem, (36e) and (36f) can be converted into
Figure BDA00026691949900001312
Figure BDA00026691949900001313
Finally, applying SDR to process rank 1 constraint, then introducing a relaxation variable t, the original problem can be rewritten as
Figure BDA00026691949900001314
Figure BDA0002669194990000141
(35e),(36d),(36h),(44),(45),(46),(47).
CVX is used to solve this problem. However, we do not know whether V is a rank 1 matrix. When the rank of the obtained V is 1, it can be written as V ═ vv by applying eigenvalue decompositionHThus, an optimum v is obtained. When the resulting rank of V is not 1, V is recovered using gaussian randomization approximation.
In this embodiment, the specific process of step S4 is as follows:
and an algorithm based on alternating optimization of ZF precoding is provided to reduce complexity. SINR of IR can be rewritten as
Figure BDA0002669194990000142
Then, the SR maximization problem can be rewritten as
Figure BDA0002669194990000143
Figure BDA0002669194990000144
Figure BDA0002669194990000145
p+Tr(W)≤Pmax, (50d)
α≥1/(1-β1), (50e)
μ≥1/β1, (50f)
p≥0, (50g)
(35e).
According to theorem 1, (50a) can be written as
Figure BDA0002669194990000146
Figure BDA0002669194990000147
Wherein
Figure BDA0002669194990000151
Figure BDA0002669194990000152
We can observe that it is for (p, W) or
Figure BDA0002669194990000153
Is concave. The fixation (p, W) can be optimized
Figure BDA0002669194990000154
Figure BDA0002669194990000155
Figure BDA0002669194990000156
Then fixed
Figure BDA0002669194990000157
The best (p, W) is obtained. By applying the formula (43), the formulae (44b) and (44c) can be simplified to
Figure BDA0002669194990000158
Figure BDA0002669194990000159
Finally, the SR maximization problem can be reduced to
Figure BDA00026691949900001510
Figure BDA00026691949900001511
(30e),(46),(47),(50d),(50g),(55),(56).
It can be seen that this is a convex problem, so a convex programming solver can be used to solve, for example, CVX.
Fig. 4 compares SDR-based algorithms and ZF-based algorithms in rayleigh fading channels. In fig. 5, the algorithm proposed in the millimeter wave channel is compared. Both fig. 4 and 5 show that SR increases with increasing maximum transmit power. In both rayleigh and millimeter wave channels, the security rate based on the ZF algorithm increases approximately linearly with increasing power. The SR is highest under the digital architecture, but it also causes higher energy consumption and hardware loss. In the digital architecture and the sub-join architecture, the security rate based on the SDR algorithm is higher than that based on the ZF algorithm. However, when the transmission power is high, the full-connected structure based on the ZF precoding algorithm has better confidentiality on both the rayleigh channel and the millimeter wave channel than the SDR algorithm. In the millimeter wave channel, the secrecy rate of the sub-connection architecture based on the ZF precoding algorithm approaches that of the digital architecture.
Fig. 6 depicts SR versus the number of ERs in the millimeter wave channel. Experimental results show that SR increases with the number of ERs, whether SDR-based or ZF-based algorithms. As the number of ERs increases, ZF precoding based algorithms fall faster than SDR based algorithms.
Fig. 7 is a schematic structural diagram of a millimeter wave wireless energy-carrying secure communication device provided in the present invention, including:
a pre-coding module: the method is used for realizing analog precoding by adopting a B bit quantization phase shifter in a full-connection and sub-connection structure;
a modeling module: the method is used for constructing a digital pre-coding vector, a power splitting rate and an artificial noise covariance matrix joint optimization problem;
a suboptimal solving module: the method is used for solving a suboptimal solution by an alternative optimization algorithm based on semi-definite relaxation;
a zero forcing solving module: the method is used for reducing complexity by proposing an alternating optimization algorithm based on zero-forcing precoding.
In this embodiment, the precoding module specifically includes:
a precoding module to maximize the array to obtain the h |, based on the channel vectork|2Obtaining an analog precoding vector, the fully concatenated analog precoding vector f of the ith elementkIs that
Figure BDA0002669194990000161
Wherein
Figure BDA0002669194990000162
Similarly, where i ═ N (k-1)SUB+1,(k-1)NSUB+2,…,kNSUBSimulating a precoding vector fkIs that
Figure BDA0002669194990000171
In the formula (I), the compound is shown in the specification,
Figure BDA0002669194990000172
the same as in (2).
In this embodiment, the modeling module specifically includes:
a modeling module for jointly optimizing the digital pre-coding vector, the PS ratio and the AN covariance matrix to realize the system SR maximization, and the optimization problem can be written as
Figure BDA0002669194990000173
Figure BDA0002669194990000174
Figure BDA0002669194990000175
||Fv||2+Tr(W)≤Pmax, (4d)
Figure BDA0002669194990000176
In this embodiment, the suboptimal solving module specifically includes:
a suboptimum solving module for applying SDR to process rank 1 constraint and then introducing a relaxation variable t, wherein the original problem can be rewritten into
Figure BDA0002669194990000177
Figure BDA0002669194990000178
Figure BDA0002669194990000179
Figure BDA00026691949900001710
Tr(FVFH)+Tr(W)≤Pmax, (5e)
Figure BDA00026691949900001711
Figure BDA00026691949900001712
Figure BDA00026691949900001713
Figure BDA00026691949900001714
This convex problem can be solved with CVX, however, we do not know if V is a rank 1 matrix. When the obtained V has a rank of 1, it can be written as V ═ vv by applying eigenvalue decompositionHThus obtaining the optimal v; v is recovered using gaussian randomization approximation when the rank of V is not 1.
In this embodiment, the zero forcing solving module specifically includes:
and the zero forcing solving module is used for providing an alternating optimization algorithm based on ZF precoding to reduce the complexity.
SINR of IR can be rewritten as
Figure BDA0002669194990000181
Finally, the SR maximization problem can be reduced to
Figure BDA0002669194990000182
Figure BDA0002669194990000183
Figure BDA0002669194990000184
Figure BDA0002669194990000185
p+Tr(W)≤Pmax, (7e)
Figure BDA0002669194990000186
Figure BDA0002669194990000187
Figure BDA0002669194990000188
p ≧ 0. (7i) this is a convex problem that can be solved with a convex programming solver, such as CVX.

Claims (1)

1. A millimeter wave wireless energy-carrying secure communication method, the method comprising:
s1: adopting a B bit quantization phase shifter in a full-connection and sub-connection structure to realize analog precoding, and constructing a secret rate maximization problem of digital precoding vector, power splitting ratio and artificial noise covariance matrix joint optimization;
s2: optimizing a digital pre-coding vector, a power splitting ratio and an artificial noise covariance matrix by using a semi-definite relaxation alternating optimization algorithm to realize the maximization of the system secret rate;
s3: zero-forcing precoding is adopted to reduce algorithm complexity, and digital precoding vectors, power splitting ratio and artificial noise covariance matrix are optimized in a combined mode to achieve maximization of system secret rate;
applying semi-deterministic relaxation to deal with rank 1 constraints, defining V ═ vvH，hb＝hbF，gk＝gkF, then introducing a relaxation variable t, the original problem can be rewritten as
Figure FDA0003349562870000011
Figure FDA0003349562870000012
Figure FDA0003349562870000013
Figure FDA0003349562870000014
Tr(FVFH)+Tr(W)≤Pmax, (1e)
Figure FDA0003349562870000015
Figure FDA0003349562870000016
Figure FDA0003349562870000017
Figure FDA0003349562870000018
When the obtained V has a rank of 1, it can be written as V ═ vv by applying eigenvalue decompositionHThus obtaining the optimal v; recovering V using a gaussian randomization approximation when the rank of V is not 1;
the algorithm of the alternate optimization based on the zero forcing precoding reduces the complexity, and the SINR of the information receiver can be rewritten as
Figure FDA0003349562870000021
Finally, the privacy rate maximization problem can be reduced to
Figure FDA0003349562870000022
Figure FDA0003349562870000023
Figure FDA0003349562870000024
Figure FDA0003349562870000025
p+Tr(W)≤Pmax, (3e)
Figure FDA0003349562870000026
Figure FDA0003349562870000027
Figure FDA0003349562870000028
p≥0. (3i)。
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