CN110601736B - Multi-antenna full-duplex cognitive radio energy capturing and information transmitting method - Google Patents
Multi-antenna full-duplex cognitive radio energy capturing and information transmitting method Download PDFInfo
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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
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
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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
- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
- H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
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- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
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- 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
- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
- H04B7/0891—Space-time diversity
- H04B7/0897—Space-time diversity using beamforming per multi-path, e.g. to cope with different directions of arrival [DOA] at different multi-paths
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- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/155—Ground-based stations
- H04B7/15528—Control of operation parameters of a relay station to exploit the physical medium
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- 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
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Abstract
The invention discloses a multi-antenna full-duplex cognitive radio energy capturing and information transmission method, which is used for improving the physical layer safety transmission rate and energy efficiency of a CR-NOMA system. And carrying out joint optimization on the emission covariance, the power division ratio, the power distribution coefficient and the emission beam forming vector by using a joint iterative algorithm to obtain the physical layer safe transmission method of the optimal multi-antenna full-duplex cognitive radio energy capture system.
Description
Technical Field
The invention belongs to the field of wireless communication, and particularly relates to a multi-antenna full-duplex cognitive radio energy capturing and information transmission method.
Background
With the development of wireless communication technology, wireless access users are increasing, and the energy utilization rate requirements of communication equipment such as base stations are also increasing. However, the actual measurement results show that the energy utilization rate is not high in many communication networks, so that in order to improve the energy utilization rate and save resources, the self-interference capturing is widely focused as a key technology for improving the energy utilization rate, and meanwhile, the non-orthogonal multiple access is widely used in the multi-user transmission process as a technology for improving the frequency spectrum efficiency, and the self-interference capturing is applied to the non-orthogonal multiple access technology, so that the energy efficiency is improved and the user access quantity is increased.
Meanwhile, a non-orthogonal multiple access (CR-NOMA) system based on a cognitive network has two problems to be solved in the signal transmission process, and on one hand, the confidentiality of a system user is improved. On the other hand, a large amount of NOMA users are accessed to generate a large amount of energy consumption, the energy utilization rate is low, and meanwhile, the limited energy in the cognitive network limits the network capacity to be further improved.
Disclosure of Invention
First, the technical problem to be solved
Aiming at the confidentiality problem of the CR-NOMA system user based on the cognitive network, in the existing research, a manual noise auxiliary cooperative interference scheme is provided through a resource distribution algorithm of the CR-NOMA system, so that the physical layer security of a primary network and a secondary network is improved. In the self-interference energy harvesting process, the repeater may act as a potential eavesdropper, so the present invention derives a closed-form expression of the transmit signal covariance and the power split ratio based on this first. And then, calculating a power distribution coefficient and a power division ratio by using an iterative algorithm so as to maximize confidentiality. And then the energy efficiency is improved by the self-interference capturing technology of the energy receiver at the relay.
The invention discloses a multi-antenna full-duplex cognitive radio energy capturing and information transmission method for improving the safety of a multi-antenna full-duplex cognitive radio energy capturing system.
(II) technical scheme
In order to solve the technical problems, the invention discloses a multi-antenna full duplex cognitive radio energy capturing and information transmission method, which comprises the following steps:
step A, constructing a multi-antenna full-duplex cognitive radio energy capturing system, determining a transmission system model according to a transmission mechanism, and calculating a received signal of each node;
step B, corresponding transmission rates are calculated according to the received signals of the cognitive user and the relay energy receiver;
step C, determining physical layer safety indexes of the cognitive user of the system according to transmission rates of the cognitive user and the relay energy receiver;
step D, changing the user physical layer security index into an equation optimal problem to solve, and obtaining the optimal system physical layer security transmission rate by optimizing the transmission covariance beam forming, the power division ratio of the receiving end, the power distribution coefficient and the transmission beam forming vector;
e, obtaining an optimal solution of the safe transmission rate of the physical layer of the system through a joint optimization algorithm;
the step A specifically comprises the following steps:
a1, constructing multi-antenna full duplex cognitive radioAn electric energy capturing system model comprising a Primary User (PU), a Cognitive Base Station (CBS), a plurality of secondary users (CU m ) A relay (S), wherein the master user respectively transmits information with the cognitive base station and the cognitive user through the relay, and a NOMA transmission mode is adopted in the information transmission process;
a2, for the system model of step A1, the transmission power of the relay and the cognitive base station can be obtained by the following formulah cp And h sp Representing the channel from the cognitive base station to the primary user and the channel relayed to the primary user, respectively, I th The interference level, P, of the primary user s Transmit power for relay, Q 0 For covariance of a signal x transmitted by a cognitive base station, tr (·) is a matrix tracing operation, i|·i|i| 2 Representing the square of the matrix second moment;
a3, obtaining the signal received by the mth cognitive user as the signal received by the mth cognitive user under the condition of utilizing the power domain for the system model in the step A1Relaying the received signal is +.>γ m Is the power distribution coefficient, H m Is a transmission channel relayed to the cognitive user m, s m Is the signal sent by the cognitive base station to the mth cognitive user, n D Is baseband additive Gaussian white noise, w m Is the transmit beam vector at the relay, ρ 0 Represents the power division ratio at the relay, H 0 Is a cognitive base station to relay transmission channel, n s1 And n s2 Respectively Gaussian noise and noise on line, n s1 ～CN(0,Iσ 2 )，n s2 ～CN(0,Iσ 2 )，σ 2 Is variance, I is identity matrix;
the step B specifically comprises the following steps:
b1, the power division strategy of the steps A1 and A3 can be obtainedThe energy obtaining formula at the relay is E s ＝η(1-ρ 0 )[tr(H 0 Q 0 H 0 H )+||H e || 2 P s ]Eta is the energy conversion efficiency, H e Is a loop-back channel between relay antennas;
b2, decoding the signal of the cognitive user with the best channel state by the power allocation strategy obtained in the step B1 through the serial interference deletion, thereby determining the transmission rate of the cognitive user with the best channel state according to the following formulaAnd the transmission rate at the relay is +.>M is the number of cognitive users, and mu is the power division ratio;
b3, because the probability of successfully decoding the needed information by the relay energy receiving end is high, the transmission rate of the energy receiver can be obtained by analogy
The step C specifically comprises the following steps:
c1, determining the physical layer safe transmission rate of the user as the transmission rate of the cognitive user with the best channel state and the energy receiver at the relay
C2, according to the physical layer safe transmission rate formula obtained by C1 and the parameter Q established by the system model of step A1 0 ，ρ 0 ，γ m ，w m Determining an optimal solution corresponding to the maximization of the physical layer safe transmission rate;
c3, because the whole system maximizes the safe transmission rate of the physical layer and is limited by other conditions, the constraint condition is E s ≥E min ，In which E is min For the threshold of the lowest energy capture, when m=1, the power distribution coefficient γ m The sum of (2) is 1;
the step D specifically comprises the following steps:
d1, converting the problem into an equation optimal problem to solve the problem because the problem of the optimal transmission rate of the physical layer safety is more in consideration, obtaining a local optimal solution of the physical layer safety by optimizing the transmission covariance, and firstly utilizing a water injection algorithm to optimize the transmission signal optimal covarianceThe system energy consumption establishes a functional relation to obtain +.>Wherein V is p Is H 0 Is =diag (p) 1 ,…,p t ) Diag (·) represents a diagonal matrix, < ->Where i=1, …, t, v represents the average water-filling power of the power-filling algorithm;
d2, obtaining the local optimal solution of the physical layer safe transmission rate by optimizing the power division ratio, firstly, according to the decoding forwarding protocol andthe constraint can determine the optimal power division ratio +.>Is->
D3, optimizing the power distribution coefficient, finding the power distribution coefficient gamma by logarithmic property m Secure transmission rate R with physical layer sec The relationship between the relationship and the relationship,
d4, finally, the power distribution coefficient gamma is deduced m Optimal solution is
D5, optimizing the emission beam forming vector, firstly, under the condition of given power distribution coefficient, obtaining w by utilizing a semi-definite relaxation algorithm m And (3) withIs a functional formula of +.>Because one constraint condition is a non-convex problem, after the constraint condition is transformed, the genetic algorithm is used to calculate +.>Is the optimal solution of (a);
the step E specifically comprises the following steps:
e1, in order to maximize the safe transmission rate of the physical layer of the user, the covariance Q of the transmission signal x of the cognitive base station needs to be respectively calculated 0 Power split ratio ρ at relay 0 Power distribution coefficient gamma m And transmit beamforming vector w at relay m Performing joint optimization, first initializing w m Order-makingWhere ζ is the tolerance;
e2, calculating an optimal power division ratio ρ 0 And covariance Q of cognitive base station transmit signal x 0 ；
E3, finally according to the obtained ρ 0 、Q 0 、Continuously iterating updatesAnd the physical layer safe transmission rate is obtained, so that the maximum value of the physical layer safe transmission rate is obtained.
(III) beneficial effects
In order to improve the physical layer safe transmission rate and the energy efficiency of the CR-NOMA system, the traditional half duplex is replaced by full duplex in the multi-antenna cognitive radio energy capture system, and the self-interference capture technology is adopted at the relay energy receiver to replace the self-interference deletion technology, so that the physical layer safety performance of system users is improved, and the energy efficiency of the system is improved. And carrying out joint optimization on the emission covariance, the power division ratio, the power distribution coefficient and the emission beam forming vector by using a joint iterative algorithm to obtain the physical layer safe transmission method of the optimal multi-antenna full-duplex cognitive radio energy capture system.
Drawings
FIG. 1 is a flow chart of a method of an embodiment of the present invention.
Detailed Description
The invention discloses a multi-antenna full duplex cognitive radio energy capturing and information transmitting method, which comprises the following steps:
step A, constructing a multi-antenna full-duplex cognitive radio energy capturing system, determining a transmission system model according to a transmission mechanism, and calculating a received signal of each node;
step B, corresponding transmission rates are calculated according to the received signals of the cognitive user and the relay energy receiver;
step C, determining physical layer safety indexes of the cognitive user of the system according to transmission rates of the cognitive user and the relay energy receiver;
step D, changing the user physical layer security index into an equation optimal problem to solve, and obtaining the optimal system physical layer security transmission rate by optimizing the transmission covariance beam forming, the power division ratio of the receiving end, the power distribution coefficient and the transmission beam forming vector;
e, obtaining an optimal solution of the safe transmission rate of the physical layer of the system through a joint optimization algorithm;
the step A specifically comprises the following steps:
a1, construction for several daysA model of a linear full duplex cognitive radio energy capture system, which comprises a Primary User (PU), a Cognitive Base Station (CBS), a plurality of secondary users (CU) m ) A relay (S), wherein the master user respectively transmits information with the cognitive base station and the cognitive user through the relay, and a NOMA transmission mode is adopted in the information transmission process;
a2, for the system model of step A1, the transmission power of the relay and the cognitive base station can be obtained by the following formulah cp And h sp Representing the channel from the cognitive base station to the primary user and the channel relayed to the primary user, respectively, I th The interference level, P, of the primary user s Transmit power for relay, Q 0 For covariance of a signal x transmitted by a cognitive base station, tr (·) is a matrix tracing operation, i|·i|i| 2 Representing the square of the matrix second moment;
a3, obtaining the signal received by the mth cognitive user as the signal received by the mth cognitive user under the condition of utilizing the power domain for the system model in the step A1Relaying the received signal is +.>γ m Is the power distribution coefficient, H m Is a transmission channel relayed to the cognitive user m, s m Is the signal sent by the cognitive base station to the mth cognitive user, n D Is baseband additive Gaussian white noise, w m Is the transmit beam vector at the relay, ρ 0 Represents the power division ratio at the relay, H 0 Is a cognitive base station to relay transmission channel, n s1 And n s2 Respectively Gaussian noise and noise on line, n s1 ～CN(0,Iσ 2 )，n s2 ～CN(0,Iσ 2 )，σ 2 Is variance, I is identity matrix;
the step B specifically comprises the following steps:
b1, power division by steps A1 and A3The cutting strategy can obtain the energy obtaining formula of the relay as followsEta is the energy conversion efficiency, H e Is a loop-back channel between relay antennas;
b2, decoding the signal of the cognitive user with the best channel state by the power allocation strategy obtained in the step B1 through the serial interference deletion, thereby determining the transmission rate of the cognitive user with the best channel state according to the following formulaAnd the transmission rate at the relay is +.>M is the number of cognitive users, and mu is the power division ratio;
b3, because the probability of successfully decoding the needed information by the relay energy receiving end is high, the transmission rate of the energy receiver can be obtained by analogy
The step C specifically comprises the following steps:
c1, determining the physical layer safe transmission rate of the user as the transmission rate of the cognitive user with the best channel state and the energy receiver at the relay
C2, according to the physical layer safe transmission rate formula obtained by C1 and the parameter Q established by the system model of step A1 0 ，ρ 0 ，γ m ，w m Determining an optimal solution corresponding to the maximization of the physical layer safe transmission rate;
c3, because the whole system maximizes the safe transmission rate of the physical layer and is limited by other conditions, the constraint condition is E s ≥E min ，In which E is min For the threshold of the lowest energy capture, when m=1, the power distribution coefficient γ m The sum of (2) is 1;
the step D specifically comprises the following steps:
d1, converting the problem into an equation optimal problem to solve the problem because the problem of the optimal transmission rate of the physical layer safety is more in consideration, obtaining a local optimal solution of the physical layer safety by optimizing the transmission covariance, and firstly utilizing a water injection algorithm to optimize the transmission signal optimal covarianceThe system energy consumption establishes a functional relation to obtain +.>Wherein V is p Is H 0 Is =diag (p) 1 ,…,p t ) Diag (·) represents a diagonal matrix, < ->Where i=1, …, t, v represents the average water-filling power of the power-filling algorithm;
d2, obtaining the local optimal solution of the physical layer safe transmission rate by optimizing the power division ratio, firstly, according to the decoding forwarding protocol andthe constraint can determine the optimal power division ratio +.>Is->
D3, optimizing the power distribution coefficient, finding the power distribution coefficient gamma by logarithmic property m Secure transmission rate R with physical layer sec The relationship between the relationship and the relationship,
d4, finally, the power distribution coefficient gamma is deduced m Optimal solution is
D5, optimizing the emission beam forming vector, firstly, under the condition of given power distribution coefficient, obtaining w by utilizing a semi-definite relaxation algorithm m And (3) withIs a functional formula of +.>Because one constraint condition is a non-convex problem, after the constraint condition is transformed, the genetic algorithm is used to calculate +.>Is the optimal solution of (a);
the step E specifically comprises the following steps:
e1, in order to maximize the safe transmission rate of the physical layer of the user, the covariance Q of the transmission signal x of the cognitive base station needs to be respectively calculated 0 Power split ratio ρ at relay 0 Power distribution coefficient gamma m And transmit beamforming vector w at relay m Performing joint optimization, first initializing w m Order-makingWhere ζ is the tolerance;
e2, calculating an optimal power division ratio ρ 0 And covariance Q of cognitive base station transmit signal x 0 ；
E3, finally according to the obtained ρ 0 、Q 0 、And continuously and iteratively updating the physical layer safe transmission rate so as to obtain the maximum value of the physical layer safe transmission rate.
The above embodiments are only for illustrating the present invention, not for limiting the present invention, and various changes and modifications may be made by one of ordinary skill in the relevant art without departing from the spirit and scope of the present invention, and therefore, all equivalent technical solutions are also within the scope of the present invention, and the scope of the present invention is defined by the claims.
Claims (1)
1. The multi-antenna full duplex cognitive radio energy capturing and information transmission method is characterized by comprising the following steps of:
step A, constructing a multi-antenna full-duplex cognitive radio energy capturing system, determining a transmission system model according to a transmission mechanism, and calculating a received signal of each node;
step B, corresponding transmission rates are calculated according to the received signals of the cognitive user and the relay energy receiver;
step C, determining physical layer safety indexes of the cognitive user of the system according to transmission rates of the cognitive user and the relay energy receiver;
step D, changing the user physical layer security index into an equation optimal problem to solve, and obtaining the optimal system physical layer security transmission rate by optimizing the transmission covariance beam forming, the power division ratio of the receiving end, the power distribution coefficient and the transmission beam forming vector;
e, obtaining an optimal solution of the safe transmission rate of the physical layer of the system through a joint optimization algorithm;
the step A specifically comprises the following steps:
a1, constructing a multi-antenna full duplex cognitive radio energy capture system model, wherein the model comprises a main user (PU), a Cognitive Base Station (CBS) and a plurality of secondary users (CU m ) A relay (S), wherein the master user respectively transmits information with the cognitive base station and the cognitive user through the relay, and a NOMA transmission mode is adopted in the information transmission process;
a2, for the system model of step A1The transmit power of the relay and cognitive base stations can be derived from thish cp And h sp Representing the channel from the cognitive base station to the primary user and the channel relayed to the primary user, respectively, I th The interference level, P, of the primary user s Transmit power for relay, Q 0 For covariance of a signal x transmitted by a cognitive base station, tr (·) is a matrix tracing operation, i|·i|i| 2 Representing the square of the matrix second moment;
a3, obtaining the signal received by the mth cognitive user as the signal received by the mth cognitive user under the condition of utilizing the power domain for the system model in the step A1Relaying the received signal is +.>γ m Is the power distribution coefficient, H m Is a transmission channel relayed to the cognitive user m, s m Is the signal sent by the cognitive base station to the mth cognitive user, n D Is baseband additive Gaussian white noise, w m Is the transmit beam vector at the relay, ρ 0 Represents the power division ratio at the relay, H 0 Is a cognitive base station to relay transmission channel, n s1 And n s2 Respectively Gaussian noise and noise on line, n s1 ～CN(0,Iσ 2 )，n s2 ～CN(0,Iσ 2 )，σ 2 Is variance, I is identity matrix;
the step B specifically comprises the following steps:
b1, the energy obtaining formula at the relay can be obtained through the power division strategy of the steps A1 and A3 as followsEta is the energy conversion efficiency, H e Is a loop-back channel between relay antennas;
b2, the power obtained in step B1The allocation strategy decodes the signal of the cognitive user with the best channel state through the serial interference deletion, so that the transmission rate of the cognitive user with the best channel state can be determined by the following sub-modesAnd the transmission rate at the relay is +.>M is the number of cognitive users, and mu is the power division ratio;
b3, because the probability of successfully decoding the needed information by the relay energy receiving end is high, the transmission rate of the energy receiver can be obtained by analogy
The step C specifically comprises the following steps:
c1, determining the physical layer safe transmission rate of the user as the transmission rate of the cognitive user with the best channel state and the energy receiver at the relay
C2, according to the physical layer safe transmission rate formula obtained by C1 and the parameter Q established by the system model of step A1 0 ，ρ 0 ，γ m ，w m Determining an optimal solution corresponding to the maximization of the physical layer safe transmission rate;
c3, because the whole system maximizes the safe transmission rate of the physical layer and is limited by other conditions, the constraint condition is E s ≥E min ，In which E is min For the threshold of the lowest energy capture, when m=1, the power distribution coefficient γ m The sum of (2) is 1;
the step D specifically comprises the following steps:
d1, converting the problem into an equation optimal problem to solve the problem because the problem of the optimal transmission rate of the physical layer safety is more in consideration, obtaining a local optimal solution of the physical layer safety by optimizing the transmission covariance, and firstly utilizing a water injection algorithm to optimize the transmission signal optimal covarianceThe system energy consumption establishes a functional relation to obtain +.>Wherein V is p Is H 0 Is =diag (p) 1 ,…,p t ) Diag (·) represents a diagonal matrix, < ->Where i=1, …, t, v represents the average water-filling power of the power-filling algorithm;
d2, obtaining the local optimal solution of the physical layer safe transmission rate by optimizing the power division ratio, firstly, according to the decoding forwarding protocol andthe constraint can determine the optimal power division ratio +.>Is->
D3, optimizing the power distribution coefficient, finding the power distribution coefficient gamma by logarithmic property m Secure transmission rate R with physical layer sec The relationship between the relationship and the relationship,
d4, finally, the power distribution coefficient gamma is deduced m Optimal solution is
D5, optimizing the emission beam forming vector, firstly, under the condition of given power distribution coefficient, obtaining w by utilizing a semi-definite relaxation algorithm m And (3) withIs a functional formula of +.>Because one constraint condition is a non-convex problem, after the constraint condition is transformed, the genetic algorithm is used to calculate +.>Is the optimal solution of (a);
the step E specifically comprises the following steps:
e1, in order to maximize the safe transmission rate of the physical layer of the user, the covariance Q of the transmission signal x of the cognitive base station needs to be respectively calculated 0 Power split ratio ρ at relay 0 Power distribution coefficient gamma m And transmit beamforming vector w at relay m Performing joint optimization, first initializing w m Order-makingWhere ζ is the tolerance;
e2, calculating an optimal power division ratio ρ 0 And covariance Q of cognitive base station transmit signal x 0 ；
E3, finally according to the obtained ρ 0 、Q 0 、And continuously and iteratively updating the physical layer safe transmission rate so as to obtain the maximum value of the physical layer safe transmission rate.
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