CN108990070A - A kind of power distribution method of the cognitive radio networks based on NOMA technology - Google Patents
A kind of power distribution method of the cognitive radio networks based on NOMA technology Download PDFInfo
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- 238000005457 optimization Methods 0.000 claims abstract description 22
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/14—Spectrum sharing arrangements between different networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/18—TPC being performed according to specific parameters
- H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
- H04W52/241—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account channel quality metrics, e.g. SIR, SNR, CIR, Eb/lo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/04—Wireless resource allocation
- H04W72/044—Wireless resource allocation based on the type of the allocated resource
- H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/50—Allocation or scheduling criteria for wireless resources
- H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
- H04W72/541—Allocation or scheduling criteria for wireless resources based on quality criteria using the level of interference
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- 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
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Abstract
The invention discloses a kind of power distribution method of cognitive radio networks based on NOMA technology, this method sequentially includes the following steps: and 1) establishes system model, the signal intelligence of secondary user's of the analysis in fringe region；2) objective optimization model is established；3) objective optimisation problems are solved, the transmission power of maximum information transfer rate and primary user base station to secondary user's optimizes.Objective function proposed by the present invention is the convex optimization problem an of standard, can be with direct solution.The present invention can study the optimal power allocation problem between secondary user's transmitting terminal and relay node under the premise of ensuring primary user's communication quality, realize the maximization of secondary user's handling capacity.
Description
Technical field
The present invention relates to wireless communication fields, are specifically related to a kind of cognition wireless based on non-orthogonal multiple access technology
The power distribution method of electric network.
Background technique
Non-orthogonal multiple access technology (NOMA) and cognitive radio technology can effectively improve spectrum efficiency and user
Transmission rate.With the rapid development of mobile communication, wireless data service amount is in explosive growth, this just needs spectrum efficiency
Higher, rate faster wireless network meets transmission demand.Non-orthogonal multiple access technology (NOMA) is applied to
The handling capacity and frequency spectrum effect of system can be increased substantially in cognitive radio networks under Underlay frequency spectrum share mode
Rate.
However in such communication mode, because aware base station can generate interference to primary user, aware base station is necessary
Above-mentioned interference is set to be less than interference threshold, in order to avoid influence primary user's communication.But if the transmission power of aware base station is too small, marginal zone
The signal-to-noise ratio of the secondary user's in domain is too small, and targeted rate, which is not achieved, can then interrupt, and influences the communication quality of system.
Summary of the invention
In view of above-mentioned deficiencies of the prior art, the purpose of the present invention is directed to a kind of cognition wireless based on NOMA technology
The power distribution method of electric network, and the cognitive radio networks are also based on the realization of non-orthogonal multiple access technology.
In order to realize the above target, the technical solution adopted by the present invention are as follows: a kind of cognitive radio based on NOMA technology
The power distribution method of network, it is characterised in that include the following steps:
Step 1: establishing the cognitive radio networks under the Underlay frequency spectrum share mode accessed based on non-orthogonal multiple
Down link model, under the premise of certain, secondary user's signal is passed in the communication quality for guaranteeing primary user cognitive base station
It is sent to relaying, relaying expand forwarding secondary user's signal to secondary user's using non-orthogonal multiple；Cognitive radio networks
Analysis relaying and secondary user's received signal；
Step 2: optimization problem model is established, with the throughput-maximized for optimization aim of secondary user's, and to guarantee to recognize
Know the lowest signal-to-noise of base station, the transimission power of relaying and secondary user's as optimal conditions；
Step 3: solving optimization problem, realizes effectively handling up for secondary user's by power allocation factor and channel conditions
The optimization aim of amount.
As the further refinement scheme of power distribution method of the present invention, the signal of relay reception described in step 1 are as follows:
WhereinFading coefficients for cognitive base station towards fading channel between relaying, a1And a2It is secondary user's 1 respectively
With the power partition coefficient of secondary user's 2, and a1+a2=1, psFor the transmission power of cognitive base station, s1And s2It is cognition base respectively
Station is sent to the signal of secondary user's 1 and secondary user's 2, and n is the additive white Gaussian noise that mean value is 0, variance is 1, spIt is main
The signal of user base station transmitting, ITIt is large scale path loss, andα is path loss index, dp,RIt is primary user
The distance between base station and relaying.
As the further refinement scheme of power distribution method of the present invention, 1 received signal of secondary user's described in step 1
Are as follows:2 received signal of secondary user's are as follows:Wherein G is the amplification factor of relaying,WithRespectively relay the fading coefficients respectively for fading channel between secondary user's 1, secondary user's 2, nRFor main user base station
To the sum of the additive white Gaussian noise power in the interference and relaying of relaying, n is the additive Gaussian white noise that mean value is 0, variance is 1
Sound, Ip1, Ip2Respectively large scale path loss, andα is path loss index, dp,iBe primary user base station and time
The distance between grade user i, i=1 or 2.
As the further refinement scheme of power distribution method of the present invention, the transmission of cognitive base station, relaying described in step 2
Power is respectively as follows:
Wherein, IpIndicate the interference threshold of primary user, psmax, pRmaxRespectively indicate the maximum transmitted of cognitive base station and relaying
Power.
As the further refinement scheme of power distribution method of the present invention, the noise score of secondary user's described in step 2
Not are as follows:
Wherein hCR,hR1,hR2Respectively indicate cognitive base station to relaying, be relayed to the channel power gains of secondary user's 1 and secondary user's 2,
pRFor the transmission power of relaying, σ1And σ2Respectively indicate secondary user's 1 and secondary user's 2 by primary user base station interference and time
The sum of additive white Gaussian noise power on grade user.
As the further refinement scheme of power distribution method of the present invention, the function representation of optimization aim described in step 2
Are as follows:Wherein γ2, γ2Respectively
For the lowest signal-to-noise of secondary user's 1 and secondary user's 2.
As the further refinement scheme of power distribution method of the present invention, solution packet is carried out to optimization aim described in step 3
Include step:
Step a), the function for simplifying optimization aim；
Step b), simplified optimization object function double optimization is obtained；
It is step c), rightIt is analyzed, when(if it is greater, then being monotone increasing letter
Number, analysis situation are similar) when, optimization object function is monotonic decreasing function, a2Value range are as follows:
Then whenWhen, the handling capacity of secondary user's reaches maximum value.
The invention adopts the above technical scheme compared with prior art, has following technical effect that
(1) primary user's distribution Poisson distribution method in this method uses system model more closing to reality；
(2) this method is based on the principle of " handling capacity is maximum ", under the premise of not interrupting, has obtained minizone secondary
Optimal power allocation factor, effectively improves throughput of system between user.
Detailed description of the invention
Fig. 1 is that the present invention is based on the flow charts of the power distribution method of the cognitive radio networks of NOMA technology.
Fig. 2 is the implementation system model figure of the corresponding above-mentioned power distribution method of the present invention.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with attached drawing and specific embodiment party
The present invention will be described in detail for formula.
The invention proposes on the basis of meeting minimum transmission rate request, adjust power by dynamic in secondary user's
Distribution factor controls the power of aware base station and relaying, can effectively improve the handling capacity of secondary user's.
As shown in Figure 1 to Figure 2, it is provided in an embodiment of the present invention it is a kind of based on non-orthogonal multiple access technology based on NOMA
The flow chart and its implementation system model figure of the power distribution method of the cognitive radio networks of technology, this method includes following step
It is rapid:
Step 1: the cognitive radio under the Underlay frequency spectrum share mode based on non-orthogonal multiple access technology is established
The down link model of network, and analyze relaying and secondary user's received signal.System operation are as follows: aware base station is being protected
The communication quality of primary user is demonstrate,proved under the premise of certain, secondary user's signal is transmitted to relaying, relaying uses non-orthogonal multiple
Technology expand forwarding secondary user's signal to secondary user's.
As shown in Fig. 2, by a primary user base station (PBS), one is recognized cognition network in Underlay-NOMA system
Know base station (CBS), an amplification repeater (R), a group primary user (PUs) and two secondary user's (SUs) compositions.Primary user's base
(PBS) is stood as primary user (PUs) offer communication.Primary user is randomly dispersed in a two-dimensional surface, obeys Poisson distribution.K-th
Fading channel between primary user and cognitive base station (CBS) is expressed as h'k.The transmission power of primary user base station (PBS) is p.?
In the fringe region of cognitive radio networks, there are two secondary user's, are divided into and are expressed as 1 (SU of secondary user's1) and secondary user's 2
(SU2).Cognitive base station (CBS) is first p to expanding repeater R to send firm powersMixed signal, signal s is as follows:
a1And a2It is 1 (SU of secondary user's respectively1) and 2 (SU of secondary user's2) power partition coefficient, and a1+a2=1.s1
And s2It is then that cognitive base station (CBS) is sent to 1 (SU of secondary user's1) and 2 (SU of secondary user's2) signal.
Cognitive base station (CBS) and the fading coefficients for expanding the fading channel between repeater (R) indicate are as follows:Recognize base
The fading coefficients for the fading channel stood between primary user indicate are as follows:Expand the decline letter between repeater R and primary user
The fading coefficients in road indicate are as follows:Expand repeater R and 1 (SU of secondary user's1), 2 (SU of secondary user's2) between decline
The fading coefficients of channel respectively indicate are as follows:Both assuming that the channel condition of secondary user's 2 is better than secondary user's 1, i.e.,
Channel power gain can indicate are as follows: hR1≤hR2(2),
If channel power gainAccording to NOMA principle it is found that power
Distribution factor a1≥a2.Expanding repeater (R) this side received signal are as follows:
N is that mean value is 0, the additive white Gaussian noise that variance is 1.spIt is the signal of primary user base station (PBS) transmitting, ITIt is
Large scale path loss, in which:
α is path loss index, dp,RIt is the distance between primary user base station (PBS) and expansion repeater (R).For letter
Primary user base station (PBS) to the interference for expanding repeater (R) and is expanded the additivity height on repeater (R) by single description, the present invention
The sum of this white noise acoustical power is defined as:
So, formula (3) can become:
The transmission power at expansion repeater is set as pR, then:
Therefore available amplification factor G:
In order to not influence the communication quality of primary user, cognitive base station (CBS) and the transimission power for expanding repeater (R) are necessary
Meet:
In formula, IpIndicate the interference threshold of primary user PU, psmax, pRmaxIt respectively indicates cognitive base station (CBS) and expands relaying
The maximum transmission power of device (R).
So secondary user's 1 and 2 received signal of secondary user's can indicate as follows:
Wherein n be mean value in secondary user's 1 and secondary user's 2 be 0, the additive white Gaussian noise that variance is 1.Ip1,
Ip2Large scale path loss respectively, whereinα is path damage
Consume index, dp,iIt is the distance between primary user base station (PBS) and secondary user's i (i=1,2).
Operation for simplicity, the present invention is in interference and secondary user's of the secondary user's by primary user base station (PBS)
The sum of additive white Gaussian noise power indicates are as follows: σi=1+IpiP, i=1,2 (14).
Because using non-orthogonal multiple access technology (NOMA) broadcasting user between repeater (R) and secondary user's expanding
Information, in order to avoid overlapped information generation interferes with each other between secondary user's, so being used when secondary user's receive signal
Serial interference elimination (SIC) method, first to signal s1It is decoded, then to signal s2It is decoded.Secondary user's 1 and secondary use
The signal-to-noise ratio at family 2 is respectively as follows:
Step 2: biobjective scheduling problem model is established.
The problem of present invention research, is: in the case where power limited, keeping total rate of all secondary user's maximum.Cause
The objective function that this present invention needs optimizes is as follows:
SINR1≥γ1, SINR2≥γ2, γ1, γ2The respectively lowest signal-to-noise of secondary user's 1 and secondary user's 2.
Step 3: objective optimisation problems are solved.
Ask local derviation that can obtain objective function:
It follows that working as(if it is greater, then being monotonic increasing function, analyze situation class
Like) when, objective function is monotonic decreasing function, a2Value range are as follows:
IfSo for
a2For, without suitable value in this section, it is pre- to also mean that secondary user's 1 or secondary user's 2 are not able to satisfy
Fixed SINR threshold value, then will interrupt.
Therefore, work as power allocation factorThe transmission rate of formula (17) reaches it
Maximum value, the i.e. handling capacity of whole system reach maximum.
In conclusion this method ensure that the transimission power of cognitive base station and relaying, proposes the transmission rate of secondary user's
Minimum speed limit requirement is gone out, establish the rate optimized model of secondary user's and has solved, the present invention is optimized by power distribution
The effective throughput and spectrum efficiency of system.
Above embodiments are merely to illustrate the present invention and not limit the technical scheme described by the invention, to this specification
Understanding should based on person of ordinary skill in the field, although this specification referring to the above embodiments to the present invention
Detailed description is had been carried out, still, those skilled in the art should understand that, person of ordinary skill in the field is still
Can so modify or equivalently replace the present invention, and all do not depart from the spirit and scope of the present invention technical solution and
It is improved, and should all be covered in scope of the presently claimed invention.
Claims (7)
1. a kind of power distribution method of the cognitive radio networks based on NOMA technology, it is characterised in that include the following steps:
Step 1: establishing under the cognitive radio networks under the Underlay frequency spectrum share mode accessed based on non-orthogonal multiple
Under the premise of certain, secondary user's signal is transmitted in the communication quality for guaranteeing primary user for line link model, cognitive base station
Relaying, relaying expand forwarding secondary user's signal to secondary user's using non-orthogonal multiple；Cognitive radio networks analysis
Relaying and secondary user's received signal；
Step 2: optimization problem model is established, with the throughput-maximized for optimization aim of secondary user's, and to guarantee to recognize base
The lowest signal-to-noise of the transimission power and secondary user's that stand, relay is as optimal conditions；
Step 3: solving optimization problem, realizes the effective throughput of secondary user's by power allocation factor and channel conditions
Optimization aim.
2. the power distribution method of the cognitive radio networks according to claim 1 based on NOMA technology, it is characterised in that:
The signal of relay reception described in step 1 are as follows:
WhereinFading coefficients for cognitive base station towards fading channel between relaying, a1And a2Be respectively secondary user's 1 and time
The power partition coefficient of grade user 2, and a1+a2=1, psFor the transmission power of cognitive base station, s1And s2It is cognitive base station hair respectively
The signal of secondary user's 1 and secondary user's 2 is given, n is the additive white Gaussian noise that mean value is 0, variance is 1, spIt is primary user
The signal of Base Transmitter, ITIt is large scale path loss, andα is path loss index, dp,RIt is primary user base station
The distance between relaying.
3. the power distribution method of the cognitive radio networks according to claim 1 based on NOMA technology, which is characterized in that
1 received signal of secondary user's described in step 1 are as follows:
2 received signal of secondary user's are as follows:Its
Middle G is the amplification factor of relaying,WithRespectively relaying is respectively for fading channel between secondary user's 1, secondary user's 2
Fading coefficients, nRIt is main user base station to the sum of the additive white Gaussian noise power in the interference and relaying of relaying, n is mean value
The additive white Gaussian noise for being 1 for 0, variance, Ip1, Ip2Respectively large scale path loss, andα is path damage
Consume index, dp,iIt is the distance between primary user base station and secondary user's i, i=1 or 2.
4. the power distribution method of the cognitive radio networks according to claim 1 based on NOMA technology, which is characterized in that
The transimission power of cognitive base station, relaying described in step 2 is respectively as follows:
Wherein, IpIndicate the interference threshold of primary user, psmax, pRmaxRespectively indicate the maximum transmission power of cognitive base station and relaying.
5. the power distribution method of the cognitive radio networks according to claim 1 based on NOMA technology, which is characterized in that
The signal-to-noise ratio of secondary user's described in step 2 is respectively as follows: Wherein hCR,hR1,hR2Respectively indicate cognitive base station to relaying, be relayed to secondary use
The channel power gain at family 1 and secondary user's 2, pRFor the transmission power of relaying, σ1And σ2Respectively indicate secondary user's 1 and secondary
User 2 is by the sum of the additive white Gaussian noise power in the interference and secondary user's of primary user base station.
6. the power distribution method of the cognitive radio networks according to claim 1 based on NOMA technology, which is characterized in that
The function representation of optimization aim described in step 2 are as follows:SINR1≥
γ1, SINR2≥γ2, wherein γ2, γ2The respectively lowest signal-to-noise of secondary user's 1 and secondary user's 2.
7. the power distribution method of the cognitive radio networks according to claim 1 based on NOMA technology, which is characterized in that
Optimization aim is solved described in step 3 comprising steps of
Step a), the function for simplifying optimization aim；
Step b), simplified optimization object function double optimization is obtained:
It is step c), rightIt is analyzed, whenWhen, optimization object function is monotone decreasing letter
Number, a2Value range are as follows:
Then whenWhen, the handling capacity of secondary user's reaches maximum value.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110337148A (en) * | 2019-04-26 | 2019-10-15 | 重庆邮电大学 | Cognitive radio efficiency resource allocation methods based on non-orthogonal multiple access |
| CN110602777A (en) * | 2019-08-28 | 2019-12-20 | 华北电力大学（保定） | CR-NOMA bidirectional relay self-interference energy recovery transmission method |
| CN111225435A (en) * | 2020-01-17 | 2020-06-02 | 北京蓝卫通科技有限公司 | 5G downlink NOMA transmission method in incomplete main user interference information |
| CN112689290A (en) * | 2020-12-09 | 2021-04-20 | 哈尔滨工业大学（深圳） | Communication system, control device, storage medium, and resource allocation method |
| CN112839338A (en) * | 2021-02-09 | 2021-05-25 | 河南垂天科技有限公司 | Fair power distribution method in shared cognitive cooperation NOMA network |
| CN113595643A (en) * | 2021-07-29 | 2021-11-02 | 中国计量大学 | Hybrid substrate cognitive RF/FSO relay transmission system and method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011109937A1 (en) * | 2010-03-10 | 2011-09-15 | 上海贝尔股份有限公司 | Method and device for allocating channel and/or power in cognitive radio network |
| CN105025547A (en) * | 2015-07-17 | 2015-11-04 | 广州大学 | Relay selection and power distribution method of energy acquisition node network |
| CN105828442A (en) * | 2016-04-26 | 2016-08-03 | 南通大学 | Cooperative relay cognitive radio network time slot allocation method |
| CN106358205A (en) * | 2016-10-08 | 2017-01-25 | 重庆大学 | Cognitive radio network power distribution method with multichannel cooperative communication |
| CN107580327A (en) * | 2017-09-19 | 2018-01-12 | 中山大学新华学院 | Cognition wireless network optimized throughput algorithm based on optimum frequency band selection |
-
2018
- 2018-08-03 CN CN201810875939.0A patent/CN108990070B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011109937A1 (en) * | 2010-03-10 | 2011-09-15 | 上海贝尔股份有限公司 | Method and device for allocating channel and/or power in cognitive radio network |
| CN105025547A (en) * | 2015-07-17 | 2015-11-04 | 广州大学 | Relay selection and power distribution method of energy acquisition node network |
| CN105828442A (en) * | 2016-04-26 | 2016-08-03 | 南通大学 | Cooperative relay cognitive radio network time slot allocation method |
| CN106358205A (en) * | 2016-10-08 | 2017-01-25 | 重庆大学 | Cognitive radio network power distribution method with multichannel cooperative communication |
| CN107580327A (en) * | 2017-09-19 | 2018-01-12 | 中山大学新华学院 | Cognition wireless network optimized throughput algorithm based on optimum frequency band selection |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110337148A (en) * | 2019-04-26 | 2019-10-15 | 重庆邮电大学 | Cognitive radio efficiency resource allocation methods based on non-orthogonal multiple access |
| CN110337148B (en) * | 2019-04-26 | 2022-04-05 | 重庆邮电大学 | Cognitive radio energy efficiency resource allocation method based on non-orthogonal multiple access |
| CN110602777A (en) * | 2019-08-28 | 2019-12-20 | 华北电力大学（保定） | CR-NOMA bidirectional relay self-interference energy recovery transmission method |
| CN110602777B (en) * | 2019-08-28 | 2022-04-26 | 华北电力大学（保定） | CR-NOMA bidirectional relay self-interference energy recovery transmission method |
| CN111225435A (en) * | 2020-01-17 | 2020-06-02 | 北京蓝卫通科技有限公司 | 5G downlink NOMA transmission method in incomplete main user interference information |
| CN111225435B (en) * | 2020-01-17 | 2023-09-15 | 北京蓝卫通科技有限公司 | Method for transmitting NOMA (non-orthogonal frequency division multiple Access) of 5G downlink in incomplete main user interference information |
| CN112689290A (en) * | 2020-12-09 | 2021-04-20 | 哈尔滨工业大学（深圳） | Communication system, control device, storage medium, and resource allocation method |
| CN112689290B (en) * | 2020-12-09 | 2022-12-20 | 哈尔滨工业大学（深圳） | Communication system, control device, storage medium, and resource allocation method |
| CN112839338A (en) * | 2021-02-09 | 2021-05-25 | 河南垂天科技有限公司 | Fair power distribution method in shared cognitive cooperation NOMA network |
| CN112839338B (en) * | 2021-02-09 | 2024-03-15 | 河南垂天科技有限公司 | Fair power distribution method in shared cognitive cooperation NOMA network |
| CN113595643A (en) * | 2021-07-29 | 2021-11-02 | 中国计量大学 | Hybrid substrate cognitive RF/FSO relay transmission system and method |
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