CN109450571A - A kind of RF energy collects the high energy efficiency channel and power combined allocation method in cognition wireless network - Google Patents

A kind of RF energy collects the high energy efficiency channel and power combined allocation method in cognition wireless network Download PDF

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Publication number
CN109450571A
CN109450571A CN201811195147.5A CN201811195147A CN109450571A CN 109450571 A CN109450571 A CN 109450571A CN 201811195147 A CN201811195147 A CN 201811195147A CN 109450571 A CN109450571 A CN 109450571A
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China
Prior art keywords
channel
energy
wireless network
power
base station
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CN201811195147.5A
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Chinese (zh)
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徐鼎
王立
朱晓荣
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Nanjing Post and Telecommunication University
Nanjing University of Posts and Telecommunications
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Nanjing Post and Telecommunication University
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Priority to CN201811195147.5A priority Critical patent/CN109450571A/en
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
    • 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
    • H04W52/30—TPC using constraints in the total amount of available transmission power
    • H04W52/34—TPC management, i.e. sharing limited amount of power among users or channels or data types, e.g. cell loading

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The present invention proposes that a kind of RF energy collects high energy efficiency channel and power combined allocation method in cognition wireless network, and the efficiency of cognition wireless network is further promoted by RF energy collection technique.It include a primary user, a cognitive base station and multiple secondary users in whole network framework.In the cognition wireless network, secondary user has RF energy collecting function, collects energy from the signal that primary user emits.The present invention maximizes the efficiency of cognition wireless network under the jamming power constraint of primary user and the transmission power constraint of cognitive base station by combined optimization channel and power distribution.

Description

A kind of RF energy collects the high energy efficiency channel and power joint in cognition wireless network Distribution method
Technical field
The present invention relates to mobile communication technology field, especially a kind of RF energy collects the high energy in cognition wireless network Channel and power combined allocation method are imitated, this method can be in cognition wireless network using real based on RF energy collection technique The channel of existing high energy efficiency and power joint distribution.
Background technique
With the rapid development of wireless communication technique, mobile communication is faced with the increasingly short problem of frequency spectrum resource.For solution Certainly this problem, cognition wireless network are widely paid close attention to.Cognition wireless network allows time user's not awarding using primary user Frequency spectrum is weighed, to improve spectrum efficiency, on condition that the service quality of primary user needs to obtain the guarantee of time user.Resource allocation is one A effective method for improving cognition wireless network performance, such as high energy efficiency resource allocation methods.Pass through high energy efficiency resource allocation Spectral efficient and energy-efficient can be achieved at the same time in method, cognition wireless network.In addition, RF energy collection technique allows to set The standby collecting energy from radiofrequency signal is one of the energy-provision way that the following small device has bright prospects.So for energy For constraint cognitive wireless network, more energy can be provided for time user by RF energy collection technique, and can lead to Cross the efficiency that efficient resource allocation methods further promote cognition wireless network.
Summary of the invention
Goal of the invention: it is an object of the invention to further promote cognition wireless network by RF energy collection technique Efficiency proposes that a kind of RF energy collects high energy efficiency channel and power combined allocation method in cognition wireless network.
Technical solution: to achieve the above object, the present invention proposes following scheme:
A kind of RF energy collects the high energy efficiency channel and power combined allocation method in cognition wireless network, the cognition Wireless network includes: K secondary user, a cognitive base station and a primary users with RF energy collecting function；
The distribution method comprising steps of
(1) to maximize the efficiency of cognition network as target problem Construct question model:
Wherein, N is the authorization channel quantity of primary user, αI, kIndicate the instruction of binary channel distribution, wherein αI, k=1 indicates letter Road i is assigned to time user k and carries out data receiver, αI, k=0 expression channel i is not allocated to time user k progress data and connects It receives, piIndicate the cognitive base station transmission power on channel i, hI, kIt indicates to increase on channel i from cognitive base station to the channel of secondary user k Benefit, σ2Indicate noise power, PcIndicate the way circuit power consumption of cognitive base station and time user, EkIt is received for secondary user k by RF energy The energy of collection, giIndicate the channel gain on channel i from cognitive base station to primary user, QmaxIndicate jamming power thresholding, PmaxTable Show the maximum total transmitter power (dBm) of cognitive base station；
(2) Solve problems model obtains the α for meeting constraint conditionI, kAnd pi, according to αI, kAnd piDistribute channel and power money Source.
Further, the specific steps of the Solve problems model are as follows:
Intermediate parameters q is arranged in (2-1), and Lagrange duality variable μ, ν is arranged, and initialization q is any positive number；
It is any positive number that (2-2), which initializes μ, ν,；
(2-3) is calculated:
Wherein, i=1,2 ..., N, k=1,2 ..., K, (x)+=max (x, 0), λkIndicate that time user k collects the effect of energy Rate, 0 < λk< 1；
The α that (2-4) is obtained according to step (2-3)I, kIt calculates:
(2-5) updates μ and ν using subgradient algorithm, that is, calculates:
Wherein, θ is to update step-length；
(2-6) judges whether μ and ν converges to default precision, if so, thening follow the steps (2-7)；Otherwise, return step (2- 3)；
(2-7) is enabled
(2-8) is calculated:
(2-9) judges whether to meet | Y | < ε, ε are preset accuracy value；If not satisfied, then end step (2-9), and it is defeated α outI, kAnd pi；Otherwise, return step (2-2).
Further, the calculation formula for the energy that the secondary user is collected into are as follows:
The utility model has the advantages that compared with prior art, present invention has the advantage that
The present invention is by combined optimization channel and power distribution, in the hair of the jamming power constraint and cognitive base station of primary user It penetrates under power constraint, maximizes the efficiency of cognition wireless network；And complexity is low, fast convergence rate, it is easy to accomplish.
Detailed description of the invention
Fig. 1 is flow diagram of the invention；
Fig. 2 is system model schematic diagram of the invention.
Specific embodiment
The present invention will be further explained with reference to the accompanying drawing.
The framework of the cognition wireless network of the invention is as shown in Fig. 2, and in entire framework including K has radio frequency The secondary user of collection of energy function, a cognitive base station and a primary user.Process of the invention is as shown in Figure 1, include following Step:
Parameter setting is carried out first: being set the authorization channel quantity of primary user as N, is enabled hI, kAnd giRespectively represent on channel i from Channel power value added in cognitive base station to the channel power value added of secondary user k and channel i from cognitive base station to primary user. In addition, piRepresent the cognitive base station transimission power on channel i.Use αI, kIt indicates binary channel distribution index number, defines αI, k=1 Indicate that channel i is assigned to time user k and carries out data transmission, αI, k=0 expression channel i is not allocated to any secondary user, and If a channel can only connect to one user, that is, haveTherefore consider noise power σ2Afterwards, secondary user k connects Receiving rate may be expressed as:For the transmission for guaranteeing primary user, need to the interference of primary user Power limits:Wherein, QmaxIndicate the jamming power thresholding of primary user.
The overall transmission power of transmission base station is restricted to:Wherein, PmaxIndicate the transmission of cognitive base station Thresholding.
Assuming that secondary user can be from the signal collection energy on the channel for being not yet assigned to it to carry out data transmission, then secondary use The energy that family k is collected into is represented as:
Wherein, λkIndicate that time user k collects the efficiency of energy, 0 < λk< 1；Therefore the energy of entire cognition wireless network disappears Consumption may be expressed as:
Wherein, PcIndicate the way circuit power consumption of cognitive base station and time user.
In conclusion the efficiency for maximizing cognition network under conditions of being subject to the above restrictions that the method for the present invention proposes is asked Topic can be described as:
The problem is nonlinear programming problem, solves the specific steps of the problem are as follows:
1) intermediate parameters q is set, and initialization q is any positive number；
2) Lagrange duality variable μ, ν are set, and initialization μ, ν are any positive number；
3) it is directed to all channel i=1,2 ..., N and all secondary user k=1,2 ..., K is calculated:
Wherein, (x)+=max (x, 0), λkIndicate that time user k collects the efficiency of energy, 0 < λk< 1；
4) it is directed to all channel i=1,2 ..., N, is calculated:
5) value that μ and ν is updated with subgradient algorithm, that is, calculate:
Wherein, θ is to update step-length；
6) judge whether μ and ν converges to default precision, if so, thening follow the steps 7)；Otherwise, return step 3)；
7) it enables
8) it calculates:
9) judge whether to meet | Y | < ε, ε are preset accuracy value；If not satisfied, then end step 9), and export αI, k And pi；Otherwise, return step 2).
The above is only a preferred embodiment of the present invention, it should be pointed out that: for the ordinary skill people of the art For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered It is considered as protection scope of the present invention.

Claims (3)

1. the high energy efficiency channel and power combined allocation method, feature in a kind of RF energy collection cognition wireless network exist In the cognition wireless network includes: K secondary user, a cognitive base station and a masters with RF energy collecting function User；
The distribution method comprising steps of
(1) to maximize the efficiency of cognition network as target problem Construct question model:
Wherein, N is the authorization channel quantity of primary user, αI, kIndicate the instruction of binary channel distribution, wherein αI, k=1 indicates channel i It is assigned to time user k and carries out data receiver, αI, k=0 expression channel i is not allocated to time user k and carries out data receiver, pi Indicate the cognitive base station transmission power on channel i, hI, kIt indicates on channel i from cognitive base station to the channel gain of secondary user k, σ2 Indicate noise power, PcIndicate the way circuit power consumption of cognitive base station and time user, EkIt is collected for secondary user k by RF energy Energy, giIndicate the channel gain on channel i from cognitive base station to primary user, QmaxIndicate jamming power thresholding, PmaxExpression is recognized Know the maximum total transmitter power (dBm) of base station；
(2) Solve problems model obtains the α for meeting constraint conditionI, kAnd pi, according to αI, kAnd piDistribute channel and power resource.
2. a kind of RF energy collects high energy efficiency channel and power joint point in cognition wireless network according to claim 1 Method of completing the square, which is characterized in that the specific steps of the Solve problems model are as follows:
Intermediate parameters q is arranged in (2-1), and Lagrange duality variable μ, ν is arranged, and initialization q is any positive number；
It is any positive number that (2-2), which initializes μ, ν,；
(2-3) is calculated:
Wherein, i=1,2 ..., N, k=1,2 ..., K, (x)+=max (x, 0), λkThe efficiency of expression time user k collection energy, 0 < λk< 1；
The α that (2-4) is obtained according to step (2-3)I, kIt calculates:
(2-5) updates μ and ν using subgradient algorithm, that is, calculates:
Wherein, θ is to update step-length；
(2-6) judges whether μ and ν converges to default precision, if so, thening follow the steps (2-7)；Otherwise, return step (2-3)；
(2-7) is enabled
(2-8) is calculated:
(2-9) judges whether to meet | Y | < ε, ε are preset accuracy value；If not satisfied, then end step (2-9), and export αI, kAnd pi；Otherwise, return step (2-2).
3. a kind of RF energy collects high energy efficiency channel and power joint point in cognition wireless network according to claim 2 Method of completing the square, which is characterized in that the calculation formula for the energy that the secondary user is collected into are as follows:
CN201811195147.5A 2018-10-12 2018-10-12 A kind of RF energy collects the high energy efficiency channel and power combined allocation method in cognition wireless network Pending CN109450571A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110769429A (en) * 2019-09-11 2020-02-07 南京邮电大学 High-energy-efficiency data unloading method based on wireless energy supply cognitive picocells
CN111787545A (en) * 2020-07-14 2020-10-16 南通大学 Full-duplex cognitive relay power distribution method based on energy collection

Citations (2)

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US20120195212A1 (en) * 2011-02-01 2012-08-02 The Hong Kong University Of Science And Technology Cooperative sensing scheduling for energy-efficient cognitive radio networks
CN107947878A (en) * 2017-11-22 2018-04-20 江苏理工学院 A kind of cognitive radio power distribution method based on efficiency and spectrum effect combined optimization

Patent Citations (2)

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US20120195212A1 (en) * 2011-02-01 2012-08-02 The Hong Kong University Of Science And Technology Cooperative sensing scheduling for energy-efficient cognitive radio networks
CN107947878A (en) * 2017-11-22 2018-04-20 江苏理工学院 A kind of cognitive radio power distribution method based on efficiency and spectrum effect combined optimization

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110769429A (en) * 2019-09-11 2020-02-07 南京邮电大学 High-energy-efficiency data unloading method based on wireless energy supply cognitive picocells
CN110769429B (en) * 2019-09-11 2022-04-29 南京邮电大学 High-energy-efficiency data unloading method based on wireless energy supply cognitive picocells
CN111787545A (en) * 2020-07-14 2020-10-16 南通大学 Full-duplex cognitive relay power distribution method based on energy collection

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Application publication date: 20190308