CN109768817A - The extensive mimo system of wireless energy transfer is based on the resource allocation methods of max-min justice - Google Patents
The extensive mimo system of wireless energy transfer is based on the resource allocation methods of max-min justice Download PDFInfo
- Publication number
- CN109768817A CN109768817A CN201910058638.3A CN201910058638A CN109768817A CN 109768817 A CN109768817 A CN 109768817A CN 201910058638 A CN201910058638 A CN 201910058638A CN 109768817 A CN109768817 A CN 109768817A
- Authority
- CN
- China
- Prior art keywords
- energy
- pyramid
- max
- power
- justice
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Mobile Radio Communication Systems (AREA)
Abstract
A kind of extensive mimo system of wireless energy transfer is claimed based on the resource allocation methods of max-min justice in the present invention; this method is in the case where considering pyramid of energy maximum transmission power and charging time constraint; transimission power from control pyramid of energy to each user and charging time by realize that system user minimum-rate maximizes.The present invention establishes the extensive mimo system of wireless energy transfer based on the resource allocator model of max-min justice, give the closed solutions that pyramid of energy distributes each user power, convex optimization problem is converted by variable replacement by former non-convex optimization problem, it is solved by the optimality equation of convex optimization problem and obtains the optimal energy charging time, finally obtain service system user rate minimum value.This method has low complex degree, and improves the fairness of user and the energy efficiency of system, has the advantages that feasibility by force and practicability.
Description
Technical field
The invention belongs to the field of resource allocation in extensive mimo system, specifically, wireless energy transfer it is extensive
In mimo system under based on max-min fairness joint Power and time resource allocation methods.
Background technique
In recent years, as mobile communications industry is quickly grown, mobile subscriber's quantity is sharply increased, and resource is seriously deficient, because
This wireless energy transfer is receive more and more attention, and wireless energy transmission technology can not only be applied to biomedical, ocean
The many aspects such as exploration, wireless sensor network, largely offer convenience for the mankind.Multiple-input and multiple-output (MIMO) technology energy
It is enough sent and received by multiple antennas, makes full use of space resources to improve the stability of channel capacity and system, therefore be considered
One of key technology in next-generation multi-user's system of broadband wireless communication.Y.Hu et al. " Wireless Networks,
Vol.20, no.8, pp.1421-1430, Aug.2014 " deliver article " Energy-efficiency resource
Allocation of very large multi-user mimo systems " is directed to uplink multi-users MIMO in this article
System proposes the resource allocation algorithm based on efficiency (EE) optimization, and mentioned method is received using force zero (ZF), is to maximize
System efficiency is criterion, optimizes efficiency function by the data rate of Joint regulation base station end transmitting antenna number and user, but
Have ignored the influence of large-scale fading.M.Cui et al. is sent out at " IEEE Access, vol.5, pp.1164-1177, Jan.2017 "
Table article " Energy-efficient power control algorithmin massive MIMO cognitive
Radio networks ", this article are proposed and are optimized based on efficiency, calculated by iteration for the problem that uplink multi-cell system
Method realizes optimal power strategy using the adaptive approach based on gradient.Its groundwork be using most fair criterion, and
Efficiency is maximized, is carried out using cognitive user (CU) of the method for joint pilot power and data power distribution to worst case
Optimization, but the power consumption of system does not account for circuit power consumption.
X.Wan, et al. in international conference International Conference on Wireless in 2018
Communications and Signal Processing (WCSP) has delivered " Energy-Efficient Resource
Allocation for Wireless Power Transfer Enabled Massive MIMO Systems with
Hardware Impairments ", this article have studied multiple antennas pyramid of energy and multiple antennas base in multisensor node scene
Energy acquisition between standing proposes the resource allocation methods based on efficiency optimization.Assuming that possessing between base station and pyramid of energy
The channel state information known is received using the method for force zero (ZF), but is not accounted for the fairness of rate between user.
User fairness is not considered when studying extensive MIMO in scholar mostly at present, and is seldom considered extensive
Mimo system combining wireless energy transmission, but in real system sensor node rate fairness to be it is critically important, only
Have fairness carries out rate-allocation to user, can effectively improve the life span of sensing node in whole network.Base
In the above analysis, the present invention considers multiple antennas pyramid of energy and multi-antenna base station, in a uplink multi-users wireless communication system
In, dispose multiple sensor node models, it is assumed that it is new that system communication possesses perfect channel status, considers to emit function in pyramid of energy
Under rate and charging time constraint condition, proposes based on max-min criterion and time and power distribution are optimized, thus most
The rate of the smallest user in the extensive mimo system of bigization wireless energy transfer.
Summary of the invention
Present invention seek to address that the above problem of the prior art.Propose a kind of energy efficiency for improving system and most
The resource allocation methods based on max-min fairness of the extensive mimo system of the wireless transmission of small user rate.The present invention
Technical solution it is as follows:
A kind of resource allocation methods based on max-min fairness of the extensive mimo system of wireless transmission comprising
Following steps:
Step 1: in the extensive mimo system of wireless energy transfer with multisensor node, establishing and be based on max-
The resource allocator model of min fairness, the extensive mimo system of the wireless energy transfer are based on max-min resource allocation and ask
An entitled non-convex optimization problem；
Step 2: initializing the total transmission power of pyramid of energy and distribute to the power of each sensor node；
Step 3: the non-convex optimization problem by the way that each sensor node of system distribution power of step 2 to be substituted into step 1, by step 1
Non-convex optimization problem be converted to the convex optimization problem of equivalence about the pyramid of energy charging time；
Step 4: using the corresponding single order Optimality equations of the 3 convex optimization problem of equivalence of dichotomy solution procedure, obtaining pyramid of energy
The optimal charging time calculates the minimum value of all user rates of system, completes based on max-min fairness
Resource allocation.
Further, in the step 1, resource allocation of the extensive mimo system of wireless energy transfer based on max-min
Model are as follows:
0≤P≤Pmax
0≤τ≤1
Wherein, K is the number of sensor, βiIt is power gain of the pyramid of energy at sensor i, P is total hair of pyramid of energy
Send power, PmaxIt is the maximum transmission power of pyramid of energy, piThe power of sensor node i is distributed to for pyramid of energy；N is pyramid of energy
Antenna amount, M be antenna for base station quantity, αiThe large scale factor between sensor i and base station, βiFor pyramid of energy and sensing
Power gain between device i, σ2It is the ambient noise of base station, τ is the pyramid of energy energy charging time.
Further, the total transmission power of the step 2 initialization pyramid of energy and the power for distributing to each sensor node,
It specifically includes:
Pyramid of energy total transmission power P value is P=Pmax, the power that pyramid of energy distributes to sensor section i is pi, value
Are as follows:
Further, the convex optimization problem of equivalence in the step 4 pyramid of energy charging time are as follows:
s.t 0≤τ≤1
Further, the optimal time τ that step 4 dichotomy solves*The single order Optimality equations expression formula of satisfaction are as follows:
Wherein A is constant, value are as follows:
τ*Indicate pyramid of energy to the sensing node optimal charging time.
Further, the rate minimum value of all users of system is in step 4
It advantages of the present invention and has the beneficial effect that:
The present invention is by giving energy based on max-min justice and adopting under pyramid of energy maximum transmission power constraint condition
Collect extensive mimo system resource allocation methods, innovation is to give the enclosed of each user's optimal power allocation
Solution, while the single order Optimality equations of the optimal charging time satisfaction of pyramid of energy are given, solving Optimality equations using dichotomy can be fast
Speed obtains the pyramid of energy optimal charging time.Make the present invention traditional extensive based on wireless energy transfer compared to other in this way
Mimo system has the advantages that low complex degree, and since optimization aim uses max-min equity criterion, improves the public affairs of user
Levelling.Since power distribution has analytical expression, execution speed is fast, has preferable feasibility and practicability.
Detailed description of the invention
Fig. 1 is that the present invention provides the extensive mimo system of preferred embodiment wireless energy transfer based on max-min justice
The flow chart of power resource allocation；
Fig. 2 is minimum user rate variation diagram of the present invention when antenna for base station number increases to 100 from 60 in system；
Fig. 3 is that when antenna for base station number increases to 100 from 60, all users close rate variation diagram to the present invention in system；
Fig. 4 is minimum user rate variation diagram of the present invention when number of users increases to 15 from 5 in system；
Fig. 5 is the energy benefits variation diagram of present invention pyramid of energy when number of users increases to 15 from 5.
Fig. 6 is that when number of users increases to 15 from 5, all users close rate variation diagram to the present invention in system.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, detailed
Carefully describe.Described embodiment is only a part of the embodiments of the present invention.
The technical solution that the present invention solves above-mentioned technical problem is:
The present embodiment is the fair power based on the extensive mimo system of wireless energy transfer under user rate fairness
Distribution method, ambient noise are the white Gaussian noise value σ of zero-mean2=10-10W, sensor be randomly dispersed in [0,0] × [-
10,10] m, sensor are distributed in the 20m radius of base station, and sensor is also distributed about in pyramid of energy 20m radius, sensing
Large-scale fading factor-alpha of the device i to base stationi=mi -3, pyramid of energy is emitted to the path-loss factor β of sensori=di -3, miWith
diAs a result respectively sensor i passes through 10 to the distance of base station and pyramid of energy3Secondary emulation is averaged.
The first step specifically establishes the resource of the extensive mimo system of wireless energy transfer based on max-min
Distribution model are as follows:
0≤P≤Pmax
0≤τ≤1
Wherein, K is the number of sensor, βiIt is power gain of the pyramid of energy at sensor i, P is total hair of pyramid of energy
Send power, PmaxIt is the maximum transmission power of pyramid of energy, piThe power of sensor node i is distributed to for pyramid of energy；N is pyramid of energy
Antenna amount, M be antenna for base station quantity, αiThe large scale factor between sensor i and base station, βiFor pyramid of energy and sensing
Power gain between device i, σ2It is the ambient noise of base station, τ is the pyramid of energy energy charging time.
Second step, the resource point according to the extensive mimo system of wireless energy transfer based on max-min fairness
Method of completing the square, which is characterized in that specifically, pyramid of energy total transmission power P value is P=Pmax, pyramid of energy distributes to sensor section i
Power be pi, value are as follows:Wherein PmaxIt is the maximum hair of pyramid of energy
Power is penetrated, K is the number of sensor, and N is the antenna amount of pyramid of energy, αiThe large scale factor between sensor i and base station,
βiFor the power gain between pyramid of energy and sensor i.Third step, according to the extensive mimo system of wireless energy transfer
Resource allocation methods based on max-min fairness, which is characterized in that specifically, the third step pyramid of energy charging time
Convex optimization problem of equal value are as follows:
s.t 0≤τ≤1
Wherein, τ is the pyramid of energy energy charging time, and K is the number of sensor, βiIt is letter of the pyramid of energy at sensor i
Road gain, PmaxIt is pyramid of energy maximum transmission power, N is the antenna amount of pyramid of energy, and M is antenna for base station quantity, αiFor sensor
The large scale factor of the i to base station, σ2It is base station ambient noise, τ is the time that pyramid of energy is transferred to sensor.
4th step, the resource point according to the extensive mimo system of wireless energy transfer based on max-min fairness
Method of completing the square, which is characterized in that specifically, the single order Optimality equations expression formula that the dichotomy solves are as follows:
Wherein A is constant, value are as follows:Wherein K is the number of sensor, βi
It is channel gain of the pyramid of energy at sensor i, PmaxIt is pyramid of energy maximum transmission power, N is the antenna amount of pyramid of energy, and M is
Antenna for base station quantity, αiFor the large scale factor of sensor i to base station, σ2It is base station ambient noise.
In the present embodiment, Fig. 2 gives is respectively adopted throughput-maximized method under different base station antenna amount
(TPTA), the distribution such as times method (Proposed of power method (EPTA) and the present embodiment method based on max-min such as
Algorithm) curve graph；Fig. 3 be respectively adopted under different base station antenna amount throughput-maximized method (TPTA), etc. the times
The conjunction rate profile for all users that constant power distribution method (EPTA) and the present embodiment method obtain；Fig. 4 is in different use
Be respectively adopted under amount amount throughput-maximized method (TPTA), etc. times constant power distribution method (EPTA) and the present embodiment method
Obtain minimum user rate curve graph；Fig. 5 be respectively adopted under different user quantity throughput-maximized method (TPTA), etc. whens
Between the obtained pyramid of energy energy efficient curves figure of constant power distribution method (EPTA) and the present embodiment method.Fig. 6 is in different use
Be respectively adopted under amount amount throughput-maximized method (TPTA), etc. times constant power distribution method (EPTA) and the present embodiment side
The conjunction rate profile for all users that method obtains.As seen from Figure 2: institute's implementation method obtains the higher rate of minimum user；
As seen from Figure 3: while ensure that fairness, the conjunction rate of all users compares throughput-maximized method difference very little；
From fig. 4, it can be seen that institute's implementation method makes the rate of minimum user obtain biggish value；As seen from Figure 5: ensure that user
While fairness, keep the energy efficiency of pyramid of energy higher；By 6 as it can be seen that while ensure that fairness, the conjunction speed of all users
Rate compares throughput-maximized method difference very little.In conjunction with Fig. 2, Fig. 3, Fig. 4, Fig. 5, Fig. 6 it is found that mentioned method is than handling capacity maximum
The times method such as change method and distribution power improves the fairness of user.This method obtains higher energy efficiency, mentioned side
Method can effectively solve the problem that the relevant issues such as the power control in wireless network based on user fairness.
The above embodiment is interpreted as being merely to illustrate the present invention rather than limit the scope of the invention.?
After the content for having read record of the invention, technical staff can be made various changes or modifications the present invention, these equivalent changes
Change and modification equally falls into the scope of the claims in the present invention.
Claims (6)
1. a kind of extensive mimo system of wireless energy transfer is based on the resource allocation methods of max-min justice, feature exists
In, comprising the following steps:
Step 1: in the extensive mimo system of wireless energy transfer with multisensor node, establishing public based on max-min
Flat resource allocator model, the resource allocator model based on max-min justice are a non-convex optimization problem；
Step 2: initializing the total transmission power of pyramid of energy and distribute to the power of each sensor node；
Step 3: the non-convex optimization problem by the way that each sensor node of system distribution power of step 2 to be substituted into step 1, by the non-of step 1
Convex optimization problem is converted to the convex optimization problem of equivalence about the pyramid of energy charging time；
Step 4: using the corresponding single order Optimality equations of the 3 convex optimization problem of equivalence of dichotomy solution procedure, it is optimal to obtain pyramid of energy
The power of energetic optimum charging time and each sensor node of step 2 is substituted into the public based on max-min of step 1 by the charging time
Flat resource allocation problem calculates the rate minimum value of all users of system, completes the resource based on max-min justice
Distribution.
2. a kind of extensive mimo system of wireless energy transfer according to claim 1 is based on the money of max-min justice
Source distribution method, which is characterized in that in the step 1, the resource allocator model based on max-min fairness are as follows:
0≤P≤Pmax
0≤τ≤1
Wherein, K is the number of sensor, βiIt is power gain of the pyramid of energy at sensor i, P is total transmission function of pyramid of energy
Rate, PmaxIt is the maximum transmission power of pyramid of energy, piThe power of sensor node i is distributed to for pyramid of energy；N is the day of pyramid of energy
Line number amount, M are antenna for base station quantity, αiThe large scale factor between sensor i and base station, βiFor pyramid of energy and sensor i it
Between power gain, σ2It is the ambient noise of base station, τ is the pyramid of energy energy charging time.
3. a kind of extensive mimo system of wireless energy transfer according to claim 2 is based on the money of max-min justice
Source distribution method, which is characterized in that the step 2 initializes the total transmission power of pyramid of energy and distributes to each sensor node
Power specifically includes:
Pyramid of energy total transmission power P value is P=Pmax, the power that pyramid of energy distributes to sensor section i is pi, value are as follows:
4. a kind of extensive mimo system of wireless energy transfer according to claim 3 is based on the money of max-min justice
Source distribution method, which is characterized in that the convex optimization problem of equivalence in the step 4 pyramid of energy charging time are as follows:
s.t 0≤τ≤1。
5. a kind of extensive mimo system of wireless energy transfer according to claim 4 is based on the money of max-min justice
Source distribution method, which is characterized in that the optimal time τ that step 4 dichotomy solves*The single order Optimality equations expression formula of satisfaction
Are as follows:
Wherein A is constant, value are as follows:
τ*Indicate pyramid of energy to the sensing node optimal charging time.
6. a kind of extensive mimo system of wireless energy transfer according to claim 5 is based on the money of max-min justice
Source distribution method, which is characterized in that the rate minimum value of all users of system is in step 4
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910058638.3A CN109768817B (en) | 2019-01-22 | 2019-01-22 | Max-min fairness-based resource allocation method for large-scale MIMO system with wireless energy transmission |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910058638.3A CN109768817B (en) | 2019-01-22 | 2019-01-22 | Max-min fairness-based resource allocation method for large-scale MIMO system with wireless energy transmission |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109768817A true CN109768817A (en) | 2019-05-17 |
| CN109768817B CN109768817B (en) | 2021-03-23 |
Family
ID=66455051
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910058638.3A Active CN109768817B (en) | 2019-01-22 | 2019-01-22 | Max-min fairness-based resource allocation method for large-scale MIMO system with wireless energy transmission |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109768817B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112290695A (en) * | 2020-09-14 | 2021-01-29 | 德清阿尔法创新研究院 | MIMO magnetic safe charging method based on magnetic resonance |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9166913B1 (en) * | 2012-08-15 | 2015-10-20 | Google Inc. | Systems and methods for balancing max-min fairness and throughput objectives in traffic engineering |
| CN108200581A (en) * | 2017-12-23 | 2018-06-22 | 西安交通大学 | Multi-user resource distributing method in the wireless power communication network of selective user cooperation |
| CN108282788A (en) * | 2018-01-19 | 2018-07-13 | 南京航空航天大学 | A kind of resource allocation methods of the Energy Efficient based on quasi- newton interior point method |
| CN108848563A (en) * | 2018-06-25 | 2018-11-20 | 重庆邮电大学 | A kind of cooperation resource allocation methods of the NOMA system down link based on efficiency |
| CN108924938A (en) * | 2018-08-27 | 2018-11-30 | 南昌大学 | A kind of resource allocation methods for wireless charging edge calculations network query function efficiency |
-
2019
- 2019-01-22 CN CN201910058638.3A patent/CN109768817B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9166913B1 (en) * | 2012-08-15 | 2015-10-20 | Google Inc. | Systems and methods for balancing max-min fairness and throughput objectives in traffic engineering |
| CN108200581A (en) * | 2017-12-23 | 2018-06-22 | 西安交通大学 | Multi-user resource distributing method in the wireless power communication network of selective user cooperation |
| CN108282788A (en) * | 2018-01-19 | 2018-07-13 | 南京航空航天大学 | A kind of resource allocation methods of the Energy Efficient based on quasi- newton interior point method |
| CN108848563A (en) * | 2018-06-25 | 2018-11-20 | 重庆邮电大学 | A kind of cooperation resource allocation methods of the NOMA system down link based on efficiency |
| CN108924938A (en) * | 2018-08-27 | 2018-11-30 | 南昌大学 | A kind of resource allocation methods for wireless charging edge calculations network query function efficiency |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112290695A (en) * | 2020-09-14 | 2021-01-29 | 德清阿尔法创新研究院 | MIMO magnetic safe charging method based on magnetic resonance |
| CN112290695B (en) * | 2020-09-14 | 2024-01-16 | 德清阿尔法创新研究院 | MIMO magnetic safety charging method based on magnetic resonance |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109768817B (en) | 2021-03-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Liu et al. | RF energy harvesting wireless powered sensor networks for smart cities | |
| Wang et al. | Joint interference alignment and power control for dense networks via deep reinforcement learning | |
| CN108924935A (en) | A kind of power distribution method in NOMA based on nitrification enhancement power domain | |
| CN107071914B (en) | Dynamic mode selection and energy distributing method in a kind of energy capture D2D network | |
| CN103746729B (en) | Distributed MIMO system base station side antenna position optimization method | |
| Zhou et al. | Dynamic spectrum management via machine learning: State of the art, taxonomy, challenges, and open research issues | |
| CN108495337A (en) | Wireless portable communications system maximum safe rate optimization method based on NOMA | |
| CN106961716B (en) | Energy cost minimization base station dormancy method with priority on energy consumption | |
| CN110430613A (en) | Resource allocation methods of the multicarrier non-orthogonal multiple access system based on efficiency | |
| CN107302766B (en) | Method for balancing and optimizing energy efficiency and spectral efficiency in distributed antenna system | |
| CN106131939B (en) | A kind of power control optimal method of several energy integrated communication networks | |
| CN106793108A (en) | Federated user selection and power distribution optimization method in mimo system downlink | |
| Tran et al. | Dynamic radio cooperation for downlink cloud-RANs with computing resource sharing | |
| CN106060917B (en) | One kind is based on the matched antenna of grouping and power combined allocation method | |
| Liu et al. | Power allocation schemes based on machine learning for distributed antenna systems | |
| Dhifallah et al. | Joint hybrid backhaul and access links design in cloud-radio access networks | |
| CN109788540A (en) | Power control and method for channel allocation in D2D system based on energy acquisition | |
| CN110536321B (en) | Optimization method for balancing energy efficiency and spectral efficiency in 5G IOT communication | |
| Li et al. | An energy-effective network deployment scheme for 5G Cloud Radio Access Networks | |
| CN109451569A (en) | A kind of resource allocation methods wirelessly taken in energy heterogeneous network | |
| CN108882352A (en) | A kind of downlink NOMA power distribution method that the weight rate based on non-perfect SIC is optimal | |
| CN101969328B (en) | Beam arrival angle-based multiuser scheduling scheme | |
| CN109768817A (en) | The extensive mimo system of wireless energy transfer is based on the resource allocation methods of max-min justice | |
| CN108337024A (en) | A kind of extensive mimo system efficiency optimization method based on energy acquisition | |
| Sun et al. | Relational reinforcement learning based autonomous cell activation in cloud-RANs |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |