CN106357315B - A kind of large-scale multiple antennas network energy efficiency resource allocation methods with incomplete CSI - Google Patents
A kind of large-scale multiple antennas network energy efficiency resource allocation methods with incomplete CSI Download PDFInfo
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- CN106357315B CN106357315B CN201610843944.4A CN201610843944A CN106357315B CN 106357315 B CN106357315 B CN 106357315B CN 201610843944 A CN201610843944 A CN 201610843944A CN 106357315 B CN106357315 B CN 106357315B
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Classifications
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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
-
- 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
-
- 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
Abstract
The invention discloses a kind of large-scale multiple antennas network energy efficiency resource allocation methods with incomplete CSI, charge to user equipment using the method for collection of energy, and user equipment gives base station to transmit data using the energy collected；Using N root antenna collocation multiaerial system, structure block fading channel model carries out channel estimation to bulk nanometer materials model, obtains the estimation channel capacity between base station and user equipment；Based on comprehensive power consumption and circuit loss for considering sending and receiving end, analyzes and obtained the Antenna Selection Algorithem that energy efficiency is optimized, so that the energy efficiency of multiaerial system is greatly improved.Method of the invention uses energy collection technology under incomplete channel estimation, and Antenna Selection Algorithem and resource allocation optimization algorithm effectively improve the energy efficiency of multiple antennas network.
Description
Technical field
The present invention relates to wireless communication technology field more particularly to a kind of large-scale multiple antennas networks with incomplete CSI
Efficiency resource allocation methods.
Background technique
The explosive increase of smart phone industry, multimedia service and mobile application is highly dependent on high-speed data wireless network
The development of network.Although the high-data-rate wireless system of rapid growth constantly changes our life, or even changes our day
Chang Hangwei, but in demand of the current network to high data rate service be still it is nervous, the battery consumption of mobile terminal also than from
It is preceding fast very much.On the other hand, for comparing high data rate service and the demand of fast wireless network, the development of battery technology is
Slow and progressive.This mismatch necessarily causes researcher to the mobile terminal for needing continuous operation in raising wireless network
Life cycle research interest and enthusiasm.
Limited battery capacity is to improve one of the major obstacle of life cycle, while it is also to improve the high data speed of user
The major obstacle of rate multimedia service.The method of the life cycle of one extension mobile terminal is to provide energy supply.However, giving
The battery that mobile terminal is perhaps replaced in battery charging may result in high cost it is sometimes even inconvenient or can not be real
Existing.Under current this environment, energy collection technology can extend the Life Cycle of energy constraint network on a continuing basis
Phase.Energy collection technology makes it possible that the receiving device in wireless network collects energy from the environment of surrounding.At the same time,
Distance since mostly energy source is, such as solar energy and wind energy etc..However, solar energy can hardly be accessed for those
Or for the wireless device of wind energy these energy sources, where how providing energy supply again and being problem.Recently, in addition to from the sun
Outside the technology for obtaining energy in energy, wind energy, vibration, pyroelectric effect or other physical phenomenons, within a wireless communication network, wireless function
Rate transmission has become a hot topic of research, it provides a promising solution for the network of traditional energy constraint.Because
Radiofrequency signal can not only carry information, can also transmit energy, this is extending the battery statement period and is improving system energy efficiency side
Face is made that huge contribution.
MIMO (Multiple-In Multi-Out, multiple-input and multiple-output) technology is to realize information in future communications network
One of key technology of high-speed transfer, it can double up the mutual information of communication system without increase in bandwidth
And spectrum efficiency.The benefit of large-scale multiple antennas not only contains the advantage of MIMO, further includes when number of antennas tends to be infinite one
A little declines and the influence of incoherent noise can all disappear, so that spectrum efficiency is unrelated with bandwidth.
Since there are many transmission antenna number in large-scale multiple antenna communication, and mobile terminal quantity is far smaller than BS's
Transmission antenna quantity, although spectrum efficiency significantly improves in system, the problem of energy consumption in communication, is also further serious.
Transmission antenna number is more, and used radio frequency (RF) link is also more, and corresponding digital analog converter in RF chain, frequency mixer,
The power loss of transmitting filter, frequency synthesizer, low-noise amplifier, audio-frequency amplifier, filter and analog-digital converter
The more, energy consumption is the more.Therefore system progress day line options are necessary, improve system while reducing power loss
Energy efficiency.
Due to the presence of channel estimation errors, transmitting terminal is difficult to obtain complete channel status information (CSI), channel training mistake
Journey is necessary to system knows CSI, and the incompleteness of this process can directly result in the decline of system performance.Therefore, with it is complete
Standby channel compares, and the research of problem then more meets actual research conditions under incomplete channel.
Summary of the invention
High, calculating that it is an object of that present invention to provide a kind of system energy efficiencies is simply with the large-scale multiple antennas of incomplete CSI
Network energy efficiency resource allocation methods.
To achieve the above object, the method for the invention the following steps are included:
Step 1, base station (BS) is trained estimation to bulk nanometer materials by channel estimator, the letter after being estimated
Road；
Step 2, in the way of wireless power transfer, user equipment collects energy from base station；
Step 3, the case where considering incomplete CSI in channel, calculates the letter in multiaerial system when transmission antenna number is N
Road capacity；
Step 4, the case where considering incomplete CSI in channel, calculates in multiaerial system and is added after Antenna Selection Technology most
Channel capacity when excellent antenna number is L；
Step 5, establish power loss model, and based on after above-mentioned day line options channel capacity and power loss model build
Vertical energy efficiency model；
Step 6, using Antenna Selection Algorithem and optimization resource allocation algorithm based on binary chop, pass through Lagrange
Multiplier method carries out the time to above-mentioned energy efficiency model and sends the combined optimization of power, obtains optimal antenna number and optimal
It can valid value.
Step 7, optimal transmission power is obtained according to above-mentioned optimal energy efficiency.
Further, the channel in step 1, after estimation are as follows:
Wherein,For the base station after estimation and the channel matrix between user；H is complete between base station and user equipment
Channel；Δ E represents evaluated error, and has It is the variance of channel estimation errors.
Further, in step 2, the communication between base station and user equipment is divided into two periods, first
In a period, base station is user's charging by wireless power transfer (WPT), and in second time period, user's utilization is collected into
Energy transfers information to base station.According to law of conservation of energy, energy that user is collected into first time period are as follows:
Wherein, η represents user and converts the transformation efficiency that power storage is got up for the power of collection；α represents base station and use
The path loss generated between the equipment of family dependent on distance；PtRepresent the transmission power of base station end；β is energy beam forming square
Battle array, hasτ is the time of the first segment in a time block.
Further, it in step 3, under the premise of incomplete channel estimation, is calculated in multiple antennas and works as transmission antenna
Quantity is N, and N > > 1 when uplink mutual channel capacity:
Wherein, T indicates the total time of one period of uplink and downlink link,It is the variance of additive white Gaussian noise,
It is the variance of channel estimation errors, Δ h obeys multiple Gauss distribution (Complex Normal Distribution), i.e.,
Further, it in step 4, under the premise of incomplete channel estimation, is calculated in multiaerial system and works as transmission
Antenna sum be N and N > > 1, select the channel capacity of uplink when optimal antenna number is L:
Further, power loss model described in step 5 are as follows:
U(Pt, τ, L) and=(LPbs+Puser)T+Ptτ
In formula, PbsIt is the power loss of every antenna of base station end, PuserIt is the power loss of user terminal, respectively by following two
A formula expression,
Puser=2Psyn+PLNA+Pmix+PIFA+Pfilr+PADC
Pbs=PDAC+Pmix+Pfilt
In formula, PDAC,Pmix,Pfilt,Psyn,PLNA,PIFA,Pfilr,PADCIt respectively indicates digital analog converter, frequency mixer, send filter
The power loss of wave device, frequency synthesizer, low-noise amplifier, audio-frequency amplifier, filter and analog-digital converter；
Based on above-mentioned power loss model, the energy efficiency model is calculated:
Further, in step 7, the corresponding optimal transmission power such as following formula of optimal efficiency is obtained:
Wherein, Χ1~Χ5It is respectively as follows:
The course of work approximately as:
The efficiency resource allocation methods that Massive mimo antenna selects under incomplete channel estimation, are received by energy
Collection, Massive MIMO, day line options, the technologies such as beam forming propose the energy efficiency model for needing to optimize, by target problem
It is solved under the conditions of constraint by method of Lagrange multipliers, obtains optimal energy efficiency, obtain the optimal transmission power in the end BS.
Compared with prior art, the method for the present invention has the advantages that
1, antenna selecting method is quickly found out optimal transmission antenna number based on a binary chop algorithm, and uses energy
Beam forming technique is measured to maximize system energy efficiency.
2, joint considers the wireless power transfer and the second period wireless information transfer of the first period, shows a resource
Allocation algorithm obtains system maximum efficiency by the time of the transmission power of combined optimization BS and first segment.
Detailed description of the invention
Fig. 1 is system model of the invention.
Fig. 2 is a specific flow chart in embodiment of the present invention.
Fig. 3 is the optimization algorithm software flow pattern in the present invention with day line options.
Specific embodiment
The present invention will be further described with reference to the accompanying drawing:
Fig. 1 is system model of the invention.Fig. 1, which is presented, has two period communication protocols under an incomplete channel estimation
Radio communications system.In system structure, there are 1 base station (BS), 1 single user (User), BS includes that a channel is estimated
Gauge (CE, channel estimator).Wherein, BS assembles N root antenna, and User assembles 1 antenna.In model, the effect of BS
It is to charge for user, carries out the transmission of energy；And User is a single user of receiving end, its effect is that storage base station is sent
Energy, so that information is sent back base station.
Fig. 1 also describes the agreement of two periods.There is a continuous energy supply in base station to user, it is therefore an objective to be not required to
Other energy are wanted to support.Therefore, it in first time period, is transmitted by infinite energy, the energy that user transmits base station carries out
It collects, and stores the energy of collection and rechargeable battery to one；In second time period, user will using the energy being collected into
Information is sent to base station.The time of entire transmission process is T, this is referred to as a time block.In each piece of beginning, in the τ time
Interior (the first period) carries out wireless energy transfer (WPT, wireless power transfer) between base station and user；?
In the Τ-τ time (the second period), wireless information transfer (WIT, wireless information is carried out between user and base station
transfer)。
Fig. 2 is the specific method process of a specific embodiment of the invention, is mainly comprised the steps that
Step 1: the channel by the channel model of training estimation bulk nanometer materials, after being estimated.
Step 2: in the way of wireless power transfer, user equipment collects energy from base station.
Step 3: the case where considering incomplete CSI in channel calculates the letter in multiaerial system when transmission antenna number is N
Road capacity.
Step 4: the case where considering incomplete CSI in channel is calculated in multiaerial system and is added after Antenna Selection Technology most
Channel capacity when excellent antenna number is L.
Step 5: establish power loss model, and based on after above-mentioned day line options channel capacity and the power loss mould
Type establishes energy efficiency model.
Step 6: in conjunction with Antenna Selection Algorithem and resource allocation optimization algorithm, time and hair being carried out to above-mentioned energy model
The combined optimization for sending power obtains optimal transmission antenna number and optimal efficiency.
Step 7: optimal transmission power is obtained according to above-mentioned optimal energy efficiency.
After algorithm starts, whether the EE calculated in judgment step 7 restrains Fig. 3, if convergence, end loop, if not receiving
It holds back, then changes Lagrange multiplier value, the power and time for obtaining circulation next time continue to obtain if meeting Rule of judgment
The antenna number and efficiency of optimization, to obtain optimal transmission power, end loop.
Embodiment described above only describe the preferred embodiments of the invention, not to model of the invention
It encloses and is defined, without departing from the spirit of the design of the present invention, those of ordinary skill in the art are to technical side of the invention
The various changes and improvements that case is made should all be fallen into the protection scope that claims of the present invention determines.
Claims (1)
1. a kind of large-scale multiple antennas network energy efficiency resource allocation methods with incomplete CSI mainly include user equipment, base
It stands, antenna, which is characterized in that the described method comprises the following steps:
(1) step 1, base station (BS) are trained estimation to bulk nanometer materials by channel estimator, the channel after being estimated；
Wherein, the channel after estimation are as follows:
Wherein,The channel matrix between BS and user after representing estimation, H represent letter complete between BS and user equipment
Road, Δ E represents evaluated error, and has
(2) step 2, in the way of wireless power transfer, user equipment collects energy from base station；Wherein, by base station and user
Communication between equipment is divided into two periods, and within first period, base station is to use by wireless power transfer (WPT)
Family charging, in second time period, user transfers information to base station using the energy being collected into；According to law of conservation of energy, use
The energy that family is collected into first time period are as follows:
Wherein, η represents user and converts the transformation efficiency that power storage is got up for the power of collection, and α represents BS and user equipment
Between dependent on distance generate path loss, PtThe transmission power at the end BS is represented, β is energy beamforming matrix, is hadτ indicates the time of the first segment in a time block；
(3) step 3, consider channel in incomplete CSI the case where, calculate multiaerial system in when transmission antenna number be N when letter
Road capacity；Under the premise of incomplete channel estimation, be calculated in multiple antennas when transmission antenna quantity be N and N > > 1 when uplink
The mutual channel capacity of link:
Wherein, T indicates the total time of one period of uplink and downlink link,It is the variance of white Gaussian noise,It is that channel is estimated
The variance of error is counted, Δ h obeys multiple Gauss distribution (Complex Normal Distribution), i.e.,
(4) step 4, consider channel in incomplete CSI the case where, calculate multiaerial system in be added Antenna Selection Technology after it is optimal
Channel capacity when antenna number is L；Under the premise of incomplete channel estimation, it is calculated in multiaerial system and works as transmission antenna
The channel capacity of uplink when sum is N and N > > 1 optimal antenna number selected is L:
(5) step 5 establishes power loss model, and based on the channel capacity and power loss model foundation energy after day line options
Amount efficiency model；Power loss model are as follows:
U(Pt, τ, L) and=(LPbs+Puser)T+Ptτ
Wherein, PbsIt is the power loss of every, the end BS antenna, PuserIt is the power loss of user terminal, respectively by following two formula
It indicates:
Ρuser=2 Ρsyn+ΡLNA+Ρmix+ΡIFA+Ρfilr+ΡADC
Ρbs=ΡDAC+Ρmix+Ρfilt
ΡDAC,Ρmix,Ρfilt,Ρsyn,ΡLNA,ΡIFA,Ρfilr,ΡADCIt respectively indicates digital analog converter, frequency mixer, send filter
The power loss of wave device, frequency synthesizer, low-noise amplifier, audio-frequency amplifier, filter and analog-digital converter；
Based on power loss model, energy efficiency model is further calculated:
(6) step 6 using the Antenna Selection Algorithem based on binary chop and optimizes resource allocation algorithm, passes through Lagrange
Multiplier method carries out the time to energy efficiency model and sends the combined optimization of power, obtains optimal antenna number and optimal efficiency
Value；
(7) step 7 obtains optimal transmission power according to optimal energy efficiency；Obtain the corresponding optimal transmission function of optimal efficiency
Rate such as following formula:
Wherein, the X in formula1~X5Are as follows:
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| CN107493124B (en) * | 2017-08-09 | 2020-12-18 | 深圳先进技术研究院 | Multi-antenna microwave wireless charging beam forming algorithm |
| CN108512579B (en) * | 2018-03-14 | 2021-02-05 | 广西师范大学 | Antenna selection method based on EH-MIMO communication system |
| CN109710006A (en) * | 2018-12-20 | 2019-05-03 | 河南省农业科学院畜牧兽医研究所 | A kind of intelligence electric monitoring system for farming cultivation |
| CN117527113B (en) * | 2024-01-08 | 2024-04-12 | 深圳市迈腾电子有限公司 | Wireless channel fading prediction method based on AI model |
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