CN115173901A - IRS (intelligent communications system) -assisted MISO (multiple input single output) wireless energy-carrying communication system energy efficiency maximization method - Google Patents
IRS (intelligent communications system) -assisted MISO (multiple input single output) wireless energy-carrying communication system energy efficiency maximization method Download PDFInfo
- Publication number
- CN115173901A CN115173901A CN202210634256.2A CN202210634256A CN115173901A CN 115173901 A CN115173901 A CN 115173901A CN 202210634256 A CN202210634256 A CN 202210634256A CN 115173901 A CN115173901 A CN 115173901A
- Authority
- CN
- China
- Prior art keywords
- irs
- user
- energy
- base station
- beam forming
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 72
- 238000004891 communication Methods 0.000 title claims abstract description 56
- 239000013598 vector Substances 0.000 claims abstract description 81
- 238000005457 optimization Methods 0.000 claims abstract description 50
- 238000009826 distribution Methods 0.000 claims abstract description 34
- 238000013178 mathematical model Methods 0.000 claims abstract description 24
- 238000005516 engineering process Methods 0.000 claims description 22
- 230000006870 function Effects 0.000 claims description 15
- 230000005540 biological transmission Effects 0.000 claims description 10
- 230000014509 gene expression Effects 0.000 claims description 6
- 238000003860 storage Methods 0.000 claims description 6
- 238000006243 chemical reaction Methods 0.000 claims description 5
- 238000005265 energy consumption Methods 0.000 claims description 5
- 230000002040 relaxant effect Effects 0.000 claims description 5
- 230000000694 effects Effects 0.000 claims description 4
- 230000009466 transformation Effects 0.000 claims description 2
- 235000015429 Mirabilis expansa Nutrition 0.000 claims 8
- 244000294411 Mirabilis expansa Species 0.000 claims 8
- 235000013536 miso Nutrition 0.000 claims 8
- 230000008901 benefit Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000001902 propagating effect Effects 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
Images
Classifications
-
- 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
- H04B7/04013—Intelligent reflective surfaces
-
- 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
- H04B7/0413—MIMO systems
- H04B7/0426—Power distribution
- H04B7/043—Power distribution using best eigenmode, e.g. beam forming or beam steering
-
- 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
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/02—Resource partitioning among network components, e.g. reuse partitioning
- H04W16/10—Dynamic resource partitioning
-
- 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
- H04W16/22—Traffic simulation tools or models
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Power Engineering (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The invention discloses an IRS (intelligent communications system) -assisted MISO (multiple input single output) wireless energy-carrying communication system energy efficiency maximization method. The method comprises the following steps: constructing an intelligent reflector assisted MISO wireless energy-carrying communication system, wherein each user can collect information and receive energy by using a power distribution scheme; establishing a mathematical model for maximizing system energy efficiency; and designing and analyzing an alternating optimization algorithm for jointly optimizing the transmitting beam forming vector, the reflecting beam forming vector and the power distribution factor to complete the maximization of the system energy efficiency. According to the invention, the intelligent reflecting surface is deployed in the wireless energy-carrying communication system, meanwhile, a power distribution strategy is utilized, a mathematical optimization problem of the system model based on the maximized energy efficiency is established, and an alternating optimization algorithm is applied to jointly optimize the transmitting beam forming vector, the reflecting beam forming vector and the power distribution factor, so that the energy efficiency of the system is maximized while the minimum communication rate requirement and the minimum energy collection requirement of each user are met.
Description
Technical Field
The invention relates to the technical field of wireless communication, in particular to an energy efficiency maximization method of a MISO wireless energy-carrying communication system based on IRS assistance.
Background
Fifth generation communication networks utilize different advanced technologies to greatly improve the spectral and energy efficiency of communication systems. However, these techniques tend to suffer from high power consumption and high implementation cost, which has constituted a bottleneck in designing a practical system. For example, internet of things devices are often limited by battery capacity. Therefore, there is a need for an extensible and sustainable solution to enable ubiquitous connectivity and continuous energy supply for these devices in 5G and beyond wireless networks.
The intelligent reflecting surface can realize high beam gain under the condition of obviously reducing energy consumption and hardware cost. The intelligent reflective surface may be installed outside a building to provide energy-saving wireless communication by reducing transmission power of a base station. The intelligent reflecting surface is composed of a large number of adjustable passive units arranged on the planar array, so that a more favorable wireless propagation channel can be established, and more reliable communication is realized. These passive components have the advantage of being cost-effective and energy efficient, and can intelligently adjust the phase and amplitude of the signal to independently control the incident signal. Thus, the reflected signal and the direct signal of the base station can be coherently combined at the desired receiver to improve the signal-to-interference-and-noise ratio of the receiver. Therefore, the intelligent reflector is a subversive technology, which can make the signal propagation environment intelligent, which can benefit industries such as traffic, manufacturing, smart cities and the like in 5G/6G.
In addition, the wireless energy-carrying communication network only propagates information in distinction from the traditional wireless communication, and can simultaneously transmit energy signals to the wireless devices when propagating wireless signals of traditional information type. After the wireless energy-carrying communication technology is applied, the cost of wires and flat cables can be reduced, the trouble of replacing batteries for wireless equipment can be avoided, and meanwhile, the energy efficiency of a communication system is improved. Therefore, there is a need for an optimization technique that can improve the energy efficiency of the communication system, configure the communication environment reasonably, and maximize the energy efficiency of the system. Users in the existing IRS-assisted wireless energy-carrying communication system are mostly divided into energy users and information users, which receive energy and information, respectively. Therefore, further research is needed to enable information decoding and energy reception for all users in a communication system.
Disclosure of Invention
In order to overcome the defects and shortcomings of the prior art, the invention provides an IRS (intelligent reflector) -assisted MISO (multiple input single output) wireless energy-carrying communication system-based energy efficiency maximization method.
A second object of the present invention is to provide an energy efficiency maximization system of the miss wireless energy-carrying communication system based on IRS assistance.
A third object of the present invention is to provide a computer-readable storage medium.
It is a fourth object of the invention to provide a computing device.
In order to achieve the purpose, the invention adopts the following technical scheme:
an energy efficiency maximization method of a MISO wireless energy-carrying communication system based on IRS assistance comprises the following steps:
establishing a downlink channel model of the intelligent reflector assisted MISO wireless energy-carrying communication network, and combining a reflection path reflected by the intelligent reflector with a direct path to form a channel model between a base station and users, wherein each user uses a power distribution scheme to collect information and receive energy;
establishing a mathematical model based on system energy efficiency maximization aiming at a downlink channel model, wherein the mathematical model comprises a mathematical expression for determining an optimization variable, an objective function and a constraint condition, and the optimization variable comprises: a base station transmits a beam forming vector, an intelligent reflecting surface reflection beam forming vector and a power distribution factor;
constructing an alternative optimization algorithm for analyzing and jointly optimizing a base station transmitting beam forming vector, an intelligent reflecting surface reflecting beam forming vector and a power distribution factor, and completing the maximization of system energy efficiency;
the alternating optimization algorithm specifically comprises:
fixing a reflected beam forming vector and a power distribution factor, and optimizing the transmitted beam forming vector by using a dinkelbach method, an SCA (supervisory control and data acquisition) technology and an SDR (standard definition link) technology;
optimizing a reflection beam forming vector at the IRS by using a dinkelbach method, SDR and SCA technology;
optimizing power distribution factors at a user by using a dinkelbach method;
and alternately optimizing until convergence.
As a preferred technical scheme, the intelligent reflector-assisted multi-user MISO wireless energy-carrying communication network comprises a base station provided with M antennas, an intelligent reflector-assisted base station and K single-antenna users;
order to
An index representing a set of users is provided,
index representing IRS reflection unit set, order
Representing the base station transmit beamforming vector, s k Representing a userk desired signal;
the channels from base station to user, base station to IRS and IRS to user are respectively represented as
And
simultaneously representing reflected beamforming vectors as
The transmission signal of the base station is represented as:
the combined channel from the base station to the user via the IRS is denoted as
Wherein,
the user uses a power allocation strategy to achieve the effect of receiving signals and energy simultaneously.
As a preferred technical solution, the establishing of the mathematical model based on system energy efficiency maximization for the downlink channel model specifically includes:
at the user, using the power allocation strategy, the signal received at user k is represented as:
wherein
Representing white gaussian noise while treating the interference of other users as noise, the rate at user k is represented as:
the total system rate is expressed as:
the energy received by user k is represented as:
where η represents the energy conversion efficiency, and the total received energy of the system is represented as:
the total power consumption of the system is therefore:
where ζ represents the reciprocal of the drain efficiency of the transmit power amplifier, P C Represents the system circuit loss, P T Representing the power consumption, P, of each transmit antenna n (b) Represents the power consumption of each IRS reflection unit;
the energy efficiency of the system is the ratio of the total transmission rate to the energy consumption, and is expressed by a mathematical model as:
the constraint conditions of the mathematical model based on the energy efficiency maximization of the system comprise:
user minimum rate:
R min is the minimum rate;
minimum received energy of user:
E min is the minimum received energy;
maximum transmission power of the base station:
P m is the base station maximum transmit power;
power allocation factor constraint:
and (3) intelligent reflecting surface constraint:
the mathematical model for energy efficiency maximization based on the system is as follows:
as a preferred technical solution, a reflected beam forming vector and a power allocation factor are fixed, and the optimization problem of the transmitted beam forming vector is expressed as:
the objective function is:
the constraint conditions are as follows:
the target function is converted into a subtractive equation by using a Dinkelbach method:
the subtraction is converted to the convex problem using the SCA method, introducing two variables:
thus is provided with
Problem P2 translates into:
using the SCA method
The transformation is to a convex constraint,
in that
The taylor expansion of (a) is:
relaxing constraints using SDR techniques
The following problems are optimized:
where K denotes the index of the set of users, N denotes the index of the set of IRS reflection units, w k Representing base station transmit beamforming vector, p k Represents the power division factor, s k Represents the signal desired by user k, G, h k And f k Denotes the base station to user, base station to IRS and IRS to user channels, respectively, v denotes the reflected beamforming vector, and ζ denotes the reciprocal of the transmit power amplifier drain efficiency.
As an optimal technical scheme, a dinkelbach method, an SDR (standard definition link) and an SCA (supervisory control and ranging) technology are used for optimizing a reflection beam forming vector at an IRS (infrared receiver system), and the specific steps comprise:
fixing the transmit beamforming vector and the power allocation factor, and expressing the original optimization as follows by using a Dinkelbach method:
V N+1,N+1 ＝1,
V≥0,
rank(V)≤1.
wherein,
the original optimization problem is represented as follows by using a Dinkelbach method:
V N+1,N+1 ＝1,
V≥0,
rank(V)≤1.
using the SCA and SDR methods, two variables were introduced:
V N+1,N+1 ＝1
where K denotes the index of the set of users, N denotes the index of the set of IRS reflection units, w k Representing base station transmit beamforming vector, p k Represents the power division factor, s k Represents the signal desired by user k, G, h k And f k Denotes the base station to user, base station to IRS and IRS to user channels, respectively, v denotes the reflected beamforming vector, and ζ denotes the reciprocal of the transmit power amplifier drain efficiency.
As a preferred technical scheme, a dinkelbach method is used for optimizing power distribution factors at a user, and the method specifically comprises the following steps:
the optimization problem with respect to power allocation factors is represented by fixing the transmit beamforming vector and the reflected beamforming vector as follows:
where K denotes the index of the set of users, N denotes the index of the set of IRS reflection units, w k Representing base station transmit beamforming vector, p k Represents the power division factor, s k Represents the signal desired by user k, G, h k And f k Denotes the base station to user, base station to IRS and IRS to user channels, respectively, v denotes the reflected beamforming vector, and ζ denotes the reciprocal of the transmit power amplifier drain efficiency.
In order to achieve the second object, the invention adopts the following technical scheme:
an energy efficiency maximization system for an IRS-assisted MISO wireless energy-carrying communication system, comprising: the system comprises a channel model building module, an energy efficiency maximization model building module and an alternative optimization module;
the channel model building module is used for building a downlink channel model of the intelligent reflector assisted MISO wireless energy-carrying communication network, and combining a reflection path reflected by the intelligent reflector with a direct path to form a channel model between a base station and users, wherein each user uses a power distribution scheme to collect information and receive energy;
the energy efficiency maximization model building module is used for building a mathematical model based on system energy efficiency maximization aiming at a downlink channel model, and comprises mathematical expressions for determining optimization variables, an objective function and constraint conditions, wherein the optimization variables comprise: a base station transmits a beam forming vector, an intelligent reflecting surface reflection beam forming vector and a power distribution factor;
the alternate optimization module is used for constructing an alternate optimization algorithm for analyzing and jointly optimizing a base station transmitting beam forming vector, an intelligent reflecting surface reflecting beam forming vector and a power distribution factor to complete the maximization of the system energy efficiency;
the alternating optimization algorithm specifically comprises:
fixing a reflected beam forming vector and a power distribution factor, and optimizing the transmitted beam forming vector by using a dinkelbach method, an SCA (supervisory control and data acquisition) technology and an SDR (standard definition link) technology;
optimizing a reflection beam forming vector at the IRS by using a dinkelbach method, SDR and SCA technology;
optimizing a power distribution factor at a user by using a dinkelbach method;
and alternately optimizing until convergence.
In order to achieve the third object, the invention adopts the following technical scheme:
a computer-readable storage medium storing a program which, when executed by a processor, implements the above-described energy efficiency maximizing method for the IRS-based assisted MISO wireless energy-carrying communication system.
In order to achieve the fourth object, the invention adopts the following technical scheme:
a computing device comprising a processor and a memory for storing processor-executable programs that, when executed by the processor, implement the above-described method for maximizing energy efficiency in an IRS-based assisted MISO wireless energy-carrying communication system.
Compared with the prior art, the invention has the following advantages and beneficial effects:
(1) According to the invention, an intelligent reflector-assisted MIMO wireless energy-carrying communication system model is constructed, an IRS system is introduced for communication assistance, an alternative optimization algorithm for jointly optimizing a transmitting beam forming vector, a reflecting beam forming vector and a power distribution factor is designed and analyzed, and the maximization of the system energy efficiency is completed; the invention adopts the SWIPT technology based on power distribution, solves the technical problem that an energy receiver and a signal receiver need two different receivers, achieves the technical effects that a user can simultaneously receive signals and store energy, can compensate communication energy consumption to a certain extent by using the stored energy per se, and further improves the energy efficiency of a communication system; meanwhile, the intelligent reflecting surface is deployed in the communication system, so that the communication environment can be reasonably configured, and higher energy efficiency is obtained.
Drawings
FIG. 1 is a schematic flow chart of an energy efficiency maximization method of an IRS-assisted MISO wireless energy-carrying communication system according to the present invention;
FIG. 2 is a schematic diagram of a model of an intelligent reflector-assisted MIMO wireless energy-carrying communication system according to the present invention;
FIG. 3 is a schematic flow chart of an alternative optimization algorithm of the present invention;
FIG. 4 is a diagram illustrating simulation results of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
As shown in fig. 1, the embodiment provides an energy efficiency maximization method of a MISO wireless energy-carrying communication system based on IRS assistance, which includes the following steps:
s1: establishing a downlink channel model of the intelligent reflector assisted MISO wireless energy-carrying communication network; combining the reflection path reflected by the intelligent reflection surface with the direct path to form a channel model between the base station and users, wherein each user can collect information and receive energy by using a power distribution scheme;
as shown in fig. 2, the MISO wireless energy-carrying communication network with the assistance of the intelligent reflector comprises a base station with M antennas, the assistance of the intelligent reflector and K single-antenna users. Wherein the user uses a power allocation strategy to achieve the effect of receiving signals and energy simultaneously;
order to
An index representing a set of users is provided,
index representing set of IRS reflection units, and order
Representing the base station transmit beamforming vector, s k Representing the signal desired by user k. In addition, the base station to user, base station to IRS and IRS to user channels are denoted as
And
simultaneously representing reflected beamforming vectors as
Thus, the transmission signal of the base station can be expressed as:
the combined channel from the base station to the user via the IRS can be represented as
Wherein
S2: establishing a mathematical model based on system energy efficiency maximization aiming at a downlink channel model, wherein the mathematical model comprises a mathematical expression for determining an optimization variable, an objective function and a constraint condition;
the step S2 includes the steps of:
at the user, using a power allocation strategy, let ρ k A factor is allocated for the power. Thus, the signal received at user k can be expressed as:
whereinn k Representing gaussian white noise. While considering the interference of other users as noise, the rate at user k can be expressed as:
thus, the total system rate can be expressed as:
on the other hand, the energy received by user k can be expressed as:
where η represents the energy conversion efficiency. The total received energy of the system can thus be expressed as:
the total power consumption of the system is therefore:
where ζ represents the reciprocal of the drain efficiency of the transmit power amplifier, P C Represents the system circuit loss, P T Representing the power consumption, P, of each transmit antenna n (b) Representing the power consumption of each IRS reflection unit.
The energy efficiency of the system is the ratio of the total transmission rate to the energy consumption, and can be expressed by a mathematical model as:
the optimization variables of the mathematical model based on the maximization of the system energy efficiency in the embodiment comprise:
1) The base station transmits a beamforming vector, i.e. { w k }；
2) The intelligent reflecting surface reflects a beam forming vector, namely v;
3) Power division factor, i.e. { ρ k }；
The constraint conditions of the mathematical model based on the energy efficiency maximization of the system comprise:
(1) User minimum rate:
R min is the minimum rate;
(2) User minimum received energy:
E min is the minimum received energy;
(3) Maximum transmission power of the base station:
pm is the maximum transmitting power of the base station;
(4) Power allocation factor constraint:
(5) And (3) intelligent reflecting surface constraint:
the mathematical model for energy efficiency maximization based on the system is as follows:
s3: according to a specific mathematical model, constructing and analyzing an alternative optimization algorithm for jointly optimizing a base station transmitting beam forming vector, an intelligent reflecting surface reflecting beam forming vector and a power distribution factor, and completing maximization of system energy efficiency;
as shown in fig. 3, the alternative optimization algorithm includes the following steps:
fixed reflected beam forming vector v and power allocation factor [ rho ] k When the objective function is with respect to the transmit beamforming vector w k Solving by using a dinkelbach method and a continuous convex approximation (SCA) and semi-definite relaxation (SDR) technology;
based on the transmit beamforming vector w k }, fixed power allocation factor [ rho ] k At the moment, the target function becomes a function about a reflected beam forming vector v, and a dinkelbach method and continuous convex approximation (SCA) and semi-definite relaxation (SDR) technology are used for solving;
based on the transmit beamforming vector w k And a reflection beam forming vector v, and optimizing a power distribution factor [ rho ] by using a dinkelbach method k }。
Step S3 includes the following steps:
s3.1 fixing v and { ρ k H, optimize { w k }. The equivalent channel from the base station to user k at this time can be represented as
Order to
Thus, optimization of transmit beamforming vectorsThe problem can be expressed as:
the fractional objective function (14) is then converted to a subtractive equation using the Dinkelbach method:
the SCA method is used to convert (20) to a convex problem. Two variables were introduced:
thus is provided with
On the basis of the above, the problem P2 can be converted into:
the (26) is converted to convex constraints using the SCA method.
In that
The taylor expansion of (a) is:
thus (26) can be written as:
using SDR technique relaxation constraints (31), the following problem is optimized:
(P2.2) the optimization problem regarding transmit beamforming becomes a convex problem and can be solved with CVX.
S3.2 in fixed { w k And { ρ k V is optimized. Definition c k，i ＝Φ k w i And
thus, there are:
wherein,
simultaneous definition of
Wherein
Definition of
Using the Dinkelbach method, the original overall problem (P1) can be further expressed as:
V N+1,N+1 ＝1, (45)
V≥0, (46)
rank(V)≤1. (47)
SCA and SDR methods are used. Two variables were introduced:
V N+1,N+1 ＝1. (55)
up to now, the optimization problem regarding reflected beam forming becomes a convex problem, which can be solved with CVX.
S3.3 fixation { w k In the case of { ρ } and v, optimization of { ρ } using Dinkelbach's method k }. Thus, with respect to { ρ k The optimization problem can be expressed as:
problem (P4) is a convex problem and can therefore be solved using a specialized convex optimization toolkit CVX.
S3.4 combines the above { w k V and [ rho ] k And (4) the solution method alternately optimizes the three sub-problems, namely, the original energy efficiency maximization problem (P1) can be solved.
As shown in fig. 4, the simulation result of the present invention is obtained, and it can be seen from the figure that as the number of IRS units increases, the energy efficiency of the system also increases, which fully explains that deploying IRS in the wireless energy-carrying communication system can improve the energy efficiency of the system.
Example 2
The embodiment provides an energy efficiency maximization system of a MISO wireless energy-carrying communication system based on IRS assistance, which comprises: the system comprises a channel model building module, an energy efficiency maximization model building module and an alternative optimization module;
as a preferred technical solution, the channel model building module is configured to build a downlink channel model of the MISO wireless energy-carrying communication network assisted by the intelligent reflector, and combine a reflection path reflected by the intelligent reflector with a direct path to form a channel model between the base station and the users, where each user uses a power allocation scheme to perform information collection and energy reception;
as a preferred technical solution, the energy efficiency maximization model building module is configured to build a mathematical model based on system energy efficiency maximization for a downlink channel model, where the mathematical model includes a mathematical expression for determining an optimization variable, an objective function, and a constraint condition, and the optimization variable includes: a base station transmits a beam forming vector, an intelligent reflecting surface reflection beam forming vector and a power distribution factor;
as an optimal technical scheme, the alternate optimization module is used for constructing an alternate optimization algorithm for analyzing and jointly optimizing a base station transmitting beam forming vector, an intelligent reflecting surface reflecting beam forming vector and a power distribution factor, and the maximization of the system energy efficiency is completed;
as a preferred technical solution, the alternating optimization algorithm specifically includes:
fixing a reflected beam forming vector and a power distribution factor, and optimizing the transmitted beam forming vector by using a dinkelbach method, an SCA (supervisory control and data acquisition) technology and an SDR (standard definition link) technology;
optimizing a reflection beam forming vector at the IRS by using a dinkelbach method, SDR and SCA technology;
optimizing power distribution factors at a user by using a dinkelbach method;
and alternately optimizing until convergence.
Example 3
The present embodiment provides a storage medium, which may be a storage medium such as a ROM, a RAM, a magnetic disk, an optical disk, etc., and the storage medium stores one or more programs, and when the programs are executed by a processor, the method for maximizing the energy efficiency of the IRS-assistance-based MISO wireless energy-carrying communication system of embodiment 1 is implemented.
Example 4
The embodiment provides a computing device, which may be a desktop computer, a notebook computer, a smart phone, a PDA handheld terminal, a tablet computer or other terminal device with a display function, and includes a processor and a memory, where the memory stores one or more programs, and when the processor executes the programs stored in the memory, the method for maximizing the energy efficiency of the miss wireless energy-carrying communication system based on IRS assistance in embodiment 1 is implemented.
The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.
Claims (9)
1. An IRS-assisted MISO wireless energy-carrying communication system energy efficiency maximization method, which is characterized by comprising the following steps:
establishing a downlink channel model of the intelligent reflector assisted MISO wireless energy-carrying communication network, and combining a reflection path reflected by the intelligent reflector with a direct path to form a channel model between a base station and users, wherein each user uses a power distribution scheme to collect information and receive energy;
establishing a mathematical model based on system energy efficiency maximization aiming at a downlink channel model, wherein the mathematical model comprises a mathematical expression for determining an optimization variable, an objective function and a constraint condition, and the optimization variable comprises: a base station transmits a beam forming vector, an intelligent reflecting surface reflection beam forming vector and a power distribution factor;
constructing an alternative optimization algorithm for analyzing and jointly optimizing a base station transmitting beam forming vector, an intelligent reflecting surface reflecting beam forming vector and a power distribution factor, and completing the maximization of system energy efficiency;
the alternating optimization algorithm specifically comprises:
fixing a reflected beam forming vector and a power distribution factor, and optimizing the transmitted beam forming vector by using a dinkelbach method, an SCA (supervisory control and data acquisition) technology and an SDR (standard definition link) technology;
optimizing a reflection beam forming vector at the IRS by using a dinkelbach method, SDR and SCA technology;
optimizing a power distribution factor at a user by using a dinkelbach method;
and alternately optimizing until convergence.
2. The IRS-based aided MISO wireless energy-carrying communication system of claim 1 wherein the intelligent reflector-aided multi-user MISO wireless energy-carrying communication network comprises a base station with M antennas, an intelligent reflector-aided and K single-antenna users;
order to
An index representing a set of users is provided,
an index representing the set of IRS reflection units, and
representing the base station transmit beamforming vector, s k A signal representing a user k desire;
the channels from base station to user, base station to IRS and IRS to user are respectively represented as
And
simultaneously representing reflected beamforming vectors as
The transmission signal of the base station is represented as:
the combined channel from the base station to the user via the IRS is denoted as f k H ΘG＝v H Φ k Wherein phi is k ＝diag(f k H ) G, the user uses a power allocation strategy to achieve the effect of receiving signals and energy simultaneously.
3. The method of claim 1, wherein the step of establishing a mathematical model based on maximization of system energy efficiency for the downlink channel model comprises:
at the user, using the power allocation strategy, the signal received at user k is represented as:
wherein
Representing white gaussian noise while treating the interference of other users as noise, the rate at user k is represented as:
the total system rate is expressed as:
the energy received by user k is expressed as:
where η represents the energy conversion efficiency, and the total received energy of the system is represented as:
the total power consumption of the system is therefore:
where ζ represents the reciprocal of the drain efficiency of the transmit power amplifier, P C Represents the system circuit loss, P T Representing the power consumption, P, of each transmit antenna n (b) Represents the power consumption of each IRS reflection unit;
the energy efficiency of the system is the ratio of the total transmission rate to the energy consumption, and is expressed by a mathematical model as:
the constraint conditions of the mathematical model based on the energy efficiency maximization of the system comprise:
user minimum rate:
R min is the minimum rate;
minimum received energy of user:
E min is the minimum received energy;
maximum transmission power of the base station:
P m is the base station maximum transmit power;
power allocation factor constraint:
and (3) intelligent reflecting surface constraint:
the mathematical model for maximizing the energy efficiency based on the system is as follows:
(P1)
4. the method of claim 1, wherein the reflected beamforming vector and the power allocation factor are fixed, and the optimization problem of the transmitted beamforming vector is expressed as:
the objective function is: (P2):
the constraint conditions are as follows:
the target function is converted into a subtractive equation by using a Dinkelbach method:
the subtraction is converted to the convex problem using the SCA method, introducing two variables:
thus is provided with
Problem P2 translates into:
(P2):
using the SCA method
The transformation is to a convex constraint,
in that
The taylor expansion of (a) is:
relaxing constraints using SDR techniques
The following problems are optimized:
(P2.2):
where K denotes the index of the set of users, N denotes the index of the set of IRS reflection units, w k Representing base station transmit beamforming vector, p k Represents the power division factor, s k Represents the signal desired by user k, G, h k And f k Denotes the base station to user, base station to IRS and IRS to user channels, respectively, v denotes the reflected beamforming vector, and ζ denotes the reciprocal of the transmit power amplifier drain efficiency.
5. The method of claim 1, wherein the dinkelbach method, the SDR, and the SCA techniques are used to optimize the beamforming vector reflected at the IRS, and the method comprises:
fixing the transmit beamforming vector and the power allocation factor, and expressing the original optimization as follows by using a Dinkelbach method:
(P3):
V N+1,N+1 ＝1,
rank(V)≤1.
wherein,
the original optimization problem is represented as follows by using a Dinkelbach method:
(P3):
V N+1,N+1 ＝1,
rank(V)≤1.
using the SCA and SDR methods, two variables were introduced:
(P3.1):
V N+1,N+1 ＝1
where K denotes the index of the set of users, N denotes the index of the set of IRS reflection units, w k Representing base station transmit beamforming vector, p k Represents the power division factor, s k Represents the signal desired by user k, G, h k And f k Denotes the base station to user, base station to IRS and IRS to user channels, respectively, v denotes the reflected beamforming vector, and ζ denotes the reciprocal of the transmit power amplifier drain efficiency.
6. The method of claim 1, wherein the dinkelbach method is used to optimize the power allocation factor at the user site, and the method comprises the following steps:
the transmit beamforming vector and the reflected beamforming vector are fixed, and the optimization problem about the power allocation factor is expressed as:
(P4):
where K denotes the index of the set of users, N denotes the index of the set of IRS reflection units, w k Representing base station transmit beamforming vector, p k Represents the power division factor, s k Represents the signal desired by user k, G, h k And f k Denotes the base station to user, base station to IRS and IRS to user channels, respectively, v denotes the reflected beamforming vector, and ζ denotes the reciprocal of the transmit power amplifier drain efficiency.
7. An energy efficiency maximization system for a MISO wireless energy-carrying communication system based on IRS assistance, comprising: the system comprises a channel model building module, an energy efficiency maximization model building module and an alternative optimization module;
the channel model building module is used for building a downlink channel model of the intelligent reflector assisted MISO wireless energy-carrying communication network, and combining a reflection path reflected by the intelligent reflector with a direct path to form a channel model between a base station and users, wherein each user uses a power distribution scheme to collect information and receive energy;
the energy efficiency maximization model building module is used for building a mathematical model based on system energy efficiency maximization aiming at a downlink channel model, and comprises the following mathematical expressions for determining optimization variables, an objective function and constraint conditions, wherein the optimization variables comprise: a base station transmits a beam forming vector, an intelligent reflecting surface reflection beam forming vector and a power distribution factor;
the alternate optimization module is used for constructing an alternate optimization algorithm for analyzing and jointly optimizing a base station transmitting beam forming vector, an intelligent reflecting surface reflecting beam forming vector and a power distribution factor to complete the maximization of the system energy efficiency;
the alternating optimization algorithm specifically comprises:
fixing a reflected beam forming vector and a power distribution factor, and optimizing the transmitted beam forming vector by using a dinkelbach method, an SCA (supervisory control and data acquisition) technology and an SDR (standard definition link) technology;
optimizing a reflection beam forming vector at the IRS by using a dinkelbach method, SDR and SCA technology;
optimizing power distribution factors at a user by using a dinkelbach method;
and alternately optimizing until convergence.
8. A computer-readable storage medium storing a program which when executed by a processor implements a method for maximizing energy efficiency of a MISO wireless energy-carrying communication system based on IRS assistance according to any one of claims 1 to 6.
9. A computing device comprising a processor and a memory for storing a program executable by the processor, wherein the processor, when executing the program stored in the memory, implements the energy efficiency maximization method for an IRS-based assisted MISO wireless energy-carrying communication system of any of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210634256.2A CN115173901A (en) | 2022-06-07 | 2022-06-07 | IRS (intelligent communications system) -assisted MISO (multiple input single output) wireless energy-carrying communication system energy efficiency maximization method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210634256.2A CN115173901A (en) | 2022-06-07 | 2022-06-07 | IRS (intelligent communications system) -assisted MISO (multiple input single output) wireless energy-carrying communication system energy efficiency maximization method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115173901A true CN115173901A (en) | 2022-10-11 |
Family
ID=83485796
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210634256.2A Pending CN115173901A (en) | 2022-06-07 | 2022-06-07 | IRS (intelligent communications system) -assisted MISO (multiple input single output) wireless energy-carrying communication system energy efficiency maximization method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115173901A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117119499A (en) * | 2023-10-23 | 2023-11-24 | 南京邮电大学 | Active reconfigurable intelligent surface-assisted wireless information and energy simultaneous transmission method |
| CN117135641A (en) * | 2023-10-26 | 2023-11-28 | 国网冀北电力有限公司 | Resource allocation method and device of RIS-based power fusion communication network |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111294096A (en) * | 2020-02-17 | 2020-06-16 | 南京信息工程大学 | Channel capacity optimization method of intelligent reflector MISO wireless communication system |
| CN112929067A (en) * | 2021-02-04 | 2021-06-08 | 重庆邮电大学 | SCA-based IRS-NOMA system low-complexity beam forming method |
| CN112929068A (en) * | 2021-02-04 | 2021-06-08 | 重庆邮电大学 | SDR-based IRS-NOMA system beam forming optimization method |
| CN113037349A (en) * | 2021-03-12 | 2021-06-25 | 重庆邮电大学 | Physical layer security design method based on alternate iteration in IRS-assisted MISO system |
| US20210288698A1 (en) * | 2020-03-10 | 2021-09-16 | University Of Electronic Science And Technology Of China | Method for Intelligent Reflecting Surface Aided Terahertz Secure Communication System |
| WO2021207748A2 (en) * | 2020-08-13 | 2021-10-14 | Futurewei Technologies, Inc. | Methods and apparatus for channel reconstruction in intelligent surface aided communications |
| WO2021221603A1 (en) * | 2020-04-27 | 2021-11-04 | Nokia Technologies Oy | Ue positioning aided by reconfigurable reflecting surfaces such as intelligent reflecting surfaces (irs) |
| CN113660051A (en) * | 2021-07-23 | 2021-11-16 | 上海电机学院 | Energy efficiency maximization method and system of millimeter wave communication system |
| CN113825159A (en) * | 2021-09-03 | 2021-12-21 | 重庆邮电大学 | Wireless energy-carrying communication system robust resource allocation method based on intelligent reflector |
| CN113965245A (en) * | 2021-09-30 | 2022-01-21 | 广西电网有限责任公司柳州供电局 | Intelligent reflecting surface communication system resource optimization method based on OPGW (optical fiber composite overhead ground wire) joint box |
| CN114071485A (en) * | 2021-11-15 | 2022-02-18 | 重庆邮电大学 | Intelligent reflecting surface safe communication energy efficiency optimization method based on imperfect channel |
| CN114222289A (en) * | 2021-12-30 | 2022-03-22 | 河南大学 | Secret communication method of intelligent reflecting surface assisted full-duplex wireless energy-carrying network |
| CN114338302A (en) * | 2021-12-22 | 2022-04-12 | 中国南方电网有限责任公司超高压输电公司 | Intelligent reflecting surface two-stage channel estimation method based on millimeter wave joint structure |
| CN114466388A (en) * | 2022-02-16 | 2022-05-10 | 北京航空航天大学 | Intelligent super-surface-assisted wireless energy-carrying communication method |
-
2022
- 2022-06-07 CN CN202210634256.2A patent/CN115173901A/en active Pending
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111294096A (en) * | 2020-02-17 | 2020-06-16 | 南京信息工程大学 | Channel capacity optimization method of intelligent reflector MISO wireless communication system |
| US20210288698A1 (en) * | 2020-03-10 | 2021-09-16 | University Of Electronic Science And Technology Of China | Method for Intelligent Reflecting Surface Aided Terahertz Secure Communication System |
| WO2021221603A1 (en) * | 2020-04-27 | 2021-11-04 | Nokia Technologies Oy | Ue positioning aided by reconfigurable reflecting surfaces such as intelligent reflecting surfaces (irs) |
| WO2021207748A2 (en) * | 2020-08-13 | 2021-10-14 | Futurewei Technologies, Inc. | Methods and apparatus for channel reconstruction in intelligent surface aided communications |
| CN112929067A (en) * | 2021-02-04 | 2021-06-08 | 重庆邮电大学 | SCA-based IRS-NOMA system low-complexity beam forming method |
| CN112929068A (en) * | 2021-02-04 | 2021-06-08 | 重庆邮电大学 | SDR-based IRS-NOMA system beam forming optimization method |
| CN113037349A (en) * | 2021-03-12 | 2021-06-25 | 重庆邮电大学 | Physical layer security design method based on alternate iteration in IRS-assisted MISO system |
| CN113660051A (en) * | 2021-07-23 | 2021-11-16 | 上海电机学院 | Energy efficiency maximization method and system of millimeter wave communication system |
| CN113825159A (en) * | 2021-09-03 | 2021-12-21 | 重庆邮电大学 | Wireless energy-carrying communication system robust resource allocation method based on intelligent reflector |
| CN113965245A (en) * | 2021-09-30 | 2022-01-21 | 广西电网有限责任公司柳州供电局 | Intelligent reflecting surface communication system resource optimization method based on OPGW (optical fiber composite overhead ground wire) joint box |
| CN114071485A (en) * | 2021-11-15 | 2022-02-18 | 重庆邮电大学 | Intelligent reflecting surface safe communication energy efficiency optimization method based on imperfect channel |
| CN114338302A (en) * | 2021-12-22 | 2022-04-12 | 中国南方电网有限责任公司超高压输电公司 | Intelligent reflecting surface two-stage channel estimation method based on millimeter wave joint structure |
| CN114222289A (en) * | 2021-12-30 | 2022-03-22 | 河南大学 | Secret communication method of intelligent reflecting surface assisted full-duplex wireless energy-carrying network |
| CN114466388A (en) * | 2022-02-16 | 2022-05-10 | 北京航空航天大学 | Intelligent super-surface-assisted wireless energy-carrying communication method |
Non-Patent Citations (5)
| Title |
|---|
| JIE TANG ET AL.: "Energy Efficiency Optimization for a Multiuser IRS-Aided MISO System With SWIPT", 《IEEE TRANSACTIONS ON COMMUNICATIONS》, vol. 71, no. 10, 18 July 2023 (2023-07-18) * |
| XIANGHAO YU ET AL.: "Power-Efficient Resource Allocation for Multiuser MISO Systems via Intelligent Reflecting Surfaces", 《2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE》, 15 February 2021 (2021-02-15) * |
| 孙巍等: "智能反射表明辅助的无线携能通信网络资源分配方法", 《通信学报》, vol. 43, no. 2, 28 February 2022 (2022-02-28), pages 34 - 43 * |
| 杨建红: "基于智能反射面的安全通信能效优化算法研究", 《万方学术》, 20 April 2022 (2022-04-20) * |
| 田霖等: "面向无人机携能网络的轨迹与资源规划算法", 《西安电子科技大学学报》, vol. 48, no. 6, 31 December 2021 (2021-12-31) * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117119499A (en) * | 2023-10-23 | 2023-11-24 | 南京邮电大学 | Active reconfigurable intelligent surface-assisted wireless information and energy simultaneous transmission method |
| CN117119499B (en) * | 2023-10-23 | 2024-03-15 | 南京邮电大学 | Active reconfigurable intelligent surface-assisted wireless information and energy simultaneous transmission method |
| CN117135641A (en) * | 2023-10-26 | 2023-11-28 | 国网冀北电力有限公司 | Resource allocation method and device of RIS-based power fusion communication network |
| CN117135641B (en) * | 2023-10-26 | 2024-01-30 | 国网冀北电力有限公司 | Resource allocation method and device of RIS-based power fusion communication network |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113193894B (en) | Reconfigurable intelligent surface-assisted multi-user MISO downlink wireless communication spectrum efficiency joint optimization method | |
| CN113726383B (en) | Intelligent reflection surface-assisted wireless communication system | |
| CN111447618A (en) | Intelligent reflector energy efficiency maximum resource allocation method based on secure communication | |
| CN110266352A (en) | A kind of intelligent reflecting surface phase shift matrix adaptive design method in extensive mimo system | |
| CN115173901A (en) | IRS (intelligent communications system) -assisted MISO (multiple input single output) wireless energy-carrying communication system energy efficiency maximization method | |
| CN107592144B (en) | Node antenna selection method and device for EH-MIMO energy collection and multi-antenna communication system | |
| CN113709687A (en) | Intelligent reflector assisted resource allocation method for wireless sensor network | |
| CN116566444A (en) | MISO wireless energy-carrying communication system energy efficiency maximization method based on IRS assistance | |
| CN114286312A (en) | Method for enhancing unmanned aerial vehicle communication based on reconfigurable intelligent surface | |
| Diamanti et al. | The joint power of NOMA and reconfigurable intelligent surfaces in SWIPT networks | |
| CN110191476B (en) | Reconfigurable antenna array-based non-orthogonal multiple access method | |
| WO2024114506A1 (en) | Method for determining secrecy rate of intelligent reflecting surface-assisted simultaneous wireless information and power transfer system | |
| CN114640379A (en) | Beam optimization method and system based on intelligent reflecting area array element grouping | |
| CN116033461B (en) | Symbiotic radio transmission method based on STAR-RIS assistance | |
| CN117527020A (en) | Combined active and passive beamforming optimization in intelligent reflector-assisted wireless energy-carrying communication system | |
| CN112803978A (en) | Intelligent surface MISO system joint beam forming method based on successive approximation | |
| CN114845363B (en) | Reflection surface-assisted low-power-consumption data unloading method and system | |
| CN116709538A (en) | Uplink transmission method and device for NOMA system assisted by double RIS collaboration | |
| CN114785387B (en) | Intelligent omnidirectional plane-assisted multi-user MISO downlink weighting and rate optimization method | |
| CN115802466A (en) | Combined power distribution and phase shift design method based on distributed RIS (RIS) assisted multi-user system | |
| Wang et al. | Beamforming Design for RIS-Aided AF Relay Networks | |
| Tan et al. | Energy minimization for wireless powered data offloading in IRS-assisted MEC for vehicular networks | |
| CN113630734B (en) | Calculation unloading and resource allocation method for intelligent power grid power supply system | |
| CN116319199B (en) | Method, device and medium for solving closed solution of maximum throughput of wireless power communication network | |
| CN118138083B (en) | Dual RIS auxiliary MU-MIMO beam forming method and system based on energy efficiency maximization |
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 |