CN113473624A - Resource allocation method, device, equipment and medium based on non-orthogonal multiple access - Google Patents

Resource allocation method, device, equipment and medium based on non-orthogonal multiple access Download PDF

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CN113473624A
CN113473624A CN202110735607.4A CN202110735607A CN113473624A CN 113473624 A CN113473624 A CN 113473624A CN 202110735607 A CN202110735607 A CN 202110735607A CN 113473624 A CN113473624 A CN 113473624A
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communication
resource allocation
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small cell
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叶先万
崔海霞
游凡
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South China Normal University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/53—Allocation or scheduling criteria for wireless resources based on regulatory allocation policies
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • 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

Abstract

The invention provides a resource allocation method, a device, equipment and a medium based on non-orthogonal multiple access, wherein the resource allocation method comprises the following steps: s1, constructing a small cell communication system, wherein the small cell base station comprises: a communication user and a communication base station; s2, dividing information received by the antenna in the area where the communication user is located into a plurality of communication scenes according to interference sources; s3, establishing a communication system model according to the communication scene; s4, providing mathematical expression for the communication system model to obtain a resource allocation model expression; and S5, performing resource allocation according to the resource allocation model expression. According to the method, the interference source is used as a constraint condition, a resource allocation model expression is provided, and an optimal solution is obtained by solving, so that the system energy efficiency is higher.

Description

Resource allocation method, device, equipment and medium based on non-orthogonal multiple access
Technical Field
The invention belongs to the technical field of resource allocation, and particularly relates to a resource allocation method, a device, equipment and a medium based on non-orthogonal multiple access.
Background
With the rapid development of scientific technology, the data traffic demand of the next generation wireless communication system will show exponential increase, and the data transmission rate requirements of various internet of things devices are increasingly increased, but the available spectrum resources are insufficient to support the future communication service demand.
In a wireless communication network, the total number of users is much larger than the number of users on a certain time line, and a traditional Orthogonal Multiple Access (OMA) technology can only allocate a single radio resource for one user, which cannot meet the requirement of high-rate communication. In order to improve the spectrum efficiency, it is necessary to allow each wavelet to serve multiple terminals simultaneously, so a new type of multiple access multiplexing, i.e. non-orthogonal multiple access (NOMA), is proposed in the industry. In this case, the sharing of the same spectrum resource by multiple users may cause more information interference.
Disclosure of Invention
In order to overcome the technical defects, a first aspect of the present invention provides a resource allocation method based on non-orthogonal multiple access, including the steps of:
s1, constructing a small cell communication system, wherein the small cell base station comprises: a communication user and a communication base station;
s2, dividing information received by the antenna in the area where the communication user is located into a plurality of communication scenes according to interference sources;
s3, establishing a communication system model according to the communication scene;
s4, providing mathematical expression for the communication system model to obtain a resource allocation model expression;
and S5, performing resource allocation according to the resource allocation model expression.
As a further improvement of the present invention, the communication user includes: small cell users and macro cell users;
the step S2 includes the following steps:
s21, marking the interference from the next small cell user of the non-orthogonal multiple access as a first communication scene;
s22, cross-layer interference from macro cellular users is marked as a second communication scene;
s23, background noise from the communication user when communicating with the communication user, and labeled as a third communication scene.
As a further improvement of the present invention, the step S3 includes the following steps:
s31, setting the condition that the small cell user is interfered by the next small cell user according to the first communication scene;
s32, setting a condition that a macro cell user generates cross-layer interference on communication of a small cell user according to the second communication scene;
s33, setting the time of downlink energy transmission between the communication user and the base station within 1-tau, wherein tau represents the time of uplink information interaction between the communication user and the base station;
s34, when decoding the information, carrying out serial interference elimination processing;
s35, setting the condition that the channel state is completely known.
As a further improvement of the present invention, the step S4 includes the following steps:
s41, calculating the data transmission rate of the kth terminal under two external interference conditions when the base station and the communication user perform uplink information interaction in unit time under the condition that the small cell user is interfered by the next small cell user and under the condition that the macro cell user generates cross-layer interference on the communication of the small cell user;
s42, calculating the sum of the total rates of all the terminals;
s43, taking the energy obtained by the wireless energy carrying transmission scene as a user as a consideration factor, and calculating the energy collected by the kth terminal;
s44, calculating the total energy consumption of the communication system model;
s45, calculating the energy efficiency of the communication system model;
and S46, obtaining a resource allocation model expression according to the data transmission rate of the kth terminal, the total rate sum of all terminals, the energy collected by the kth terminal, the total energy consumption of the communication system model and the energy efficiency of the communication system model.
As a further improvement of the present invention, the step S5 includes the following steps:
s51, calculating the optimal power;
s52, updating the switching time according to the optimal power;
and S53, repeating the step S51-the step S52 until an optimal convergence solution is obtained, and obtaining an optimal energy-efficient value of the system.
As a further improvement of the present invention, the step S51 includes the following steps:
s511, introducing auxiliary variables and converting the resource allocation model expression;
s512, constructing a multivariable Lagrange function for the transformed resource allocation model;
s513, calculating the gradient of the Lagrange function to the small cell user power;
s514, calculating the optimal small cell user power by using a gradient descent method;
s515, updating the Lagrange multiplier by using a gradient descent method;
and S516, repeating iteration until the variable factor is converged, and acquiring the optimal transmission power under the transmission time.
As a further improvement of the present invention, the step S52 includes the following steps:
s521, converting the resource allocation model into an optimization problem model;
s522, converting the optimization problem model into a parameterized subtraction form problem model;
s523, obtaining an expression of optimal switching time according to the optimization problem model and the parameterized subtraction form problem model;
and S524, solving the corresponding optimal switching time according to the transmitting power, solving again and updating the transmitting power according to the optimal switching time, and repeatedly iterating to obtain the optimal solution of the transmitting power and the optimal switching time.
In a second aspect of the present invention, there is provided a resource allocation apparatus based on non-orthogonal multiple access, including:
a communication system building module, configured to build a small cell communication system, where the small cell base station includes: a communication user and a communication base station;
the communication scene dividing module is used for dividing information received by an antenna in an area where the communication user is located into a plurality of communication scenes according to interference sources;
the communication system model establishing module is used for establishing a communication system model according to the communication scene;
the expression calculation module is used for providing mathematical expression to the communication system model to obtain a resource distribution model expression;
and the resource allocation module is used for allocating resources according to the resource allocation model expression.
In a third aspect of the present invention, a computer-readable storage medium is provided, in which at least one instruction, at least one program, code set, or instruction set is stored, and the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the above-mentioned resource allocation method.
In a fourth aspect of the present invention, there is provided a computer device comprising a processor and a memory, wherein at least one instruction, at least one program, set of codes, or set of instructions is stored in the memory, and the at least one instruction, at least one program, set of codes, or set of instructions is loaded and executed by the processor to implement the above-mentioned resource allocation method.
Compared with the prior art, the invention has the following beneficial effects: according to the method, the interference source is used as a constraint condition, a resource allocation model expression is provided, and an optimal solution is obtained by solving, so that the system energy efficiency is higher.
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Embodiments of the invention are described in further detail below with reference to the attached drawing figures, wherein:
FIG. 1 is a flowchart of a resource allocation method according to embodiment 1;
FIG. 2 is a diagram of a communication system model constructed as described in embodiment 1;
FIG. 3 is a schematic structural diagram of a resource allocation apparatus according to embodiment 2;
fig. 4 is a schematic structural diagram of the computer device according to embodiment 3.
Description of the labeling: 1. a communication system construction module; 2. a communication scene division module; 3. a communication system model building module; 4. an expression calculation module; 5. and a resource allocation module.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
As the data transmission rate of communication networks increases, the battery capacity of network node devices will become a bottleneck, and limited battery life is considered to be a key factor limiting the overall performance of the system. Wireless energy transfer (SWIPT) is regarded as a promising solution that can be implemented to provide both information transfer and energy supply for low-power internet of things devices, and the technology makes full use of the advantage that radio frequency signals can carry energy, and can collect energy of a transmitting terminal to wirelessly charge a receiving terminal when information transfer is completed. Through this kind of mode, thing networking device not only can rely on the battery to supply power, can also realize lasting controllable energy through SWIPT and supply, and then extension communication equipment's life.
The invention mainly combines the SWIPT technology and the NOMA technology, and provides a joint optimization problem of power distribution and time switching under the constraints of conditions such as the maximum transmitting power of a base station, the minimum transmission rate of users, mutual interference among users, information transmission time and the like in the actual scene of communication networking. And (4) solving the optimal solution of the model through two iterative algorithms to expect to obtain greater system energy efficiency.
Example 1
The embodiment discloses a resource allocation method based on non-orthogonal multiple access, wherein a communication mode related in the method is that a user and a base station perform interactive time division into two stages, an uplink stage performs information communication, and a downlink stage performs energy transmission, as shown in fig. 1, the method comprises the following steps:
s1, as shown in fig. 2, constructing a small cell communication system, the small cell base station comprising: the communication user and the communication base station, to be explained, are: 1. the small cell users mainly communicate with the small base station and are uniformly distributed in the cell; 2. macro cell users communicate primarily with macro base stations, which generate interference 3 with small cells within a cell, each user being served by one antenna.
And S2, dividing the information received by the antenna in the area of the communication user into a plurality of communication scenes according to the interference source.
In the above embodiment, the communication user includes: the system comprises small cell users and macro cell users, wherein the small cell base station is positioned in the center of an assumed model, and the cell users are uniformly distributed in a cell; step S2 includes the following steps:
s21, interference from the next small cell user of non-orthogonal multiple access, marked as a first communication scenario.
S22, cross-layer interference from the macro cell user, marked as a second communication scenario.
S23, background noise from the communication user when communicating with the communication user, and labeled as a third communication scene.
And S3, establishing a communication system model according to the communication scene.
In the above embodiment, step S3 includes the steps of:
s31, according to the first communication scenario, setting a condition that the small cell user will be interfered by the next small cell user.
And S32, setting conditions for cross-layer interference generated by the M macro-cell users on the communication of the small-cell users according to the second communication scene.
And S33, each terminal has information decoding and energy collecting functions for the base station and the terminal, when the terminal and the base station carry out information energy interaction, wireless energy carrying transmission based on a time switching mode is adopted, and the time for the communication user and the base station to carry out downlink energy transmission is set within the time of 1-tau, wherein tau represents the time for the communication user and the base station to carry out uplink information interaction.
And S34, for the terminal and the terminal, all the terminals share the same bandwidth, so that the terminals can interfere with each other during information decoding, at the moment, the non-orthogonal multiple access is adopted, and during the information decoding, the interference generated by the third communication scene is subjected to serial interference elimination processing, so that the overall performance of the system is improved.
S35, setting the channel gain g from the small cell user to the small base stationkThe channel gain from the small cell user to the macro base station is hkA condition in which the channel state is completely known is set.
And S4, providing mathematical expression to the communication system model to obtain a resource allocation model expression.
In the above embodiment, step S4 includes the steps of:
s41, the base station decodes the information of the small cell user K by serial interference deletion, at this time, when the uplink information interaction between the base station and the communication user is calculated in unit time under the condition that the small cell user K is interfered by the next small cell user K +1, …, K and the cross-layer interference generated by the macro cell user m to the communication of the small cell user, at this time, the power of the small cell user K is assumed to be pkTherefore, when the base station performs uplink information interaction with the user in unit time, the data transmission rate of the kth terminal (K is greater than or equal to 1 and less than or equal to K-1) is as follows:
Figure BDA0003140106660000051
wherein the content of the first and second substances,
Figure BDA0003140106660000052
the external interference obtained for each small cell user is expressed and mainly comprises three items, namely the interference of the next small cell user of non-orthogonal multiple access, the cross-layer interference of a macro cell user and the background noise during self communication. Herein, p iskmExpressed as the interference power, σ, of the small cell user k to the macro cell user m2Representing the power of gaussian white noise.
For the kth terminal, where the interference between the previous small cell users has been eliminated (i.e. the third communication scenario), under two external interference conditions, the data transmission rate of the kth terminal is:
Figure BDA0003140106660000053
s42, calculating the sum of the total rates of all terminals:
Figure BDA0003140106660000054
s43, in unit time, the energy transmission time is 1-tau, and the emission power of the base station is assumed to be P0And taking the energy obtained by the wireless energy-carrying transmission scene as the user mainly from the small base station as a consideration factor, and calculating the energy collected by the kth terminal:
Ek＝(1-τk)ηgkP0
wherein eta represents energy collection coefficient, and energy transmission and information interaction share the same channel gk。
S44, calculating the total energy consumption of the communication system model:
Figure BDA0003140106660000061
wherein the content of the first and second substances,
Figure BDA0003140106660000062
representing the power consumption of all users, ζ is a coefficient, usually the reciprocal of the power amplifier. p is a radical ofcRepresenting the power consumption of the static circuitry of the cellular network, the total energy consumption of the system is equal to the power consumption of the two parts and minus the energy collected by all users using wireless energy-carrying transmission.
S45, calculating an energy efficiency of the communication system model, where the energy efficiency of the wireless energy-carrying transmission-based non-orthogonal multiple access system considered in this embodiment may be defined as:
Figure BDA0003140106660000063
and S46, obtaining a resource allocation model expression according to the data transmission rate of the kth terminal, the total rate sum of all terminals, the energy collected by the kth terminal, the total energy consumption of the communication system model and the energy efficiency of the communication system model.
P1:maxλEE
s.t.[1]Rk≥Rmin
[2](1-τk)ηgkP0≥τkpk
Figure BDA0003140106660000064
[4]P0≤Pmax
[5]0≤τk≤1
[6]pk≥0
Where [1] represents the minimum transmission rate constraint for the user; [2] the energy collected by the user in unit time in the considered system needs to meet the energy consumed by user information interaction, so that the energy consumption of the system can be reduced to the maximum extent; [3] represents the total power limit of the users used; [4] represents a maximum transmit power constraint of the base station; [5] and [6] respectively representing the time constraint of SWIPT and the transmit power constraint of the user in unit time.
And S5, allocating resources according to the resource allocation model expression in the step S46.
The variable of the optimization problem P2 is PkAnd τkThe method belongs to a multivariable optimization problem, and the optimization problem is divided into two layers for optimization solution, so the step S5 comprises the following steps:
s51, fixing taukOptimization of pkCalculating the optimum power
Figure BDA0003140106660000065
Let the information transmission time at this time be tau0∈[0,1]。
Specifically, step S51 includes the steps of:
s511, converting the fractional optimization problem into an equivalent parameterized subtraction form problem by using a Dinkelbach method, introducing an auxiliary variable q, and converting a resource allocation model expression:
Figure BDA0003140106660000071
s.t.[1]Rk≥Rmin
[2](1-τ0)ηgkPmax≥τ0pk
Figure BDA0003140106660000072
[4]pk≥0
s512, solving the optimization problem through a Lagrangian dual algorithm, and constructing a multivariable Lagrangian function as follows:
Figure BDA0003140106660000073
s513, calculating the power p of the Lagrange function to the small cell userkGradient (2):
Figure BDA0003140106660000074
s514, calculating the optimal small cell user power p by using a gradient descent methodk：
Figure BDA0003140106660000075
S515, updating the Lagrange multiplier by using a gradient descent method:
μk(t+1)＝[μk(t)+s1(t)(Rk-Rmin)]+
vk(t+1)＝[vk(t)+s2(t)((1-τ0)ηgkPmax-τ0pk)]+
Figure BDA0003140106660000076
s516, repeating iteration until the variable factor is converged, and acquiring the transmission time tau0Optimum transmission power of
Figure BDA0003140106660000077
S52, updating the switching time according to the optimal power; the method specifically comprises the following steps:
s521, converting the resource allocation model into an optimization problem model:
Figure BDA0003140106660000078
s.t.[1]Rk≥Rmin
[2](1-τk)ηgkPmax≥τkp0
[3]0≤τk≤1
wherein the content of the first and second substances,
Figure BDA0003140106660000079
Figure BDA0003140106660000081
Figure BDA0003140106660000082
s522, converting the optimization problem model into a parameterized subtraction form problem model by adopting a Dinkelbach method:
Figure BDA0003140106660000083
s523, obtaining an expression of optimal switching time according to the optimization problem model and the parameterized subtraction form problem model; specifically, the constraint of [1] in (5.2.1)]Can obtain taukThe lower bound of (1):
Figure BDA0003140106660000084
wherein
Figure BDA0003140106660000085
Figure BDA0003140106660000086
By the constraint in (6.2.1) [2]]Can obtain taukUpper bound of (2): tau isk≤EkWherein
Figure BDA0003140106660000087
The objective function in (5.2.2) is subjected to one-time derivation to obtain
Figure BDA0003140106660000088
Final optimum
Figure BDA0003140106660000089
Can be determined by the following formula:
Figure BDA00031401066600000810
s524, transmitting power p0Solving for the corresponding optimal switching time
Figure BDA00031401066600000811
And (3) giving the step (S52) with the optimal transmission power obtained in the step (S51), updating the corresponding optimal time, assigning the optimal time to the step (S51) to obtain the optimal power obtained by the second iteration, and repeating the iteration for multiple times until the objective function is converged, wherein at this time:
Figure BDA00031401066600000812
Figure BDA00031401066600000813
obtained by
Figure BDA00031401066600000814
Is the systemAnd (4) the optimal energy efficiency value.
S53, repeating the steps S51-S52, transmitting the optimal power obtained in the step S51 to the step S52, updating the corresponding optimal time, assigning the optimal time to the step S51 to obtain the optimal power obtained by the second iteration, and repeating the iteration for multiple times until the objective function is converged, wherein the steps comprise:
Figure BDA00031401066600000815
obtained by
Figure BDA00031401066600000816
The system optimal energy value is obtained.
In summary, the present embodiment has the following technical effects:
1. the adoption of the non-orthogonal multiple access technology can allow each wavelet to serve a plurality of terminals simultaneously, improve the spectrum efficiency, and the adoption of the wireless energy-carrying transmission technology can collect the energy of a transmitting terminal to wirelessly charge a receiving terminal when the information transmission is completed, so that the service life of the communication equipment is prolonged;
2. when resource allocation is carried out, the original problem is solved into a convex optimization problem by using a Dinkelbach method and a Lagrangian dual method, and the optimal power and time allocation scheme is repeatedly and iteratively solved by using a gradient descent method, so that the optimal energy efficiency of the system is obtained. The invention can obtain the optimal energy efficiency of the system by carrying out resource allocation on the users, and has important significance for actual network deployment;
3. under the actual scene of considering communication networking, under the condition constraints of maximum transmitting power of a base station, minimum transmission rate of users, mutual interference among users, information transmission time and the like, the problem of joint optimization of power distribution and time switching is provided. And (4) solving the optimal solution of the model through a multi-iteration algorithm so as to expect to obtain higher system energy efficiency.
Example 2
The embodiment provides a resource allocation device based on non-orthogonal multiple access, which comprises: the system comprises a communication system building module 1, a communication scene dividing module 2, a communication system model building module 3, an expression calculating module 4 and a resource allocation module 5; the communication system constructing module 1 is used for constructing a small cell communication system, and a small cell base station includes: a communication user and a communication base station; the communication scene division module 2 is used for dividing information received by an antenna in an area where a communication user is located into a plurality of communication scenes according to an interference source; the communication system model establishing module 3 is used for establishing a communication system model according to a communication scene; the expression calculation module 4 is used for providing mathematical expression to the communication system model to obtain a resource distribution model expression; the resource allocation module 5 is configured to perform resource allocation according to the resource allocation model expression.
For a specific implementation process of this embodiment, please refer to embodiment 1, which is not described herein.
In the present embodiment, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.
Example 3
The present embodiment provides a computer device, as shown in fig. 4, including a processor and a storage, where the storage stores program codes, and the processor executes the program codes to execute the resource allocation method of embodiment 1.
Those skilled in the art will recognize that, in one or more of the examples described above, the functions described in the embodiments of the present application may be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
The present invention is not intended to be limited to the particular embodiments shown and described, but is to be accorded the widest scope consistent with the principles and novel features herein disclosed.
Example 4
The present embodiment provides a computer-readable storage medium, in which at least one instruction, at least one program, a set of codes, or a set of instructions is stored, and the at least one instruction, the at least one program, the set of codes, or the set of instructions is loaded and executed by a processor to implement the resource allocation method of embodiment 1.
Optionally, the computer-readable storage medium may include: a Read Only Memory (ROM), a Random Access Memory (RAM), a Solid State Drive (SSD), or an optical disc. The Random Access Memory may include a resistive Random Access Memory (ReRAM) and a Dynamic Random Access Memory (DRAM).

Claims (10)

1. A resource allocation method based on non-orthogonal multiple access is characterized by comprising the following steps:
s1, constructing a small cell communication system, wherein the small cell base station comprises: a communication user and a communication base station;
s2, dividing information received by the antenna in the area where the communication user is located into a plurality of communication scenes according to interference sources;
s3, establishing a communication system model according to the communication scene;
s4, providing mathematical expression for the communication system model to obtain a resource allocation model expression;
and S5, performing resource allocation according to the resource allocation model expression.
2. The resource allocation method according to claim 1, wherein the communication user comprises: small cell users and macro cell users;
the step S2 includes the following steps:
s21, marking the interference from the next small cell user of the non-orthogonal multiple access as a first communication scene;
s22, cross-layer interference from macro cellular users is marked as a second communication scene;
s23, background noise from the communication user when communicating with the communication user, and labeled as a third communication scene.
3. The method according to claim 1, wherein the step S3 comprises the steps of:
s31, setting the condition that the small cell user is interfered by the next small cell user according to the first communication scene;
s32, setting a condition that a macro cell user generates cross-layer interference on communication of a small cell user according to the second communication scene;
s33, setting the condition of downlink energy transmission between the communication user and the base station within 1-tau, wherein tau represents the time for uplink information interaction between the communication user and the base station;
s34, when decoding the information, carrying out serial interference elimination processing on the interference generated by the third communication scene;
s35, setting the condition that the channel state is completely known.
4. The method according to claim 3, wherein the step S4 comprises the steps of:
s41, calculating the data transmission rate of the kth terminal under two external interference conditions when the base station and the communication user perform uplink information interaction in unit time under the condition that the small cell user is interfered by the next small cell user and under the condition that the macro cell user generates cross-layer interference on the communication of the small cell user;
s42, calculating the sum of the total rates of all the terminals;
s43, taking the energy obtained by the wireless energy carrying transmission scene as a user as a consideration factor, and calculating the energy collected by the kth terminal;
s44, calculating the total energy consumption of the communication system model;
s45, calculating the energy efficiency of the communication system model;
and S46, obtaining a resource allocation model expression according to the data transmission rate of the kth terminal, the total rate sum of all terminals, the energy collected by the kth terminal, the total energy consumption of the communication system model and the energy efficiency of the communication system model.
5. The method according to claim 4, wherein the step S5 comprises the steps of:
s51, calculating the optimal power;
s52, updating the switching time according to the optimal power;
and S53, repeating the step S51-the step S52 until an optimal convergence solution is obtained, and obtaining an optimal energy-efficient value of the system.
6. The resource allocation method according to claim 5, wherein said step S51 comprises the following steps:
s511, introducing auxiliary variables and converting the resource allocation model expression;
s512, constructing a multivariable Lagrange function for the transformed resource allocation model;
s513, calculating the gradient of the Lagrange function to the small cell user power;
s514, calculating the optimal small cell user power by using a gradient descent method;
s515, updating the Lagrange multiplier by using a gradient descent method;
and S516, repeating iteration until the variable factor is converged, and acquiring the optimal transmission power under the transmission time.
7. The method according to claim 6, wherein the step S52 comprises the steps of:
s521, converting the resource allocation model into an optimization problem model;
s522, converting the optimization problem model into a parameterized subtraction form problem model;
s523, obtaining an expression of optimal switching time according to the optimization problem model and the parameterized subtraction form problem model;
and S524, solving the corresponding optimal switching time according to the transmitting power, solving again and updating the transmitting power according to the optimal switching time, and repeatedly iterating to obtain the optimal solution of the transmitting power and the optimal switching time.
8. A resource allocation apparatus based on non-orthogonal multiple access, comprising:
a communication system building module, configured to build a small cell communication system, where the small cell base station includes: a communication user and a communication base station;
the communication scene dividing module is used for dividing information received by an antenna in an area where the communication user is located into a plurality of communication scenes according to interference sources;
the communication system model establishing module is used for establishing a communication system model according to the communication scene;
the expression calculation module is used for providing mathematical expression to the communication system model to obtain a resource distribution model expression;
and the resource allocation module is used for allocating resources according to the resource allocation model expression.
9. A computer readable storage medium having stored therein at least one instruction, at least one program, set of codes, or set of instructions, which is loaded and executed by a processor to implement a method of resource allocation as claimed in any one of claims 1 to 7.
10. A computer device comprising a processor and a memory, the memory having stored therein at least one instruction, at least one program, set of codes, or set of instructions, which is loaded and executed by the processor to implement a method of resource allocation according to any one of claims 1 to 7.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2015062034A1 (en) * 2013-10-31 2015-05-07 富士通株式会社 Resource allocation method and device, and user equipment
CN110708711A (en) * 2019-10-10 2020-01-17 重庆邮电大学 Heterogeneous energy-carrying communication network resource allocation method based on non-orthogonal multiple access
CN111194042A (en) * 2020-02-25 2020-05-22 重庆邮电大学 Heterogeneous network robust energy efficiency optimization method based on non-orthogonal multiple access

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2015062034A1 (en) * 2013-10-31 2015-05-07 富士通株式会社 Resource allocation method and device, and user equipment
CN110708711A (en) * 2019-10-10 2020-01-17 重庆邮电大学 Heterogeneous energy-carrying communication network resource allocation method based on non-orthogonal multiple access
CN111194042A (en) * 2020-02-25 2020-05-22 重庆邮电大学 Heterogeneous network robust energy efficiency optimization method based on non-orthogonal multiple access

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
徐勇军;李国权;陈前斌;林金朝;: "基于非正交多址接入异构携能网络稳健能效资源分配算法", 通信学报 *
杨雪: "基于能效优化异构网络资源分配算法研究", 中国优秀硕士学位论文全文数据库信息科技辑 *

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