CN108024370B - Original resource and detected hole resource joint distribution method based on cognition - Google Patents

Original resource and detected hole resource joint distribution method based on cognition Download PDF

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CN108024370B
CN108024370B CN201711384097.0A CN201711384097A CN108024370B CN 108024370 B CN108024370 B CN 108024370B CN 201711384097 A CN201711384097 A CN 201711384097A CN 108024370 B CN108024370 B CN 108024370B
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CN108024370A (en
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贾敏
王欣玉
郭庆
顾学迈
刘晓锋
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Harbin Institute of Technology
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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
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H04W72/541—Allocation or scheduling criteria for wireless resources based on quality criteria using the level of interference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • 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
    • H04W72/542—Allocation or scheduling criteria for wireless resources based on quality criteria using measured or perceived quality
    • 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
    • H04W16/14—Spectrum sharing arrangements between different networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
    • H04W52/243—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account interferences
    • H04W52/244—Interferences in heterogeneous networks, e.g. among macro and femto or pico cells or other sector / system interference [OSI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/26—TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service]
    • H04W52/267—TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service] taking into account the information rate
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0453—Resources in frequency domain, e.g. a carrier in FDMA
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power

Abstract

The invention provides a cognitive-based original resource and detected hole resource joint distribution method, and belongs to the technical field of information and communication. The invention comprises the following steps: setting user minimum data transmission rate R min Upper limit of power available to user
Figure DDA0001516214420000011
Frequency spectrum detection threshold
Figure DDA0001516214420000012
Sum sub-channel interference preset threshold
Figure DDA0001516214420000013
The BS/AP node in the multi-generic heterogeneous system allocates an original sub-channel for each user and utilizes a frequency spectrum detection threshold
Figure DDA0001516214420000014
Sum sub-channel interference preset threshold
Figure DDA0001516214420000015
Detecting a spectrum hole sub-channel in the multi-genus heterogeneous system, and distributing the detected spectrum hole sub-channel for each user by the BS/AP node; when dispensing, R is m ≥R min And
Figure DDA0001516214420000016
when the user is taken as a limiting condition, the Lagrange dual method is utilized to obtain the optimal user original sub-channel distribution result and the optimal spectrum hole sub-channel distribution result; r m Representing the total rate of data transmission, P, for user m m The total power consumed for user m.

Description

Original resource and detected hole resource joint distribution method based on cognition
Technical Field
The invention relates to a bandwidth resource joint distribution method, in particular to a cognition-based original resource and detected hole resource joint distribution method, and belongs to the technical field of information and communication.
Background
In the last decades, researchers in the radio field have been looking for ways to achieve thousands of times the growth of multimedia applications. The multi-homed network framework is considered as a potential solution that can help achieve this goal. The user equipment with multi-attribute capability can transmit data with different Base Stations (BSs) and access nodes (APs) in the heterogeneous wireless network at the same time, so that the purpose of increasing the data transmission rate is achieved by integrating and utilizing the bandwidth resources of the BSs/APs. Moreover, compared with single-genus network access, the network can obtain greater resource utilization efficiency by considering the potential diversity gain in the available resources of different BSs/APs in the multi-genus network. In a multi-homed network, the resources of different networks are considered as a whole and allocated to the most appropriate users. Compared with a single-genus network, a user with a multi-genus function has more choices, and therefore is more likely to find a more reasonable distribution method. Therefore, the multi-genus networks are not only widely adopted in practical scenes, but also bring great benefits to system performance. These two reasons make relevant research very necessary.
However, the problem of resource allocation in a multi-homed network has the following difficulties compared to a single-homed network. First, the property of being generic results in more resource variables needing to be efficiently allocated. Moreover, the relation between system variables is more complex, and the problem of established resource allocation is more difficult to solve. In addition, many subscribers spend additional power establishing such connections in order to communicate with multiple BSs/APs simultaneously. How to efficiently perform resource allocation, making full use of limited resources (e.g., total power available per user, spectrum resources per BS/AP), is a significant challenge.
Disclosure of Invention
In order to solve the problems that the existing allocation method cannot fully utilize limited resources and cannot obtain large system throughput and energy efficiency, the invention provides a cognitive-based original resource and detected hole resource joint allocation method.
The invention relates to a cognition-based original resource and detected hole resource joint distribution method, which comprises the following steps: step one, setting user minimum data transmission rate R min Upper limit of power available to user
Figure BDA0001516214400000011
Frequency spectrum detection threshold
Figure BDA0001516214400000012
Sum sub-channel interference preset threshold
Figure BDA0001516214400000013
Step two: the BS/AP node in the multi-generic heterogeneous system allocates an original sub-channel for each user and utilizes a frequency spectrum detection threshold
Figure BDA0001516214400000014
Sum sub-channel interference preset threshold
Figure BDA0001516214400000015
Detecting a spectrum hole sub-channel in the multi-genus heterogeneous system, and distributing the detected spectrum hole sub-channel for each user by the BS/AP node;
when dispensing, R is m ≥R min And
Figure BDA0001516214400000021
when the user is taken as a limiting condition, the Lagrange dual method is utilized to obtain the optimal user original sub-channel distribution result and the optimal spectrum hole sub-channel distribution result;
R m representing the total rate of data transmission, P, for user m m The total power consumed for user m.
Preferably, every time the channel condition information changes, a second step is executed, wherein the second step includes:
step two, initializing Lagrange multiplier
Figure BDA0001516214400000022
Enabling the current iteration times j of the outer loop to be =1, and enabling an iteration stop indication variable F of the outer loop to be =1;
step two, if the current F =1 and j is less than or equal to T, T represents the upper limit of the outer layer iteration times, and the step four is carried out; otherwise, determining that the current original sub-channel distribution result and the spectrum hole sub-channel distribution result are optimal, and outputting;
step two and step three, initializing Lagrange multiplier v m (1) The iteration stop indication variable F '=1 by enabling the current iteration times j' =1 of the inner loop;
Step two, if the current F '=1 and j' ≦ T ', T' represents the upper limit of the iteration times of the inner layer, the step is shifted to step two five; otherwise, go to step twenty;
step two, the BS/AP node in the multi-heterogeneous system allocates an original sub-channel for each user to obtain the current original sub-channel allocation result;
step two and step six, utilizing frequency spectrum to detect threshold
Figure BDA0001516214400000023
Sum sub-channel interference preset threshold
Figure BDA0001516214400000024
The BS/AP node carries out frequency spectrum detection, and detects that the sub-channel is a hole sub-channel;
seventhly, the BS/AP node allocates and detects a hole sub-channel for each user and obtains a current spectrum hole sub-channel allocation result;
step two eight, if
Figure BDA0001516214400000025
And v is m (j ') =0, then let F' =0, proceed to step twenty-nine; if it is used
Figure BDA0001516214400000026
And v is m (j′)>If 0, making F' =0, and transferring to the step two nine; if it is not
Figure BDA0001516214400000027
And v is m (j′)>0, then v is decreased m (j'), proceeding to step twenty-nine; otherwise, increase v m (j'), proceeding to step twenty-nine;
step two nine, j '= j' +1, return to step two four;
step twenty, if R m ≥R min And is
Figure BDA0001516214400000028
If the result is F =0, the step is shifted to twenty-one; if R is m ＝R min And is
Figure BDA0001516214400000029
If the F =0, the step is shifted to twenty-one; if R is m >R min And is
Figure BDA00015162144000000210
Then decrease
Figure BDA00015162144000000211
Turning to the twenty-first step; otherwise, increase
Figure BDA00015162144000000212
Step twenty-one, j = j +1, and returns to step two.
Preferably, in the second step, the original sub-channel allocation result includes
Figure BDA0001516214400000031
And
Figure BDA0001516214400000032
Figure BDA0001516214400000033
Figure BDA0001516214400000034
indicating whether the s-th BS/AP node of the network n will originate the subchannel k ns Is assigned to the user m and,
Figure BDA0001516214400000035
1 or 0,1 is taken to represent allocation, and 0 represents no allocation;
wherein
Figure BDA0001516214400000036
Figure BDA0001516214400000037
Representing a set of users located in the coverage area of the s-th BS/AP node in the network n;
intermediate volume
Figure BDA0001516214400000038
Figure BDA0001516214400000039
The channel gain between the user m on the original sub-channel k and the s-th BS/AP node of the network n; n is a radical of 0 Is the single-sided noise power spectral density; b is 0 A bandwidth for each subcarrier;
v m representing a Lagrange multiplier of the corresponding limiting condition user available power upper limit in a Lagrange dual method, wherein an initial value is a small enough positive number generated randomly;
Figure BDA00015162144000000310
representing Lagrange multiplier corresponding to limiting condition user minimum data transmission rate in Lagrange dual method, wherein the initial value is a small enough positive number generated randomly;
Figure BDA00015162144000000311
indicating that user m is on subchannel k ns Power consumption of the circuit when data are transmitted between the s-th BS/AP node of the network n and the S-th BS/AP node;
original subchannel k ns Corresponding power
Figure BDA00015162144000000312
Figure BDA00015162144000000313
Preferably, in the second step, the spectrum empty hole sub-channel allocation result includes
Figure BDA00015162144000000314
And
Figure BDA00015162144000000315
Figure BDA0001516214400000041
Figure BDA0001516214400000042
denoting whether the s ' th BS/AP node of the network n ' will spectrum the hole sub-channel k ' n′s′ Is assigned to the user m and,
Figure BDA0001516214400000043
1 or 0,1 is taken to represent allocation, and 0 represents no allocation;
wherein the content of the first and second substances,
Figure BDA0001516214400000044
representing a set of users located in the coverage area of the s 'th BS/AP node in the network n';
Figure BDA0001516214400000045
N 0 is the single-sided noise power spectral density; b is 0 A bandwidth for each subcarrier;
Figure BDA0001516214400000046
representing Lagrange multipliers corresponding to the sub-channel interference upper limit of the limiting condition in the Lagrange dual method, wherein the initial value is a small enough positive number generated randomly;
Figure BDA0001516214400000047
representing the s-th BS/AP node of the network n for the sub-channel k 'when detecting the spectrum hole sub-channel' n′s′ As a result of the detection being carried out,
Figure BDA0001516214400000048
1 or 0,0 is taken to represent sub-channel k' n′s′ Is a spectral hole subchannel, 1 denotes subchannel k' n′s′ Cannot be reused;
Figure BDA0001516214400000049
is spectral hole subchannel k' n′s′ Channel gain between the upper user m and the s 'th BS/AP node of the network n';
intermediate volume
Figure BDA00015162144000000410
Figure BDA00015162144000000411
Representing user m at sub-channel k' n′s′ Power consumption by the circuitry in transmitting data between the s 'th BS/AP node of network n';
original sub-channel k' n′s′ Corresponding power
Figure BDA00015162144000000412
Figure BDA00015162144000000413
Preferably, in the second step, an iteration method of the optimal value of the lagrangian multiplier in the lagrangian dual method is as follows:
Figure BDA0001516214400000051
Figure BDA0001516214400000052
Figure BDA0001516214400000053
iteration step size epsilon 2 And ε 3 Is a sufficiently small positive number, i denotes the optimal v m 、
Figure BDA0001516214400000054
And
Figure BDA0001516214400000055
The number of iterations of (c);
Figure BDA0001516214400000056
representing spectral hole sub-channel k' n′s′ Channel power gain between the s ' th BS/AP node of the upper user m and the network n ' and the spectrum hole sub-channel k ' n′s′ Has been previously allocated to user m', wherein
Figure BDA0001516214400000057
A threshold value is preset for sub-channel interference.
Preferably, the second step includes:
step two, firstly: BS/AP node in multi-generic heterogeneous system allocates original sub-channel for each user, and utilizes
Figure BDA0001516214400000058
Iteration is carried out by taking the parameters as limiting conditions and corresponding Lagrange multipliers to obtain an optimal user original sub-channel distribution result;
step two: when the channel condition information changes, the detection threshold of the available power upper limit frequency spectrum is utilized
Figure BDA0001516214400000059
Sum sub-channel interference preset threshold
Figure BDA00015162144000000510
Detecting the spectrum hole sub-channel in the multi-genus heterogeneous system, and turning to the second step and the third step;
step two and step three: the BS/AP node allocates the detected spectrum hole sub-channel for each user and utilizes
Figure BDA00015162144000000511
R m ≥R min Iteration is carried out as a limiting condition and a corresponding Lagrange multiplier to obtain an optimal frequency spectrumAnd (5) the empty hole sub-channel distribution result is transferred to the second step.
Preferably, in the second step, the original sub-channel allocation result is:
Figure BDA00015162144000000512
Figure BDA00015162144000000513
indicating whether the s-th BS/AP node of the network n will be the original sub-channel k ns Is assigned to the user m and,
Figure BDA00015162144000000514
1 or 0,1 is taken to represent allocation, and 0 represents no allocation;
wherein
Figure BDA00015162144000000515
Representing a set of users located in the coverage area of the s-th BS/AP node in network n;
Figure BDA00015162144000000516
Figure BDA00015162144000000517
representing the channel power gain expectation;
Figure BDA0001516214400000061
the channel gain between the user m on the original sub-channel k and the s-th BS/AP node of the network n;
N 0 is the single-sided noise power spectral density; b is 0 A bandwidth for each subcarrier;
Figure BDA0001516214400000062
indicating that user m is on subchannel k ns Upper and netThe circuit consumption power when transmitting data between the s-th BS/AP node of the network n;
v 1m representing Lagrange multipliers corresponding to the upper limit of the available power of the conditional user when the original sub-channels are distributed in the Lagrange dual method, wherein the initial value is a small enough positive number generated randomly;
original subchannel k ns Corresponding power
Figure BDA0001516214400000063
Preferably, in the second step, the spectrum hole sub-channel allocation result is:
Figure BDA0001516214400000064
Figure BDA0001516214400000065
denoting if the s ' th BS/AP node of network n ' will spectrum the hole sub-channel k ' n′s′ Is assigned to the user m and,
Figure BDA0001516214400000066
1 or 0,1 is taken to represent allocation, and 0 represents no allocation;
wherein the content of the first and second substances,
Figure BDA0001516214400000067
representing a set of users located in the coverage area of the s 'th BS/AP node in the network n';
Figure BDA0001516214400000068
N 0 is the single-sided noise power spectral density; b is 0 A bandwidth for each subcarrier;
v 2m the initial value of the Lagrange multiplier which represents the corresponding limitation condition user available power upper limit when the frequency spectrum cave sub-channel is distributed in the Lagrange dual method is enough randomly generated A small positive number;
Figure BDA0001516214400000069
representing a Lagrange multiplier corresponding to the minimum data transmission rate of a user with a limiting condition when a spectrum empty hole sub-channel is allocated in a Lagrange dual method, wherein an initial value is a small enough positive number generated randomly;
Figure BDA00015162144000000610
the Lagrange multiplier represents the corresponding limitation condition sub-channel interference upper limit in the spectrum hole detection in the Lagrange dual method, and the initial value is a small enough positive number generated randomly;
Figure BDA0001516214400000071
representing the s-th BS/AP node of network n for subchannel k 'when detecting the spectral hole subchannel' n′s′ As a result of the detection being carried out,
Figure BDA0001516214400000072
1 or 0,0 is taken to represent sub-channel k' n′s′ Is a spectral hole subchannel, 1 denotes subchannel k' n′s′ Cannot be reused;
Figure BDA0001516214400000073
is spectral hole subchannel k' n′s′ Channel gain between the upper user m and the s 'th BS/AP node of the network n';
Figure BDA0001516214400000074
representing user m at sub-channel k' n′s′ Power consumption by the circuitry in transmitting data between the s 'th BS/AP node of network n';
original subchannel k' n′s′ Corresponding power
Figure BDA0001516214400000075
Figure BDA0001516214400000076
Preferably, in the second step, an iteration method of the optimal value of the lagrangian multiplier in the lagrangian dual method is as follows:
Figure BDA0001516214400000077
Figure BDA0001516214400000078
Figure BDA0001516214400000079
Figure BDA00015162144000000710
wherein the content of the first and second substances,
Figure BDA00015162144000000711
representing the upper power limit, iteration step size epsilon, at which the original subchannel is allocated 4 、ε 5 、ε 6 And ε 7 Is a sufficiently small positive number, i denotes the optimum v 1m 、
Figure BDA00015162144000000712
v 2m And
Figure BDA00015162144000000713
the number of iterations of (a) is,
Figure BDA00015162144000000714
representing spectral hole sub-channel k' n′s′ Between upper user m and s' th BS/AP node of network nChannel power gain and the spectral hole sub-channel k' n′s′ Has been previously allocated to user m', wherein
Figure BDA00015162144000000715
A threshold value is preset for sub-channel interference.
The features mentioned above can be combined in various suitable ways or replaced by equivalent features as long as the object of the invention is achieved.
The invention has the beneficial effects that the invention provides a method for jointly allocating original resources and detected hole resources based on the cognitive radio thought aiming at the multi-generic heterogeneous network that each user can simultaneously access a plurality of systems. In the invention, the maximized system throughput is taken as an optimization objective function, just as an actual system, the system spectrum resource and the power resource are considered to be limited, and the user is considered to have the lowest transmission rate limit. The problem is modeled, and is found to be actually a mixed integer nonlinear optimization problem through analysis. The problem is converted into a convex optimization problem by using a continuous relaxation method, and the solution is carried out according to the Karush-Kuhn-Tucker condition. The method of the present invention considers that different networks in the system can share the frequency spectrum resource with each other, which is the biggest difference from the existing allocation method. Therefore, the limited resources of the system can be more fully utilized, and the system performance is improved. Simulation results show that compared with a comparison algorithm which cannot realize resource sharing, the allocation method can obviously improve the system throughput and Energy Efficiency (EE). The invention also proves that the suboptimal method corresponding to the method of the invention can actually greatly reduce the computational complexity of the system.
Drawings
FIG. 1 is a schematic diagram of respective coverage areas of different networks in a heterogeneous multi-network system;
FIG. 2 is a simplified simulation model diagram of a heterogeneous network system;
FIG. 3 is a comparison graph of the relationship between throughput and the upper limit of available power for users, which can be obtained by systems respectively adopting the optimal method in embodiment 1 of the present invention, the suboptimal method in embodiment 2 of the present invention, and the comparison algorithm, under different circuit power losses;
FIG. 4 shows that, for different numbers of users, the optimal method in embodiment 1 of the present invention, the suboptimal method in embodiment 2 of the present invention, and the system of the comparison algorithm can obtain throughput and the number K of original sub-channels of BS 11 A relationship comparison graph;
FIG. 5 shows that under different circuit power losses, the energy efficiency that can be achieved by the system using the optimal method of embodiment 1 of the present invention, the suboptimal method of embodiment 2 of the present invention, and the comparison algorithm, and the number K of original sub-channels of BS are respectively used 11 A relationship comparison graph;
fig. 6 is a comparison graph of the relationship between throughput and the pre-set threshold for sub-channel interference/noise power, which can be obtained by the system using the optimal method of embodiment 1 of the present invention, the suboptimal method of embodiment 2 of the present invention, and the comparison algorithm, respectively, under the limitation of different upper limits of the available power for the user;
Fig. 7 is a bar chart comparing the total iterative computation times and the upper limit of the available power for the user at the end of the iterative process according to the optimal method in embodiment 1 of the present invention, the suboptimal method in embodiment 2 of the present invention, and the comparison algorithm.
Detailed Description
In the multi-user heterogeneous network system shown in fig. 1, although each coverage area of different networks is schematically illustrated, although both user a and user B have multi-user functions, a is only in the coverage area of the BS, so it can only transmit data to the BS. And user B can communicate with both the BS and the AP or one of them. Currently, other researchers have studied the resource allocation problem of multi-generic networks, and they all assume that different networks can only use their own spectrum resources. It is also this premise assumption that these systems do not truly make full use of the radio resources. The present embodiment breaks this limitation, so that the user can use the same band at the same time. In the present embodiment, the resource of each network before resource allocation is referred to as an original resource, and the additional resource obtained after spectrum detection is referred to as a detected hole resource, which is a resource that can be shared and reused. In the embodiment, the idea of introducing Cognitive Radio (CR) is to jointly allocate these two types of resources by using the key technologies (spectrum sensing and spectrum sharing) so as to maximize the throughput of the system.
Radio resource allocation can be divided into two categories, single-genus network and multi-genus network resource allocation. The current research on the resource allocation problem of the multi-genus network has proposed a corresponding allocation method from the perspective of different objective functions such as throughput, service quality, energy efficiency, energy consumption and the like. However, these researchers have assumed that the operating frequency bands of the different networks in the system under consideration do not overlap. The invention provides a method for jointly allocating frequency spectrum and power resources in a multi-genus heterogeneous network capable of sharing frequency spectrum according to the above behavior examples, thereby more fully utilizing network resources. The method completely and comprehensively considers the whole process of original resource allocation, spectrum detection and detected hole resource allocation, and then jointly and uniformly allocates all involved power and frequency band resources. At present, no other researchers have proposed a method for jointly allocating original resources and detected hole resources of a multi-generic heterogeneous network based on cognitive sharable spectrum resources.
In the embodiment, a multi-genus heterogeneous wireless network resource joint allocation scheme is proposed based on the idea of cognitive radio. It is considered that users in different networks can mutually use counterpart spectrum resources. The present embodiment adopts an Orthogonal Frequency Division Multiple Access (OFDMA) method, and the above operation example is described. This is why the bandwidth allocation is actually the subcarrier allocation in this embodiment. The present embodiment then mathematically formulates the entire assignment problem. Through analysis, the embodiment finds that the established optimization problem is actually a mixed shaping nonlinear optimization problem. Therefore, the embodiment adopts a relaxation method to convert the solution into a convex optimization problem, and further successfully utilizes a Lagrange dual method to solve the problem. Finally, according to the simulation results, the embodiment proves that the provided allocation method can obviously improve the system performance (throughput and energy efficiency) compared with the comparison algorithm which cannot realize resource sharing. Moreover, the embodiment also proves that the corresponding suboptimal method can actually greatly reduce the computational complexity of the algorithm. The embodiment is directed to a multi-heterogeneous network capable of sharing network spectrum resources.
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
The invention is further described with reference to the following drawings and specific examples, which are not intended to be limiting.
In the present embodiment, a multi-generic heterogeneous network system is considered, as shown in fig. 1. The system includes a set of all N wireless networks
Figure BDA0001516214400000101
This set includes several cellular networks of varying sizes (e.g., macrocells and microcells). With areas of overlap between the cells. Each network
Figure BDA0001516214400000102
Has a series of macro-cell BSs or micro-cell APs. Writing a set of BSs or APs
Figure BDA0001516214400000103
M users constitute a user set
Figure BDA0001516214400000104
Order to
Figure BDA0001516214400000105
Representing the set of users located in the coverage area of the s-th BS/AP node in the network n. Each user can transmit data with multiple BSs/APs nodes simultaneously. Due to the OFDMA access strategy employed, the resources in the network include subcarriers and transmission power.
Figure BDA0001516214400000106
Denotes the K owned by the s-th BS/AP access point of the network n in the original resource allocation phase ns A set of original subcarriers. Then there is any one of the original sub-carriers,
Figure BDA0001516214400000107
each subcarrier has a bandwidth of B 0 。
In the original resource allocation stage, user m is in sub-channel k ns The result of the signal transmission power distribution of the communication with the s-th BS/AP node of the network n is
Figure BDA0001516214400000108
The power consumption of each user is divided into two parts: transmission power consumption and circuit power consumption. Suppose user m is on subchannel k ns The power consumption of the circuit for transmitting data between the s-th BS/AP node of the network n is
Figure BDA0001516214400000109
Then the total power consumed by each user on each radio interface is
Figure BDA00015162144000001010
Figure BDA00015162144000001011
Representing user m in original subchannel k ns Channel power gain of the channel between the s-th BS/AP node of the upper and network n. d is a radical of nsm Representing the distance between user m and the s-th BS/AP of network n. Corresponding path loss of
Figure BDA00015162144000001012
Where β refers to the path loss exponent. The present embodiment assumes
Figure BDA00015162144000001013
Is a rayleigh random variable corresponding to the transmission link between the user m and the s-th BS/AP of the network n. So the channel power gain can be written as
Figure BDA00015162144000001014
N 0 Representing the single-sided noise power spectral density.
Example 1: embodiment 1 is an optimal allocation scheme of the present invention, and this embodiment includes the following steps:
step one, setting user minimum data transmission rate R min Upper limit of power available to user
Figure BDA00015162144000001015
Frequency spectrum detection threshold
Figure BDA00015162144000001016
Sum sub-channel interference preset threshold
Figure BDA00015162144000001017
Step two: the BS/AP node in the multi-generic heterogeneous system allocates an original sub-channel for each user and utilizes a frequency spectrum detection threshold
Figure BDA00015162144000001018
Sum sub-channel interference preset threshold
Figure BDA00015162144000001019
Detecting a spectrum hole sub-channel in the multi-genus heterogeneous system, and distributing the detected spectrum hole sub-channel for each user by the BS/AP node;
roughly speaking, step two includes three parts. The first is the original resource allocation phase. The heterogeneous network system allocates original sub-channels of BSs/APs nodes to respective users, and at the same time, they calculate out thatAnd power distribution results corresponding to the sub-carriers. Let the allocation result include
Figure BDA0001516214400000111
And
Figure BDA0001516214400000112
binary variable
Figure BDA0001516214400000113
Is a function of the indication of the position of the object,
Figure BDA0001516214400000114
meaning the original subchannel k of the s-th BS/AP node of the network n ns Is assigned to user m. If not, then,
Figure BDA0001516214400000115
representing that user m is not allocated. The second part is the spectrum sensing stage. As mentioned, spectrum sensing is essential in view of the need to accurately identify which spectrum resources are currently spectrum holes so that they can be shared for reuse, and also to ensure that users sharing the same segment of sub-channel resources can communicate properly. The embodiment expands the traditional definition of cognitive radio. In a multi-user heterogeneous network system, a master user and a cognitive user are not distinguished. In the present embodiment, all users are considered to be the same, and can share the spectrum resources of the other users with each other. The spectrum sensing process is not the focus of the present invention, so a common method, i.e., energy detection, is used here. Aiming s & ltth & gt BS/AP of network n to sub-channel k' n′s′ The results of the tests were expressed as
Figure BDA0001516214400000116
Wherein k' n′s′ Is the original subchannel of the s 'th BS/AP belonging to network n'. Detection result "0" represents subchannel k' n′s′ Is a hole subchannel that can be reused by the s-th BS/AP of the network n. "1" means not possible. Order to
Figure BDA0001516214400000117
Denotes a set of hole sub-channels that can be shared of the s ' th BS/AP belonging to the network n ', the total number of these channels being K ' n′s′ . All currently detected K' n′s′ The hole is the spectrum resource that the embodiment will reuse next. The third part is the detected hole resource allocation phase. In this embodiment, it is necessary to allocate the currently detected hole sub-channels to the user, and at the same time, calculate the power allocation results corresponding to these sub-channels. Using a binary variable
Figure BDA0001516214400000118
An indicator function representing the result of the assignment of the hole sub-channels, the corresponding transmission power being
Figure BDA0001516214400000119
If it is not
Figure BDA00015162144000001110
Or
Figure BDA00015162144000001111
Equal to 0, then the corresponding power allocation results and the lagrange multiplier are both equal to 0. These three phases cycle through until the results of the allocation converge.
The joint allocation method according to the present embodiment will be described in detail below.
The problem under consideration is modeled first. In the first phase, the user
Figure BDA00015162144000001112
In the original sub-channel k ns The rate of data transmission with the s-th BS/AP node of network n is:
Figure BDA00015162144000001113
in the spectrum detection stage, the obtained detection result
Figure BDA00015162144000001114
Hole resources are given that can be reused by the s-th BS/AP node of the network n. Then in the hole sub-carrier allocation phase, user m is in hole sub-channel k' n′s′ The transmission rate that can be obtained is
Figure BDA0001516214400000121
Wherein the content of the first and second substances,
Figure BDA0001516214400000122
is a hole sub-channel k 'reused by user m' n′s′ Channel power gain between upper user m and the s-th BS/AP of network n. The total data transmission rate achievable for the overall system is therefore
Figure BDA0001516214400000123
Because the number of subcarriers of each BS/AP node in each network is limited, and the subcarriers are mutually orthogonal, the method has the advantages that
Figure BDA0001516214400000124
Figure BDA0001516214400000125
According to the above description about the consumed power component, the total power consumed by user m can be expressed as:
Figure BDA0001516214400000126
considering the hardware limitations of the actual system, P m Has a maximum value
Figure BDA0001516214400000127
And (4) limiting.
Figure BDA0001516214400000128
Moreover, the data transmission rate R of user m takes into account the requirements of user fairness and quality of service m Will suffer from a minimum data transmission rate R min The limit of (2). Thus, there are
Figure BDA0001516214400000129
Wherein the content of the first and second substances,
Figure BDA00015162144000001210
the goal of the allocation scheme of the present embodiment is to maximize system throughput. The problem of resource joint allocation in this embodiment can be written as the following formula.
Figure BDA0001516214400000131
The restrictions are (3), (4), (5), (6),
Figure BDA0001516214400000132
Figure BDA0001516214400000133
Figure BDA0001516214400000134
Figure BDA0001516214400000135
wherein x, P, x' r And P' r Are respectively divided intoCompounding result
Figure BDA0001516214400000136
And
Figure BDA0001516214400000137
a matrix is formed. This embodiment assumes the original sub-channel k ' of the s ' th BS/AP node of network n ' n′s′ In the first stage is assigned to user m'. Let subchannel k' n′s′ The channel power gain between the upper user m' and the s-th BS/AP node of the network n is
Figure BDA0001516214400000138
And if subchannel k' n′s′ The channel power gain between user m and the s 'th BS/AP node of network n' is expressed as the channel power gain when it is reused by user m in the detected hole subchannel allocation phase
Figure BDA0001516214400000139
At the same time, the spectrum detection threshold is set to
Figure BDA00015162144000001310
When reusing spectrum resources, the BS/AP node must ensure that the interference caused to the user that originally uses this subchannel does not exceed a preset threshold
Figure BDA00015162144000001311
The requirement that the interference does not exceed the threshold is also a prerequisite for the implementation of spectrum sharing. The constraints (8) and (9) describe the spectrum detection process, and the detection result is
Figure BDA00015162144000001312
The constraint (10) guarantees the premise of spectrum sharing. The restrictions (8), (9), and (10) are actually specific implementation methods of the present embodiment to ensure that users sharing the same spectrum resource in the first and third allocation stages can communicate normally without mutual influence. The limiting condition (11) is a boundary limiting strip of the transmission power itselfAnd (3) a component.
Intuitively, the greatest difficulty in solving problems (3) - (11) is due to the presence of binary variable matrices x and x' r This optimization problem is a mixed integer non-linear programming problem, not a convex optimization problem. To solve this problem, the present embodiment converts the relaxation method into a convex optimization problem, and further solves the problem by using the lagrangian dual method.
First, the present embodiment considers a variable that originally can only take a value of 0 or 1
Figure BDA00015162144000001313
And
Figure BDA00015162144000001314
relaxation to continuous region [0,1]Then introduce two corresponding variables
Figure BDA00015162144000001315
And
Figure BDA00015162144000001316
Figure BDA00015162144000001317
Figure BDA00015162144000001318
then, the present embodiment rewrites the problems (3) to (11) into the following forms.
Figure BDA0001516214400000141
With the proviso that
Figure BDA0001516214400000142
Figure BDA0001516214400000143
Figure BDA0001516214400000144
Figure BDA0001516214400000145
Figure BDA0001516214400000146
Figure BDA0001516214400000147
Figure BDA0001516214400000148
Figure BDA0001516214400000149
Wherein the matrix
Figure BDA00015162144000001410
It can be easily seen that the problem (14) - (22) obtained after the relaxation method is actually a convex optimization problem that can be solved using the lagrangian dual method given below.
In the embodiment, lagrange multiplier variables v are respectively introduced into constraint conditions (17), (18) and (21) m ，
Figure BDA00015162144000001411
And
Figure BDA00015162144000001412
v m 、
Figure BDA0001516214400000151
and
Figure BDA0001516214400000152
representing the lagrangian multiplier in the lagrangian dual method, the initial value is a small enough positive number generated randomly, and the lagrangian function (23) is obtained.
Figure BDA0001516214400000153
Wherein the matrix v = [ v = m ] 1×M ，
Figure BDA0001516214400000154
A dual function of
Figure BDA0001516214400000155
The limitations are (15), (16) and (22).
Then the dual problem of (14) - (22) can be written as
Figure BDA0001516214400000156
The minimum value of (25) is equal to the maximum values of (14) - (22). First, the present embodiment derives the original resource allocation result. That is, now this embodiment needs to solve for (15), (16), (22), (24) and (25) in order to find the optimal values of x and s.
According to the conditional expression of Karush-Kuhn-Tucker (KKT) with respect to (14), the present embodiment can calculate to obtain the following relational expression of x and s.
Figure BDA0001516214400000157
Wherein [ x ]] + ＝max{0 , x }. Order to
Figure BDA0001516214400000158
Is a K ns X M matrix of elements
Figure BDA0001516214400000159
Satisfy the expression
Figure BDA0001516214400000161
Substituting (26) into (24), and then the embodiment leads
Figure BDA0001516214400000162
Figure BDA0001516214400000163
Suppose that
Figure BDA0001516214400000164
Then (15), (16), (22) and (24) can be rewritten as:
Figure BDA0001516214400000165
the limiting condition is (15).
This is in fact a linear allocation problem. Distribution result
Figure BDA0001516214400000166
The optimal value of (a) can only be taken at the end points where all possible values form a set, i.e. can only be selected from "0" or "1". Thus in pair
Figure BDA0001516214400000167
After the relaxation operation is performed, the present embodiment can obtain an optimal result of a binary system. The optimal subchannel allocation result is:
Figure BDA0001516214400000168
using the equation relationship given in equation (12), the optimal power allocation result can be written according to (26) after the optimal subchannel allocation result is calculated:
Figure BDA0001516214400000169
it should be noted that if found at the time of calculation (28)
Figure BDA00015162144000001610
There is more than one maximum, considering that a subchannel cannot be allocated to two users simultaneously in the original resource allocation phase, the currently considered subchannel k will be ns The user with less sub-channel resources is allocated to ensure user fairness. And if a certain subchannel k ns All calculated of
Figure BDA00015162144000001611
Are negative, then the channel condition for this subchannel must be very poor. Blindly accessing this channel results in a waste of power resources. The present embodiment decides to drop such sub-channels. It is this "drop mechanism" that makes it possible for user B in fig. 1 to select only one of the several networks to which it belongs for access.
As for the currently detected hole spectrum resource allocation result, similarly, according to the KKT condition of equation (14), the present embodiment can obtain
Figure BDA0001516214400000171
To simplify the following description, let
Figure BDA0001516214400000172
Is one K' ns X M matrix of elements
Figure BDA0001516214400000173
Satisfy the equation
Figure BDA0001516214400000174
Bring (30) into (27) to make
Figure BDA0001516214400000175
Suppose that
Figure BDA0001516214400000176
Then (27) can be rewritten as
Figure BDA0001516214400000177
So that the sub-channel is optimally allocated
Figure BDA0001516214400000178
It is also possible to equal only the end of its range, i.e. 0 or 1.
Figure BDA0001516214400000179
According to the equality relation
Figure BDA00015162144000001710
And (30), the optimal power allocation result can be obtained after the optimal subchannel allocation result is obtained through calculation:
Figure BDA0001516214400000181
if found after calculating formula (33)
Figure BDA0001516214400000182
There is more than one maximum value, or a certain subchannel k 'is found' n′s′ All of
Figure BDA0001516214400000183
Are negative and the process is as per the first allocation stage given above. Moreover, these treatment methods are also applicable to the suboptimal solution given in example 2.
According to the gradient descent method, lagrange multiplier matrices γ', v and
Figure BDA0001516214400000184
of optimum value γ' * ，v * And
Figure BDA0001516214400000185
is obtained by solving (25):
Figure BDA0001516214400000186
Figure BDA0001516214400000187
Figure BDA0001516214400000188
v m representing a Lagrange multiplier of the corresponding limiting condition user available power upper limit in a Lagrange dual method, wherein an initial value is a small enough positive number generated randomly;
Figure BDA0001516214400000189
Representing Lagrange multiplier corresponding to limiting condition user minimum data transmission rate in Lagrange dual method, wherein the initial value is a small enough positive number generated randomly;
Figure BDA00015162144000001810
lagrange multiplication for representing corresponding constraint condition subchannel interference upper limit in Lagrange duality methodThe initial value is a positive number which is generated randomly and is small enough;
wherein the positive iteration step size epsilon 1 ，ε 2 And ε 3 Are sufficiently small, i is the current iteration number.
According to the above solving process, the second step of the present embodiment includes:
step two, initializing Lagrange multiplier
Figure BDA00015162144000001811
Enabling the current iteration number j of the outer loop to be =1, and enabling an iteration stop indicating variable F of the outer loop to be =1;
step two, if the current F =1 and j is less than or equal to T, T represents the upper limit of the outer layer iteration times, and the step four is carried out; otherwise, determining that the current original sub-channel distribution result and the spectrum hole sub-channel distribution result are optimal, and outputting;
step two and step three, initializing Lagrange multiplier
Figure BDA00015162144000001812
Letting the current iteration number j '=1 of the inner loop, and letting the iteration stop indication variable F' =1 of the inner loop;
step two, if the current F '=1 and j' ≦ T ', T' represents the upper limit of the iteration times of the inner layer, the step is shifted to step two five; otherwise, go to step twenty;
Step two, distributing original sub-channels for each user by the BS/AP node in the multi-heterogeneous system, and respectively obtaining the distribution result of the current original sub-channels according to formulas (28) and (29)
Figure BDA0001516214400000191
And
Figure BDA0001516214400000192
step two and step six, utilizing frequency spectrum to detect threshold
Figure BDA0001516214400000193
Sum sub-channel interference preset threshold
Figure BDA0001516214400000194
The BS/AP node carries out frequency spectrum detection, and detects that the sub-channel is a hole sub-channel;
step two, the BS/AP node allocates and detects the hole sub-channel for each user, and obtains the current spectrum hole sub-channel allocation result according to the formulas (31), (33), (34) and (35)
Figure BDA0001516214400000195
And
Figure BDA0001516214400000196
step two and eight, if
Figure BDA0001516214400000197
And v is m (j ') =0, then let F' =0, go to step twenty-nine; if it is not
Figure BDA0001516214400000198
And v is m (j′)>If 0, making F' =0, and then transferring to the step two to nine; if it is not
Figure BDA0001516214400000199
And v is m (j′)>0, then v is reduced according to equation (36) m (j'), proceeding to step twenty-nine; otherwise, equation (36) increases v m (j'), proceeding to step twenty-nine;
step two nine, j '= j' +1, return to step two four;
step twenty, if R m ≥R min And is provided with
Figure BDA00015162144000001910
If the F =0, the step is shifted to twenty-one; if R is m ＝R min And is
Figure BDA00015162144000001911
If the result is F =0, the step is shifted to twenty-one; if R is m >R min And is
Figure BDA00015162144000001912
Then decrease according to equation (37)
Figure BDA00015162144000001913
Turning to the twenty-first step; otherwise, increase according to equation (37)
Figure BDA00015162144000001914
Step twenty-one, j = j +1, and returns to step two.
Example 2:
considering the complex calculation process of the optimal allocation scheme given in example 1, this embodiment further provides a sub-optimal framework thereof, thereby reducing the overhead and computational complexity of the system. This is done to better meet the needs of the actual system.
The allocation result of the optimal strategy proposed in embodiment 1 must be updated every time the Channel State Information (CSI) changes. This results in a large amount of data transmission, multiple spectrum sensing and high system overhead. In order to reduce the overhead and reduce the computational complexity, the following embodiment provides a three-step sub-optimal allocation strategy for step two of example 1. The first step of step two is the original resource allocation, which only needs to be performed once at the beginning of the whole allocation process. The original resource allocation of this step is based not on instantaneous channel gain estimates but on averages over a period of time
Figure BDA00015162144000001915
This embodiment uses this average value to represent the long-term approximate status of the channel corresponding to each user. E [ x ]]Representing the expectation of x. The second step is naturally the spectrum sensing stage. And thirdly, corresponding to the currently detected hole resource allocation process, the channel condition information is required to be executed again every time the channel condition information is changed.
First, the first step is the original resource allocation phase. Using expectations of channel power gain
Figure BDA00015162144000001916
Accordingly, an optimization objective is also a throughput expectation. The optimization model of this step can then be expressed as:
Figure BDA0001516214400000201
the limitation is that the number of the (3),
Figure BDA0001516214400000202
Figure BDA0001516214400000203
wherein
Figure BDA0001516214400000204
And also
Figure BDA0001516214400000205
Representing the upper limit of the power with which the user allocates the original sub-channel. Then, using a method similar to the method given in (12) to (37), the present embodiment can obtain the power allocation results of the optimization problems (38) to (40):
Figure BDA0001516214400000206
wherein v is 1m Represents the Lagrangian multiplier corresponding to the constraint (39). The result of the subchannel allocation is:
Figure BDA0001516214400000207
wherein the sub-channels allocate decision quantities
Figure BDA0001516214400000208
The lagrange multiplier v can be obtained by using the gradient descent method and the following iteration method 1m The optimum value of (c).
Figure BDA0001516214400000209
Iteration step size epsilon 4 Is a sufficiently small positive number.
In the second step, spectrum detection needs to be performed on the system subjected to the original resource allocation. And in the third step, calculating the optimal distribution result of the currently detected hole sub-channel and power according to the instantaneous channel power gain. The third step needs to be performed again each time the CSI changes. The goal of the optimization problem is still to expect the system throughput to be maximized, i.e.
Figure BDA00015162144000002010
The limitation is that the number of the (4),
Figure BDA0001516214400000211
Figure BDA0001516214400000212
Figure BDA0001516214400000213
Figure BDA0001516214400000214
wherein the content of the first and second substances,
Figure BDA0001516214400000215
indicating the data transmission rate that can be achieved after the first step is finished. Also, using a similar approach, the power allocation result can be solved:
Figure BDA0001516214400000216
Wherein v is 2m Represents the Lagrangian multiplier corresponding to the constraint (45). The detected hole subchannel allocation result is:
Figure BDA0001516214400000217
wherein the decision quantity of the detected hole sub-channel allocation
Figure BDA0001516214400000218
Figure BDA0001516214400000219
The lagrange multiplier matrices γ', v can be obtained using the gradient descent method using the following iterative methods (51), (52), and (53) 2 (v 2 ＝[v 2m ] 1×M ) And
Figure BDA00015162144000002110
has an optimum value of γ' * ，
Figure BDA00015162144000002111
And
Figure BDA00015162144000002112
Figure BDA00015162144000002113
Figure BDA0001516214400000221
Figure BDA0001516214400000222
v 1m representing a Lagrange multiplier corresponding to the upper limit of the available power of the user with the limiting condition when an original sub-channel is distributed in the Lagrange dual method, wherein the initial value is a small enough positive number generated randomly;
v 2m representing Lagrange multipliers corresponding to the upper limit of the available power of the user under the limiting condition when the spectrum hole sub-channels are distributed in the Lagrange dual method, wherein the initial value is a small enough positive number generated randomly;
Figure BDA0001516214400000223
representing Lagrange multiplier corresponding to the minimum data transmission rate of the user with the limitation condition when the frequency spectrum hole sub-channel is distributed in the Lagrange dual method, wherein the initial value is a small enough positive number generated randomly;
Figure BDA0001516214400000224
representing a Lagrange multiplier corresponding to sub-channel interference in frequency spectrum hole detection in a Lagrange dual method, wherein an initial value is a small enough positive number generated randomly;
wherein the iteration step size epsilon 5 ，ε 6 And ε 7 Is a sufficiently small positive number. Thus, an optimal and corresponding suboptimal solution for jointly allocating original and detected hole resources is given:
The second step of the present embodiment includes:
step two, firstly: BS/AP node in multi-generic heterogeneous system allocates original sub-channel for each user, and utilizes
Figure BDA0001516214400000225
Iteration is carried out as a limiting condition and a corresponding Lagrange multiplier, and an optimal user original sub-channel distribution result is obtained according to formulas (41) and (42);
step two: when the channel condition information changes, the threshold is detected by using the upper limit spectrum of the available power
Figure BDA0001516214400000226
Sum sub-channel interference preset threshold
Figure BDA0001516214400000227
Detecting the frequency spectrum hole sub-channel in the multi-genus heterogeneous system, and turning to the second step and the third step;
step two and step three: the BS/AP node allocates the detected spectrum hole sub-channel for each user and utilizes
Figure BDA0001516214400000228
R m ≥R min And (5) iteration is carried out by using the parameters as limiting conditions and corresponding Lagrange multipliers, the optimal spectrum hole subchannel allocation result is obtained according to the formulas (49) and (50), and the step two is carried out.
In order to verify the superior performance of the allocation scheme proposed by the present invention, a comparison algorithm needs to be introduced in the present embodiment. The reason this comparison algorithm is chosen by this embodiment is that its system framework is most similar to that of this embodiment. Heterogeneous cellular networks of varying cell sizes (macrocells and microcells) are all addressed. Moreover, the scenarios of limited bandwidth and power resources and limited user data transmission rate are considered. In order to enhance the persuasion of the simulation comparison result of the present embodiment, it is necessary to ensure that the optimization target of the comparison algorithm is the same as that of the present embodiment, and the comparison algorithm also adopts the OFDMA access method. However, as proposed by other researchers at present, the comparison algorithm selected in this embodiment also fails to share and reuse spectrum resources by using the idea of cognitive radio. But otherwise, the objective function and the constraints of the method of the invention and the comparative algorithm are the same in the simulation experiments. Thus, in simulation experiments, this embodiment considers this comparison algorithm to be comparable to the method of the present invention and can be taken as a representation of an existing distribution scheme to be compared to the scheme of this embodiment. And after such comparison, the fact that the method of the present invention can obtain more superior performance can strongly explain the rationality and effectiveness of the introduction of the cognitive radio idea.
Finally, simulation experiments prove that the optimal method of embodiment 1 and the suboptimal method of embodiment 2 based on the joint allocation of the cognitive original resources and the detected hole resources can obtain performances obviously superior to those of a comparison algorithm in the heterogeneous network, namely, higher throughput and higher energy efficiency, as shown in fig. 3 to 7. And proved that compared with the optimal scheme, the suboptimal method corresponding to the algorithm of the invention can actually greatly reduce the computational complexity.
The invention has the following characteristics and remarkable progress:
1. the invention uses the thought of cognitive radio for reference, and utilizes two key technologies of the cognitive radio, namely frequency spectrum sharing and frequency spectrum detection. Therefore, system resources are utilized more fully, the resource utilization rate is improved, and the system throughput, energy efficiency and other performances can be effectively improved.
2. The present invention considers that different networks in the system can share spectrum resources with each other, which is the biggest difference from the proposal proposed by other researchers. Thereby making more efficient use of the limited resources of the system.
3. The invention takes the original resources and the detected cavity resources into consideration and carries out combined overall distribution.
Although the invention herein has been described with reference to particular embodiments, it is to be understood that these embodiments are merely illustrative of the principles and applications of the present invention. It is therefore to be understood that numerous modifications may be made to the illustrative embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims. It should be understood that features described in different dependent claims and herein may be combined in ways different from those described in the original claims. It is also to be understood that features described in connection with individual embodiments may be used in other described embodiments.

Claims (7)

1. A method for jointly allocating original resources and detected hole resources based on cognition is characterized by comprising the following steps:
step one, setting user minimum data transmission rate R min Upper limit of power available to user
Figure FDA0003739623750000011
Frequency spectrum detection threshold
Figure FDA0003739623750000012
Sum sub-channel interference preset threshold
Figure FDA0003739623750000013
Step two: the BS/AP node in the multi-generic heterogeneous system allocates an original sub-channel for each user and utilizes a frequency spectrum detection threshold
Figure FDA0003739623750000014
Sum sub-channel interference preset threshold
Figure FDA0003739623750000015
Detecting a spectrum hole sub-channel in the multi-genus heterogeneous system, and distributing the detected spectrum hole sub-channel for each user by the BS/AP node;
when dispensing, R is m ≥R min And
Figure FDA0003739623750000016
when the user is taken as a limiting condition, the Lagrange dual method is utilized to obtain the optimal user original sub-channel distribution result and the optimal spectrum hole sub-channel distribution result;
R m representing the total rate of data transmission, P, for user m m Total power consumed for user m;
executing a second step when the channel condition information changes, wherein the second step comprises the following steps:
step two, initializing Lagrange multiplier
Figure FDA0003739623750000017
Enabling the current iteration number j of the outer loop to be =1, and enabling an iteration stop indicating variable F of the outer loop to be =1;
step two, if the current F =1 and j is less than or equal to T, T represents the upper limit of the outer layer iteration times, and the step four is carried out; otherwise, determining that the current original sub-channel distribution result and the spectrum hole sub-channel distribution result are optimal, and outputting;
Step two and step three, initializing Lagrange multiplier v m (1) The iteration stop indication variable F '=1 by enabling the current iteration times j' =1 of the inner loop;
step two, if the current F '=1 and j' ≦ T ', T' represents the upper limit of the iteration times of the inner layer, the step is shifted to step two five; otherwise, go to step twenty;
step two, the BS/AP node in the multi-heterogeneous system allocates an original sub-channel for each user to obtain the current original sub-channel allocation result;
step two and step six, utilizing frequency spectrum to detect threshold
Figure FDA0003739623750000018
Sum sub-channel interference preset threshold
Figure FDA0003739623750000019
The BS/AP node carries out spectrum detection, and detects that the sub-channel is a hole sub-channel;
seventhly, the BS/AP node allocates and detects a hole sub-channel for each user and obtains a current spectrum hole sub-channel allocation result;
step two eight, if
Figure FDA00037396237500000110
And v is m (j ') =0, then let F' =0, proceed to step twenty-nine; if it is not
Figure FDA00037396237500000111
And v is m (j ') is greater than 0, then F' =0, and the process is shifted to the step twenty-nine; if it is not
Figure FDA00037396237500000112
And v is m (j') is > 0, then v is decreased m (j'), and then the step II is carried out; otherwise, increase v m (j'), and then the step II is carried out;
step two nine, j '= j' +1, return to step two four;
Step twenty, if R m ≥R min And is provided with
Figure FDA0003739623750000021
If the result is F =0, the step is shifted to twenty-one; if R is m ＝R min And is
Figure FDA0003739623750000022
If the F =0, the step is shifted to twenty-one; if R is m ＞R min And is
Figure FDA0003739623750000023
Then decrease
Figure FDA0003739623750000024
Turning to the twenty-first step; otherwise, increase
Figure FDA0003739623750000025
Twenty one, j = j +1, and returning to the step two;
v m (j ') represents a Lagrange multiplier of the corresponding limiting condition user available power upper limit in the Lagrange dual method when the current iteration number of the inner layer circulation is j';
Figure FDA0003739623750000026
and the Lagrange multiplier corresponding to the minimum data transmission rate of the user with the limiting condition in the Lagrange dual method is expressed when the outer iteration number is j.
2. The method of claim 1, wherein the cognizant-based original resources are allocated in conjunction with the detected hole resources,
in the second step, the original sub-channel allocation result includes
Figure FDA0003739623750000027
And
Figure FDA0003739623750000028
Figure FDA0003739623750000029
Figure FDA00037396237500000210
indicating whether the s-th BS/AP node of the network n will originate the subchannel k ns Is assigned to the user m and,
Figure FDA00037396237500000211
1 or 0,1 is taken to indicate allocation, and 0 indicates no allocation;
wherein
Figure FDA00037396237500000212
Figure FDA00037396237500000213
Representing a set of users located in the coverage area of the s-th BS/AP node in the network n;
intermediate volume
Figure FDA00037396237500000214
Figure FDA00037396237500000215
The channel gain between the user m on the original sub-channel k and the s-th BS/AP node of the network n; n is a radical of 0 Is the single-sided noise power spectral density; b is 0 A bandwidth for each subcarrier;
v m representing a Lagrange multiplier of the corresponding limiting condition user available power upper limit in a Lagrange dual method, wherein an initial value is a small enough positive number generated randomly;
Figure FDA0003739623750000031
representing Lagrange multiplier corresponding to limiting condition user minimum data transmission rate in Lagrange dual method, wherein the initial value is a small enough positive number generated randomly;
Figure FDA0003739623750000032
indicating that user m is on subchannel k ns Power consumption of the circuit when data are transmitted between the s-th BS/AP node of the network n and the S-th BS/AP node;
original subchannel k ns Corresponding power
Figure FDA0003739623750000033
Figure FDA0003739623750000034
3. The method of claim 2, wherein in step two, the spectrum hole sub-channel allocation result comprises spectrum original resource and detected hole resource joint allocation
Figure FDA0003739623750000035
And
Figure FDA0003739623750000036
Figure FDA0003739623750000037
Figure FDA0003739623750000038
denoting if the s ' th BS/AP node of network n ' will spectrum the hole sub-channel k ' n′s′ Is assigned to the user m and,
Figure FDA0003739623750000039
1 or 0,1 is taken to represent allocation, and 0 represents no allocation;
wherein, the first and the second end of the pipe are connected with each other,
Figure FDA00037396237500000310
representing a set of users located in the coverage area of the s 'th BS/AP node in the network n';
Figure FDA00037396237500000311
N 0 is the single-sided noise power spectral density; b is 0 A bandwidth for each subcarrier;
Figure FDA00037396237500000312
representing Lagrange multipliers corresponding to the sub-channel interference upper limit of the limiting condition in the Lagrange dual method, wherein the initial value is a small enough positive number generated randomly;
Figure FDA00037396237500000313
Representing the s-th BS/AP node of network n for subchannel k 'when detecting the spectral hole subchannel' n′s′ As a result of the detection being carried out,
Figure FDA00037396237500000314
1 or 0,0 is taken to represent sub-channel k' n′s′ Is a spectral hole subchannel, 1 denotes subchannel k' n′s′ Cannot be reused;
Figure FDA0003739623750000041
is spectral hole sub-channel k' n′s′ Channel gain between the upper user m and the s 'th BS/AP node of the network n';
intermediate volume
Figure FDA0003739623750000042
Figure FDA0003739623750000043
Denotes that user m is at subchannel k' n′s′ Power consumption by the circuitry in transmitting data between the s 'th BS/AP node of network n';
original subchannel k' n′s′ Corresponding power
Figure FDA0003739623750000044
Figure FDA0003739623750000045
4. The cognition-based original resource and detected hole resource joint allocation method according to claim 3, wherein in the second step, a Lagrangian multiplier optimal value iteration method in a Lagrangian dual method is as follows:
Figure FDA0003739623750000046
Figure FDA0003739623750000047
Figure FDA0003739623750000048
iteration step size epsilon 2 And epsilon 3 Is a sufficiently small positive number, i denotes the optimum v m 、
Figure FDA0003739623750000049
And
Figure FDA00037396237500000410
the number of iterations of (c);
Figure FDA00037396237500000411
representing spectral hole sub-channel k' n′s′ Channel power gain between the upper user m and the s ' th BS/AP node of the network n ' and the spectrum hole sub-channel k ' n′s′ Has been previously allocated to user m' where
Figure FDA00037396237500000412
A threshold value is preset for sub-channel interference.
5. A method for jointly allocating original resources and detected hole resources based on cognition is characterized by comprising the following steps:
Step one, setting user minimum data transmission rate R min Upper limit of power available to user
Figure FDA00037396237500000413
Frequency spectrum detection threshold
Figure FDA00037396237500000414
Sum sub-channel interference preset threshold
Figure FDA00037396237500000415
Step two: the BS/AP node in the multi-generic heterogeneous system allocates an original sub-channel for each user and utilizes a frequency spectrum detection threshold
Figure FDA00037396237500000416
Sum sub-channel interference preset threshold
Figure FDA00037396237500000417
Detecting the spectrum hole sub-channel in the multi-genus heterogeneous system, and distributing the detected spectrum hole sub-channel for each user by the BS/AP node;
when dispensing, R is m ≥R min And
Figure FDA0003739623750000051
when the user is taken as a limiting condition, the Lagrange dual method is utilized to obtain the optimal user original sub-channel distribution result and the optimal spectrum hole sub-channel distribution result;
R m representing the total rate of data transmission, P, for user m m Total power consumed for user m;
the second step comprises the following steps:
step two, firstly: BS/AP node in multi-generic heterogeneous system allocates original sub-channel for each user, and utilizes
Figure FDA0003739623750000052
Iteration is carried out by using the parameters as limiting conditions and corresponding Lagrange multipliers to obtain an optimal user original sub-channel distribution result;
step two: when the channel condition information changes, the detection threshold of the available power upper limit frequency spectrum is utilized
Figure FDA0003739623750000053
Sum sub-channel interference preset threshold
Figure FDA0003739623750000054
Detecting the frequency spectrum hole sub-channel in the multi-genus heterogeneous system, and turning to the second step and the third step;
Step two and step three: the BS/AP node allocates the detected spectrum hole sub-channel for each user and utilizes
Figure FDA0003739623750000055
R m ≥R min Iteration is carried out by taking the optimal spectrum hole subchannel distribution result as a limiting condition and a corresponding Lagrange multiplier, and the second step is carried out;
in the second step, the original sub-channel allocation result is:
Figure FDA0003739623750000056
Figure FDA0003739623750000057
indicating whether the s-th BS/AP node of the network n will be the original sub-channel k ns Is assigned to the user m and,
Figure FDA0003739623750000058
1 or 0,1 is taken to represent allocation, and 0 represents no allocation;
wherein
Figure FDA0003739623750000059
Representing a set of users located in the coverage area of the s-th BS/AP node in network n;
Figure FDA00037396237500000510
Figure FDA00037396237500000511
representing the channel power gain expectation;
Figure FDA00037396237500000512
the channel gain between the user m on the original sub-channel k and the s-th BS/AP node of the network n;
N 0 is the single-sided noise power spectral density; b is 0 A bandwidth for each subcarrier;
Figure FDA00037396237500000513
indicating that user m is on subchannel k ns Power consumption of the circuit when data are transmitted between the s-th BS/AP node of the network n and the S-th BS/AP node;
v 1m representing Lagrange multipliers corresponding to the upper limit of the available power of the conditional user when the original sub-channels are distributed in the Lagrange dual method, wherein the initial value is a small enough positive number generated randomly;
original subchannel k ns Corresponding power
Figure FDA0003739623750000061
6. The method for jointly allocating original resources and detected hole resources based on cognition according to claim 5, wherein in the second step, the spectrum hole sub-channel allocation result is:
Figure FDA0003739623750000062
Figure FDA0003739623750000063
Denoting if the s ' th BS/AP node of network n ' will spectrum the hole sub-channel k ' n′s′ Is assigned to the user m and is,
Figure FDA0003739623750000064
1 or 0,1 is taken to indicate allocation, and 0 indicates no allocation;
wherein, the first and the second end of the pipe are connected with each other,
Figure FDA0003739623750000065
represents a set of users located in the coverage area of the s 'th BS/AP node in the network n';
Figure FDA0003739623750000066
N 0 is the single-sided noise power spectral density; b 0 A bandwidth for each subcarrier;
v 2m representing a Lagrange multiplier corresponding to the upper limit of the available power of the user under the limiting condition when a spectrum empty hole sub-channel is distributed in the Lagrange dual method, wherein the initial value is a small enough positive number generated randomly;
Figure FDA0003739623750000067
representing a Lagrange multiplier corresponding to the minimum data transmission rate of a user with a limiting condition when a spectrum empty hole sub-channel is allocated in a Lagrange dual method, wherein an initial value is a small enough positive number generated randomly;
Figure FDA0003739623750000068
representing Lagrange multipliers corresponding to the sub-channel interference upper limit of the limiting condition during spectrum hole detection in a Lagrange dual method, wherein an initial value is a small enough positive number generated randomly;
Figure FDA0003739623750000069
representing the s-th BS/AP node of the network n for the sub-channel k 'when detecting the spectrum hole sub-channel' n′s′ As a result of the detection being carried out,
Figure FDA00037396237500000610
1 or 0,0 is taken to represent sub-channel k' n′s′ Is oneSpectral hole subchannel, 1 denotes subchannel k' n′s′ Cannot be reused;
Figure FDA00037396237500000611
Is spectral hole sub-channel k' n′s′ Channel gain between the upper user m and the s 'th BS/AP node of the network n';
Figure FDA0003739623750000071
representing user m at sub-channel k' n′s′ Power consumption by the circuitry in transmitting data between the s 'th BS/AP node of network n';
original sub-channel k' n′s′ Corresponding power
Figure FDA0003739623750000072
Figure FDA0003739623750000073
7. The cognition-based original resource and detected hole resource joint allocation method as claimed in claim 6, wherein in the second step, a Lagrangian multiplier optimal value iteration method in a Lagrangian dual method is as follows:
Figure FDA0003739623750000074
Figure FDA0003739623750000075
Figure FDA0003739623750000076
Figure FDA0003739623750000077
wherein the content of the first and second substances,
Figure FDA0003739623750000078
representing the upper power limit, iteration step size epsilon, at which the original subchannel is allocated 4 、ε 5 、ε 6 And ε 7 Is a sufficiently small positive number, i denotes the optimal v 1m 、
Figure FDA0003739623750000079
v 2m And
Figure FDA00037396237500000710
the number of iterations of (a) is,
Figure FDA00037396237500000711
representing spectral hole sub-channel k' n′s′ Channel power gain between the upper user m and the s ' th BS/AP node of the network n ' and the spectrum hole sub-channel k ' n′s′ Has been previously allocated to user m', wherein
Figure FDA00037396237500000712
A threshold value is preset for sub-channel interference.
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