CN107567055B - Robust resource allocation method based on user outage probability in two-layer heterogeneous wireless network - Google Patents

Robust resource allocation method based on user outage probability in two-layer heterogeneous wireless network Download PDF

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CN107567055B
CN107567055B CN201711002186.4A CN201711002186A CN107567055B CN 107567055 B CN107567055 B CN 107567055B CN 201711002186 A CN201711002186 A CN 201711002186A CN 107567055 B CN107567055 B CN 107567055B
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user
femtocell
femtocell user
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resource allocation
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CN107567055A (en
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徐勇军
胡圆
舒凡一
李国权
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Shenzhen Hongyue Information Technology Co ltd
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Chongqing University of Post and Telecommunications
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Abstract

The invention discloses a robust resource allocation method based on user outage probability in a two-layer heterogeneous wireless network. The invention guarantees QoS of the femtocell user and the macrocell user, solves the optimization problem of jointly optimizing the interference interruption probability constraint and the data rate interruption probability constraint condition, and maximizes the total transmission rate of the femtocell user by controlling the transmitting power of the femtocell user. In order to overcome the influence of channel uncertainty on communication system transmission, the original random constraint and mixed integer optimization problem is converted into a solvable convex optimization problem based on robust optimization and an uncertain parameter statistical model. Compared with the traditional resource allocation algorithm, the robust resource allocation problem under the imperfect channel information state is considered, the method has the advantages of good convergence, strong robustness and the like, the service quality of femtocell and macrocell users can be well protected, the stability of the system is improved, and the interruption probability of the users is reduced.

Description

Robust resource allocation method based on user outage probability in two-layer heterogeneous wireless network
Technical Field
The invention relates to the technical field of resource allocation in a heterogeneous wireless network, in particular to a robust resource allocation method based on user outage probability in a two-layer heterogeneous wireless network.
Background
In recent years, the technology of embedding femtocells into macrocells is capable of well enhancing the coverage of conventional cellular networks, improving system capacity, and meeting high data rate requirements in indoor wireless environments. However, when multiple types of base stations are deployed in a heterogeneous wireless network, the phenomenon that coverage areas of different base stations overlap inevitably occurs, so that the problems of cross-layer interference and intra-layer interference management are caused. Thus, it is a great challenge to implement resource sharing between two layers of heterogeneous wireless networks. An efficient resource allocation algorithm is considered as one of the important approaches to solve this problem.
However, the conventional heterogeneous wireless network resource allocation algorithm considers the interference management problem between the femto cell and the macro cell only under perfect channel state information (perfect CSI). Not only are the quality of service requirements of the femto users ignored, such as meeting a minimum transmission data rate, but also the impact of channel uncertainty on system performance is ignored. In practical communication scenarios, it is always not feasible to assume perfect channel state information due to factors such as complex, time-varying radio environment and channel estimation errors. Imperfect channel state information may cause performance degradation of a resource allocation algorithm, and therefore, a robust resource allocation algorithm of a heterogeneous wireless network provides a new challenge for realizing multi-layer network resource sharing and practical engineering application of the resource allocation algorithm.
Disclosure of Invention
The invention aims to ensure the QoS of macro cellular users and femtocell users under the condition of channel uncertainty, reduce the interruption probability of the users and realize the convergence of the algorithm.
The technical scheme adopted by the invention is as follows:
a robust resource allocation method based on user outage probability in a two-layer heterogeneous wireless network comprises the following steps:
s1: initializing system parameters; the system parameters comprise the number M of the femtocell users, the system bandwidth, the number K of subcarriers, the channel gain, the interruption probability threshold, the interference temperature value, the minimum rate request and the maximum transmitting power value of each user.
S2: and (5) performing iteration initialization. And setting iteration times, acquiring channel information and distributing subcarriers.
S3: it is determined whether the subcarrier allocation factor is allocated to only one user, and if so, the process proceeds to S4. Otherwise, return to S2.
S4: calculating the optimal transmission power of the femtocell user, and updating the transmission power limiting factor lambda of the femtocell userm(t +1), quality of service protection factor mum(t +1) and an interference power control factor v (t + 1).
S5: and ensuring the QoS of the femtocell user. It is determined whether the data rate of the femtocell user is greater than or equal to a minimum rate constraint. If yes, the process proceeds to S6. Otherwise, the process proceeds to S7.
S6: and ensuring the QoS of the macro cell users, calculating the interference power of all the femtocell users to the macro cell users, judging whether the interference power is less than or equal to an interference power threshold value, and if so, entering S7. Otherwise, the process proceeds to S8.
S7: and judging whether the sum of the transmission power of the femtocell user on all the subcarriers is less than or equal to the maximum transmission power. If yes, the process proceeds to S8. Otherwise, the optimal transmission power of the femtocell user is the maximum transmission power and enters the next iteration, and the step returns to S4.
S8: and judging whether the current iteration times are larger than the maximum iteration times, if so, ending the process, and obtaining the optimal transmitting power of the femtocell user. Otherwise, the next iteration is entered, returning to S4.
Specifically, the S3 specifically is: according to the formula
Figure BDA0001443649540000021
Determining whether the subcarrier allocation factor is allocated to only one user, where M ∈ [1, M]，k∈[1,K]，ρm,kAllocating a factor, C, to a subcarriermA set of subcarriers representing femto user m.
Specifically, in S4, the optimal transmit power of the femtocell user is based on
Figure BDA0001443649540000022
Calculating; wherein the content of the first and second substances,
Figure BDA0001443649540000023
is the optimum transmitting power, lambda, of the femtocell user obtained when the iteration number is tm(t) is the femtocell user transmit power limiting factor, μ, for a number of iterations tm(t) is a femtocell user service quality protection factor when the iteration number is t, upsilon (t) is an interference power control factor when the iteration number is t, B represents the bandwidth of a subcarrier,
Figure BDA0001443649540000024
representing the estimated channel gain on the femtocell user transmitter to femtocell receiver link, ξmInterrupt probability threshold, σ, representing an interrupt event for a femtocell userm,kIn the case of background noise, the noise level,
Figure BDA0001443649540000025
is the estimated channel gain between the femtocell transmitter and the macrocell receiver, Q (x) is a Gaussian Q function, upsilonm,kStandard deviation, Δ h, for the independent Gaussian distribution modelm,kObey a uniform distribution, i.e. Δ hm,k∈[-m,k,m,k]，m,kIs the upper bound of the uncertainty domain.
Specifically, in S4, the transmit power limiting factor λ of the femtocell user is updatedm(t +1), quality of service protection factor mum(t +1) and an interference power control factor upsilon (t +1), wherem(t+1)、μmThe expressions (t +1) and υ (t +1) are as follows:
Figure BDA0001443649540000026
Figure BDA0001443649540000027
Figure BDA0001443649540000031
wherein d is1，d2And d3Is λm(t+1)、μm(t +1) and upstep (t + 1);
Figure BDA0001443649540000032
representing the maximum transmission power, I, of the femtocell user m allowed to transmitthIndicating the interference temperature threshold of the macro user receiver,
Figure BDA0001443649540000033
representing the minimum rate requirement, p, of a femtocell user mm,k(t) represents the transmit power of the femtocell user m on subcarrier k,
Figure BDA0001443649540000034
representation of femtocell user transmitter and macroEstimated channel gain between the user receivers; amplifying the subcarrier allocation factor into a continuous variable, order
Figure BDA0001443649540000035
Represents the effective data rate due to the true physical channel gain, and x]+＝max{0,x}。
Specifically, the S5 specifically is: optimal transmit power according to femtocell users
Figure BDA0001443649540000036
Combination formula
Figure BDA0001443649540000037
The data rate of the femtocell user is calculated, wherein,
Figure BDA0001443649540000038
is the data rate of the femtocell user,
Figure BDA0001443649540000039
representing the effective data rate, p, due to the true channel gainm,kIs the allocation factor of femtocell user m on subcarrier k.
Specifically, the S6 specifically is: by the formula
Figure BDA00014436495400000310
Judging whether the interference power of the femtocell user to the macrocell user is less than or equal to an interference power threshold value; wherein, IthIs a disturbance temperature threshold value, upsilonm,k′Is an independent Gaussian distribution Δ gm,k′Standard deviation of (2).
The invention simultaneously considers the uncertainty constraints of the data rate and the interference of the macro user and the femtocell user, combines a subcarrier allocation scheme, converts the original non-convex optimization problem into a convex optimization problem by converting the corresponding interruption probability constraints into a deterministic form and performing mixed integer programming, and finally calculates the transmitting power of the femtocell user by using a Carlo-Kuen-Tack condition (KKT) and a Lagrange decomposition method. The invention not only ensures the QoS performance of the macro cellular user and the femtocell user, but also ensures that the resource allocation algorithm has good convergence and practicability.
Drawings
FIG. 1 is a flow chart of the present invention;
fig. 2 is a graph of femto cell transmit power versus interference for the present invention as the number of iterations t increases from 1 to 40;
FIG. 3 shows the total data rate and maximum transmission power of femtocell users under different outage probabilities of the femtocell users
Figure BDA00014436495400000311
A graph of (a);
fig. 4 is a graph of the interference power experienced by macro-cellular users versus the maximum transmit power of the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings.
As shown in fig. 1, a robust resource allocation method based on user outage probability in a two-layer heterogeneous wireless network includes the following steps:
s1: initializing system parameters; the system parameters comprise the number of users, the system bandwidth, the number of subcarriers, the channel gain, the interruption probability threshold, the interference temperature value, the minimum rate request and the maximum transmitting power value of each user.
Considering a heterogeneous wireless network based on OFDM multi-user uplink, there are M femtocell users, K subcarriers, whose sets are M ∈ [1, M respectively]And K ∈ [1, K ]]. Considering the power control problem of the uplink, the channel gain between the femtocell user and the macrocell user link is g on the subcarrierm,kThe transmission power of the femtocell user m on the subcarrier k is pm,kAt a data rate of rm,kBackground noise of σm,k。
S2: performing iteration initialization; and setting iteration times, acquiring channel information and distributing subcarriers. And taking T as 1 in the initial iteration, taking the maximum iteration number as T, acquiring channel information, allocating subcarrier resources, and allocating subcarriers to users with the optimal channel conditions.
Definition of
Figure BDA0001443649540000041
Expressed as a subcarrier selection factor, the expression is as follows:
Figure BDA0001443649540000042
where B is the bandwidth of each subcarrier,
Figure BDA0001443649540000043
representing the estimated channel gain, mu, over the femtocell user transmitter to femtocell receiver linkmIs the femtocell user quality of service protection factor.
The subcarrier allocation scheme is as follows:
Figure BDA0001443649540000044
where ρ ism,kWhich represents the sub-carrier allocation factor,
Figure BDA0001443649540000045
representing the optimal subcarrier allocation factor.
S3: judging whether the subcarrier allocation factor is allocated to only one user or not, wherein the judgment formula is
Figure BDA0001443649540000046
If yes, go to S4; otherwise, return to S2.
S4: calculating the optimal transmission power of the femtocell user, and updating the transmission power limiting factor lambda of the femtocell userm(t +1), quality of service protection factor mum(t +1) and an interference power control factor v (t + 1).
Solving and deducing the convex optimization problem by adopting a Lagrange decomposition method and a Carrocon-Kuen-Tack condition (KKT condition) to obtain the optimal transmitting power of the femtocell user, wherein the optimal transmitting power of the femtocell user is obtained according to the
Figure BDA0001443649540000051
And (4) calculating.
Wherein the content of the first and second substances,
Figure BDA0001443649540000052
is the optimum transmitting power, lambda, of the femtocell user obtained when the iteration number is tm(t) is the femtocell user transmit power limiting factor, μ, for a number of iterations tm(t) is a femtocell user service quality protection factor when the iteration number is t, upsilon (t) is an interference power control factor when the iteration number is t, B represents the bandwidth of a subcarrier,
Figure BDA0001443649540000053
representing the estimated channel gain on the femtocell user transmitter to femtocell receiver link, ξmInterrupt probability threshold, σ, representing an interrupt event for a femtocell userm,kIn the case of background noise, the noise level,
Figure BDA0001443649540000054
is the estimated channel gain between the femtocell transmitter and the macrocell receiver, Q (x) is a Gaussian Q function, upsilonm,kStandard deviation, Δ h, for the independent Gaussian distribution modelm,kObey a uniform distribution, i.e. Δ hm,k∈[-m,k,m,k]，m,kIs the upper bound of the uncertainty domain.
Updating a transmit power limiting factor lambda of a femtocell userm(t +1), quality of service protection factor mum(t +1) and an interference power control factor upsilon (t +1), wherem(t+1)、μmThe expressions (t +1) and υ (t +1) are as follows:
Figure BDA0001443649540000055
Figure BDA0001443649540000056
Figure BDA0001443649540000057
wherein d is1，d2And d3Is λm(t+1)、μm(t +1) and upstep (t + 1);
Figure BDA0001443649540000058
representing the maximum transmission power, I, of the femtocell user m allowed to transmitthIndicating the interference temperature threshold of the macro user receiver,
Figure BDA0001443649540000059
representing the minimum rate requirement, p, of a femtocell user mm,k(t) represents the transmit power of the femtocell user m on subcarrier k,
Figure BDA00014436495400000510
representing an estimated channel gain between the femtocell user transmitter and the macrocell user receiver; amplifying the subcarrier allocation factor into a continuous variable, order
Figure BDA00014436495400000511
Represents the effective data rate due to the true physical channel gain, and x]+＝max{0,x}。
S5: QoS of the femtocell user is guaranteed; judging whether the data rate of the femtocell user is greater than or equal to the minimum rate constraint; if yes, go to S6; otherwise, the process proceeds to S7.
In order to protect the QoS performance of macro cell users, the original rate probability constraint condition needs to be converted into a deterministic form, and the original constraint condition is:
Figure BDA0001443649540000061
wherein the user data rate of femto user m on sub-carrier k is
Figure BDA0001443649540000062
hm,kRepresenting the channel gain on the femtocell user transmitter to femtocell receiver link,
Figure BDA0001443649540000063
representing minimum velocity requirement for femtocell user m, ξmAn outage probability threshold for an outage event occurring for a femtocell user.
Converting the outage probability constraint into an efficient and calculable expression, representing the channel uncertainty parameter as uncertainty parameter gm,kAnd hm,kAn additive model of (1). Respectively as follows:
Figure BDA0001443649540000064
wherein
Figure BDA0001443649540000065
Is the estimated channel gain on the femtocell transmitter to macro user receiver link,
Figure BDA0001443649540000066
representing the estimated channel gain on the femtocell user transmitter to femtocell receiver link. Δ gm,kIs the estimation error, Δ h, on the femtocell transmitter to macrocell receiver linkm,kIs the estimation error on the femtocell user transmitter to femtocell receiver link.
Converting equation (3) into the following form:
Figure BDA0001443649540000067
wherein the content of the first and second substances,
Figure BDA0001443649540000068
due to channel estimation error Δ hm,kObey a uniform distribution, i.e., Δ hm,k∈[-m,k,m,k]，m,kIs the upper uncertainty bound. And according to:
Figure BDA0001443649540000069
equation (5) can be converted to the following form:
Figure BDA00014436495400000610
wherein the content of the first and second substances,
Figure BDA00014436495400000611
according to the optimal transmitting power of the femtocell user calculated in S4
Figure BDA00014436495400000612
Calculating the data rate of the femtocell user in combination with equation (7); determining data rates for femtocell users
Figure BDA00014436495400000613
Whether or not to be greater than or equal to femtocell user minimum rate
Figure BDA00014436495400000614
If yes, go to S5; otherwise, the process proceeds to S7.
S6: QoS of a macro cell user is guaranteed, interference interruption probability constraint conditions are converted, and the original uncertain interference constraint conditions are as follows:
Figure BDA0001443649540000071
to make the optimization problem solvable, equation (8) is transformed into the following form:
Figure BDA0001443649540000072
wherein C ismRepresenting the set of subcarriers for femtocell user m.
According to the worst-case mechanism, it can be found that:
Figure BDA0001443649540000073
wherein the content of the first and second substances,
Figure BDA00014436495400000710
representing the interfering link under the worst criteria.
Definition Bm＝|Cm|ρm,kpm,kAnd
Figure BDA0001443649540000074
due to the variable Δ gm,k′Subject to independent Gaussian random distribution models, i.e.
Figure BDA0001443649540000075
Then variable
Figure BDA00014436495400000711
And still obey a Gaussian distribution according to the sum of Gaussian random variables, i.e.
Figure BDA0001443649540000076
The following can be obtained:
Figure BDA0001443649540000077
wherein the content of the first and second substances,
Figure BDA0001443649540000078
is a gaussian Q function.
Calculating the interference power of all femtocell users to the macrocell user by combining the formula (11), judging whether the interference power is less than or equal to an interference power threshold value, and if so, entering S7; otherwise, the process proceeds to S8. Wherein, IthIs a disturbance temperature threshold value, upsilonm,k′Is an independent Gaussian distribution Δ gm,k′Standard deviation of (2).
S7: judging whether the sum of the transmitting power of the femtocell user on all subcarriers is less than or equal to the maximum transmitting power, wherein the judgment formula is as follows:
Figure BDA00014436495400000712
wherein s ism,kIs the sum of the transmit power of the femto user on all sub-carriers,
Figure BDA0001443649540000079
is the maximum transmit power allowed for transmission by the femtocell user m; if yes, go to S8; otherwise, the optimal transmission power of the femtocell user is the maximum transmission power and enters the next iteration, and the step returns to S4.
S8: judging whether the current iteration times are larger than the maximum iteration times, if so, ending the process to obtain the optimal transmitting power of the femtocell user; otherwise, the next iteration is entered, returning to S4.
The invention is further explained below by the assumption of initial values for the communication network.
S1, establishing a communication network, initializing system parameters, assuming that there are 4 femtocell users (M is 4), system bandwidth, number of subcarriers (K is 128), and outage probability threshold (∈ (0, 0.5)), ξm∈(0,1]) Interference temperature value (I)th＝10- 5W), minimum rate per user request
Figure BDA0001443649540000081
And maximum transmission power value
Figure BDA0001443649540000082
White gaussian noise value sigma with zero mean background noisem,k＝10-8W is added. Channel estimation
Figure BDA0001443649540000083
And
Figure BDA0001443649540000084
all fall within (0, 1)]。
And S2, setting the iteration number T, taking T as 1 in the first iteration and taking the maximum iteration number as T as 40, and acquiring the channel information.
S3: judging whether the formula is satisfied
Figure BDA0001443649540000085
Ensuring that each subcarrier is allocated to only one user, where pm,kA factor is assigned to the subcarrier. If yes, go to S4; otherwise, return to S2.
S4: calculating the optimal transmission power of the femtocell user, and updating the transmission power limiting factor lambda of the femtocell userm(t +1), quality of service protection factor mum(t +1) and an interference power control factor v (t + 1).
Optimum transmit power of femtocell user based on
Figure BDA0001443649540000086
And (4) calculating.
Wherein the content of the first and second substances,
Figure BDA0001443649540000087
is the optimum transmitting power, lambda, of the femtocell user obtained when the iteration number is tm(t) is the femtocell user transmit power limiting factor, μ, for a number of iterations tm(t) is a femtocell user service quality protection factor when the iteration number is t, upsilon (t) is an interference power control factor when the iteration number is t, B represents the bandwidth of a subcarrier,
Figure BDA0001443649540000088
representing the estimated channel gain on the femtocell user transmitter to femtocell receiver link, ξmInterrupt probability threshold, σ, representing an interrupt event for a femtocell userm,kIn the case of background noise, the noise level,
Figure BDA0001443649540000089
is the estimated channel gain between the femtocell transmitter and the macrocell receiver, Q (x) is a Gaussian Q function, upsilonm,kStandard deviation of the independent gaussian distribution model; Δ hm,kObey a uniform distribution, i.e. Δ hm,k∈[-m,k,m,k]，m,kIs the upper bound of the uncertainty domain.
Updating a transmit power limiting factor lambda of a femtocell userm(t +1), quality of serviceProtective factor mum(t +1) and an interference power control factor upsilon (t +1), wherem(t+1)、μmThe expressions (t +1) and υ (t +1) are as follows:
Figure BDA00014436495400000810
Figure BDA00014436495400000811
Figure BDA00014436495400000812
wherein d is1，d2And d3Is λm(t+1)、μm(t +1) and upstep (t + 1);
Figure BDA00014436495400000813
representing the maximum transmission power, I, of the femtocell user m allowed to transmitthIndicating the interference temperature threshold of the macro user receiver,
Figure BDA00014436495400000814
representing the minimum rate requirement, p, of a femtocell user mm,k(t) represents the transmit power of the femtocell user m on subcarrier k,
Figure BDA00014436495400000815
representing an estimated channel gain between the femtocell user transmitter and the macrocell user receiver; amplifying the subcarrier allocation factor into a continuous variable, order
Figure BDA0001443649540000091
Represents the effective data rate due to the true physical channel gain, and x]+＝max{0,x}。
S5: according to the femtocell user transmitting power calculated in S2
Figure BDA0001443649540000092
Then by the formula
Figure BDA0001443649540000093
The data rate of the femtocell user is calculated. And judging whether the service quality requirement of the femtocell user is met. If yes, go to S6; otherwise, the process proceeds to S7.
S6: optimal transmit power according to femtocell users
Figure BDA0001443649540000094
Combination formula
Figure BDA0001443649540000095
Calculating the interference power of all femtocell users to the macrocell user, judging whether the interference power is less than or equal to an interference power threshold value, and if so, entering S7; otherwise, the process proceeds to S8. Wherein, IthIs a disturbance temperature threshold value, upsilonm,k′Is an independent Gaussian distribution Δ gm,k′Standard deviation of (2).
S7: and judging whether the sum of the transmission power of the femtocell user on all the subcarriers is less than or equal to the maximum transmission power. If yes, go to S8; otherwise, the optimal transmission power of the femtocell user is the maximum transmission power and enters the next iteration, and the step returns to S4.
S8: judging whether the current iteration times are larger than the maximum iteration times, if so, ending the process to obtain the optimal transmitting power of the femtocell user; otherwise, the next iteration is entered, returning to S4.
In this embodiment, fig. 2 shows a convergence relationship diagram between the transmission power and the interference power obtained in the method of this embodiment and the number of iterations t. Fig. 3 shows the impact of femtocell user outage probability and channel estimation error on femtocell user performance in the example method. Fig. 4 shows the interference power level experienced by the macrocell user at different channel uncertainties in the method of the present example. As can be seen from fig. 2: the implementation method is convergent, and has high convergence speed and good convergence. As can be seen from fig. 3: total data rate and following maximum for femtocell usersTransmitting power
Figure BDA0001443649540000096
Is increased. And followm,kThe value of (c) increases, the rate sum also increases, since more transmit power is required to overcome the effects of channel uncertainty. As can be seen from fig. 4: in the proposed robust (robust) resource allocation algorithm, the interference power suffered by the macro cell user is along with the interference power
Figure BDA0001443649540000097
Increases, but its interference power can be well controlled and the interference temperature value is not exceeded, as can be seen in comparison with the non-robust (non-robust) algorithm. Obviously, the robust resource allocation algorithm and the traditional non-robust resource allocation algorithm can reduce the user interruption probability and protect the QoS of the femtocell user and the macro user.

Claims (6)

1. A robust resource allocation method based on user outage probability in a two-layer heterogeneous wireless network is characterized by comprising the following steps:
s1: initializing system parameters; the system parameters comprise the number M of femtocell users, system bandwidth, the number K of subcarriers, channel gain, an interruption probability threshold, an interference temperature value, a minimum rate request and a maximum transmitting power value of each user;
s2: performing iteration initialization; setting iteration times, acquiring channel information and distributing sub-carriers;
s3: judging whether the subcarrier allocation factor is allocated to only one user, if so, entering S4; otherwise, returning to S2;
s4: calculating the optimal transmission power of the femtocell user, and updating the transmission power limiting factor lambda of the femtocell userm(t +1), quality of service protection factor mum(t +1) and an interference power control factor upsilon (t + 1);
s5: determining data rates for femtocell users
Figure FDA0001443649530000011
Whether or not to be greater than or equal to the minimum rate
Figure FDA0001443649530000012
If yes, go to S6; otherwise, go to S7;
s6: calculating the interference power of all femtocell users to the macrocell user, judging whether the interference power is less than or equal to an interference power threshold value, and if so, entering S7; otherwise, go to S8;
s7: judging whether the sum of the transmitting power of the femtocell user on all subcarriers is less than or equal to the maximum transmitting power; if yes, go to S8; otherwise, the optimal transmitting power of the femtocell user is the maximum transmitting power and enters the next iteration, and the step returns to S4;
s8: judging whether the current iteration times are larger than the maximum iteration times, if so, ending the process to obtain the optimal transmitting power of the femtocell user; otherwise, the next iteration is entered, returning to S4.
2. The robust resource allocation method according to claim 1, wherein the S3 specifically is: according to the formula
Figure FDA0001443649530000013
Determining whether the subcarrier allocation factor is allocated to only one user, where M ∈ [1, M]，k∈[1,K]，ρm,kAllocating a factor, C, to a subcarriermA set of subcarriers representing femto user m.
3. The robust resource allocation method as claimed in claim 1, wherein the optimum transmit power of the femtocell user is based on S4
Figure FDA0001443649530000014
Calculating; wherein the content of the first and second substances,
Figure FDA0001443649530000015
is the optimum transmitting power, lambda, of the femtocell user obtained when the iteration number is tm(t) is the femtocell user transmit power limiting factor, μ, for a number of iterations tm(t) is a femtocell user service quality protection factor when the iteration number is t, upsilon (t) is an interference power control factor when the iteration number is t, B represents the bandwidth of a subcarrier,
Figure FDA0001443649530000016
representing the estimated channel gain on the femtocell user transmitter to femtocell receiver link, ξmInterrupt probability threshold, σ, representing an interrupt event for a femtocell userm,kFor background noise, Q (x) is a Gaussian Q function, upsilonm,kStandard deviation, Δ h, for the independent Gaussian distribution modelm,kObey a uniform distribution, i.e. Δ hm,k∈[-m,k,m,k]，m,kIs the upper bound of the uncertainty domain.
4. The robust resource allocation method as claimed in claim 1, wherein the step of updating the transmit power limiting factor λ of the femtocell user in S4m(t +1), quality of service protection factor mum(t +1) and an interference power control factor upsilon (t +1), wherem(t+1)、μmThe expressions (t +1) and υ (t +1) are as follows:
Figure FDA0001443649530000021
Figure FDA0001443649530000022
Figure FDA0001443649530000023
wherein d is1，d2And d3Is λm(t+1)、μm(t +1) and upstep (t + 1);
Figure FDA0001443649530000024
representing the maximum transmission power, I, of the femtocell user m allowed to transmitthIndicating the interference temperature threshold of the macro user receiver,
Figure FDA0001443649530000025
representing the minimum rate requirement, p, of a femtocell user mm,k(t) represents the transmit power of the femtocell user m on subcarrier k,
Figure FDA0001443649530000026
representing an estimated channel gain between the femtocell user transmitter and the macrocell user receiver; amplifying the subcarrier allocation factor to a continuous variable, order sm,k＝ρm, kpm,k，
Figure FDA0001443649530000027
Represents the effective data rate due to the true physical channel gain, and x]+＝max{0,x}。
5. The robust resource allocation method according to claim 1, wherein the S5 specifically is: optimal transmit power according to femtocell users
Figure FDA0001443649530000028
Combination formula
Figure FDA0001443649530000029
Calculating a data rate of a femtocell user; wherein the content of the first and second substances,
Figure FDA00014436495300000210
is the data rate, p, of the femtocell userm,kIs the allocation factor of femtocell user m on subcarrier k.
6. The robust resource allocation method according to claim 1, wherein the S6 specifically is: by the formula
Figure FDA00014436495300000211
Judging whether the interference power of the femtocell user to the macrocell user is less than or equal to an interference power threshold value; wherein, IthIs a disturbance temperature threshold value, upsilonm,k′Is an independent Gaussian distribution Δ gm,k′The standard deviation of (a) is determined,
Figure FDA0001443649530000031
representing the interfering link under the worst criteria.
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