WO2014201663A1

WO2014201663A1 - Resource allocation method and apparatus

Info

Publication number: WO2014201663A1
Application number: PCT/CN2013/077568
Authority: WO
Inventors: 李娜; 池琛; 韩广林; 费泽松
Original assignee: 华为技术有限公司
Priority date: 2013-06-20
Filing date: 2013-06-20
Publication date: 2014-12-24
Also published as: CN104969644A; CN104969644B

Abstract

The present invention provides a resource allocation method and apparatus. The method comprises: obtaining user information and requested service information of all user equipments (UEs) under a current service, so as to obtain a QCI priority of each service in all services; obtaining membership function values of all the UEs under different services according to the user information and the requested service information; and scheduling each UE and allocating a resource according to the user information, the request service information, the QCI priorities and the membership function values. By using the method, experience quality of all UEs in an OFDM wireless communications system can be basically kept consistent in different services.

Description

Resource allocation method and device

Technical field

The present invention relates to the field of communications technologies, and in particular, to a resource allocation method and apparatus. Background technique

In the future, cellular mobile communication will be based on data and multimedia communication, and the quality of wireless communication technology will be higher. Internet will be used as the bearer network and communication will be based on Internet Protocol (IP). The emergence of Orthogonal Frequency Division Multiplexing (OFDM) technology has met the ever-expanding communication needs. In addition to high spectrum utilization, OFDM systems can flexibly select the appropriate subcarriers for transmission to achieve dynamic frequency domain resource allocation, making full use of frequency diversity and multi-user diversity for optimal system performance. Due to the many advantages of OFDM technology, it has been widely used in the field of fixed wireless access and mobile access.

In IP-based applications, network providers and service providers are often concerned about Internet Protocol Television (IPTV), Voice over Internet Protocol (VoIP), and file downloads. The quality of experience of services such as File Download (hereinafter referred to as FD), and the traditional Quality of Service (QoS) parameters do not intuitively reflect the user experience.

The concept of Quality of Experience (QoE) has emerged in order to more directly represent the user experience of users (User Equipment, hereinafter referred to as UE) for services such as IPTV, VoIP, and FD. The Mean Opinion Score (hereinafter referred to as MOS) is a universal metric that reflects the QoE of UE users. The value range of MOS is 1~5, 1 means the service quality is very poor, the user can't be satisfied; 5 means the service quality is very good, the user is very satisfied; MOS is refined into 5 files, which means that the user has no quality service. satisfaction level. Therefore, how to ensure QoE of all UEs in different services is an urgent problem to be solved. Summary of the invention The present invention provides a resource allocation method and apparatus, which are used for achieving the purpose of basically matching QoEs of all UEs in different services in a wireless communication system of OFDM.

In a first aspect, an embodiment of the present invention provides a resource allocation method, including:

Obtaining user information of all user equipment UEs in the current service, requesting service information, and obtaining QCI priorities of services in all services;

Obtaining, according to the user information and the request service information, a membership function value of all UEs in different services;

According to the user information, the request service information, the QCI priority and the membership function value, scheduling and resource allocation are performed for each UE.

With reference to the first aspect, in a first possible implementation manner, the scheduling, and resource allocation, by using the user information, the request service information, the QCI priority, and the membership function value, include :

Determining, according to the user information, the request service information, the QCI priority and the membership function value, a scheduling decision formula for scheduling and resource allocation of the UE, and scheduling and resources for the UE according to the scheduling decision formula distribution.

With reference to the first aspect and the first possible implementation manner, in a second possible implementation manner, the user information includes:

Geographical location information of the UE, the maximum data rate of the UE at the current time, the average throughput of the UE in the communication system, and the QoE of the UE at the current time;

The request service information includes: a service optimal QoE provided by the current service to the UE, and a service QoE provided by the current service to the UE.

With reference to the first aspect and the second possible implementation manner, in a third possible implementation, the membership function values of all user equipments in different services are obtained according to the user information and the request service information, including: 1, if QoE^ > QoE÷

QoE, -QoE-

MiQ E _k ] if QoE _y < QoE _k ≤ QoE

0, such as if QQooEE,, << QQooEE _A ;,.

Obtaining the membership function values of all UEs in different services according to the formula; wherein Q° is the optimal QoE of the service provided by the current service X to the UE,

^{QqE: y} is the worst QoE of the service provided by the current service X to the UE,

QoE _k is the QoE of the kth UE at the current moment,

^ is the membership function value of the kth UE under the current service X. With reference to the first aspect and the third possible implementation manner, in a fourth possible implementation manner, the QCI priority and the membership function value according to the user information, the request service information, The UE performs scheduling and resource allocation, including:

Establishing a scheduling decision formula for scheduling and resource allocation of the UE according to the user information, the request service information, the QCI priority, and the membership function value

^{= ar} gmax ^w " *

According to the dispatch decision

The formula performs scheduling and resource allocation for each UE;

Where k = l " , κ is the membership function value of the kth UE under the current service X; « is a weight parameter for controlling the membership function value to determine the entire schedule;

Qei _pn . _Nty is the QCI priority of the _kth UE; K represents the number of UEs, and the denominator W represents the average throughput of the kth UE; the numerator ^« is the maximum data rate of the current time t. With reference to the first aspect and the second possible implementation manner, in the fifth possible implementation manner, when the current service is a video service,

Obtaining request service information of all user equipment UEs in the current service, including:

Estimating the optimal quality of service provided by the video service to the UE and the worst quality of service provided by the video service to the UE according to the QoE mapping relationship of the video service;

The QoE mapping relationship of the video service is a mapping relationship between the transmission rate of the video service and the QoE.

With reference to the first aspect and the first to fourth possible implementation manners, in the sixth possible implementation manner, the foregoing services include: an IPTV service, an FD service, and a VoIP service.

In a second aspect, an embodiment of the present invention provides a resource allocation apparatus, including: a memory and a processor, where the memory is configured to store an instruction including the processor executing a program, where the processor is configured to execute according to the instruction The program specifically includes:

And performing scheduling and resource allocation on the UE according to the user information, the request service information, the QCI priority, and the membership function value.

With reference to the second aspect, in a first possible implementation manner, the processor is configured to establish, according to the user information, the request service information, the QCI priority, and the membership function value, A scheduling decision formula for scheduling and resource allocation is performed, and scheduling and resource allocation are performed on the UE according to the scheduling decision formula.

With reference to the second aspect and the foregoing possible implementation manner, in a second possible implementation manner, the user information includes:

Geographical location information of the UE, the maximum data rate of the UE at the current moment, the average throughput of the UE in the communication system, and the QoE of the UE at the current moment; The request service information includes: a service optimal QoE provided by the current service to the UE, and a service minimum QoE provided by the current service to the UE.

With reference to the second aspect and the second possible implementation manner, in a third possible implementation manner, the processor is specifically used to

' 1, if QoE, 〉QoE+ _v

QoE. -QoE"

[QoE _i . ]= If QoE _x ≤ QoE^≤ QoE

QoE÷ -QoEj

0, if QoE, < QoE"

Obtaining the membership function values of all UEs under different services according to the formula;

Where Q° is the optimal QoE of the service provided by the current service X to the UE,

^QqE ^ is the worst QoE of the service provided by the current service X to the UE,

QoE _k is the QoE of the kth UE at the current moment,

It is the membership function value of the kth UE under the current service X.

With reference to the second aspect and the third possible implementation manner, in a fourth possible implementation manner, the processor is specifically configured to perform scheduling and resource allocation according to a formula UE;

Of which, κ,

w ^[2i ^ ^] is the membership function value of the kth UE under the current service X;

« is a weight parameter for determining the value of the membership function for the entire schedule;

Q _p „ _OTlty is the QCI priority of the _kth UE;

K represents the number of UEs,

Data rate. According to the foregoing technical solution, the resource allocation method and device of the embodiment of the present invention obtains the user information, the request service information, and the QCI priority of different services of the user equipment of the current service, and obtains the membership information according to the user information and the request service information. The function value is used to implement scheduling and resource allocation for the user equipment according to the foregoing information, priority, and membership function values, thereby achieving the purpose that the QoEs of all UEs in different services in the OFDM wireless communication system are substantially consistent.

BRIEF DESCRIPTION OF THE DRAWINGS In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief description of the drawings used in the embodiments or the prior art description will be briefly described below. The drawings are some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without any inventive labor.

1 is a schematic flowchart of a resource allocation method according to an embodiment of the present invention;

2A and 2B are schematic flowcharts of a resource allocation method according to an embodiment of the present invention; FIG. 3 is a schematic diagram of QCI information in an LTE system according to another embodiment of the present invention; FIG. 4 is an IPTV service according to an embodiment of the present invention; Schematic diagram of mapping relationship between QoE and transmission rate of the UE;

FIG. 5 is a schematic diagram of mapping relationship between QoE and transmission rate of a UE in an FD service according to an embodiment of the present disclosure;

6 is a schematic diagram of mapping relationship between QoE and transmission rate of a UE in a VoIP service according to an embodiment of the present invention;

FIG. 7 is a schematic diagram of comparison of MOS scores of UEs in three services according to an embodiment of the present invention; FIG. 8 is a schematic diagram of distribution of membership function values of UEs in three services according to an embodiment of the present invention; FIG. 9 is an IPTV according to an embodiment of the present invention; FIG. 10 is a schematic diagram showing the distribution of the membership function values of the UE in the IPTV service according to the embodiment of the present invention; FIG. 11 is a schematic structural diagram of the resource allocation apparatus according to an embodiment of the present invention; A schematic structural diagram of a resource allocation apparatus according to another embodiment of the present invention. detailed description

The technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. It is a partial embodiment of the invention, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present invention without creative efforts are within the scope of the present invention.

A technical solution provided by the prior art uses a Round Robin (RR) algorithm to solve the above problem. The RR algorithm assumes that all UEs have the same priority, and provides fair service in an equal opportunity manner. All UEs are allocated the same amount of resources for communication. This technical solution mainly provides resources for each UE in the system at the expense of throughput. Since the RR algorithm does not consider the specific conditions of the radio channels of different UEs, although the fairness between the UEs is guaranteed, the system throughput may be degraded, because some UEs with poor channel conditions are served, Low data rate transmission, and even retransmissions. However, a good UE is not served, resulting in a decrease in system throughput.

The other technology solution provided by the prior art adopts the maximum carrier to dry ratio (Maximum)

Carrier/Interference; hereinafter referred to as: Max C/I) scheduling algorithm solves the above problem. The Max C/I scheduling algorithm ensures that the UE with the best link condition gets the highest priority, and the UE with good wireless channel status has high priority. The probability of correct data transmission increases, the number of error retransmissions decreases, and the throughput of the entire system is improved. However, the disadvantage of the Max C/I scheduling algorithm is that it cannot meet the UE's fairness requirements. For example, a UE close to the base station has good channel conditions, and its priority always has an advantage, which will result in other UEs in the base station getting service at this time. Very small.

In another technical solution provided by the prior art, a Proportion Fairness (hereinafter referred to as PF) scheduling algorithm is used to solve the above problem, and the PF scheduling algorithm takes into consideration the fairness between the UEs and the throughput of the system. In the PF scheduling algorithm, each UE is given a priority, and each time the UE starts to receive the scheduling, the UE with the highest priority in the cell always receives the service, which is consistent with the idea that the Max C/I scheduling algorithm is based on the priority queuing. However, the calculation methods of the two priorities are different. The advantage of the PF scheduling algorithm is that it is beneficial to increase the throughput of the system through longer channel latency, but the disadvantage is that the UE delay is increased, which may not be tolerable for delay-sensitive applications.

The algorithm corresponding to the above three technical solutions has another disadvantage, that is, the core of the above three algorithms The heart is based on the quality of service, ie QoS, and cannot allocate resources according to the experience of the UE. Currently, the main targets of wireless resource allocation are service fairness and system throughput, and the two are contradictory. Maximizing system throughput can lead to serious inequities, that is, there will be some UEs that are not allocated resources; on the other hand, maintaining fairness will significantly reduce the efficiency of the system. For example, the traditional resource allocation algorithm in Long Term Evolution (LTE) cannot guarantee the QoE and fairness of different services between UEs. Therefore, how to obtain all UEs in different services in a resource-constrained scenario A nearly identical QoE is currently addressed.

The purpose of the embodiments of the present invention is to ensure that the quality of experience of all UEs in different services is basically the same through radio resource allocation. The embodiment of the present invention is based on the PF scheduling algorithm, and combines the QoS class identifier (QCI) priority parameter of the LTE system, and proposes a resource allocation method, which can remove the effect of the utility model on the scheduling decision. , in turn, can guarantee the QoE of all UEs in different services. Gp, an embodiment of the present invention proposes a resource allocation method for ensuring the quality of experience of all UEs in different services in an OFDM system with limited resources.

FIG. 1 is a schematic flowchart of a resource allocation method according to an embodiment of the present invention. As shown in FIG. 1, the resource allocation method in this embodiment is as follows.

101. Acquire user information of all UEs in the current service, request service information, and obtain QCI priorities of services in all services.

In this embodiment, the user information may include: geographic location information of the UE (such as longitude, dimension, etc.), maximum data rate of the UE at the current moment, average throughput of the UE in the communication system, and QoE of the UE at the current moment. ;

The service information of the request includes: an optimal QoE of the service provided by the current service to the UE, and a service QoE of the service provided by the current service to the UE.

For example, the QCI priority of the service can be obtained according to the QCI information of different services.

In addition, the foregoing current service may be an IPTV service, an FD service, or a VoIP service, and all services may include an IPTV service, an FD service, and a VoIP service. The average throughput included in the user information may be the average throughput of the UE at historical moments in the communication system.

102. Acquire, according to the user information and the request service information, a membership function value of all UEs in different services. 103. Perform scheduling and resource allocation for each UE according to the user information, the request service information, the QCI priority, and the membership function value.

In an alternative implementation scenario, the aforementioned step 103 may include the following step 103', as shown in FIG. 2A.

103. The scheduling decision formula for scheduling and resource allocation of the user equipment is established according to the user information, the request service information, the QCI priority, and the membership function value, and according to the scheduling decision formula A user equipment performs scheduling and resource allocation.

It should be understood that the execution body of the above step 101 to step 103 or step 101 to step 103' may be a core network device, such as a gateway (Gate way).

The resource allocation method in the foregoing embodiment obtains the user function information of the UEs of the current service, the request service information, and the QCI priority of the different services, and obtains the membership function value according to the user information and the request service information, so that the user information is obtained according to the user information, The service information, the QCI priority, and the membership function value are used to implement scheduling and resource allocation for the UE, and the QoE of all UEs in different services in the OFDM wireless communication system is basically the same.

In the specific implementation process, the resource allocation method will be further described in detail below with reference to FIG.

Step 1: Obtain the user information of all UEs in the current service X, request service information, and obtain the QCI priority of different services.

For example, the k-th UE UE may be expressed as _k; Accordingly, the user information comprises: the location information of UE _k, _k UE maximum data rate of the current time t ¾ (0, average throughput of the UE ^ _k, UE _k 's experience quality ^QqE at the current moment.

It should indicate that the average throughput of the UE _k UE _k may refer to average throughput in a communication system (e.g. LTE system) historical moment.

Further, location information may be reported by the UE _k UE _k to the base station or core network apparatus (such as a gateway).

The request service information may include: a service optimal QoE provided by the current service X to the UE _k , that is, ^QoE -, and a service QDE, which is the worst QoE of the current service X provided to the UE _k , that is, Q ^QE ^.

It can be understood that the QCI priority of different services can be obtained by sending QCI information when the core bearer establishes a service bearer. For example, the core network device may send QCI information to the base station, where the QCI information includes: service type, QCI priority information, QoS requirements, and the like. Step 2: Obtain the membership function values of all UEs under different services according to the following formula (1).

1, if QoE^ > QoE ⁺ _x

QoE _k -QoE _x

QoE ≤ QoE _t ≤ QoE (1 )

QoE÷ -QoEj

0, if QoE^ QoE, where the current service X provides the best service QoE to the UE;

^QQ is the worst QoE of the service provided by the current service X to the UE;

QoE _k is the QoE of UE _k at the current moment;

^{11 [QoE} ^ ^] is the membership function value of UE _k under current service X.

Step 3: Establish a scheduling formula (2) for scheduling and resource allocation of the UE according to the acquired user information, request service information, QCI priority, and membership function values of all UEs under no service (ie, constructing a scheduling decision formula) (2 ) ) .

Where "[2 is the membership function value of UE _k under current service X;

n is a QCI priority for controlling the weight of the membership function value to the entire scheduling judgment to be UE _k ;

K represents the number of UEs; denominator W represents the average throughput of UE _k ; numerator (0 is the maximum data rate of the current time t

The fourth step: scheduling and resource allocation to the UE according to the above scheduling decision formula (2). The resource allocation method in the foregoing embodiment can achieve the same quality of experience for users corresponding to all user equipments in different services in the OFDM wireless communication system.

For a better understanding of the present embodiment, the above-described scheduling decision formula (2) will be described in detail.

That is,

In the formula (2'), the expression is judged for the traditional PF scheduling algorithm, in particular, PF

3⁄4 (the numerator ^^ in the scheduling algorithm decision expression) is the maximum data rate at the current time t, and the denominator is the average throughput of UE _k . , _pn . _Nty is the scheduling factor of the current service, where ^Qa

For the QCI priority in the QCI information, the QCI information is shown in Figure 3. It should be noted that QCI represents the highest priority. &, _Pri . _The use of exponential form in _rity ^=ex P enhances the impact of parameter QCI priority on UE scheduling and resource allocation.

Also, in formula (2'), . _Ε is a factor used to weigh the QoE quality consistency of different user equipments under a single service, F _Q . _E =^ ^[Q ° ^E (n > l) , which guarantees _Q in exponential form. _{E is} monotonous, non-negative.

^F Q. The purpose of introducing the parameter n in ^E is to further enhance the membership function value Q. The influence of the EJ on the scheduling and resource allocation of the UE. The larger the value of n, the greater the influence of the membership function value of the UE on the scheduling and resource allocation of the UE, so that the QoE quality between different UEs can be consistent. It should be noted that ^Fq . The parameter "in ^e " is a weight parameter that can be set according to the actual situation, and is used to control the influence of the membership function value ^[( ^ ^{Ε ]} on the scheduling and resource allocation of the UE in the whole system.

In the case that the resource is limited, the foregoing embodiment ensures QoE scheduling and resource allocation for all UEs corresponding to different UEs in different services.

In addition, it should be noted that K in the above formula (2) represents the number of UEs, if each

If the UE has only one service, K can also represent all the numbers of services. In this embodiment, it is assumed that each UE has only one service. In a third implementation scenario, the process of implementing the bearer and allocating resources of the IPTV service (such as a video service) of the UE in the LTE system is as described in the following steps S01 to S04, as shown in FIG. 2B. 501. The base station (evolved NodeB; hereinafter referred to as: eNB) acquires a QoE mapping relationship of the video service from the gateway.

502. The base station acquires user information of all UEs in the video service, such as a video encoding format, a frame rate, a code rate, a resolution, and the like.

The base station estimates the request service information of all the UEs according to the QoE mapping relationship of the video service, such as the service optimal experience quality ^Qq provided by the video service X to the UE, and the worst experience quality of the service provided by the video service X to the UE ^Qq .

The QoE mapping relationship of the video service X in this embodiment is a mapping relationship between the transmission rate of the video service X and QoE.

S03. The base station acquires all services under different services according to the user information and the requested service information.

The membership function value of the UE.

For example, the membership function values of all UEs under different services are obtained according to the foregoing formula (1).

S04. The base station establishes, according to the user information, the request service information, the QCI priority, and the membership function value, a scheduling decision formula for scheduling and resource allocation of the UE, and scheduling the UE according to the scheduling decision formula. Resource allocation. Optionally, the base station performs access control on the UE according to the availability of the radio channel resource.

From the above, the method of resource allocation realizes the basic consistency of the user experience quality of all UEs under different services under the condition of limited resources of the OFDM system.

The VoIP, IPTV, and FD services are used as an example to perform scheduling and resource allocation for UEs of the three services to ensure QoE-based UEs in different services.

Currently, MOS is a general metric that reflects the UE's QoE. In the following description, the UE's QoE can be given by MOS.

It is assumed that there is a one-to-one mapping relationship between QoE and transmission rate of UEs under different services. This relationship can be obtained by establishing a prediction model, which is the prediction model shown in the following formula (3).

QoE _k = ^ (R _k ) ( 3 ) In formula (3 ), the number of the UE, which is the service identifier, is the average transmission rate of UE _k , and 7 (·) indicates the transmission rate and QoE of UE _k under service. The mapping relationship between QoE and the quality of experience of UE _k under the service.

According to the above formula (3), the base station establishes three services of VoIP, IPTV and FD respectively. The mapping relationship between QoE and transmission rate is shown in Figure 4, Figure 5 and Figure 6.

In the IPTV service, the mapping relationship between the QOE of the UE and the transmission rate can be as a formula.

(4) As shown.

a _x + a ₂ FR + a ₃ ln(R)

l + a ₄ PER + a ₅ (PER)

(4) In equation (4), _ι ~« ₅ is a mapping parameter based on different video types (including light motion type video, slow motion type video, and fast motion type video), FR (Frame Rate) is the frame rate. PER (Package error rate) is the packet loss rate and R is the transmission rate. This embodiment only considers fast motion type video, and sets the FR to 10 frames per second and the PER to 0.

FIG. 4 shows the QoE and the transmission rate of the UE of the fast motion type video in the IPTV service. The mapping relationship between the QoE and the transmission rate of the UE may be as shown in the following formula (5).

Where, "=2.3473, ^=0.2667, at this time, the mapping relationship between the QoE of the UE and the transmission rate is as shown in FIG. 5.

For VoIP services, the QoE and rate curves of VoIP services at different coding rates are shown in Figure 6. In Figure 6, four points represent four coding rates, 6.4 kbps, 15.2 kbps, 24.6 kbps, and 64 kbps.

In addition, in this embodiment, a simulation description of the OFDM-based communication system is performed.

Assume that the base station has a transmit power of 40 W and a cell coverage radius of 1000 m. Fifteen UEs are evenly distributed within the coverage.

The UEs numbered 1 to 4 are UEs in the FD service, and the minimum rate requirement is set to

_32kbps; numbered UE 5 ~ 10 for the UE in IPTV services, which is set to 128kbps minimum rate requirements; number of UE 11 ~ 15 for the UE under the VoIP service, which is set to the minimum rate requirements of 5.9kbps.

The large-scale fading model is based on the 3GPP (The 3rd Generation Partnership Project) protocol. The communication system bandwidth is 10 MHz, and the number of PRBs (resource block pairs) is 50, and each PRB. Contains 12 subcarriers with a subcarrier spacing of 15 kHz.

To explain the advantages of the resource allocation method provided in the embodiment of the present invention, the resource allocation method provided by the embodiment of the present invention is compared with the PF scheduling algorithm and the maximum and minimum MOS scheme.

Since the PF scheduling algorithm considers the priority relationship of different services, the maximum and minimum MOS scheme maximizes the minimum MOS score based on the PF scheduling algorithm, so that the MOS scores of different UEs are approximately the same.

However, the maximum and minimum MOS schemes are susceptible to the aforementioned prediction models. Each type of service can construct multiple prediction models. The mapping relationship between QoE and transmission rate of MOS points under different prediction models is different.

The resource allocation method provided in the embodiment of the present invention effectively removes the influence of the prediction model by adopting the concept of membership function values.

For better description, FIG. 7 is a schematic diagram showing comparison of MOS points of UEs in three services provided by an embodiment of the present invention. It can be seen from the simulation results in Figure 7:

The PF scheduling algorithm cannot guarantee that the QoE of all UEs under different services is maintained at a high level.

The maximum and minimum MOS schemes reduce the difference between the MOS points of different UEs in the same service. However, compared with the resource allocation method provided by the embodiment of the present invention, the floating range of the MOS points between different UEs is still large.

In the resource allocation method provided by the embodiment of the present invention, the QoE of all UEs is maintained at a high level, and the QoEs of the UEs in the same service are approximately equal. As can be seen from FIG. 7, the number of 1-4 UEs (UEs using FD services) is approximately 3, and the numbers of 5 to 10 (UEs using IPTV services) are approximately 3.5, and the numbers are 11-15. The UE (UE using VoIP service) has a MOS score of approximately 4. In the resource allocation scheme in this embodiment, the distribution of different service MOS values is related to the parameter QCI priority in the scheduling decision formula (2).

In addition, FIG. 8 shows a distribution diagram of the membership function values of the UE under the three services provided in the embodiment of the present invention, and the membership function value reflects the satisfaction degree of the UE to the QoE obtained by the UE. The larger the value of the membership function, the more satisfactory the UE is to the current resource allocation. It can be seen from FIG. 8 that the resource allocation method provided by the embodiment of the present invention is consistent with the PF scheduling algorithm and the maximum and minimum MOS scheme, and the QoE satisfactions of different UEs in the same service are relatively consistent.

In addition, taking the IPTV service as an example, scheduling and resource allocation for the UE under the IPTV service Match. For IPTV services, only fast motion type video is considered, and the FR is set to 10 frames per second, and the PER is set to 0. The relationship between the QoE and the transmission rate of the UE of the fast motion type video in the IPTV service is as shown in FIG. 4 .

Accordingly, it is assumed that the base station has a transmit power of 40 W and a cell coverage radius of 1000 m. 15 UEs are evenly distributed within the coverage. The UE minimum rate requirement is set to 128 kbps. The large scale fading model is based on the 3GPP protocol. The system bandwidth is 10 MHz, the number of physical resource blocks (Physical Resource Blocks; hereinafter referred to as PRBs) is 50, and each PRB contains 12 subcarriers with a subcarrier spacing of 15 kHz.

At this time, as shown in FIG. 9 and FIG. 10, FIG. 9 is a schematic diagram showing the distribution of MOS points of the UE under the IPTV service in the embodiment of the present invention, and FIG. 10 is a schematic diagram showing the distribution of the membership function values of the UE under the IPTV service. The PF scheduling algorithm cannot guarantee that the QoE of all UEs is maintained at a high level. In the resource allocation method provided by the embodiment of the present invention, the QoE of all UEs is maintained at a high level, and the QoE of the UE is approximated. equal. Although the maximum and minimum MOS scheme can reduce the floating range of the user group MOS score, the resource allocation method provided by the embodiment of the present invention can make the floating range of the MOS score narrower by adjusting the value of the parameter n in the scheduling decision formula (2). .

According to another aspect of the present invention, an embodiment of the present invention further provides a resource allocation apparatus. As shown in FIG. 11, the resource allocation apparatus in this embodiment includes: a memory 011 and a processor 012, where the memory 011 For storing the program including the processor 012, the processor 012 is configured to execute the program according to the instruction, and specifically includes:

Obtaining a membership function value of all UEs in different services according to the user information and the request service information; and performing, according to the user information, the request service information, the QCI priority level and the membership function value, to the UE Scheduling and resource allocation.

Optionally, the processor is specifically configured to establish, according to the user information, the request service information, the QCI priority, and the membership function value, a scheduling decision formula for scheduling and resource allocation of the UE, and The UE is scheduled and resource allocated according to the scheduling decision formula.

For example, the foregoing user information may include: geographic location information of the UE, a maximum data rate of the UE at the current moment, an average throughput of the UE in the communication system, and a current time of the UE at the current moment. 1, if QoE^ > QoE ⁺ _x

QoE, -QoE- if QoE _x ≤ QoE _k ≤ QoE

QoE -QoEj

0, if (3οΕ ≤(3οΕ: _γ)

Obtaining the membership function values of all UEs in different services according to the formula; wherein, the current service X provides the optimal QoE of the service to the UE,

^{Qc) E} ^ is the worst QoE of the service provided by the current service X to the UE,

QoE _k is the QoE of the kth UE at the current time, and is the membership function value of the kth UE under the current service X. In another optional implementation scenario, the processor 012 is specifically configured to establish, according to the user information, the request service information, the QCI priority, and the membership function value, scheduling and resources for the UE. Assigned scheduling decision formula

= arg _max < exp

QCI,

Scheduling and resource allocation for each UE according to a scheduling decision formula;

Where k 2 ..., κ,

^ is the membership function value of the kth UE under the current service X;

QCI _pn is the QCI priority of the _kth UE; K represents the number of UEs, The denominator W represents the average throughput of the kth UE; the numerator (0 is the maximum data rate of the current time t. For example, the foregoing service may be: Internet Protocol Television IPTV Service, File Download FD Service or VoIP Phone VoIP Service.

The resource allocation apparatus in this embodiment can achieve the same QoE of users corresponding to all UEs in different services in the OFDM wireless communication system.

According to still another aspect of the present invention, an embodiment of the present invention further provides a resource allocation apparatus. As shown in FIG. 12, the resource allocation apparatus in this embodiment includes: a first acquiring unit 021, a second acquiring unit 022, and scheduling. Unit 023:

The first obtaining unit 021 is configured to obtain user information of all user equipment UEs under the current service, request service information, and obtain QCI priorities of services in all services.

The second obtaining unit 022 is configured to obtain, after the first acquiring unit 021 acquires the user information and the request service information, the membership function values of all UEs in different services according to the user information and the request service information;

The scheduling unit 023 is configured to: after the second obtaining unit 022 acquires the membership function value, perform scheduling on each UE according to the user information, the request service information, the QCI priority, and the membership function value. And resource allocation.

Optionally, the scheduling unit 023 is specifically configured to: establish, according to the user information, the request service information, the QCI priority, and the membership function value, a scheduling decision formula for scheduling and resource allocation of the UE, and The UE is scheduled and resource allocated according to the scheduling decision formula.

For example, the user information includes: geographic location information of the UE, a maximum data rate of the UE at the current moment, an average throughput of the UE in the communication system, and a QoE of the UE at the current moment;

In an optional implementation scenario, the foregoing second obtaining unit 022 may be specifically configured to use, > QoE ⁺ _x

< QoE _k ≤ QoE

QoE

According to the formula

Obtaining a membership function value of all UEs in different services; where ^Q ° is the optimal QoE of the service provided by the current service X to the UE,

^QoE - the worst QoE of the service provided to the UE for the current service X,

QoE _k is the QoE of the kth UE at the current moment,

[e^J is the membership function value of the kth UE in the current service X. In another optional implementation scenario, the foregoing scheduling unit 023 may be specifically configured to: according to the user information, the request service Information, the QCI priority, and the membership function value, establishing a scheduling decision formula for scheduling and resource allocation of the UE

- "[e.3⁄4] exp W]

k ^{= ar} gmax

Q ) R _t (t)

Scheduling decision formula

Scheduling and resource allocation for each UE;

Wherein, k = \, ~, κ , for the current service X k th UE Dir membership function value; n is used to control the membership function value for the entire weight of the heavy scheduling decision QC'I _p _"k th. The QCI priority of the UE; K indicates the number of UEs, and the denominator ^W indicates the average throughput of the kth UE; numerator (0 is the maximum data rate of the current time t. For example, when the current service is video service X,

Obtaining request service information of all user equipment UEs in the current service, including: Estimating the service optimal experience quality ^QQ provided by the video service X to the UE and the service worst experience quality Q provided by the video service X to the UE according to the QoE mapping relationship of the video service X. E _X. Wherein, the QoE mapping relationship between video service X for a transmission rate of the video service X to the QoE mapping relationship.

For example, the service can be: IPTV service, FD service or VoIP service.

The resource allocation device in this embodiment may be located in the base station, or located in the gateway, or in other core network devices.

A person skilled in the art can understand that all or part of the steps of implementing the above method embodiments may be completed by using hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, and the program is executed when executed. The foregoing steps include the steps of the foregoing method embodiments; and the foregoing storage medium includes: a medium that can store program codes, such as a ROM, a RAM, a magnetic disk, or an optical disk.

A person skilled in the art can understand that the drawings are only a schematic diagram of a preferred embodiment, and the modules or processes in the drawings are not necessarily required to implement the invention.

Those skilled in the art can understand that the modules in the apparatus in the embodiments may be distributed in the apparatus of the embodiment according to the embodiment description, or the corresponding changes may be located in one or more apparatuses different from the embodiment. The modules of the above embodiments may be combined into one module, or may be further split into a plurality of sub-modules.

It should be noted that the above embodiments are only for explaining the technical solutions of the present invention, and are not intended to be limiting; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that: The technical solutions described in the foregoing embodiments are modified, or some of the technical features are equivalently replaced; and the modifications or substitutions do not deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

Claim

A resource allocation method, characterized in that it comprises:

The method according to claim 1, wherein the scheduling, resource allocation, and the resource allocation are performed according to the user information, the request service information, the QCI priority, and the membership function value, including :

The method according to claim 1 or 2, wherein the user information comprises:

The method according to claim 3, wherein the obtaining the membership function values of all the user equipments in different services according to the user information and the request service information includes:

1, if QoE^ > QoE

QoE _t -QoE- iQ E _k ]= If QoE _x ≤ QoE^≤ QoE

QoE÷ -QoEj

0, if QoE _k ≤ QoE"

Obtaining the membership function values of all the UEs according to the formula; wherein, the service optimal QoE Q ^Q provided to the UE for the current service X is the worst QoE of the service provided by the current service X to the UE, QoE _k is the QoE of the kth UE at the current moment,

"[e^J is the membership function value of the kth UE under the current service X.

The method according to claim 4, wherein the scheduling and resource allocation are performed on the UE according to the user information, the request service information, the QCI priority, and the membership function value, including :

^{= ar} gmax ^w *

^ = arg _max exp should

QCI

Where k = l " , κ,

"[β^ ^ is the membership function value of the kth UE under the current service X;

^{Qa pTM} " is the QCI priority of the kth UE;

K represents the number of UEs, and the denominator represents the average throughput of the kth UE; numerator ₍ 0 is the maximum data rate of the current time t.

The method according to claim 3, wherein, when the current service is a video service,

Obtain the request service information of all UEs in the current service, including:

7. The method according to any one of claims 1 to 5, characterized in that said all industries Services include: Internet Protocol TV IPTV service, file download FD service and VoIP service.

A resource allocation apparatus, comprising: a memory and a processor, wherein the memory is configured to store an instruction including the processor executing a program, and the processor is configured to execute a program according to the instruction, specifically Includes:

The device according to claim 8, wherein the processor is specifically configured to be used in

10. The apparatus according to claim 8 or 9, wherein the user information comprises:

Geographical location information of the UE, the maximum data rate of the UE at the current time, the average throughput of the UE in the historical moment of the communication system, and the QoE of the UE at the current time;

The device according to claim 10, wherein the processor is specifically configured to:

1, if QoE^ > QoE

QoE. -QoE"

MiQoE _k ] If QoE _x ≤ QoE^≤ QoE:

QoE^-QoEj

0, if QoE^ QoE

Obtaining the membership function values of all UEs according to the formula, wherein the current service X provides the optimal QoE of the service to the UE, ^Qq is the worst QoE of the service provided by the current service X to the UE,

QoE _k is the QoE of the kth UE at the current time, and is the membership function value of the kth UE under the current service X.

12. The device according to claim 1, wherein the processor is specifically configured to be used according to

^{= ar} gmax ^w *

According to the dispatch decision

The formula performs scheduling and resource allocation for each UE;

Where ι,···, κ is the membership function value of the _kth UE under the current service X; n is a weight parameter for controlling the membership function value to determine the entire schedule; QCl _pnOTty is the _kth UE QCI priority; K represents the number of UEs, the denominator represents the average throughput of the _kth UE; numerator ₍ 0 is the maximum data rate of the current time t.

The device according to any one of claims 8 to 12, wherein the current service is: an internet protocol television IPTV service, a file download FD service, or a network telephone VoIP service.