CN106507485A - A quality-of-service-oriented wireless layered multicast transmission resource allocation method - Google Patents

Abstract

Consider that the complexity in practical application requires that the present invention realizes a kind of low complex degree resource allocation algorithm based on greedy method.Consider between multicast user to require the difference of QoS in practical application, using layered multicast, data source is divided into Primary layer and enhancement layer.Algorithm is adopted and conventional two-step identical assignment order, as different layers adopt different resource allocation algorithms, meet the minimum-rate requirement of Primary layer multicast service first by subcarrier distribution, and then adjustment surplus power gives enhancing layer service between all subcarriers, with improve enhancement layer multicast service and speed, so as to effectively reduce algorithm complex.Finally according to the algorithm that realizes, reasonable systematic function is obtained in Primary layer and enhancement layer.

Description

A quality-of-service-oriented wireless layered multicast transmission resource allocation method

technical field

The present invention relates to the technical field of wireless communication, in particular to an Orthogonal Frequency Division Multiplexing (OFDM, Orthogonal Frequency Division Multiplexing) layered transmission system

Background technique

In recent years, the rapid development of mobile communication technology has provided higher and higher rates for human communication. Since the core network of the 3G system has not completely separated from the core network structure of the second-generation mobile communication system, it is generally believed that the 3G system is only a transition from narrowband to future broadband mobile communication system. Therefore, people pay more and more attention to the mobile communication system after 3G, and the speed of the system in LTE mobile communication can reach 100 Mbps at present. The future mobile communication system will provide greater bandwidth, combine wireless communication with the Internet, and multimedia communication, and expand mobile communication services from voice to multimedia services such as data, images, and videos. The combination of wireless communication, Internet and multimedia communication must be the trend of the times.

With the breakthrough of wireless network technology and the rapid development of Internet services, people hope that wireless networks can carry diversified broadband multimedia services. Due to its unique ability to resist frequency selective fading and intersymbol interference, OFDM technology can effectively improve the spectrum utilization rate of the system and achieve high-speed transmission. It has become one of the core technologies of the next generation wireless network. Considering the importance of multicast services in wireless networks, how to provide QoS (Quality of Service) support for users with different needs through effective wireless resource management in the next-generation OFDM-based network, It is a problem that urgently needs to be studied. This resource allocation algorithm realizes a multicast joint resource allocation scheme in an OFDM system according to the QoS requirements of different users.

At present, the LTE system has been commercialized, and people's demand for high-speed data transmission is also increasing day by day, but the current wireless resources cannot fully meet the requirements of all users. Therefore, according to the channel situation of the user and its QoS requirements, layering the transmission data will effectively improve the user experience. In layered multicast, the sender encodes the data source into multiple data streams in a layered coding manner, which are divided into basic layer and enhanced layer, and transmits data streams of different layers in multiple multicast groups. Receivers can receive data streams at different rates by choosing to receive data of different layers from the basic layer to the enhanced layer according to their own receiving capabilities.

According to the different QoS requirements of the base layer and enhancement layer transmission, the resource allocation problem is modeled as the allocation problem of maximizing the enhancement layer and the rate under the condition of ensuring the minimum rate required by the base layer transmission. The basic idea of the low-complexity algorithm used in the present invention is to firstly satisfy the minimum rate requirement of the basic layer through the least subcarrier allocation, and then assign the remaining unallocated subcarriers to users (also known as enhancement layers) with stronger channel gain. may be multiple users), and finally adjust the power to increase the sum rate of the enhancement layer.

Contents of the invention

Considering the complexity requirements in practical applications, the present invention implements a low-complexity resource allocation algorithm (hereinafter referred to as the greedy algorithm) based on a greedy method. This algorithm adopts the same allocation order as the traditional two-step method. The distribution meets the minimum rate requirement of the basic layer multicast service, and then adjusts the excess power among all subcarriers to the enhancement layer service to increase the sum rate of the enhancement layer multicast service, thereby effectively reducing the complexity of the algorithm.

The principle of the greedy algorithm is to try to find the best choice as close as possible to the target each time, and then solve the sub-problems brought about by the choice. This choice depends on the current choice, not on future choices or sub-problems. The solution is actually a local optimal choice. It is hoped that this choice can lead to the global optimal solution. If the local optimal solution is exactly equal to the global optimal solution at the end of the algorithm, this method is optimal, otherwise, a suboptimal solution is obtained. When performing optimal search, the greedy algorithm is more inclined to search along a selected path until the optimization goal is achieved. When the selected path cannot reach the optimization goal, it will return; it may also search along an infinite path, and There is no fallback to try other paths, so the algorithm cannot guarantee an optimal solution every time, nor is it complete.

If there is a good heuristic function, the complexity of the algorithm is significantly reduced, and the magnitude of the decrease depends on the specific problem and the quality of the heuristic function.

The algorithm first allocates subcarriers for basic layer multicast services, divides the allocation process into multiple steps, and allocates a subcarrier in each step. In order to meet the minimum rate requirement of the basic layer with as few sub-carriers as possible, the sub-carrier allocation criterion for each step is: select the sub-carrier that can increase the multicast rate of the basic layer the most, until the multicast service of the basic layer gets enough Subcarriers that can meet their minimum rate requirements. After determining the subcarrier allocation of the basic layer, in order to increase the sum rate of the multicast service of the optimization target enhancement layer, the remaining subcarriers in the system are allocated to users with the best channels.

Beneficial effect

Aiming at the current situation where OFDM multicast resource allocation is mainly studied and data layering is not used to achieve different user QoS requirements, the present invention studies the joint allocation scheme for hierarchical transmission of OFDM multicast wireless resources, that is, dynamic subcarriers and transmission power Joint distribution scheme. Finally, according to the implemented algorithm, the simulation is carried out, and a relatively good system performance is obtained in both the basic layer and the enhanced layer.

Considering the different requirements for QoS among multicast users in practical applications, the present invention adopts layered multicast, divides data sources into basic layer and enhanced layer, and solves resource allocation problem It is modeled as the allocation problem of maximizing the enhancement layer and the rate under the condition of guaranteeing the minimum rate required by the base layer transmission. Since different layers adopt different resource allocation algorithms, the minimum rate requirement of the system is first met, and as many subcarriers as possible are allocated to the enhancement layer services to maximize the sum rate.

Description of drawings

Figure 1 is a scene diagram of layered multicast transmission;

Fig. 2 is the algorithm implementation flowchart of the present invention;

Figure 3 is the relationship curve between the minimum rate of the basic layer and the minimum rate requirement R0 _;

Fig. 4 is the relationship curve of the enhancement layer and the rate and the minimum rate requirement R ₀ .

detailed description

The implementation cases of the present invention are described in detail in conjunction with the accompanying drawings.

Considering the complexity requirements in practical applications, the present invention implements a low-complexity resource allocation algorithm (hereinafter referred to as the greedy algorithm) based on a greedy method. This algorithm adopts the same allocation order as the traditional two-step method. The allocation meets the minimum rate requirements of the basic layer multicast service, and then adjusts the excess power among all subcarriers to the enhancement layer service to increase the sum rate of the enhancement layer multicast service. In the allocation process, the allocation based on the greedy method is adopted way, thereby effectively reducing the complexity of the algorithm.

Accompanying drawing 1 is the system framework and scene of example application, the OFDM system studied by the present invention is composed of a base station and K user terminals, and the total number of subcarriers of the system is N. The downlink between the base station and the user is a slow fading frequency selective channel. Assuming that the base station can obtain the channel gain H _k,n of user k on subcarrier n through user feedback, then the channel capacity of user k on subcarrier n is

in, is the noise power on subcarrier n, and p _n is the power allocated on subcarrier n.

In order to ensure that all users in the system can reliably receive multicast data, the base station sets the rate at which all users can reliably receive multicast services The minimum value in is to send multicast data, that is, the multicast rate is

In practical applications, in order to ensure QoS, the multicast service has a certain minimum rate requirement, namely:

R ^(m) ≥ R ₀ (3)

Among them, R ₀ is the lower limit of the rate required by the multicast service.

For the enhanced layer multicast service in the system, the rate of the enhanced layer user k on the allocated subcarrier is

in Subcarrier allocation coefficients for enhancement layer multicast services, Indicates that subcarrier n is allocated to user k to transmit multicast services, and vice versa

To sum up, when considering the basic layer and enhanced layer multicast services at the same time, the optimization goal of OFDM system resource allocation studied in this paper is to make all The sum rate of the enhancement layer user multicast service is the largest, that is, the objective function is:

Restrictions:

Among them, formula (6) is the minimum rate requirement of the multicast service, formula (7) is the power constraint of the system, _PT is the total power; formula (8) is the constraint condition of subcarrier allocation, that is, any subcarrier can only use It is used to transmit the multicast service of the basic layer or the multicast service of the enhanced layer.

Fig. 2 is a flow chart of the implementation of the algorithm of the present invention. The algorithm first allocates subcarriers for basic layer multicast services, divides the allocation process into multiple steps, and allocates a subcarrier in each step. In order to meet the minimum rate requirement of the basic layer with as few sub-carriers as possible, the sub-carrier allocation criterion for each step is: select the sub-carrier that can increase the multicast rate of the basic layer the most, until the multicast service of the basic layer gets enough Subcarriers that can meet their minimum rate requirements. After determining the subcarrier allocation of the basic layer, in order to increase the sum rate of the multicast service of the optimization target enhancement layer, the remaining subcarriers in the system are allocated to users with the best channels.

The specific steps of the subcarrier allocation algorithm are as follows.

S200. Set all subcarrier allocation coefficients ρ _n =0.

S210, traversing all subcarriers to be allocated satisfying ρ _n =0, and for any subcarrier n among them, calculating the multicast rate that can be obtained if the subcarrier is allocated to the basic layer is

From all subcarriers n to be allocated, select the corresponding multicast rate R _n , the largest subcarrier

n ^* ＝arg _n maxR _n , n∈{ρ _n ＝0}, (10)

Assign n ^* to the multicast service, set

S220, if R _n ≤ R ₀ , return to step 2, and continue to select subcarriers allocated to the base layer; otherwise, execute S230.

S230. Allocate all subcarriers satisfying ρ _n =0 to the enhancement layer multicast service, and allocate subcarrier n to one user or multiple users with the best channel conditions on the subcarrier. Arrange the rates of each user in descending order as c _1,n ,c _2,n ...,c _k,n , if allocated to the best user, then k=1,R _n =c _1,n . If assigned to the best two users, then k=1,2, R _n =2*c _2,n , and so on.

{k ^* }=arg _{k} maxR _n , n∈{ρ _n =0}, (11)

place Algorithm ends.

On the basis of determining the allocation of subcarriers, by adjusting the power between subcarriers, the sum rate of the enhancement layer can be further improved while meeting the minimum rate requirement of the base layer. The power adjustment is divided into two steps. First, under the premise of ensuring the basic rate of the basic layer multicast service, reduce the power allocated to the subcarriers of the basic layer multicast service; and then allocate this part of power to the enhancement layer multicast service. The power allocation allocated to the enhancement layer subcarriers is readjusted according to the water filling principle. When adjusting the power on the subcarriers allocated to the basic layer multicast service, consider that the power adjusted each time is a small amount

Among them, N is the number of subcarriers, M is any positive integer, which determines the granularity of the power adjustment amount, is the total power on the subcarriers allocated to the multicast service, and its initial value is

S240, reduce the power of the basic layer multicast service, and among all the subcarriers allocated to the basic layer, select the solution with the highest corresponding multicast rate after reducing the power, that is, select the subcarrier

n ^* ＝arg _n maxR _n , n∈{ρ _n ＝1}, (14)

Reduce the power Δp on this subcarrier:

Repeat this step to reduce the power in the set of subcarriers allocated to the base layer, so that the multicast rate of the base layer satisfies R _n > R ₀ while continuously decreasing until it is close to (or equal to) the minimum rate requirement. Compared with the original equal power allocation, the power saved after adjusting the power allocation of the basic layer multicast service is

This part of the power is allocated to the enhancement layer multicast service. Considering the initial equal power allocation of the subcarriers, the total power of the enhancement layer is

For the users of the enhancement layer, the power allocation algorithm that pursues the maximum and the best rate is adopted, while taking into account the proportional fairness among the users of the enhancement layer.

Figure 3 compares the change of the corresponding normalized basic layer multicast rate when the minimum rate requirement R ₀ of the multicast service increases gradually. In order to facilitate the judgment of the degree of satisfaction of the constraints, the base layer rate given in the simulation results is normalized according to the required minimum rate, which is the ratio of the base layer rate to the minimum rate R ₀ . In Fig. 3, the signal-to-noise ratio SNR=5dB, the total number of users K=16, and the minimum rate requirement increases from 50kbps to 170kbps. For the fixed ratio allocation algorithm, because the ratio of resource allocation is given in advance, the change of the multicast minimum rate requirement will not have any impact on the multicast rate, and its multicast rate remains unchanged, so the normalization in Figure 3 The unified multicast rate decreases monotonically as the minimum rate requirement increases. For the greedy algorithm, when the minimum rate requirement is small, the algorithm can meet the requirement through subcarrier allocation and power allocation, so that the normalized multicast rate in Figure 3 remains near 1; and when the minimum rate increases to the point where the system resources are not enough to meet When this requirement is met (on the x-axis of Figure 3: the minimum rate requirement is >120 kbps), the algorithm cannot allocate resources that meet its requirements for the basic layer, so that the normalized multicast rate drops below 1.

Figure 4 compares the multicast and rate changes of the corresponding enhancement layer when the minimum rate requirement R ₀ of the multicast service increases gradually. Among them, for the fixed ratio allocation algorithm, since the ratio of resource allocation is predetermined, the change of the multicast minimum rate requirement will not have any impact on the multicast rate, so the sum rate of the enhancement layer is fixed. . To sum up, the greedy-like algorithm allocates as many subcarrier resources as possible to the enhancement layer services on the basis of ensuring the basic layer services, in order to maximize the sum capacity; even if the minimum rate requirements of the basic layer services cannot be met In this case, the business of the enhancement layer will be abandoned. The fixed ratio algorithm can only analyze the data flow and channel conditions in advance to set the allocation ratio coefficient. Although the algorithm is simple, it cannot adapt to the different QoS requirements of the basic layer and the enhancement layer.

Claims (4)

1. The present invention takes into account the different requirements for QoS among multicast users in practical applications, and adopts hierarchical multicast to propose a joint allocation scheme for hierarchical transmission of OFDM multicast wireless resources, that is, joint allocation of dynamic subcarriers and transmit power solution to meet the QoS requirements of different users. 2. The present invention adopts adaptive resource allocation technology in the multicast resource allocation process, considers the different requirements to QoS among the multicast users in the actual application, adopts layered multicast, at first the data of transmission is carried out layering, is divided into base layer and enhancement layer. 3. In view of the different QoS requirements for the transmission of the base layer and the enhancement layer, the present invention models the resource allocation problem as an allocation problem of maximizing the enhancement layer and the rate under the condition of ensuring the minimum rate required for the transmission of the base layer. 4. In order to reduce the complexity, the present invention carries out the low-complexity resource allocation algorithm design of different layers based on the greedy algorithm, and its basic idea is to first meet the minimum rate requirement of the basic layer through subcarrier allocation, and then adjust the power between all subcarriers To increase the sum rate of the enhancement layer.