CN106712817B - Low-complexity pilot frequency distribution method based on user exchange - Google Patents

Abstract

The present invention relates to a low-complexity pilot frequency allocation method based on user switching, which can achieve system performance basically consistent with the exhaustive traversal method with low complexity, effectively reduce the influence of pilot frequency pollution, and can use Lower complexity maximizes system and rate performance while taking into account the fairness among users, which is more beneficial to real-world applications due to the lower complexity of the method.

Description

A low-complexity pilot allocation method based on user switching

technical field

The invention relates to a low-complexity pilot frequency allocation method based on user switching, and belongs to the technical field of communication systems.

Background technique

Pilot contamination is a widely studied problem in Massive MIMO systems. It is an interference problem caused by users sharing pilots and generally occurs in TDD mode in Massive MIMO systems. In the TDD mode, the uplink and downlink channels are reciprocal, so the channel estimated in the uplink can be used as the channel for downlink transmission. Since both the transmission of pilots and the transmission of information are performed within the coherence time of the channel, the length of the pilots is limited, which limits the number of available pilots in the system, thus making it inevitable that adjacent cells will be separated from each other. The pilot frequency is reused, and the pilot frequency pollution has become an unavoidable problem in Massive MIMO.

The pilot allocation with the optimization goal of maximizing the user rate product can effectively reduce the influence of pilot pollution, and can maximize the system and rate while taking into account the fairness among users. However, the traditional method to solve the optimization problem is the method of exhaustive traversal, which means to traverse all the possibilities of pilot allocation, and select the pilot allocation scheme with the largest user rate product. This scheme can achieve the optimal solution to the problem, but it is extremely complicated to implement.

Another greedy-based pilot allocation method can solve the optimization problem with lower complexity. A combination with the largest rate product is used as the optimal solution for this iteration, and then the selected users are removed from the system, and the iteration is continued until all users have been allocated pilot frequencies. But this greedy-based allocation strategy can only achieve locally optimal performance.

SUMMARY OF THE INVENTION

Aiming at the pilot frequency allocation problem where the optimization objective is to maximize the system user rate product, the present invention proposes a pilot frequency allocation method based on user exchange.

This method can achieve almost the same system performance as the exhaustive traversal method, but the implementation complexity is greatly reduced, which is more conducive to practical applications.

The technical scheme of the present invention is:

A low-complexity pilot frequency allocation method based on user switching, suitable for a Massive MIMO system, the Massive MIMO system includes L equivalent hexagonal cells, each cell includes 1 central base station and K users, 1 Each central base station serves K users at the same time, the users in the same cell use mutually orthogonal pilots, the users in the cells reuse pilots, and the number of pilots available for allocation in the Massive MIMO system is K. Specifically Steps include:

i，j∈[1，2，…，L]，k∈[1，2，…，K]，

是指i小区中的用户k到j小区中的中心基站的大尺度衰落因子；(1) According to the distance from the user to the central base station, obtain the large-scale fading information from each user in each cell in the Massive MIMO system to each central base station

i, j∈[1,2,…,L], k∈[1,2,…,K],

refers to the large-scale fading factor of the central base station in the user k in the i cell to the j cell;

(2) Construct an objective function for the pilot allocation problem, the objective function max U(P) is to maximize the product of the rates of all users in the Massive MIMO system, as shown in formula (I):

In formula (I), is the rate of the user using the kth pilot in cell l, l∈[1, 2,...,L],

是指l小区中的用户k到j小区中的中心基站的大尺度衰落因子； refers to the large-scale fading factor from user k in cell l to the central base station in cell l;

refers to the large-scale fading factor of user k in cell l to the central base station in cell j;

(3) Use the greedy strategy to select a pilot group with the largest user rate product each time, and iterate K times to complete the pilot assignment as the initial pilot group;

The set of users using the same pilot is a pilot group, and the users in each pilot group are from different cells, and P _k represents the pilot group using pilot K; there are K pilot groups in the Massive MIMO system, That is, P ₁ , P ₂ , ..., P _K , there are L users in each pilot group;

(4) Starting from the initial pilot group obtained in step (3), users are exchanged between the pilot groups: if the user exchange between the two pilot groups, the user rate product is greater than the user rate product before the exchange , exchange is performed, otherwise, no exchange is performed until all pilot groups complete user exchange.

Preferably according to the present invention, the step (3), the specific steps include:

A, randomly select a user from each cell, and obtain the rate product of the selected L users;

B, L users corresponding to the maximum value of the rate product obtained in step A are used as pilot frequency group P ₁ ;

C. According to the methods of steps A and B, from the remaining users, obtain pilot frequency groups P ₂ , . . . , P _k , . . , P _K in turn;

D. The obtained pilot frequency groups P ₁ , P ₂ , . . . , _PK are taken as the initial pilot frequency group states.

Preferably according to the present invention, the step (4), the specific steps include:

_E. The pilot frequency groups P ₁ , P ₂ , .

F. Set the iteration counter l, and initialize l=1;

G. The user exchange in the 1 cell is performed between any two pilot groups: if the user rate product is greater than the user rate product before the exchange after the user exchange, the exchange is performed, otherwise, the exchange is not performed;

H. Determine whether l is equal to L, if yes, end, otherwise, add 1 to l, and return to step G.

The beneficial effects of the present invention are:

1. The present invention realizes a pilot frequency allocation scheme that takes into account both system effectiveness and fairness by maximizing the product of the user rates of the system. Compared with the existing pilot frequency allocation scheme, the pilot frequency allocation scheme considered by the present invention not only maximizes the overall performance of the system, but also takes into account the fairness among users.

2. The present invention can realize the system performance basically consistent with the exhaustive traversal method through a pilot frequency allocation method based on user switching. Compared with the exhaustive traversal method, the pilot frequency allocation method based on user switching has lower complexity. In the L cells used in the present invention, in the system model of K users in each cell, when the exhaustive method is used, (K!) ^L-1 times of traversal are required, but the pilot frequency allocation method based on user exchange only needs to perform traversal and User exchanges, where n is the number of rounds used for exchange, which greatly reduces the complexity of the system.

Description of drawings

1 is a block diagram of the implementation steps of a pilot frequency allocation method based on user switching in the present invention;

Fig. 2 is the simulation effect diagram of system user rate product when n=1 in the embodiment;

FIG. 3 is a simulation effect diagram of the system user rate product when n=2 in the embodiment.

Detailed ways

The present invention is further defined below with reference to the accompanying drawings and embodiments of the description, but is not limited thereto.

Example

A low-complexity pilot frequency allocation method based on user switching, suitable for Massive MIMO system, the Massive MIMO system is shown in Figure 1, including 3 equivalent hexagonal cells, each cell includes 1 central base station And 5 users, 1 central base station serves 5 users at the same time, the system model diagram simply describes the configuration of cell users and central base stations in the system. It can be seen from the model diagram that due to sharing the same pilot frequency, the base station will simultaneously receive the pilot frequency information that interferes with each other during uplink pilot frequency estimation, and this mutual interference will cause pilot frequency pollution; the specific steps include:

i，j∈[1，2，…，L]，k∈[1，2，…，K]，是指i小区中的用户k到j小区中的中心基站的大尺度衰落因子；(1) According to the distance from the user to the central base station, obtain the large-scale fading information from each user in each cell in the Massive MIMO system to each central base station

i, j∈[1,2,…,L], k∈[1,2,…,K], refers to the large-scale fading factor of the central base station in the user k in the i cell to the j cell;

(2) Construct an objective function for the pilot allocation problem, the objective function max U(P) is to maximize the product of the rates of all users in the Massive MIMO system, as shown in formula (I):

为l小区中使用第k个导频的用户的速率，l∈[1，2，…，L]，In formula (I),

is the rate of the user using the kth pilot in cell l, l∈[1, 2,...,L],

是指l小区中的用户k到l小区中的中心基站的大尺度衰落因子；

是指l小区中的用户k到j小区中的中心基站的大尺度衰落因子；

refers to the large-scale fading factor from user k in cell l to the central base station in cell l;

refers to the large-scale fading factor of user k in cell l to the central base station in cell j;

(3) Use the greedy strategy to select a pilot group with the largest user rate product each time, and iterate K times to complete the pilot assignment as the initial pilot group; the specific steps include:

A, randomly select a user from each cell, and obtain the rate product of the selected L users;

B, L users corresponding to the maximum value of the rate product obtained in step A are used as pilot frequency group P ₁ ;

C. According to the methods of steps A and B, from the remaining users, obtain pilot frequency groups P ₂ , . . . , P _k , . . , P _K in turn;

D. The obtained pilot frequency groups P ₁ , P ₂ , . . . , _PK are taken as the initial pilot frequency group states.

The set of users using the same pilot is a pilot group, and the users in each pilot group are from different cells, and P _k represents the pilot group using pilot K; there are K pilot groups in the Massive MIMO system, That is, P ₁ , P ₂ , ..., P _K , there are L users in each pilot group;

(4) Starting from the initial pilot group obtained in step (3), users are exchanged between the pilot groups: if the user exchange between the two pilot groups, the user rate product is greater than the user rate product before the exchange , exchange is performed, otherwise, no exchange is performed until all pilot groups complete user exchange. Specific steps include:

_E. The pilot frequency groups P ₁ , P ₂ , .

F. Set the iteration counter l, and initialize l=1;

G. The user exchange in the 1 cell is performed between any two pilot groups: if the user rate product is greater than the user rate product before the exchange after the user exchange, the exchange is performed, otherwise, the exchange is not performed;

H. Determine whether l is equal to L, if yes, end, otherwise, add 1 to l, and return to step G.

Figures 2 and 3 show the effects of the user-switched-based pilot allocation method proposed in this embodiment on maximizing the system product. From the results shown in Fig. 2 and Fig. 3, the pilot frequency allocation method based on user switching proposed by the present invention can achieve an effect comparable to the exhaustive traversal method when maximizing the system product, especially in Fig. 3, when When n=2, the whole system goes through two rounds of user exchange, and the pilot frequency allocation method based on user exchange has almost the same performance as the exhaustive traversal method. n is the number of times for switching, when n=2, taking 3 cells and 5 users as an example, the exhaustive traversal method requires 14,400 traversals to obtain optimal performance, while the method based on user switching only needs to use greedy The method performs 225 traversal to obtain the pilot group in the initial state, and then the pilot group performs 60 user exchanges to achieve almost the same system performance as the exhaustive traversal method, which greatly reduces the complexity. Although the method based on user exchange adds 60 additional user exchanges on the basis of the greedy method, the system performance has been greatly improved, so the pilot frequency allocation method based on user exchange proposed in the present invention can be The lower complexity achieves almost the same performance as the exhaustive traversal method.

Claims (2)

1. A low-complexity pilot frequency allocation method based on user switching, applicable to a Massive MIMO system, wherein the Massive MIMO system includes L equivalent hexagonal cells, each cell including a central base station and K users , one central base station serves K users at the same time, the users in the same cell use mutually orthogonal pilots, the users in the cells reuse pilots, and the number of pilots available for allocation in the Massive MIMO system is K , characterized in that the specific steps include: (1) According to the distance from the user to the central base station, obtain the large-scale fading information from each user in each cell in the Massive MIMO system to each central base station i,j∈[1,2,…,L],k∈[1,2,…,K],

refers to the large-scale fading factor of the central base station in the user k in the i cell to the j cell; (2) Construct an objective function for the pilot allocation problem, the objective function max U(P) is to maximize the product of the rates of all users in the Massive MIMO system, as shown in formula (I): In formula (I),

is the rate of the user using the kth pilot in cell l, l∈[1,2,…,L],

refers to the large-scale fading factor from user k in cell l to the central base station in cell l; refers to the large-scale fading factor of user k in cell l to the central base station in cell j; (3) Use the greedy strategy to select a pilot group with the largest user rate product each time, and iterate M times to complete the pilot assignment as the initial pilot group; The set of users using the same pilot is a pilot group, and the users in each pilot group are from different cells, and P _k represents the pilot group using pilot k; there are K pilot groups in the Massive MIMO system, That is, P ₁ , P ₂ ,..., P _K , there are L users in each pilot group; the specific steps include: A, randomly select a user from each cell, and obtain the rate product of the selected L users; B, L users corresponding to the maximum value of the rate product obtained in step A are used as pilot frequency group P ₁ ; C. According to the method of steps A and B, from the remaining users, obtain pilot frequency groups P ₂ ,...,P _k ,...,P _K in turn; D. The obtained pilot groups P ₁ , P ₂ ,...,P _k ,...,P _K are taken as the initial pilot group state; (4) Starting from the initial pilot group obtained in step (3), users are exchanged between the pilot groups: if the user exchange between the two pilot groups, the user rate product is greater than the user rate product before the exchange , exchange is performed, otherwise, no exchange is performed until all pilot groups complete user exchange. 2. A kind of low-complexity pilot frequency allocation method based on user switching according to claim 1, is characterized in that, described step (4), concrete steps comprise: E, the pilot frequency groups P ₁ , P ₂ ,...,P _k ,...,P _K obtained in step (3) are used as the initial state of the pilot frequency allocation method based on user exchange; F. Set the iteration counter l, and initialize l=1; G. The user exchange in the 1 cell is performed between any two pilot groups: if the user rate product is greater than the user rate product before the exchange after the user exchange, the exchange is performed, otherwise, the exchange is not performed; H. Determine whether l is equal to L, if yes, end, otherwise, add 1 to l, and return to step G.

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