CN103259578B - The cooperation partner selection method of cooperation MIMO system - Google Patents

Abstract

A cooperative partner selection method for a cooperative MIMO system relates to the field of wireless communication. It is to solve the problem of large energy gain loss in the existing partner selection method using the WLF algorithm. The method: if the number of cell users in the cooperative MIMO system is greater than 2, the base station selects the cell user i with the worst channel state; and judges whether the SNR γ _i of the link between the cell user i with the worst channel state and the base station is greater than the preset Set the No. 1 threshold γ _th1 , if not, select user j with the best channel state between user i and user i in the cooperative MIMO system, and judge whether the SNR of the link between user i and user j is greater than the preset two number threshold γ _th2 , if it is, user j is taken as the cooperative partner of user i, user i and user j are deleted from the user list, and the cooperative partner selection of a cooperative MIMO system is completed. The invention is applicable to the selection of cooperative partners of cooperative MIMO systems.

Description

Cooperative partner selection method for cooperative MIMO systems

technical field

The invention relates to the field of wireless communication.

Background technique

Studies have shown that the performance of cooperative diversity systems mainly depends on the way of cooperation and the channel quality of links between nodes. Therefore, for a wireless network with multiple candidate cooperative partners, how to select a suitable cooperative partner to optimize the performance of the system is of great significance, which has become one of the current research hotspots in cooperative diversity technology.

According to the basis of selection, the cooperative partner selection methods mainly include three categories: selection methods based on location information, selection methods based on average channel state information, and selection methods based on instantaneous channel state information. The selection method based on location information needs to know the distance between each node; the selection method based on average channel state information is more suitable for continuous data transmission, or the situation of fast fading channels, and the situation where the system cannot obtain accurate instantaneous channel state information; The selection method based on instantaneous channel state information is more suitable for bursty data transmission, or the case of slow fading channel.

According to the different decision-making power, the cooperative partner selection methods can be divided into two categories: centralized selection methods and distributed selection methods. The centralized selection method is suitable for a network with a center, such as a cellular network. The central node (base station) has the location information of all users or the signal-to-noise ratio information between all users and between users and the base station, and selects One or more cooperative partners optimize the overall performance of the network according to a certain optimization goal. More representative centralized partner selection algorithms include maximum weight matching algorithm, greedy matching algorithm, worst link first matching algorithm and so on. The distributed selection method is suitable for networks without a center, such as wireless ad hoc networks and wireless sensor networks, and each node independently selects a cooperative partner.

In the classic algorithm of partner selection, both the maximum weight matching algorithm and the Greedy matching algorithm need to be exhaustive within a certain range, and the computational complexity is very high. In the actual system, it is necessary to complete the grouping of users in real time and quickly, so the proposed The Worst Link First Algorithm (WLF), which has less energy gain loss and can reduce computational complexity, is the partner choice for this key research.

The traditional WLF algorithm regards the transmission distance loss as the main factor of the signal-to-noise ratio, that is, the channel conditions of users close to the base station are better than those of users far away from the base station, which requires the base station to know the location information of all users in the cell.

Contents of the invention

The invention solves the problem of large energy gain loss in the existing partner selection method using the WLF algorithm, thereby providing a cooperative partner selection method for a cooperative MIMO system.

A cooperative partner selection method for a cooperative MIMO system, which is implemented by the following steps:

Step 1, judging whether the number of cell users in the cooperative MIMO system is greater than 2, if the judgment result is yes, then perform step 2; if the judgment result is no, then perform step 5;

Step 2, the base station judges the channel state of each cell user to the base station in the cooperative MIMO system one by one, and selects the cell user i with the worst channel state; and judges the signal of the link between the cell user i with the worst channel state and the base station Whether the noise ratio γ _i is greater than the preset No. 1 threshold γ _th1 , if the judgment result is yes, go to step 5; if the judgment result is no, go to step 3;

Step 3: Select user j with the best channel state between user i and user i in the cooperative MIMO system, and judge whether the SNR of the link between user i and user j is greater than the preset second threshold γ _th2 , if the judgment result If yes, execute step 4; if the judgment result is no, delete user i from the user list, and return to execute step 1;

Step 4. Use user j as the collaborating partner of user i, delete user i and user j from the user list, and return to step 1;

Step 5, completing the selection of the cooperative partner of the cooperative MIMO system.

During the cooperative partner selection process of the cooperative MIMO system, the signal-to-noise ratio of each link is according to the formula:

$\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; E.</span>}{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}{\mathrm{<span\; class="notranslate">\; N</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}$

get;

Among them: E is the energy required by the terminal to transmit 1 bit of information, N ₀ is the unilateral power spectral density of Gaussian white noise, H is the channel matrix of the corresponding link, is the Frobenius square norm, namely:

${<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{{\mathrm{<span\; class="notranslate">\; j</span>}}^{<span\; class="notranslate">\; \text{'}</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; i</span>}}^{<span\; class="notranslate">\; \text{'}</span>}}<span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ;</span>$

where H _{j′, i′} represent the channel complex fading coefficient from transmitting antenna i′ to receiving antenna j′, and both M _t and M _r are positive integers.

The energy gain loss of the partner selection method of the present invention is small, and the calculation complexity is greatly reduced, so that the selection speed is greatly improved.

Description of drawings

Fig. 1 is a schematic diagram of a signal processing flow chart of the present invention;

Fig. 2 is a schematic diagram of performance simulation of channel priority matching and random selection algorithm among users in the first embodiment;

Fig. 3 is a schematic diagram of a performance simulation of an inter-user channel priority matching algorithm under different situations in the first embodiment.

Detailed ways

Embodiment 1. A method for selecting a cooperative partner of a cooperative MIMO system, which is implemented by the following steps:

Step 1, judging whether the number of cell users in the cooperative MIMO system is greater than 2, if the judgment result is yes, then perform step 2; if the judgment result is no, then perform step 5;

Step 2, the base station judges the channel state of each cell user to the base station in the cooperative MIMO system one by one, and selects the cell user i with the worst channel state; and judges the signal of the link between the cell user i with the worst channel state and the base station Whether the noise ratio γ _i is greater than the preset No. 1 threshold γ _th1 , if the judgment result is yes, go to step 5; if the judgment result is no, go to step 3;

Step 3: Select user j with the best channel state between user i and user i in the cooperative MIMO system, and judge whether the SNR of the link between user i and user j is greater than the preset second threshold γ _th2 , if the judgment result If yes, execute step 4; if the judgment result is no, delete user i from the user list, and return to execute step 1;

Step 4. Use user j as the collaborating partner of user i, delete user i and user j from the user list, and return to step 1;

Step 5, completing the selection of the cooperative partner of the cooperative MIMO system.

During the cooperative partner selection process of the cooperative MIMO system, the signal-to-noise ratio of each link is according to the formula:

$\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; E.</span>}{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}{\mathrm{<span\; class="notranslate">\; N</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}$

get;

Among them: E is the energy required by the terminal to transmit 1 bit of information, N ₀ is the unilateral power spectral density of Gaussian white noise, H is the channel matrix of the corresponding link, is the Frobenius square norm, namely:

${<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{{\mathrm{<span\; class="notranslate">\; j</span>}}^{<span\; class="notranslate">\; \text{'}</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; i</span>}}^{<span\; class="notranslate">\; \text{'}</span>}}<span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ;</span>$

where H _{j′, i′} represent the channel complex fading coefficient from transmitting antenna i′ to receiving antenna j′, and both M _t and M _r are positive integers.

The present invention proposes to use the channel matrix H as a judgment channel condition to select cooperative users, so that the base station does not need to know the location information of the users, and the channel matrix is included in the CSI as a basic information. And because in the multi-antenna system, the space-time block code is used, the CSIs need to be known, so the use of the CSIs will not increase the extra overhead caused by the channel estimation due to cooperation.

If the distance loss is used to represent the channel state for selection, the difference between the single-antenna system and the multi-antenna system will be discarded, and since the present invention intends to apply this partner selection method to a multi-antenna system and analyze its performance in a multi-antenna system, Therefore, choosing the channel matrix and using the distance loss to represent the channel state can better reflect the performance difference of the algorithm in single-antenna and multi-antenna systems.

In terms of specific methods, the present invention studies a proposed WLF algorithm with a threshold. The threshold 1 (λ _th1 ) is to avoid the situation that the cooperation benefit is not large or there is no cooperation gain due to the channel condition between the source user and the base station is good enough, and the setting of this threshold also simplifies the selection algorithm to a certain extent, that is, There is no need to select a partner for all users, only for the required selection, which reduces the number of selections. Threshold 2 (λ _th2 ) is set to ensure the effect of cooperation. If the link status between the cooperation partner and the base station is very bad, and the cooperation itself is costly, the transmission performance will be degraded, and the gain outweighs the gain. Based on the above analysis, the new WLF selection process is shown in Figure 1.

Part A of the process is to avoid resource waste when selecting a cooperating user for user j whose channel condition is good enough and does not need to cooperate. The WLF user grouping method is derived from the matching algorithm in graph theory, so the situation that j is i's collaborating partner and other users are j's collaborating partner is not considered here.

Beneficial effects obtained by the present invention: Table 1 shows that in a multi-antenna system under the inter-user channel priority matching algorithm, the number of cooperative partner users is not found when the total number of users in the cell is different. The data is the average of 1000 simulation calculations. It can be seen from the data in the table that the number of users who have not found a partner due to the algorithm has nothing to do with the number of users in the cell. That is, when the total number of users in a cell increases, the number of users who have not found a partner remains basically unchanged. Therefore, in a cell with a high user density (that is, the total number of users in the cell is large), the probability of users not being able to find a partner is low. . We consider the performance of the algorithm in both cases of high density and low density by changing the number of cells. It can be concluded that the average energy gain of the system increases with the increase of the number of users in the cell, and Table 1 explains the reasons for this trend. This shows that the inter-user channel priority algorithm performs better in high-density residential areas, and is more suitable for high-density user systems such as shopping malls, schools, and apartments.

Table 1 The number of users who cannot find collaborative users when the total number of users is different

Fig. 2 is the performance comparison between the user channel priority matching algorithm and the random selection algorithm in the multi-antenna system. It can be clearly seen that the superiority of channel priority matching performance among users. Random selection Because the selection does not consider the benefits, the selection algorithm is simple. And choosing an inappropriate partner will require more energy to transmit data at the same bit error rate. In a multi-antenna system, since the performance of the system itself is better than that of the single-antenna system under the same standard, the limited energy gain generated by random selection cooperation cannot offset the loss of the cooperation itself, so that the cooperation not only does not bring gain to the multi-antenna system , but degrades system performance. From the perspective of users, in the whole cell, some users have positive cooperation gain, but more users have negative cooperation energy gain, so the average energy gain of the whole cell is negative. This also illustrates the importance of selection algorithms in cooperative MIMO systems. Careless collaboration can backfire. The average energy gain randomly selected in the figure does not change with the total number of users in the cell like the channel priority matching algorithm among users. This is because the surrounding user conditions are not taken into consideration during random selection, and the user density in the cell does not affect it.

Figure 3 shows how the average energy gain of a multi-antenna system varies with the number of users in the cell under the cooperation of channel priority matching algorithms between users with and without a threshold, and the channel priority matching between users when the total number of users in the cell is different. Comparison of average energy gain in multi-antenna and single-antenna systems. It can be clearly seen from the figure that the selection algorithm with a threshold provides a higher average energy gain for the system than the selection algorithm without a threshold, which improves the average energy gain by about 2dB.

The average energy gain in a multi-antenna system is consistently lower than that in a single-antenna system. That is, the channel priority matching method between users brings average energy gain to the multi-antenna system, but the average energy gain is smaller than that of the single-antenna system. The reason for this result is that since each user terminal in the multi-antenna system has multiple antennas (each terminal is assumed to have 2 antennas), even if the user terminals in the system do not cooperate, there is still diversity gain . According to Equation (1-1), when the system bit error rate is constant, the energy required to transmit 1 bit in a non-cooperative multi-antenna system is less than the corresponding energy required by a single-antenna system, and the gain generated by the cooperation itself is limited, so The average energy gain brought by multi-antenna system is not as large as that of single-antenna system.

During the simulation process, under the same number of simulations, the performance of the multi-antenna system is relatively stable, while the performance of the single-antenna system fluctuates greatly. The performance metrics stabilized when the number of simulations in the single-antenna system was increased by an order of magnitude. This point also shows that the stability of the multi-antenna cooperative system is better than that of the single-antenna cooperative system.

Claims (1)

1. the cooperative partner selection method of cooperative MIMO system is characterized in that: it is realized by the following steps: Step 1, judging whether the number of cell users in the cooperative MIMO system is greater than 2, if the judgment result is yes, then perform step 2; if the judgment result is no, then perform step 5; Step 2, the base station judges the channel state of each cell user to the base station in the cooperative MIMO system one by one, and selects the cell user i with the worst channel state; and judges the signal of the link between the cell user i with the worst channel state and the base station Whether the noise ratio γ _i is greater than the preset No. 1 threshold γ _th1 , if the judgment result is yes, go to step 5; if the judgment result is no, go to step 3; The signal-to-noise ratio of each link is according to the formula: $\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; E.</span>}{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}{\mathrm{<span\; class="notranslate">\; N</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}$ get; Among them: E is the energy required by the terminal to transmit 1 bit of information, N ₀ is the unilateral power spectral density of Gaussian white noise, H is the channel matrix of the corresponding link, is the Frobenius square norm, namely: ${<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{{\mathrm{<span\; class="notranslate">\; j</span>}}^{<span\; class="notranslate">\; \&prime;</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; i</span>}}^{<span\; class="notranslate">\; \&prime;</span>}}<span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ;</span>$ where H _{j', i'} represent the channel complex fading coefficient from transmitting antenna i' to receiving antenna j', M _t and M _r are both positive integers; Step 3: Select user j with the best channel state between user i and user i in the cooperative MIMO system, and judge whether the SNR of the link between user i and user j is greater than the preset second threshold γ _th2 , if the judgment result If yes, execute step 4; if the judgment result is no, delete user i from the user list, and return to execute step 1; Step 4. Use user j as a partner of user i, delete user i and user j from the user list, and return to step 1; Step 5, completing the selection of the cooperative partner of the cooperative MIMO system.