CN113556195B - Multi-user cooperation wireless transmission network performance prediction method based on outage probability - Google Patents

Multi-user cooperation wireless transmission network performance prediction method based on outage probability Download PDF

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CN113556195B
CN113556195B CN202110824389.1A CN202110824389A CN113556195B CN 113556195 B CN113556195 B CN 113556195B CN 202110824389 A CN202110824389 A CN 202110824389A CN 113556195 B CN113556195 B CN 113556195B
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CN113556195A (en
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黄海燕
师玉洁
张学军
李亚红
王春丽
李新颖
张鸿生
李翔
张宁
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Lanzhou Jiaotong University
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
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Abstract

The invention discloses a multi-user cooperation wireless transmission network performance prediction method based on outage probability, which comprises the following steps: step 1: according toChannel state information, calculating signal-to-interference ratio delta from source node to relay node sr Signal-to-interference ratio delta from source node to destination node sd And the signal-to-interference ratio delta from the relay node to the destination node rd The method comprises the steps of carrying out a first treatment on the surface of the Step 2: selecting optimal source node s in a multi-source multi-relay cooperative wireless network b And the optimal relay node r b The method comprises the steps of carrying out a first treatment on the surface of the Step 3: optimal source node s b Transmitting information to the best relay node r b And destination node d, best relay node r b To receive the source node signal y sbrb Decoding and forwarding to a destination node d; step 4: the destination node d adopts a selective combination method to combine the signals received by the two time slots and calculates the end-to-end signal-to-noise-and-interference ratio gamma end SC The method comprises the steps of carrying out a first treatment on the surface of the Step 5: and carrying out outage probability analysis on the multi-user cooperative wireless network.

Description

Multi-user cooperation wireless transmission network performance prediction method based on outage probability
Technical Field
The invention belongs to cooperative relay technology, and particularly relates to a multi-user cooperative wireless transmission network performance prediction method based on outage probability.
Background
With the development of society and the continuous improvement of information technology, mobile wireless communication has become an indispensable part of people's daily life. In order to meet the demands of people on high quality and high performance of communication service, cooperative communication is proposed as a new idea.
Typical cooperative relay transmissions include three-node single-relay two-hop cooperative relay transmissions of a source node, a relay node, and a destination node. In a single relay transmission system, a communication node and other nodes share resources by utilizing the broadcast transmission characteristic of wireless communication to form a virtual antenna array, so that the space gain similar to that of the MIMO technology can be obtained. In order to improve the spectrum utilization rate and the system capacity, the MIMO technology needs to install multiple antennas at the transceiver end of the communication node to form multiple parallel independent transmission channels. Unlike MIMO technology, cooperative communication provides a new direction of research, i.e. communication nodes share antennas and frequencies with other network nodes in the vicinity, and the communication links are no longer point-to-point, but cover the entire network system. The cooperative communication network improves the space diversity gain of the communication system, enhances the reliability of information transmission, increases the capacity of the network and improves the system performance.
Along with the development of cooperative communication, the relay cooperative model is also continuously changed, and the single-source single-relay cooperative model is developed to a single-source multi-relay cooperative model and then is extended to a multi-source multi-relay cooperative model. And in a real wireless network, the multi-source multi-relay model is closer to reality.
Disclosure of Invention
The invention aims to provide a multi-user cooperative wireless transmission network performance prediction method based on outage probability, which comprises the following steps:
the multi-user wireless transmission network model comprises M source nodes s m N relay nodes r n And one destination node d, Q co-channel interferences at the relay node and T co-channel interferences at the destination node. M is more than or equal to 1 and less than or equal to M, N is more than or equal to 1 and less than or equal to N, Q is more than or equal to 1 and less than or equal to Q, and T is more than or equal to 1 and less than or equal to T.
Each node is equipped with a single omni-directional antenna.
Step 1: calculating the signal-to-interference ratio delta from the source node to the relay node according to the obtained channel state information sr Signal-to-interference ratio delta from source node to destination node sd And the signal-to-interference ratio delta from the relay node to the destination node rd ；
Step 2: selecting the best source node s b And the optimal relay node r b The method comprises the steps of carrying out a first treatment on the surface of the Step 1 andstep 2 is the prior art, and is directly transferred here.
Step 2.1: at all source nodes s m On the direct link to the destination node d, the source node with the largest SINR is selected as the optimal source node s b 。
Figure GDA0004156526110000021
Step 2.2: selecting an optimal relay node r by a relay selection method of Opportunistic Relay (OR) b 。
Figure GDA0004156526110000022
Step 3: in the first time slot, the best source node s b Transmitting information to the best relay node r b And a destination node d;
optimal relay node r b The received signals are:
Figure GDA0004156526110000023
wherein P is all source nodes s m And all relay nodes r n P, of (a) is set I For interference power x s For signals transmitted by source nodes, x q In order to interfere with the signal(s),
Figure GDA0004156526110000024
representing the best source node s b To the best relay node r b Channel coefficient of>
Figure GDA0004156526110000025
Representing interference q to best relay node r b Channel coefficient of>
Figure GDA0004156526110000026
Representing noise.
r b SINR at is
Figure GDA0004156526110000027
Wherein the method comprises the steps of
Figure GDA0004156526110000028
Representing the best source node s b To the best relay node r b Channel gain, N 0 Representing the variance of the additive gaussian white noise.
The signal received by the destination node d is
Figure GDA0004156526110000029
Wherein x is t For an interfering signal at the destination node,
Figure GDA00041565261100000210
representing the best source node s b Channel coefficient, h, to destination node d td Channel coefficient representing interference t to best relay node d,/->
Figure GDA00041565261100000211
Representing noise.
SINR at d is
Figure GDA0004156526110000031
Wherein the method comprises the steps of
Figure GDA0004156526110000032
Representing the best source node s b Channel gain to destination node d, N 0 Representing the variance of the additive gaussian white noise.
In the second time slot, the best relay node r b To receive source node signal
Figure GDA0004156526110000033
Decoding andforwarding to the destination node d; d the received signal is
Figure GDA0004156526110000034
Wherein the method comprises the steps of
Figure GDA0004156526110000035
Representing the best relay node r b Channel coefficient, h, to destination node d td Channel coefficient representing interference t to destination node d, < ->
Figure GDA0004156526110000036
Representing noise, x t For interfering signals at destination node x s A signal sent for the source node.
SINR at destination node d is
Figure GDA0004156526110000037
/>
Wherein the method comprises the steps of
Figure GDA0004156526110000038
Representing the best relay node r b Channel gain to destination node d, N 0 Representing the variance of the additive gaussian white noise.
Step 4: the destination node d adopts a selective combination method to receive signals from two time slots
Figure GDA0004156526110000039
And->
Figure GDA00041565261100000310
Combining, i.e. selecting one path with the maximum SINR in the direct link and the relay link, the end-to-end signal-to-noise-and-interference ratio is
Figure GDA00041565261100000311
Step 5: outage probability is the most important performance index of the cooperative wireless network. Outage probability analysis, i.e., gamma, for multi-user cooperative wireless networks end SC Below threshold gamma th ，γ th ＝2 2R -1. I.e.
P out SC ＝Pr(s b ∩γ end SC ＜γ th ) (4-1)
Selecting the best source node s according to the formula (1-1) calculation b The probability of (2) is
Figure GDA00041565261100000312
Calculating that the signal-to-noise-and-interference ratio of the relay link is smaller than a threshold value gamma according to a formula (1-2) th Probability of (2)
Figure GDA0004156526110000041
Wherein the probability density function of the interference at the interrupt node is
Figure GDA0004156526110000042
Calculating end-to-end SINR gamma end SC Less than threshold value gamma th The probability of (2) is
Figure GDA0004156526110000043
Wherein the probability density function of the interference at the destination node is
Figure GDA0004156526110000044
The system interrupt probability can be calculated as
Figure GDA0004156526110000045
Drawings
FIG. 1 is a model diagram of a method for predicting performance of a multi-user cooperative wireless transmission network based on outage probability in the presence of co-channel interference;
fig. 2 is a graph of the probability of system outage with signal to noise ratio SIR gamma at different numbers of source nodes M;
fig. 3 is a graph of the probability of system outage with signal to noise ratio SIR gamma at different numbers of relay nodes M;
fig. 4 is a graph of outage probability with system outage probability with signal to noise ratio SIR gamma at different disturbances Q, T.
Detailed Description
The invention will be further elucidated with reference to the drawings and to specific embodiments. The present invention is not limited to these examples, although they are described in order to assist understanding of the present invention. Functional details disclosed herein are merely for describing example embodiments of the invention. This invention may, however, be embodied in many alternate forms and should not be construed as limited to the embodiments set forth herein.
It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments of the invention. The terms "comprises," "comprising," "includes," and/or "including," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, and do not preclude the presence or addition of one or more other features, amounts, steps, operations, elements, components, and/or groups thereof.
It should be appreciated that in some alternative embodiments, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may in fact be executed substantially concurrently or the figures may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
It should be understood that specific details are provided in the following description to provide a thorough understanding of the example embodiments. However, it will be understood by those of ordinary skill in the art that the example embodiments may be practiced without these specific details. For example, a system may be shown in block diagrams in order to avoid obscuring the examples with unnecessary detail. In other instances, well-known processes, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the example embodiments.
Example 1:
a multi-user cooperative wireless transmission network performance prediction method based on outage probability comprises the following steps:
establishing a multi-user wireless transmission network model, which comprises a plurality of source nodes, a plurality of relay nodes and a destination node;
step 1, calculating the signal-to-interference ratio delta from a source node to a relay node according to the obtained channel state information sr Signal-to-interference ratio delta from source node to destination node sd And the signal-to-interference ratio delta from the relay node to the destination node rd ；
Step 2: in a multi-source multi-relay cooperative wireless network, a best source node and a best relay node are selected.
Step 2.1: at all source nodes s m On the direct link to the destination node d, the source node with the largest SINR is selected as the optimal source node s b 。
Step 2.2: selecting an optimal relay node r by a relay selection method of Opportunistic Relay (OR) b 。
Step 3: in the first time slot, the best source node s b Transmitting information to the best relay node r b And a destination node d;
optimal relay node r b The received signal is
Figure GDA0004156526110000061
Optimal relay node r b SINR at +.>
Figure GDA0004156526110000062
The signal received by the destination node d is +.>
Figure GDA0004156526110000063
SINR at destination node d is +.>
Figure GDA0004156526110000064
Step 4: in the second time slot, the best relay node r b To receive source node signal
Figure GDA0004156526110000065
Decoding and forwarding to a destination node d;
the signal received by the destination node d is:
Figure GDA0004156526110000066
SINR at destination node d is:
Figure GDA0004156526110000067
step 5: the destination node d adopts a selective combination method to receive signals from two time slots
Figure GDA0004156526110000068
And->
Figure GDA0004156526110000069
Combining, i.e. selecting the path with the largest SINR in the direct link and the relay link.
Step 6: outage probability is the most important performance index of the cooperative wireless network. And carrying out outage probability analysis on the multi-user cooperative wireless network.
Example 2:
the multi-user wireless transmission network model comprises M source nodes s m N relay nodes r n And one destination node d, Q co-channel interferences at the relay node and T co-channel interferences at the destination node. M is more than or equal to 1 and less than or equal to M, N is more than or equal to 1 and less than or equal to N, Q is more than or equal to 1 and less than or equal to Q, and T is more than or equal to 1 and less than or equal to T.
Each node is equipped with a single omni-directional antenna.
Step 1, calculating the signal-to-interference ratio delta from a source node to a relay node according to the obtained channel state information sr Signal-to-interference ratio delta from source node to destination node sd And the signal-to-interference ratio delta from the relay node to the destination node rd ；
Step 2.1: at all source nodes s m On the direct link to the destination node d, the source node with the largest SINR is selected as the optimal source node s b 。
Figure GDA0004156526110000071
Step 2.2: selecting an optimal relay node r by a relay selection method of Opportunistic Relay (OR) b 。
Figure GDA0004156526110000072
Step 3: in the first time slot, the best source node s b Transmitting information to the best relay node r b And a destination node d;
optimal relay node r b The received signals are:
Figure GDA0004156526110000073
wherein P is all source nodes s m And a relay node r n P, of (a) is set I For interference power x s For signals transmitted by source nodes, x q In order to interfere with the signal(s),
Figure GDA0004156526110000074
representing the best source node s b To the best relay node r b Channel coefficient of>
Figure GDA0004156526110000075
Representing interference q to best relay node r b Channel coefficient of>
Figure GDA0004156526110000076
Representing noise.
r b SINR at is
Figure GDA0004156526110000077
Wherein the method comprises the steps of
Figure GDA0004156526110000078
Figure GDA0004156526110000079
Representing the best source node s b To the best relay node r b N0 represents the variance of the additive gaussian white noise.
The signal received by the destination node d is
Figure GDA00041565261100000710
Wherein x is t For an interfering signal at the destination node,
Figure GDA00041565261100000711
representing the best source node s b Channel coefficient, h, to destination node d td Channel coefficient representing interference t to best relay node d,/->
Figure GDA00041565261100000712
Representing noise.
SINR at d is
Figure GDA00041565261100000713
Wherein the method comprises the steps of
Figure GDA00041565261100000714
Figure GDA00041565261100000715
Representing the best source node s b The channel gain to the destination node d, N0, represents the variance of the additive gaussian white noise.
Step 4:
in the second time slot, the best relay node r b To receive source node signal
Figure GDA0004156526110000081
Decoding and forwarding to a destination node d; d the received signal is
Figure GDA0004156526110000082
Wherein the method comprises the steps of
Figure GDA0004156526110000083
Representing the best relay node r b Channel coefficient, h, to destination node d qd Channel coefficient representing interference q to destination node d, < ->
Figure GDA0004156526110000084
Representing noise.
SINR at destination node d is
Figure GDA0004156526110000085
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure GDA0004156526110000086
Figure GDA0004156526110000087
representing the best relay node r b Channel gain to destination node d, N 0 Representing the variance of the additive gaussian white noise.
Step 5: the destination node d adopts a selective combination method to receive signals from two time slots
Figure GDA0004156526110000088
And->
Figure GDA0004156526110000089
Combining, i.e. selecting one path with the maximum SINR in the direct link and the relay link, the end-to-end signal-to-noise-and-interference ratio is
Figure GDA00041565261100000810
Step 6: outage probability is the most important performance index of the cooperative wireless network. Outage probability analysis, i.e., gamma, for multi-user cooperative wireless networks end SC Below threshold gamma th ，γ th ＝2 2R -1. I.e.
P out SC ＝Pr(s b ∩γ end SC ＜γ th ) (5-1)
Selecting the best source node s according to the formula (1-1) calculation b The probability of (2) is
(5-2)
Calculating that the signal-to-noise-and-interference ratio of the relay link is smaller than a threshold value gamma according to a formula (1-2) th Probability of (2)
Figure GDA00041565261100000811
Wherein the probability density function of the interference at the interrupt node is
Figure GDA0004156526110000091
Calculating end-to-end SINR gamma end SC Less than threshold value gamma th The probability of (2) is
Figure GDA0004156526110000092
Wherein the probability density function of the interference at the destination node is
Figure GDA0004156526110000093
The system interrupt probability can be calculated as
Figure GDA0004156526110000094
Example 3:
simulation conditions
Figure GDA0004156526110000095
σ 2 td ＝σ 2 d 1≤m≤M,1≤n≤N，1≤q≤Q,1≤t≤T
Wherein sigma 2 sr Representing source node s m To the relay node r n Variance, sigma, of rayleigh channel fading coefficients between 2 rd Representing relay node r n Variance, sigma, of the rayleigh channel fading coefficients to destination node d 2 r Representing relay node r n The Rayleigh Li Cuila coefficient variance, sigma, of the interfering link 2 d Representing the rayleigh Li Cuila coefficient variance of the interfering link at destination node d.
Simulation 1: fig. 2 depicts the impact on the outage probability of the system as the signal-to-noise ratio γ changes and the outage probability versus the number of source nodes for the same number of relay nodes and co-channel interference. It can be clearly seen that the analysis results are consistent with the simulation results, verifying the validity of the deduction. Under the condition that M is 1,4 and 8, sigma is taken sr 2 ＝8dB，σ rd 2 ＝8dB,σ sd 2 ＝8dB,σ r 2 ＝1dB,σ d 2 When 1db, n=4, q=4, and t=4, the outage probability of the system decreases with increasing SNR γ, i.e., the greater the signal-to-noise ratio, the better the system performance, and the transmit power can be increased appropriately given the outage threshold of the system. While giving the impact on system performance as the number of source nodes changes,i.e. when the number M of source nodes increases, the outage probability of the system decreases.
Example 4:
fig. 3 depicts the relationship of outage probability and the number of relay nodes under the same number of source nodes and co-channel interference. Under the condition that the number N of the relay nodes is 1,4 and 8, sigma is taken sr 2 ＝8dB，σ rd 2 ＝8dB,σ sd 2 ＝8dB,σ r 2 ＝1dB,σ d 2 =1 db, m=5, q=4, t=4, it can be seen that the outage probability of the system decreases with increasing SNR γ, i.e. the larger the signal-to-noise ratio, the better the system performance. Meanwhile, when the number of relay nodes N increases, the outage probability of the system decreases. Combining fig. 2 and 3, system performance may be improved by increasing the number of source nodes or the number of relay nodes.
Example 5:
fig. 4 depicts the relationship between outage probability and co-channel interference under the same number of source nodes and relay nodes, and the magnitude relationship of the influence of relay node interference Q and destination node interference T on the outage probability of the system is studied. The interference Q of the relay node and the interference T of the target node are respectively Q=10, and T=10; q=2, t=10; q=10, t=2; taking sigma under the variation condition of Q=2 and T=2 sr 2 ＝8dB，σ rd 2 ＝8dB,σ sd 2 ＝8dB，σ r 2 ＝1dB，σ d 2 As SNR γ increases, system outage probability decreases, i.e., the greater the interference, the worse the system performance, the greater the magnitude of outage probability decrease when destination node interference T decreases, i.e., the greater the impact of interference at the destination node on system performance, than the magnitude of outage probability decrease when relay node interference Q decreases.
It will be apparent to those skilled in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, or they may alternatively be implemented in program code executable by computing devices, such that they may be stored in a memory device for execution by the computing devices, or they may be separately fabricated into individual integrated circuit modules, or multiple modules or steps within them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The embodiments described above are merely illustrative and may or may not be physically separate if reference is made to the unit being described as a separate component; if a component is referred to as a unit, it may or may not be a physical unit, and may be located in one place or distributed across multiple network elements. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those skilled in the art will understand and practice the invention without undue burden.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some of the technical features thereof can be replaced by equivalents. Such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
The invention is not limited to the alternative embodiments described above, but any person may derive other various forms of products in the light of the present invention. The above detailed description should not be construed as limiting the scope of the invention, which is defined in the claims and the description may be used to interpret the claims.

Claims (3)

1. The multi-user cooperative wireless transmission network performance prediction method based on outage probability establishes a multi-user wireless transmission network model, and the method comprises a plurality of source nodes, a plurality of relay nodes and a destination node, wherein each node is provided with a single omni-directional antenna, and the method is characterized by comprising the following steps:
step 1: calculating the signal-to-interference ratio delta from the source node to the relay node according to the obtained channel state information sr Signal-to-interference ratio delta from source node to destination node sd And the signal-to-interference ratio delta from the relay node to the destination node rd ；
Step 2: selecting the best source node s b And the optimal relay node r b ；
Step 3: in the first time slot, the best source node s b Transmitting information to the best relay node r b And destination node d, best relay node r b The received signal is
Figure FDA0004156526080000011
At this time, the best relay node r b Is equal to or less than the SINR>
Figure FDA0004156526080000012
The signal received by the destination node d is +.>
Figure FDA0004156526080000013
At this time, the SINR of the destination node d is +.>
Figure FDA0004156526080000014
In the second time slot, the best relay node r b To receive source node signal
Figure FDA0004156526080000015
Decoding and forwarding to destination node d, the signal received by destination node d is +>
Figure FDA0004156526080000016
At this time, the SINR of the destination node d is +.>
Figure FDA0004156526080000017
Step 4:the destination node d adopts a selective combination method to combine the signals received by the two time slots and calculates the end-to-end signal-to-noise-and-interference ratio gamma end SC ；
Step 5: the outage probability analysis for the multi-user cooperative wireless network specifically comprises the following steps:
step 5.1: calculating the probability of selecting the optimal source node;
step 5.2: calculating the probability that the signal-to-noise-and-interference ratio of the broken link is smaller than a threshold value;
step 5.3: calculating end-to-end SINR gamma end SC Less than threshold value gamma th Probability of (2);
step 5.4: calculating the interruption probability of the system;
the step 2 specifically comprises the following steps:
step 2.1: at all source nodes s m On the direct link to the destination node d, the source node with the largest SINR is selected as the optimal source node s b ；
Figure FDA0004156526080000018
Step 2.2: selecting an optimal relay node r by a relay selection method of Opportunistic Relay (OR) b ；
Figure FDA0004156526080000019
Wherein M represents the number of source nodes in the wireless transmission network model, and N represents the number of relay nodes;
the step 3: in the first time slot, the best relay node r b The received signals are:
Figure FDA0004156526080000021
wherein P is all source nodes s m And all relay nodes r n P, of (a) is set I For interferencePower, x s For signals transmitted by source nodes, x q In order to interfere with the signal(s),
Figure FDA0004156526080000022
representing the best source node s b To the best relay node r b Channel coefficient of>
Figure FDA0004156526080000023
Representing interference q to best relay node r b Channel coefficient of>
Figure FDA0004156526080000024
Representing noise;
r b SINR at:
Figure FDA0004156526080000025
/>
wherein the method comprises the steps of
Figure FDA0004156526080000026
Figure FDA0004156526080000027
Representing the best source node s b To the best relay node r b Channel gain of>
Figure FDA0004156526080000028
Representing interference q to best relay node r b Channel gain, N 0 Representing the variance of additive gaussian white noise;
the signal received by the destination node d is:
Figure FDA0004156526080000029
wherein x is t For an interfering signal at the destination node,
Figure FDA00041565260800000210
representing the best source node s b Channel coefficient, h, to destination node d td Channel coefficient representing interference t to destination node d, < ->
Figure FDA00041565260800000211
The method comprises the steps of representing noise, Q represents the co-channel interference number existing in a relay node, and T represents the co-channel interference number existing in a target node;
SINR at destination node d is:
Figure FDA00041565260800000212
wherein the method comprises the steps of
Figure FDA00041565260800000213
Figure FDA00041565260800000214
Representing the best source node s b Channel gain to destination node d, N 0 Representing the variance, g, of additive white gaussian noise td Representing the channel gain of the interference t to the destination node d;
in the second time slot, the best relay node r b To receive source node signal
Figure FDA00041565260800000215
Decoding and forwarding to a destination node d;
the signal received by the destination node d is:
Figure FDA00041565260800000216
wherein the method comprises the steps of
Figure FDA00041565260800000217
Indicating optimal relayNode r b Channel coefficient, h, to destination node d td Representing interference t to destination node d channel coefficient, < > and>
Figure FDA00041565260800000218
representing noise;
SINR at destination node d is:
Figure FDA0004156526080000031
wherein the method comprises the steps of
Figure FDA0004156526080000032
Figure FDA0004156526080000033
Representing the best relay node r b Channel gain to destination node d, N 0 Representing the variance of additive gaussian white noise;
in the step 5, gamma end SC Below threshold gamma th ，γ th ＝2 2R -1；
Namely: p (P) out SC ＝Pr(s b ∩γ end SC ＜γ th ) (5-1)
Step 5.1: selecting the best source node s according to the formula (1-1) calculation b The probability of (2) is:
Figure FDA0004156526080000034
the step 5.2 specifically comprises the following steps: calculating that the signal-to-noise-and-interference ratio of the interrupted link is smaller than a threshold value gamma according to the formula (1-2) th The probability of (2) is:
Figure FDA0004156526080000035
wherein the probability density function of the interference at the break node is:
Figure FDA0004156526080000036
in step 5.3, the end-to-end SINR gamma is calculated end SC Less than threshold value gamma th Specifically, the probability of (1) includes:
Figure FDA0004156526080000037
wherein the probability density function of the interference at the destination node is:
Figure FDA0004156526080000041
in the step 5.4, the system interrupt probability is calculated as follows:
Figure FDA0004156526080000042
2. the outage probability-based multi-user cooperative wireless transmission network performance prediction method according to claim 1, wherein: the step 4 specifically comprises the following steps: the destination node d adopts a selective combination method to receive signals from two time slots
Figure FDA0004156526080000043
And
Figure FDA0004156526080000044
and combining, namely selecting one path with the maximum SINR from a direct link and a relay link, wherein the end-to-end signal-to-noise-and-interference ratio is as follows: />
Figure FDA0004156526080000045
3. The outage probability-based multi-user cooperative wireless transmission network performance prediction method according to claim 1, wherein: the multi-user wireless transmission network model comprises M source nodes s m N relay nodes r n One destination node d, Q co-channel interferences at the relay node and T co-channel interferences at the destination node, wherein: m is more than or equal to 1 and less than or equal to M, N is more than or equal to 1 and less than or equal to N, Q is more than or equal to 1 and less than or equal to Q, and T is more than or equal to 1 and less than or equal to T.
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