A method for measuring the interruption performance of cognitive vehicle networking systems

Abstract

The present invention discloses a method for measuring the interruption performance of a cognitive vehicle networking system, which belongs to the field of wireless network security transmission technology. In view of the problems of poor transmission reliability, high latency and shortage of spectrum resources in complex channels caused by the dense density of vehicles in the vehicle network, the present invention jointly considers the influence of actual NOMA non-ideal serial interference cancellation (ipSIC) and residual hardware impairment (RHI), and considers the non-ideal characteristics of the actual channel caused by actual vehicle movement. Based on the double Rayleigh fading channel model suitable for mobile scenarios, the interruption performance of the NOMA system under consideration is analyzed. The method of the present invention provides a practical reference for effectively measuring V2X communication performance under actual non-ideal channel conditions.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless network security transmission, and in particular relates to a method for measuring the interruption performance of a cognitive vehicle networking system. Background Art

[0002] In the rapidly developing information age, people are placing higher demands on mobile communications. The sixth-generation (6G) wireless communication network is expected to provide improved coverage, spectrum efficiency, and abundant bandwidth resources. Vehicle-to-Everything (V2X) is gaining increasing attention within 6G networks. However, in densely populated or complex channel environments, the massive number of users accessing the network simultaneously can significantly increase information congestion, leading to insufficient spectrum resources, low spectrum utilization, and even high latency and low reliability. To avoid vehicle overload, resource collisions, and low spectrum utilization, non-orthogonal multiple access (NOMA) and cognitive radio technologies hold great promise in meeting the low-latency and high-reliability requirements of V2X scenarios. NOMA technology goes beyond orthogonal resource allocation and instead achieves multi-user communication on the same time-frequency resources through power allocation, at the expense of increased receiver complexity. Cognitive radio, which provides dynamic spectrum access, is also a promising technology for improving spectrum efficiency.

[0003] In the future, enhanced vehicle-to-everything (E-V2X) networks, where a large number of potentially active devices can act as relays for each other, will be one of the primary application scenarios for collaborative CR-NOMA technology. Therefore, combining non-orthogonal multiple access (NORMA) with cognitive radio technology can meet the high-bandwidth, wide-connectivity, and highly reliable transmission requirements of V2X in future 6G wireless networks.

[0004] Currently, the performance of cognitive non-orthogonal multiple access (CNOMA) technology for IoV communications has mostly been studied under idealized conditions, ideal channels, and simple channels. However, in real-world IoV communications, vehicles move rapidly, causing rapid channel changes and potentially leading to channel estimation errors. Furthermore, due to inaccurate calibration and time-varying hardware characteristics, some residual hardware impairments may remain, and serial interference techniques cannot be implemented at the receiver. Therefore, exploring the impact of non-ideal channel conditions on the performance of CNOMA-based IoV transmission systems under complex channels has become a pressing technical challenge for those skilled in the art. Summary of the Invention

[0005] To address the problems of poor transmission reliability, high latency and scarce spectrum resources in complex channels caused by the dense density of vehicles in vehicular networks, the present invention jointly considers the impact of actual NOMA non-ideal serial interference cancellation (ipSIC) and residual hardware impairment (RHI), and considers the non-ideal characteristics of actual channels caused by actual vehicle movement. Based on the double-Rayleigh fading channel model suitable for mobile scenarios, the interruption performance of the considered NOMA system is analyzed, and a method for measuring the interruption performance of cognitive vehicle networking systems is provided.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for measuring the interruption performance of a cognitive vehicle networking system includes the following steps:

[0008] Step 1: Establish a cognitive non-orthogonal multiple access vehicle network transmission system; the system includes a transmitting source (BS, Base Station), a group of cognitive vehicle users SU n (SU, Secondary User) (n = 1, 2 ..., M) and the main vehicle user (PU, Primary User); wherein the transmitting source uses non-orthogonal multiple access (NOMA) technology to send data to the cognitive vehicle user and the main vehicle user. At the same time, the cognitive vehicle user assists the main vehicle user in a collaborative manner to achieve reliable communication. The cognitive vehicle user and the main vehicle user perform actual non-ideal serial interference cancellation (ipSIC) when decoding their own signals. Moreover, the actual hardware RF characteristics of the transmitting source, the cognitive vehicle user, and the main vehicle user are non-ideal.

[0009] Step 2: In the cognitive non-orthogonal multiple access vehicle network transmission system, the transmitter sends a composite signal ɑ containing the main vehicle user information x1 and the cognitive vehicle information x2 to the main vehicle user PU and the cognitive vehicle user SU at a transmission power of P1. p x1+ɑ s x2, where ɑ p represents the power allocation coefficient of the main vehicle user information x1, ɑ s represents the power allocation coefficient of the cognitive vehicle user information x2, and ɑ p +ɑ s =1(ɑ p >ɑ s); Signal transmission will be divided into two time slots, the first time slot and the second time slot; After the cognitive vehicle user SU receives the signal sent by the transmitting source BS, it uses the serial interference cancellation (SIC, Successive Interference Cancellation) technology to decode the signal x1 containing the main vehicle user PU information, and then decodes the signal x2 containing the cognitive vehicle user SU information; Only when the cognitive vehicle user SU successfully decodes the information of x1 and x2, it is considered that the cognitive vehicle user SU has successfully decoded; If the cognitive vehicle user SU fails to successfully decode the information of x1 and x2, it is considered that the cognitive vehicle user SU has failed to decode; The successfully decoded cognitive vehicle user SU will use the SIC technology to decode the received composite signal, and then re-encode the composite signal and forward it to the main vehicle user PU. In particular, due to the limitation of actual hardware capabilities, the SU performs the ipSIC operation during decoding, that is, the SU fails to completely decode x1 and x2; The main vehicle user PU combines and processes the signals from the transmitting source BS and the cognitive vehicle user SU;

[0010] Step 3: Due to the mobility of vehicles, the communication link status between vehicles changes rapidly and dynamically, which will cause the channel state information to be outdated. The linear minimum mean square error is used to model the actual channel state information. represents the actual channel coefficient on the link from the sending node i to the receiving node j, represents the ideal channel coefficient on the link from the sending node i to the receiving node j. The error between the actual channel coefficient and the ideal channel coefficient is expressed as CN means it obeys normal distribution, δ i,j represents the standard deviation of the corresponding channel estimation error; then

[0011] Step 4: Considering the fast fading characteristics of the channel in the actual vehicle network mobile scenario, double Rayleigh fading is used to describe the channel fading characteristics. Each link in the system obeys independent and identically distributed double Rayleigh fading. The probability density function (CDF) under fast fading channel is expressed as:

[0012]

[0013] Where K0(·) represents the modified Bessel function of the second kind;

[0014] Step 5: Considering that the non-ideal characteristics of the actual hardware will affect the interrupt performance of the system, the residual hardware impairment factor (RHI) is used to describe the impact of the non-ideal characteristics of the actual hardware during signal transmission, and η is used to represent the impact of the non-ideal characteristics of the actual hardware during signal transmission. ijrepresents the signal loss value between the transmitting node i and the receiving node j;

[0015] Step 6: Analyze the interruption probability of the cognitive vehicle user SU;

[0016] There are two situations in which the cognitive vehicle user SU is interrupted:

[0017] The first one is that in the first time slot, the link from the transmitting source BS to all cognitive vehicle users SU is interrupted, that is, when any cognitive vehicle user SU receives the composite signal sent from the transmitting source BS, the cognitive vehicle user SU uses the SIC technology to first decode the main vehicle user PU signal x1 and then decode the cognitive vehicle user signal x2. If the signal decoding fails, the interruption probability of the cognitive vehicle user SU is calculated.

[0018] The second type is that, under the premise that the decoding of SU in the first time slot is successful, not all cognitive vehicle user SUs are decoded successfully. Only the successfully decoded SUs are represented as SUs. n , the signal can be re-encoded and forwarded to the main vehicle user PU, while the unsuccessfully decoded SU is denoted as SU m , will also receive SU n Recoded signal; in the second time slot, SU m Failure to decode the received signal results in a signal interruption event, i.e. SU m Using SIC technology, first decode the main vehicle user signal x1 and then decode the cognitive vehicle user signal x2. If the signal decoding fails, calculate SU m Interruption probability

[0019] Finally, the interruption probability of the cognitive vehicle user SU is calculated

[0020] Step 7, analyzing the interruption probability of the main vehicle user PU;

[0021] There are two situations in which the main vehicle user PU is interrupted during signal transmission:

[0022] The first one is that in the first time slot, based on step 6, the link from the transmitting source BS to all SUs is interrupted and the direct link from the transmitting source BS to the main vehicle user PU is interrupted, that is, PU receives the data from SU n After the composite signal is sent, the SIC technology is used to treat the cognitive vehicle user signal x2 as interference and directly decode the main vehicle user signal x1; if the signal decoding fails, the PU interruption probability is calculated

[0023] The second type is that in the second time slot, the main vehicle user PU receives the data from SU n The composite signal sent by the main vehicle user PU also receives the signal of the direct link sent by the transmitting source BS. When the main vehicle user PU combines the two signals, an interruption occurs. That is, after the PU combines the two information, it uses the SIC technology to regard the cognitive vehicle user signal x2 as interference and directly decodes the main vehicle user signal x1. In the case of decoding failure, the PU interruption probability is calculated.

[0024] Calculate the interruption probability of the main vehicle user PU

[0025] Furthermore, the signal transmission in step 2 is divided into two time slots, a first time slot and a second time slot;

[0026] In the first time slot, the transmitting source BS sends a composite signal to the cognitive vehicle user SU and the main vehicle user PU respectively. The signals received by the cognitive vehicle user SU and the main vehicle user PU are respectively expressed as:

[0027]

[0028]

[0029] Among them, y SU represents the signal received by the cognitive vehicle user SU, represents the signal received by the main vehicle user PU in the first time slot, P1 represents the transmitting source power, and represent the theoretical and actual channel coefficients respectively;

[0030] ε b,n ,ε b,p represents the channel estimation error; w n With w p The mean is 0 and the variance is δ 2 A complex Gaussian random variable; Represents the residual hardware impairment RHI on the transmission link between the transmitting source BS and the cognitive vehicle user SU, t represents the transmitter, r represents the receiver, K B,t , K S,r They represent the RHI of the transmitting source BS and the cognitive vehicle user SU as the receiving end; Represents the residual hardware damage RHI on the transmission link between the transmitting source BS and the main vehicle user PU, K P,r Indicates the RHI of the main vehicle user PU as the receiving end;

[0031] Successfully decoded cognitive vehicle user SUn The set formed is denoted as D, let D k The cognitive vehicle user SU that is successfully decoded n A subset of the set D is successfully decoded in |D k |=k, k=1,2…2 M -1, unsuccessfully decoded cognitive vehicle user SU m The set formed is represented as exist Choose so that each group h n,m The smallest part forms a subset, where h n,m Indicates SU n and SU m The channel gain between them is used to select the optimal cognitive vehicle user from D Forwarding signal, The selection criteria are:

[0032]

[0033] In the second time slot, the cognitive vehicle user SU that successfully decodes the composite signal n The information is forwarded to the primary vehicle user PU. At this time, the signal received by the primary vehicle user PU is expressed as:

[0034]

[0035] in, Represent the theoretical and actual channel coefficients, ε n,p represents the channel estimation error, P2 represents The transmission power, The signal sent by the cognitive user after re-encoding using the ipSIC operation.

[0036] Furthermore, the calculation in step 2 is The interruption probability of ipSIC operation is analyzed for the cognitive vehicle user SU that is not successfully decoded. m The impact of outage probability, and experimental comparison of ideal SIC and ipSIC;

[0037] According to step 6, analyze the cognitive vehicle user SU m The interruption probability of ipSIC is Conduct analysis and deduction;

[0038] Expressed as D represents the entire decoding set, represents an empty set, Pr represents the probability of an event occurring; when SU ​​performs an imperfect SIC operation (ipSIC) during the decoding process, Expressed as Further calculation is:

[0039]

[0040] in,

[0041] Expressed as in, Indicates the accumulation of events a to b, Pr(D=D k ) indicates SU n Belongs to the successful decoding set D k The probability of out,s (D=D k ) indicates SU m Decoding SU n The probability of failure in sending a composite signal;

[0042] Similarly, Pr(D=D k ) is expressed as:

[0043]

[0044] Finally, the interruption probability of the cognitive vehicle user SU is calculated

[0045]

[0046] Furthermore, the calculation in step 2 is The impact of imperfect decoding on the interruption probability of the main vehicle user PU is analyzed, and an experimental comparison is made between perfect decoding and imperfect decoding;

[0047] According to step 6, the interruption probability of the main vehicle user PU is analyzed, and we execute the SU under ipSIC in turn. Conduct analysis and deduction;

[0048] Expressed as in It is expressed as the interruption probability from the transmitting source to the cognitive vehicle user SU; Expressed as:

[0049]

[0050] in,

[0051] Expressed as Among them, P out,p (D=D k ) represents the interruption probability of decoding failure when the main vehicle user combines two links;

[0052] P out,p (D=D k ) is expressed as:

[0053]

[0054] in,

[0055] Finally, the interruption probability of the main vehicle user PU is calculated

[0056]

[0057] Compared with the prior art, the present invention has the following advantages:

[0058] This paper applies relay-cooperative CR-NOMA technology to V2X systems, taking into account complex channels, residual hardware impairments, and non-ideal channel characteristics. Furthermore, it considers the situation in which a cognitive radio network secondary network assists primary network communication in V2X communications, the rapid movement of vehicles during V2X communications, and the impact of double-Rayleigh channel characteristics caused by rapid channel changes. The method provides a practical reference for effectively measuring V2X communication performance under actual non-ideal channel conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a system model diagram;

[0060] Figure 2 It is a schematic diagram of the situation where the outage probability of SU changes with RHI;

[0061] Figure 3 This is a schematic diagram of the impact of channel estimation error on PU disconnection probability; DETAILED DESCRIPTION

[0062] Example 1

[0063] A method for measuring the interruption performance of a cognitive vehicle networking system includes the following steps:

[0064] Step 1: Establish a cognitive non-orthogonal multiple access vehicle network transmission system; the system includes a transmitting source (BS, Base Station), a group of cognitive vehicle users SU in a scene with dense traffic at an urban traffic intersection n(SU, Secondary User) (n=1,2,3) and a main vehicle user (PU, Primary User), where the transmitting source adopts non-orthogonal multiple access (NOMA, Non-orthogonal Multiple Access) technology to send data to the cognitive vehicle user and the main vehicle user, and at the same time the cognitive vehicle user assists the main vehicle user in a collaborative manner to achieve reliable communication. The cognitive vehicle user and the main vehicle user perform actual non-ideal serial interference cancellation (ipSIC) when decoding their own signals, and the actual hardware RF characteristics of the transmitting source, cognitive vehicle user and main vehicle user are non-ideal.

[0065] Step 2: In the cognitive non-orthogonal multiple access vehicle network transmission system, the transmitter sends a composite signal ɑ containing the main vehicle user information x1 and the cognitive vehicle information x2 to the main vehicle user PU and the cognitive vehicle user SU at a transmission power of P1. p x1+ɑ s x2, where ɑ p represents the power allocation coefficient of the main vehicle user information x1, ɑ s represents the power allocation coefficient of the cognitive vehicle user information x2, and ɑ p +ɑ s =1(ɑ p >ɑ s ); Signal transmission will be divided into two time slots, the first time slot and the second time slot; After the cognitive vehicle user SU receives the signal sent by the transmitting source BS, it uses the serial interference cancellation (SIC, Successive Interference Cancellation) technology to decode the signal x1 containing the main vehicle user PU information, and then decodes the signal x2 containing the cognitive vehicle user SU information; Only when the cognitive vehicle user SU successfully decodes the information of x1 and x2, it is considered that the cognitive vehicle user SU has successfully decoded; If the cognitive vehicle user SU fails to successfully decode the information of x1 and x2, it is considered that the cognitive vehicle user SU has failed to decode; The successfully decoded cognitive vehicle user SU will use the SIC technology to decode the received composite signal, and then re-encode the composite signal and forward it to the main vehicle user PU. In particular, due to the limitation of actual hardware capabilities, the SU performs the ipSIC operation during decoding, that is, the SU fails to completely decode x1 and x2; The main vehicle user PU combines and processes the signals from the transmitting source BS and the cognitive vehicle user SU;

[0066] Step 3: Due to the mobility of vehicles, the communication link status between vehicles changes rapidly and dynamically, which will cause the channel state information to be outdated. The linear minimum mean square error is used to model the actual channel state information. represents the actual channel coefficient on the link from the sending node i to the receiving node j, represents the corresponding ideal channel coefficient, and the error between the actual channel coefficient and the ideal channel coefficient is expressed as Among them, CN means it obeys the normal distribution, δ i,j Representing the standard deviation of the corresponding channel estimation error, the formula can be obtained:

[0067]

[0068] Step 4: Considering the fast fading characteristics of the channel in the actual vehicle network mobile scenario, double Rayleigh fading is used to describe the channel fading characteristics. Each link in the system obeys independent and identically distributed double Rayleigh fading. The probability density function (CDF) under fast fading channel is expressed as:

[0069]

[0070] where K0(·) represents the modified Bessel function of the second kind;

[0071] Step 5: Considering that the non-ideal characteristics of the actual hardware will affect the interrupt performance of the system, the residual hardware impairment factor (RHI) is used to describe the impact of the non-ideal characteristics of the actual hardware during signal transmission, and η is used to represent the impact of the non-ideal characteristics of the actual hardware during signal transmission. ij Represents the signal loss value between transmitting node i and receiving node j.

[0072] Step 6: Analyze the interruption probability of the cognitive vehicle user SU;

[0073] In step 2, the signal transmission of the cognitive vehicle user SU is divided into two time slots, and the first time slot and the second time slot are analyzed;

[0074] In the first time slot, the transmitting source BS sends a composite signal to the cognitive vehicle user SU. The signals received by the cognitive vehicle user SU are expressed as follows:

[0075]

[0076] Among them, y SU represents the signal received by the cognitive vehicle user SU, and Represent the theoretical and actual channel coefficients respectively, and obey the double Rayleigh fading distribution; ε b,n represents the channel estimation error; w n The mean is 0 and the variance is δ 2 A complex Gaussian random variable; represents the residual hardware damage RHI at the transmitting source BS and the cognitive vehicle user SU, P1 represents the transmitting source power, t represents the transmitting end, and r represents the receiving end. B,t , K S,r They represent the RHI of the transmitting source BS and the cognitive vehicle user SU respectively.

[0077] In the first time slot, the link from the transmitting source BS to all SUs is interrupted. That is, when any SU receives the composite signal sent from the BS, the SU uses the SIC technology to first decode the main vehicle user signal x1 and then decode the cognitive vehicle user signal x2. If the signal decoding fails, the SU interruption probability is calculated as

[0078] It can be expressed as D represents the entire decoding set, represents an empty set, Pr represents the probability of an event occurring; when SU ​​performs an imperfect SIC operation (ipSIC) during the decoding process, Expressed as Further calculation is:

[0079]

[0080] in,

[0081] Under the premise that the decoding of SU in the first time slot is successful, not all cognitive vehicle user SUs are decoded successfully. Only the successfully decoded SUs are represented as SUs. n , the signal can be re-encoded and forwarded to the main vehicle user PU, while the unsuccessfully decoded SU is denoted as SU m , will also receive SU n Recoded signal. Successfully decoded cognitive vehicle user SU n The set formed is denoted as D, let D k The cognitive vehicle user SU that is successfully decoded n A subset of the set D is successfully decoded in |D k |=k, k=1,2…2 M -1, unsuccessfully decoded cognitive vehicle user SU m The set formed is represented as exist Choose so that each group h n,m The smallest part forms a subset, where h n,m Indicates SU n and SU m The channel gain between them is used to select the optimal cognitive vehicle user from D Forwarding signal, The selection criteria are:

[0082]

[0083] In the second time slot, SU m Failure to decode the received signal leads to signal interruption. m Using SIC technology, first decode the main vehicle user signal x1 and then decode the cognitive vehicle user signal x2. If the signal decoding fails, calculate SU m Interruption probability Expressed as in, Indicates the accumulation of events a to b, Pr(D=D k ) indicates SU n Belongs to the successful decoding set D k The probability P out,s (D=D k ) indicates SU m Decoding SU n The probability of failure in sending a composite signal.

[0084] Similarly, Pr(D=D k ) is expressed as:

[0085]

[0086] Finally, the interruption probability of the cognitive vehicle user SU is calculated

[0087]

[0088] Step 6: Analyze the interruption probability of the main vehicle user PU;

[0089] In step 2, the PU signal transmission between the host vehicle and the user will be divided into two time slots, and the first time slot and the second time slot will be analyzed;

[0090] In the first time slot, the transmitting source BS sends a composite signal to the cognitive vehicle user SU and the main vehicle user PU respectively. The signals received by the cognitive vehicle user SU and the main vehicle user PU are respectively expressed as:

[0091]

[0092]

[0093] Among them, y SU represents the signal received by the cognitive vehicle user SU, represents the signal received by the main vehicle user PU in the first time slot, and Represent the theoretical and actual channel coefficients respectively; ε b,n ,ε b,p represents the channel estimation error w n With w p The mean is 0 and the variance is δ 2 A complex Gaussian random variable; η BN represents the residual hardware damage RHI at the transmitting source BS and the cognitive vehicle user SU, P1 represents the transmitting source power, t represents the transmitter, r represents the receiver, K B,t , K S,r Respectively represent the RHI of the transmitting source BS and the cognitive vehicle user SU. ; η BP represents the residual hardware damage RHI at the transmitting source BS and the main vehicle user PU, K P,r represents the RHI of the primary vehicle user PU;

[0094] In the first time slot, based on step 6, the link from the transmitting source BS to all SUs is interrupted and the direct link from the transmitting source BS to the main vehicle user PU is interrupted, that is, PU receives the data from SU n After the composite signal is sent, the SIC technology is used to treat the cognitive vehicle user signal x2 as interference and directly decode the main vehicle user signal x1. If the signal decoding fails, the PU interruption probability is calculated. Expressed as in It is expressed as the interruption probability from the transmitting source to the cognitive vehicle user SU; It can be expressed as:

[0095]

[0096] in,

[0097] In the second time slot, the cognitive vehicle user SU that successfully decodes the composite signal n The information is forwarded to the primary vehicle user PU. At this time, the signal received by the primary vehicle user PU can be expressed as:

[0098]

[0099] in Represent the theoretical and actual channel coefficients, ε n,p represents the channel estimation error, P2 represents The transmission power, The signal sent by the cognitive user after re-encoding using the ipSIC operation.

[0100] In the second time slot, the main vehicle user PU receives the data from SU n The composite signal sent by the main vehicle user PU also receives the signal of the direct link sent by the transmitting source BS. The main vehicle user PU is interrupted when it combines the two signals. That is, after the PU combines the two information, it uses the ipSIC technology to recognize the vehicle user signal. It is considered as interference and directly affects the main vehicle user signal. Decode. If decoding fails, calculate the PU interruption probability Expressed as Among them, P out,p (D=D k ) represents the interruption probability of decoding failure when the main vehicle user combines two links;

[0101] Similarly, P out,p (D=D k ) can be expressed as

[0102]

[0103] in,

[0104] Finally, the interruption probability of the main vehicle user PU is calculated

[0105]

[0106] Figure 2 、 Figure 3 It is the system performance verification diagram; Figure 2 Schematic diagram of the SU outage probability changing with RHI and Figure 3 The schematic diagram of the influence of channel estimation error on PU disconnection probability shows that the analysis result is consistent with the simulation result, which proves the correctness of the method of the present invention.

[0107] Any matters not described in detail in this specification are prior art known to those skilled in the art. Although the above description of the present invention is based on specific embodiments to facilitate understanding of the present invention by those skilled in the art, it should be understood that the present invention is not limited to the scope of the specific embodiments. As long as various modifications are within the spirit and scope of the present invention as defined and determined by the appended claims, such modifications will be obvious to those skilled in the art, and all inventions and creations utilizing the concepts of the present invention are protected.

Claims

1. A method for measuring the interruption performance of a cognitive vehicle networking system, characterized in that: The following steps are involved: Step 1: Establish a cognitive non-orthogonal multiple access vehicle network transmission system; the system includes a transmitting source BS, a group of cognitive vehicle users SU n (n=1,2…,M) and the main vehicle user PU; wherein the transmitting source uses non-orthogonal multiple access (NOMA) technology to send data to the cognitive vehicle user and the main vehicle user. At the same time, the cognitive vehicle user assists the main vehicle user in a collaborative manner to achieve reliable communication. The cognitive vehicle user and the main vehicle user perform actual non-ideal serial interference cancellation (ipSIC) when decoding their own signals. The actual hardware RF characteristics of the transmitting source, the cognitive vehicle user, and the main vehicle user are non-ideal. Step 2: In the cognitive non-orthogonal multiple access vehicle network transmission system, the transmitter sends a composite signal ɑ containing the main vehicle user information x1 and the cognitive vehicle information x2 to the main vehicle user PU and the cognitive vehicle user SU at a transmission power of P1. p x1+ɑ s x2, where ɑ p represents the power allocation coefficient of the main vehicle user information x1, ɑ s represents the power allocation coefficient of the cognitive vehicle user information x2, and ɑ p +ɑ s =1(ɑ p >ɑ s ); Signal transmission will be divided into two time slots, the first time slot and the second time slot; After the cognitive vehicle user SU receives the signal sent by the transmitting source BS, it uses the serial interference cancellation SIC technology to decode the signal x1 containing the main vehicle user PU information, and then decodes the signal x2 containing the cognitive vehicle user SU information; Only when the cognitive vehicle user SU successfully decodes the information of x1 and x2, it is considered that the cognitive vehicle user SU has successfully decoded; If the cognitive vehicle user SU fails to successfully decode the information of x1 and x2, it is considered that the cognitive vehicle user SU has failed to decode; The successfully decoded cognitive vehicle user SU will use the SIC technology to decode the received composite signal, and then re-encode the composite signal and forward it to the main vehicle user PU. In particular, due to the limitation of actual hardware capabilities, the SU performs the ipSIC operation during decoding, that is, the SU fails to completely decode x1 and x2; The main vehicle user PU combines and processes the signals from the transmitting source BS and the cognitive vehicle user SU; Step 3: Due to the mobility of vehicles, the communication link status between vehicles changes rapidly and dynamically, which will cause the channel state information to be outdated. The linear minimum mean square error is used to model the actual channel state information. represents the actual channel coefficient on the link from the sending node i to the receiving node j, represents the ideal channel coefficient on the link from the sending node i to the receiving node j. The error between the actual channel coefficient and the ideal channel coefficient is expressed as CN means it obeys normal distribution, δ i,j represents the standard deviation of the corresponding channel estimation error; then Step 4: Considering the fast fading characteristics of the channel in the actual vehicle network mobile scenario, double Rayleigh fading is used to describe the channel fading characteristics. Each link in the system obeys independent and identically distributed double Rayleigh fading. The probability density function CDF under fast fading channel is expressed as: where K0(·) represents the modified Bessel function of the second kind; Step 5: Considering that the non-ideal characteristics of the actual hardware will affect the interrupt performance of the system, the residual hardware damage factor RHI is used to describe the impact of the non-ideal characteristics of the actual hardware during signal transmission, and η is used to describe the impact of the non-ideal characteristics of the actual hardware during signal transmission. ij represents the signal loss value between the transmitting node i and the receiving node j; Step 6: Analyze the interruption probability of the cognitive vehicle user SU; There are two situations in which the cognitive vehicle user SU is interrupted: The first one is that in the first time slot, the link from the transmitting source BS to all cognitive vehicle users SU is interrupted, that is, when any cognitive vehicle user SU receives the composite signal sent from the transmitting source BS, the cognitive vehicle user SU uses the SIC technology to first decode the main vehicle user PU signal x1 and then decode the cognitive vehicle user signal x2. If the signal decoding fails, the interruption probability of the cognitive vehicle user SU is calculated. The second type is that, under the premise that the decoding of SU in the first time slot is successful, not all cognitive vehicle user SUs are decoded successfully. Only the successfully decoded SUs are represented as SUs. n , the signal can be re-encoded and forwarded to the main vehicle user PU, while the unsuccessfully decoded SU is denoted as SU m , will also receive SU n Recoded signal; in the second time slot, SU m Failure to decode the received signal results in a signal interruption event, i.e. SU m Using SIC technology, first decode the main vehicle user signal x1 and then decode the cognitive vehicle user signal x2. If the signal decoding fails, calculate SU m Interruption probability Finally, the interruption probability of the cognitive vehicle user SU is calculated Step 7, analyzing the interruption probability of the main vehicle user PU; There are two situations in which the main vehicle user PU is interrupted during signal transmission: The first one is that in the first time slot, based on step 6, the link from the transmitting source BS to all SUs is interrupted and the direct link from the transmitting source BS to the main vehicle user PU is interrupted, that is, PU receives the data from SU n After the composite signal is sent, the SIC technology is used to treat the cognitive vehicle user signal x2 as interference and directly decode the main vehicle user signal x1; if the signal decoding fails, the PU interruption probability is calculated The second type is that in the second time slot, the main vehicle user PU receives the data from SU n The composite signal sent by the main vehicle user PU also receives the signal of the direct link sent by the transmitting source BS. When the main vehicle user PU combines the two signals, an interruption occurs. That is, after the PU combines the two information, it uses the SIC technology to regard the cognitive vehicle user signal x2 as interference and directly decodes the main vehicle user signal x1. In the case of decoding failure, the PU interruption probability is calculated. Calculate the interruption probability of the main vehicle user PU 2. The method for measuring the interruption performance of a cognitive vehicle networking system according to claim 1, characterized in that: The signal transmission in step 2 is divided into two time slots, a first time slot and a second time slot; In the first time slot, the transmitting source BS sends a composite signal to the cognitive vehicle user SU and the main vehicle user PU respectively. The signals received by the cognitive vehicle user SU and the main vehicle user PU are respectively expressed as: Among them, y SU represents the signal received by the cognitive vehicle user SU, represents the signal received by the main vehicle user PU in the first time slot, P1 represents the transmitting source power, and represent the theoretical and actual channel coefficients respectively; ε b,n ,ε b,p represents the channel estimation error; w n With w p The mean is 0 and the variance is δ 2 A complex Gaussian random variable; Represents the residual hardware impairment RHI on the transmission link between the transmitting source BS and the cognitive vehicle user SU, t represents the transmitter, r represents the receiver, K B,t , K S,r They represent the RHI of the transmitting source BS and the cognitive vehicle user SU as the receiving end; Represents the residual hardware damage RHI on the transmission link between the transmitting source BS and the main vehicle user PU, K P,r Indicates the RHI of the main vehicle user PU as the receiving end; Successfully decoded cognitive vehicle user SU n The set formed is denoted as D, let D k The cognitive vehicle user SU that is successfully decoded n A subset of the set D is successfully decoded in |D k |=k,k=1,2···2 M -1, unsuccessfully decoded cognitive vehicle user SU m The set formed is represented as exist Choose so that each group h n,m The smallest part forms a subset, where h n,m Indicates SU n and SU m The channel gain between them is used to select the optimal cognitive vehicle user from D Forwarding signal, The selection criteria are: In the second time slot, the cognitive vehicle user SU that successfully decodes the composite signal n The information is forwarded to the primary vehicle user PU. At this time, the signal received by the primary vehicle user PU is expressed as: in, Represent the theoretical and actual channel coefficients, ε n,p represents the channel estimation error, P2 represents The transmission power, The signal sent by the cognitive user after re-encoding using the ipSIC operation.

3. The method for measuring the interruption performance of a cognitive vehicle networking system according to claim 1, characterized in that: The calculation in step 2 The interruption probability of ipSIC operation is analyzed for the cognitive vehicle user SU that is not successfully decoded. m The impact of outage probability, and experimental comparison of ideal SIC and ipSIC; According to step 6, analyze the cognitive vehicle user SU m The interruption probability of ipSIC is Conduct analysis and deduction; Expressed as D represents the entire decoding set, represents an empty set, Pr represents the probability of an event occurring; when SU ​​performs an imperfect SIC operation during the decoding process, Expressed as Further calculation is: in, Expressed as in, Indicates the accumulation of events a to b, Pr(D=D k ) indicates SU n Belongs to the successful decoding set D k The probability of out,s (D=D k ) indicates SU m Decoding SU n The probability of failure in sending a composite signal; Similarly, Pr(D=D k ) is expressed as: Finally, the interruption probability of the cognitive vehicle user SU is calculated 4. The method for measuring the interruption performance of a cognitive vehicle networking system according to claim 1, characterized in that: The calculation in step 2 The impact of imperfect decoding on the interruption probability of the main vehicle user PU is analyzed, and an experimental comparison is made between perfect decoding and imperfect decoding; According to step 6, the interruption probability of the main vehicle user PU is analyzed, and we execute the SU under ipSIC in turn. Conduct analysis and deduction; Expressed as in It is expressed as the interruption probability from the transmitting source to the cognitive vehicle user SU; Expressed as: in, Expressed as Among them, P out,p (D=D k ) represents the interruption probability of decoding failure when the main vehicle user combines two links; P out,p (D=D k ) is expressed as: in, Finally, the interruption probability of the main vehicle user PU is calculated

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