CN108900269A - The Analysis on BER Performance method of the double medium cooperation communication systems of wireless and power line - Google Patents

Abstract

The invention provides a bit error rate performance analysis method of a wireless and power line dual-media cooperative communication system, and belongs to the technical field of dual-media cooperative communication. The dual-media cooperative communication system includes a signal source S, a relay node R, and a destination node D. The wireless communication link SR is between the signal source S and the relay node R, and the wireless communication link SD is between the signal source S and the destination node D. The power line communication link RD is between the relay node R and the destination node D. This method first calculates the bit error rate P ₁ ^BER of SR, and then calculates the distribution parameters of the SD signal-to-noise ratio after approximating the log-normal distribution based on the probability density function approximation algorithm of the moment generating function equation; then calculates SD and RD for selection The cumulative distribution function of the instantaneous output signal-to-noise ratio and the bit error rate P ₂ ^BER of the second hop after permanent combination; finally, the total bit error rate is obtained by combining P ₁ ^BER and P ₂ ^BER , and performance analysis is performed according to the total bit error rate. The invention reduces the computational complexity, can obtain the optimal distribution parameter of the instantaneous signal-to-noise ratio, and accurately calculates the bit error rate of the system.

Description

Bit error rate performance analysis method for wireless and power line dual-media cooperative communication system

technical field

The invention relates to the technical field of dual-media cooperative communication systems, in particular to a bit error rate performance analysis method of a wireless and power line dual-media cooperative communication system.

Background technique

Power Line Communication (PLC) and wireless communication technology are important components of distribution network communication, and have broad application prospects in the fields of smart electricity consumption and home Internet of Things. PLC can rely on the existing power line infrastructure to transmit information; wireless communication has the characteristics of flexible wireless access and simple networking. Wireless communication and PLC have their own characteristics. Combined power line and wireless dual-media cooperative communication technology can integrate resources, optimize complementarity, save construction costs, and improve overall system performance.

The latest research models power line channel fading as a lognormal distribution (Log normal, LogN) model. Wireless communication mainly adopts distributions such as Rayleigh and Nakagami. The Nakagami model can simulate deep fading and shallow fading, it is easy to handle in mathematics, and has been widely used; the Rayleigh distribution is a special case of Nakagami in essence.

In the power line and wireless cooperative relay system, the system performance analysis for Nakagami-LogN mixed fading conditions has the following main problems: there is no closed expression for the theoretical performance of communication, the complexity of performance calculation is too high, and the performance analysis of key technologies relies too much on computer simulation, etc.

Considering that under the Nakagami fading condition, the instantaneous fading energy and SNR of the channel satisfy the Gamma distribution, and the Gamma distribution and the LogN distribution have a certain similarity, this patent proposes a LogN distribution parameter for the approximation of the Gamma and LogN distribution functions The calculation method can be applied to the system theoretical performance calculation under Nakagami-LogN mixed fading conditions, and has a wide application prospect and practical value.

Contents of the invention

The purpose of the present invention is to provide a wireless and power line dual-media cooperative communication system that can simplify the complexity of system performance calculation, obtain the optimal distribution parameters of the instantaneous signal-to-noise ratio, and accurately calculate the bit error rate and interruption rate of the system The efficiency performance analysis method is used to solve the technical problems in the above-mentioned background technology.

In order to achieve the above object, the present invention has taken the following technical solutions:

The present invention provides a bit error rate performance analysis method for a wireless and power line dual-media cooperative communication system. The dual-media cooperative communication system includes a signal source S, a relay node R, and a destination node D. The signal source S is connected to The wireless communication between the relay node R and the destination node D, and the power line communication between the relay node R and the destination node D, the method includes the following steps:

Step S110: calculating the bit error rate P ₁ ^BER of the wireless link SR between the signal source S and the relay node R;

Step S120: Establish a performance function model based on the PDF approximation algorithm of the moment generating function MGF equation, and obtain parameters approximate to the LogN distribution according to the performance function model;

Step S130: For the wireless link SD from the signal source S to the destination node D and its signal-to-noise ratio γ _WD , and the power line link RD from the relay node R to the destination node D and its signal-to-noise ratio Ratio γ _PLD , obtain the cumulative distribution function F ^DF (λ) of the instantaneous output signal-to-noise ratio γ ^DF after SC is merged;

Step S140: According to the F ^DF (λ), the bit error rate performance analysis under the mixed fading condition is converted into the performance analysis under the same LogN distribution condition, and the bit error rate P ₂ ^BER of the second hop after the SC combination is obtained;

Step S140: Combining the bit error rate P ₁ ^BER and the bit error rate P ₂ ^BER to obtain the total bit error rate of the system

Further, the step S110 includes:

Combined with the wireless channel fading coefficient and the average signal-to-noise ratio, using the moment generating function MGF and Gaussian hypergeometric function, the closed expression of the bit error rate P ₁ ^BER can be obtained as:

Among them, Ω _R represents the variance of the fading amplitude of the wireless link SR, m _R represents the fading parameter of the wireless link SR, Δ _W represents the average signal-to-noise ratio of the wireless communication link, ₂ F ₁ (.,.;.;.) Represents Gaussian hypergeometric function, Γ(.) represents Gamma function.

Further, the step S120 includes:

Step S121: Establish the MGF equations of Gamma distribution and LogN distribution variables respectively:

It is known that H _WD represents the fading coefficient of the wireless link SD, then Satisfy G(α _D , β _D ), where α _D ＝m _D , β _D ＝Ω _D /m _D ; where Ω _D represents the variance of the fading amplitude of the wireless link SD, and m _D represents the fading magnitude of the wireless link SD Shape parameter, in order to satisfy channel fading normalization, set Ω _D =1;

The MGF satisfies Approximate The MGF of the distributed variable satisfies When i takes 1 and 2 respectively, it corresponds to variables s ₁ and s ₂ .

Distribute G(α _D ,β _D ) Approximate to Set M _Pl (s _i )=M _D (s _i ) to get the approximate MGF equation:

Among them, w _n and a _n represent the weight and zero point of the Gauss-Hermite formula respectively.

Step S122: Based on the approximated MGF equation established in step S121, a performance function model is established, and the parameters of the approximated LogN distribution are obtained:

with G(α _D ,β _D ) distribution and The difference in the distribution is the smallest to establish a performance function model for the goal:

The following conditions:

1):

2):

3): H _j =0.01+0.05*(j-1);

4): j=1,2,...N;

5): s ₁ >0;

6): s ₂ >0;

Among them, H _j represents the sampling value of the wireless channel fading H, and N represents the total sampling points of the probability density function;

According to the performance function model, the PDF distribution parameters s ₁ , s ₂ and Approximate parameters μ _D and σ _D of LogN distribution;

Step S123: According to Combined with the parameters μ _D and σ _D , determine that γ _WD is approximated as After the parameters μ _wD and in, μ _wD =ln( _ΔW )+μ _D .

Further, the step S130 includes:

It is known that H _PLD represents the fading coefficient of the power line link RD, and H _PLD satisfies Let γ _PLD represent the instantaneous signal-to-noise ratio at the receiving end of the power line link RD, and according to the average signal-to-noise ratio _ΔPL and the nature of the logarithmic normal variable, determine will also satisfy the lognormal distribution and

Combining the output signal-to-noise ratio γ _PLD of the power line link RD and the output signal-to-noise ratio γ _WD of the wireless link SD, the cumulative distribution function F ^DF (λ) of the instantaneous output signal-to-noise ratio γ ^DF after the combination of SCs is obtained:

F ^DF (λ) = Pr(γ ^DF <λ) = Pr(γ _WD <λ);

Using the complementary cumulative distribution function of the standard normal distribution, also known as the Q function, the calculation is obtained:

Among them, λ represents the cutoff threshold signal-to-noise ratio of the combined SCs.

Further, the step S140 includes:

Integrating the cumulative distribution function F ^DF (λ), converting the bit error rate performance analysis under mixed fading conditions into performance analysis under the same LogN distribution condition, then the bit error rate P ^BER is _:

in, Indicates that the pulse number k of the power line link RD obeys the Poisson distribution with the mean value A; PN indicates the maximum number of impulse noise, and PN is greater than 20;

Convert the bit error rate performance analysis under the condition of mixed fading to the performance analysis under the same LogN distribution condition, then the bit error rate P ₂ ^BER is:

Among them, according to the fading distribution parameters of the power line link RD and The approximate distribution parameter of Solve for constants W _tk , V _tk , U _tk .

Further, the total bit error rate of the system is obtained by combining the bit error rate P ₁ ^BER and the bit error rate P ₂ ^BER for:

The invention has beneficial effects: the complexity of system performance calculation can be simplified, the optimal distribution parameter of the instantaneous signal-to-noise ratio can be obtained, and the bit error rate and interruption rate of the system can be accurately calculated.

Additional aspects and advantages of the invention will be set forth in part in the description which follows, and will become apparent from the description, or may be learned by practice of the invention.

Description of drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the accompanying drawings that need to be used in the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For Those of ordinary skill in the art can also obtain other drawings based on these drawings without making creative efforts.

FIG. 1 is a structural diagram of a wireless and power line dual-media cooperative communication system according to an embodiment of the present invention.

FIG. 2 is a comparative schematic diagram of PDF curves when _ΔW is 1 according to an embodiment of the present invention.

FIG. 3 is a comparative schematic diagram of PDF curves when _ΔW is 2 according to the embodiment of the present invention.

Fig. 4 is a schematic diagram showing a comparison between outage probability Monte Carlo simulation performance and theoretical performance according to an embodiment of the present invention.

FIG. 5 is a schematic diagram showing a comparison between the Monte Carlo simulation performance of the bit error rate and the theoretical performance according to the embodiment of the present invention.

Detailed ways

Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals denote the same or similar elements or modules having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

Those skilled in the art will understand that unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the word "comprising" used in the description of the present invention refers to the presence of said features, integers, steps, operations, elements and/or modules, but does not exclude the presence or addition of one or more other features, Integers, steps, operations, elements, modules, and/or groups thereof.

It should be noted that, in the embodiments of the present invention, unless otherwise specified and limited, the terms "connection" and "fixation" should be interpreted in a broad sense, which may be a fixed connection or a detachable connection. Or integrated, can be mechanically connected, can also be electrically connected, can be directly connected, can also be indirectly connected through an intermediary, can be the internal communication of two components, or the interaction relationship between two components, unless there is a clear limit. Those skilled in the art can understand the specific meanings of the above terms in the embodiments of the present invention according to specific situations.

Those skilled in the art can understand that, unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It should also be understood that terms such as those defined in commonly used dictionaries should be understood to have a meaning consistent with the meaning in the context of the prior art, and unless defined as herein, are not to be interpreted in an idealized or overly formal sense explain.

In order to facilitate the understanding of the embodiments of the present invention, the following will further explain and illustrate by taking specific embodiments as examples in conjunction with the accompanying drawings, and the embodiments do not constitute a limitation to the embodiments of the present invention.

Those skilled in the art should understand that the accompanying drawing is only a schematic diagram of an embodiment, and the components or devices in the accompanying drawings are not necessarily necessary for implementing the present invention.

Embodiment one

As shown in FIG. 1 , Embodiment 1 of the present invention provides a wireless and power line dual-media cooperative communication system, which adopts a dual-media hybrid cooperative three-node (terminal S, D and relay R) two-hop relay model. Wireless communication (WIC) is performed between the mobile terminal S and the nodes R, D. Power line (PLC) communication is performed between nodes R and D. The fading of the wireless channel satisfies the Nakagami distribution.

In the above system, the first time slot is for _{S to send a signal X S to} the relay node R and the destination node D with the transmission power PS; the second time slot is for R to process the received signal (hard decision decoding) to obtain the relay node signal, and then send the signal to the destination node D with power _PR .

Channels in both slots are affected by multiplicative fading and additive noise. Since the implementation complexity of selective SC combining is relatively low, and it is suitable for dual-media hybrid communication systems, terminal D finally uses the SC combining algorithm to combine the received signals.

In Figure 1, S refers to smart meters or sensors on power equipment or independently, such as smart meters in buildings or homes, wireless sensor nodes in underground substations, non-contact infrared temperature cameras in substations, mobile RFID card reader etc. The typical application scenario corresponding to Figure 1: In order to solve the problems that the PLC cannot be accessed by mobile, the penetration ability of high-frequency radio waves is limited, and the fading is relatively large, the smart instrument or sensor (S) and the gateway D adopt wireless access (S —>R) and PLC-wireless parallel relay (R—>D) hybrid cooperation mode to achieve mobile access and long-distance communication.

The wireless signals received by nodes R and D in the first time slot are:

Among them, the noise n _WR and n _WD satisfy the normal distribution N(0,N _W ); H _WR and H _WD are the wireless fading coefficients, which satisfy the Nakagami distribution:

Where I∈{D,R}, m _I ≥ 0.5 is the Nakagami parameter; Г(x) is the gamma function; Is the variance of the fading amplitude. In order to ensure that the fading does not change the average power of the received signal, normalization is performed so that Ω _I is 1.

Let _ΔW = _PS / _NW denote the channel average signal-to-noise ratio. Then according to the forwarding formulas (1) and (2), the instantaneous SNR at the receiving end of the wireless channel are:

A known Satisfy the Gamma distribution G(α _I ,β _I ), which has the following form:

Among them, the parameter relationship between G(α _I , β _I ) and Nakagami distribution satisfies α _I ＝m _I ; β _I ＝Ω _I /m _I . According to the properties of Gamma distribution, under the same average signal-to-noise ratio, when Δ _W is a fixed constant, there is γ _WI ～G(m _I , Δ _W Ω _I /m _I ).

In the second time slot, the relay node R uses the decoding and forwarding DF protocol to make a hard decision on the received signal, and then forwards it to the destination node D with power P _R . Let X _R represent the signal forwarded by the relay, then the signal received by the receiving end is:

where H _PLD is the power line fading coefficient satisfying

Among them, μ _PLD and σ _PLD represent the mean value and mean square error of _lnHP , respectively. Normalize the energy of the channel fading envelope to ensure that the channel fading does not change the average power of the signal, so that,

which is

In formula (7), n _PLD is the impulse noise of the power line, and the Mid-A impulse noise model is adopted. The model consists of Gaussian background noise N _G and impulse noise N _I , and the probability density function of the impulse noise amplitude Z is:

Wherein N _k =N ₀ ·(k/A+T)/(1+T), represents the instantaneous total noise power of the power line, and _T =NG/N _I represents the ratio of the background noise power to the impulse noise power. N ₀ =N _G +N _I is the average total noise power. At a specific sampling moment, the impulse noise of the Mid-A model is superimposed by k Gaussian noises, and each noise model satisfies N(0, N _I /A). The number k of pulses obeys the Poisson distribution with mean A (e ^-A ·A ^k )/k! , PN represents the maximum number of impulse noise, and PN is greater than 20.

Let Δ _PL =P _R /N _k , the instantaneous signal-to-noise ratio at the receiving end of the power line can be expressed as:

Then, after node D adopts SC, the total output signal-to-noise ratio of the system is:

γ ^DF = max(γ _PLD ,γ _WD ) (11)

The instantaneous mutual information of the system is:

Embodiment two

Embodiment 2 of the present invention provides a performance analysis method for the outage probability of the dual-media cooperative system shown in FIG. 1 . In order to obtain the outage probability of the system, it is necessary to analyze the information rate of each branch. When the system information rate R is lower than the required minimum rate threshold, the normal communication of the system will be interrupted. According to the Shannon formula, the information rate of each branch is directly related to the signal-to-noise ratio, so the PDF of the signal-to-noise ratio of each branch is analyzed first.

The signal-to-noise ratio γ _WR and γ _WD of the wireless channel satisfy the Gamma distribution. When the signal-to-noise ratio at the receiving end is smaller than the signal-to-noise ratio γ _th corresponding to the interruption threshold, the communication link is interrupted. According to the formulas (4) and (6), the Gamma distribution function is integrated, then the outage probability of the SR branch is:

Among them, ν(a,b) represents the incomplete Gamma function, and the mathematical expression is Г (x) is the gamma function.

Similarly, the outage probability of the wireless direct SD branch is:

It is known that the fading coefficient H _PLD of the power line channel satisfies LogN. According to the LogN property, when the average signal-to-noise ratio Δ _PL is constant, then γ _PLD will also satisfy the lognormal distribution and

For γ _PLD satisfying the LogN distribution, the interruption probability of the PLC link can be expressed by the Q function:

Combined with the outage probability of each branch in (13), (14) and (15), the total outage probability of the dual-media cooperative relay system under the condition of mixed fading and impulse noise can be calculated as:

Embodiment three

Embodiment 3 of the present invention provides a bit error rate performance analysis method of the system shown in FIG. 1 .

In order to obtain the bit error rate of the DF cooperative relay system, the communication system is divided into two hops: the SR link is the first hop, and the RD and SD parallel communication links are the second hop. Let P ₁ ^BER be the bit error rate of the SR link (first hop); P ₂ ^BER is the bit error rate of the second hop parallel communication link after SC combining.

It is known that the fading coefficient H _WR of the SR branch of the first hop satisfies the Nakagami distribution. When the average signal-to-noise ratio of the link is Δ _W , integrate H _WD and use MGF and Gaussian hypergeometric function to obtain wireless SR The closed expression of the bit error rate of the branch:

Among them, ₂ F ₁ (.,.;.;.) is a Gaussian hypergeometric function.

In order to obtain the bit error rate of the second hop, it is necessary to calculate the cumulative distribution function of the instantaneous output signal-to-noise ratio γ ^DF after the system adopts SC combination. Because the signals of the wireless branch and the power line branch in the second hop are independent of each other, the cumulative distribution function F ^DF (λ) is obtained as:

F ^DF (λ) = Pr(γ ^DF <λ) = Pr(γ _WD <λ)Pr(γ _PLD <λ) (18)

Obviously, formula (18) involves the product of formula (14) and formula (15), and the bit error rate P ₂ ^BER can be obtained by integrating formula (18) F ^DF (λ):

In the case of mixed fading, integrating functions such as ν(a, b) and Γ(x) in formula (18), the algorithm complexity is relatively large. Therefore, this embodiment adopts the method of PDF approximation to formula (19) Process to expect a closed expression.

Due to the similarity between the LogN distribution and the Gamma distribution, the distribution of G(α _D , β _D ) can be Approximate to According to the nature of the LogN distribution, the signal-to-noise ratio γ _WD will also obey the LogN distribution, so the bit error rate performance analysis can be transformed into a performance analysis problem under the same LogN distribution.

In the process of PDF approximation, the PDF parameters after approximation are usually solved in the way that the PDF statistics are equal. Let the mean and variance of G(α _D ,β _D ) and LogN(μ _D ,σ ² _D ) be equal, then:

After the equation transformation, the key parameters of LogN can be obtained:

Aiming at the problem of poor approximation accuracy when using the method of equal mean and variance to perform PDF approximation. The third embodiment proposes a PDF approximation algorithm based on a moment generating function (Moment Generating Function, MGF) equation, which has high precision and can be used to calculate the PDF parameters of the instantaneous signal-to-noise ratio γ _WD .

A known Satisfy the Gamma distribution G(α _D , β _D ), where α _D ＝m _D , β _D ＝Ω _D /m _D , Ω _D ＝1;

The MGF satisfies The MGF of the distributed variable satisfies

Among them, H _WD represents the fading coefficient of the wireless link SD, i=(1,2), then the distribution of G(α _D ,β _D ) is calculated using the MGF approximation method Approximate to Make M _Pl (s _i )=M _D (s _i ) to get:

Among them, w _n and a _n represent the weight and zero point of the Gauss-Hermite formula respectively, and GN represents the weight of the Gauss-Hermite formula and the number of zero points, which can generally be 5, 8 or 12. The larger the value of GN, the approximate calculation of Gauss-Hermite The higher the accuracy is.

As shown in Fig. 2, it is a schematic diagram comparing the PDF curves of H2 _WD under different approximation methods when _ΔW is 1. Under the condition of channel fading normalization (Ω _D =1), for different combinations of parameters m and s ₁ , s ₂ , the comparison of PDF curves of the two approximation methods for H2 _WD is given. It can be seen from Fig. 2 that, compared with the PDF statistical value approximation method, although the MGF equation approximation method lacks analytical expressions, it can be optimized by s ₁ and s ₂ , and the accuracy of the algorithm is relatively high; the smaller the fading parameter m _D , The more serious the channel fading is, so the MGF equation approximation method is suitable for the case of low channel fading. When m _D > 1.5, the probability density approximation effect of the channel is better; when m _D > 1.5, s ₁ can be set as 3; s ₂ increases with the increase of m _D value, when m _D = 2, s ₂ takes 7; when m _D increases to 2.5, s ₂ can take 10; when m _D = 3, s ₂ It is more appropriate to take 15.

Embodiment Four

Embodiment 4 of the present invention provides a method for reducing the parameters μ _D and A method of calculating complexity, which is based on the goal of minimizing the difference of PDF curves, and establishes a performance function model.

In order to reduce complexity, _s1 is set to 3 in this embodiment. In practical applications, mathematical modeling can be carried out with the goal of minimizing the difference of probability density curves, and the best combination of s ₁ and s ₂ can be solved. For the wireless fading parameters α _D ＝m _D ; β _D ＝Ω _D /m _D , use PDF expressions (6) and ( ₈ ), with _s1 and s2 as variables, establish the following mathematical model:

The following conditions:

1):

2):

3): H _j =0.01+0.05*(j-1);

4): j=1,2,...N;

5): s ₁ >0;

6): s ₂ >0;

Among them, H _j represents the sampling value of the wireless channel fading H, and N represents the total number of sampling points of the probability density function (N=100 is selected in this paper). The mathematical model takes the coincidence degree of the PDF curve as the optimization goal, calculates the square of the difference between the two probability density function values corresponding to each fading sample value H _i , and then weights it. The mathematical model can be solved by intelligent optimization algorithms such as genetic algorithm. Using the above method, the optimal s value approximated by the MGF equation can be established, as shown in Table 1.

Table 1

Embodiment five

Embodiment 5 of the present invention provides a method of first approximating the fading normalized PDF, and then calculating the equivalent parameter of γ _WD in combination with the signal-to-noise ratio Δ _W. The specific steps are summarized as follows:

1) at That is, under the condition of Ω _D = 1, for Different fading parameters m _D , using MGF equation approximation, s ₁ and s ₂ optimal selection method, calculate G(α _D , β _D ) to approximate the parameters μ _D and σ _D of LogN distribution;

2) because In the second step, the variable γ _WD needs to be determined according to Δ _W to approximate After the key parameters:

σ _WD ² =σ _D ² (24)

μ _WD ＝ln( _ΔW )+μ _D (25)

According to the above calculation steps, as shown in FIG. 3 , when Δ _W is 2, it is a schematic diagram comparing PDF curves of γ _WD under different approximation methods. In FIG. 3 , compared with the mean-variance approximation method, the MGF method adopted in this embodiment has a better approximation effect. Obviously, the MGF approximation method proposed above can obtain better PDF approximation effect without repeated computer numerical experiments.

In the fourth embodiment, after the PDF approximate processing, the bit error rate performance analysis under the mixed fading condition is converted into a performance analysis problem under the same LogN distribution condition, then the bit error rate performance of the second hop is:

Where W _tk , V _tk , U _tk constants and power line channel fading distribution parameters and The approximate distribution parameter of related, the following relationship is satisfied:

Y _t,k =σ _L +T ₂ +4(μ _L +R2 _k -ln0.5)σ _L /R3 _k ² ;

T ₁ =0.769; T ₂ =1.527; T ₃ =1.393;

The values of R1 _k , R2 _k and R3 _k are shown in Table 2:

Table 2

According to (17) and (26), the bit error rates P ₁ ^BER and P ₂ ^BER of the two-hop link under BPSK modulation can be calculated, and finally the total bit error rate of the hybrid cooperative system for:

Simulation comparison experiment

In order to verify the accuracy of the theoretical formula, a Monte Carlo simulation experiment was carried out using Matlab software. The Monte Carlo simulation method, also known as the statistical experiment method, is a stochastic simulation and calculation method based on probability and statistical theory. It uses statistical sampling theory to approximately solve mathematical and engineering problems, and has been widely used in the field of information and communication. In experimental verification. First, the simulation performance is compared with the theoretical performance of numerical calculations to ensure the reliability of the subsequent analysis of the mechanism of mixed fading and power affecting system performance.

Referring to the existing references, without loss of generality, during the simulation and calculation process, if there is no special instruction, the parameters in the model in Figure 1 adopt the following default settings: the power is defined by the variance of the noise PDF distribution, and the total power of the system is set to 2 , P _S ＝1, _PR ＝1; In order to highlight the impact of channel fading and noise distribution on performance, it is assumed that the average SNR of the system channel is SNR, N _W ＝N _k ＝1/SNR, that is, Δ _PL ＝ Δ _W = Δ; parameters of impulse noise: A = 0.2, T = 0.01, the maximum value of k in the theoretical formula is PN = 100.

Using the above parameter settings, let MGF represent the moment generating function approximation, and Mean-Var represent the mean variance approximation. Figure 4 and Figure 5 compare the outage probability and bit error rate performance of the DF relay system with different channel attenuation parameters. Considering that in practical applications, the channel condition of the direct link SD is not as good as that of the short-distance wireless link SR, m _D is set to 1 in the simulation, and the value of m _R is greater than 1. The analysis can draw the following conclusions:

1) In Figure 4, since the derived outage probability formula does not involve probability density approximation, as the SNR increases, the theoretical performance (theo) and simulation (simu) performance curves of outage probability calculated according to the theoretical formula are relatively consistent, which verifies the outage probability The reliability of the theoretical formula. In Fig. 4, when the fading index is constant, the greater the average signal-to-noise ratio SNR, the smaller the system outage probability.

2) Figure 5 compares the simulation (simu) and theoretical results (theo) of the system bit error rate. Although the probability density of Gamma distribution and LogN distribution is approximated on the direct link SD, under the condition of high signal-to-noise ratio (when SNR is greater than 14dB), the theoretical performance and simulation performance are basically consistent.

In summary, the combined power line and wireless dual-media cooperative communication technology described in the embodiments of the present invention can integrate superior resources, save construction costs, and improve overall system performance. For the dual-media hybrid cooperative system, a hybrid channel fading and multi-dimensional impulse noise model based on Nakagami and LogN is used to establish a system performance analysis framework and use MGF equation approximation and other algorithms to solve the closed system performance expression. For indoor and outdoor general wireless Nakagami fading, the signal-to-noise ratio of wireless branches using Gamma distribution-LogN distribution approximation transformation has good reliability. The relevant conclusions can provide the necessary theoretical support for the application of indoor and outdoor dual-media cooperative communication technology.

It can be seen from the above description of the implementation manners that those skilled in the art can clearly understand that the present invention can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the essence of the technical solution of the present invention or the part that contributes to the prior art can be embodied in the form of software products, and the computer software products can be stored in storage media, such as ROM/RAM, disk , CD, etc., including several instructions to make a computer device (which may be a personal computer, server, or network device, etc.) execute the methods described in various embodiments or some parts of the embodiments of the present invention.

The above is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed in the present invention can easily think of changes or Replacement should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.

Claims (6)

1. A bit error rate performance analysis method of a wireless and power line dual-media cooperative communication system, the dual-media cooperative communication system includes a signal source S, a relay node R, and a destination node D, and the signal source S is respectively connected to the described Wireless communication between the relay node R and the destination node D, power line communication between the relay node R and the destination node D, characterized in that the method includes the following steps: Step S110: calculating the bit error rate P ₁ ^BER of the wireless link SR between the signal source S and the relay node R; Step S120: Establish a performance function model based on the PDF approximation algorithm of the moment generating function MGF equation, and obtain parameters approximate to the LogN distribution according to the performance function model; Step S130: For the wireless link SD from the signal source S to the destination node D and its signal-to-noise ratio γ _WD , and the power line link RD from the relay node R to the destination node D and its signal-to-noise ratio Ratio γ _PLD , obtain the cumulative distribution function F ^DF (λ) of the instantaneous output signal-to-noise ratio γ ^DF after the selective combination of SC; Step S140: According to the F ^DF (λ), the bit error rate performance analysis under the mixed fading condition is converted into the performance analysis under the same LogN distribution condition, and the bit error rate of the second hop after the SC combination is obtained Step S140: Combining the bit error rate P ₁ ^BER with the bit error rate The total bit error rate of the system is obtained 2. The bit error rate performance analysis method of the wireless and power line dual-media cooperative communication system according to claim 1, wherein the step S110 comprises: Combined with the wireless channel fading coefficient and the average signal-to-noise ratio, using the moment generating function MGF and Gaussian hypergeometric function, the closed expression of the bit error rate P ₁ ^BER can be obtained as: Among them, Ω _R represents the variance of the fading amplitude of the wireless link SR, m _R represents the fading parameter of the wireless link SR, Δ _W represents the average signal-to-noise ratio of the wireless communication link, ₂ F ₁ (.,.;.;.) Represents Gaussian hypergeometric function, Γ(.) represents Gamma function. 3. The bit error rate performance analysis method of the wireless and power line dual-media cooperative communication system according to claim 2, wherein the step S120 comprises: Step S121: Establish the MGF equations of Gamma distribution and LogN distribution variables respectively: It is known that H _WD represents the fading coefficient of the wireless link SD, then Satisfy the Gamma distribution, represented by G(α _D , β _D ), where α _D ＝m _D , β _D ＝Ω _D /m _D ; where Ω _D represents the variance of the fading amplitude of the wireless link SD, m _D represents the wireless The fading shape parameter of the link SD, in order to satisfy the channel fading normalization, let Ω _D =1; The MGF satisfies Approximate The MGF of the distributed variable satisfies When i takes 1 and 2 respectively, the corresponding variables s ₁ and s ₂ ; Distribute G(α _D ,β _D ) Approximate to Set M _Pl (s _i )=M _D (s _i ) to get the approximate MGF equation: Among them, w _n and a _n represent the weight and zero points of the Gauss-Hermite formula respectively, and GN represents the weight of the Gauss-Hermite formula and the number of zero points; Step S122: Based on the approximated MGF equation established in step S121, a performance function model is established, and the parameters of the approximated LogN distribution are obtained: with G(α _D ,β _D ) distribution and The difference in the distribution is the smallest to establish a performance function model for the goal: The following conditions: 1): 2): 3): H _j =0.01+0.05*(j-1); 4): j=1,2,...N; 5): s ₁ >0; 6): s ₂ >0; Among them, H _j represents the sampling value of the wireless channel fading H, and N represents the total sampling points of the probability density function; According to the performance function model, the PDF distribution parameters s ₁ , s ₂ and Approximate parameters μ _D and σ _D of LogN distribution; Step S123: According to Combined with the parameters μ _D and σ _D , determine that γ _WD is approximated as After the parameters μ _wD and in, μ _wD =ln( _ΔW )+μ _D . 4. The bit error rate performance analysis method of the wireless and power line dual-media cooperative communication system according to claim 3, wherein the step S130 comprises: It is known that H _PLD represents the fading coefficient of the power line link RD, and H _PLD satisfies Let γ _PLD represent the instantaneous signal-to-noise ratio at the receiving end of the power line link RD, and according to the average signal-to-noise ratio _ΔPL and the nature of the logarithmic normal variable, determine will also satisfy the lognormal distribution and Combining the output signal-to-noise ratio γ _PLD of the power line link RD and the output signal-to-noise ratio γ _WD of the wireless link SD, the cumulative distribution function F ^DF (λ) of the instantaneous output signal-to-noise ratio γ ^DF after the combination of SCs is obtained: F ^DF (λ) = Pr(γ ^DF <λ) = Pr(γ _WD <λ); Use the Q function to calculate: Among them, λ represents the cutoff threshold signal-to-noise ratio of the combined SCs. 5. The bit error rate performance analysis method of the wireless and power line dual-media cooperative communication system according to claim 4, wherein the step S140 comprises: Integrating the cumulative distribution function F ^DF (λ), the bit error rate performance analysis under the mixed fading condition is converted into the performance analysis under the same LogN distribution condition, then the bit error rate for: in, Indicates that the pulse number k of the power line link RD obeys the Poisson distribution with the mean value A; PN indicates the maximum number of impulse noise, and PN is greater than 20; Convert the bit error rate performance analysis under the condition of mixed fading to the performance analysis under the same LogN distribution condition, then the bit error rate P ₂ ^BER is: Among them, according to the fading distribution parameters of the power line link RD and The approximate distribution parameter of Solve for constants W _tk , V _tk , U _tk . 6. The bit error rate performance analysis method of the wireless and power line dual-media cooperative communication system according to claim 5, characterized in that: the combination _of the bit error rate P ^BER and the bit error rate The total bit error rate of the system is obtained for: