CN113194496B - Error rate analysis method for NOMA short packet communication based on space-time block coding - Google Patents
Error rate analysis method for NOMA short packet communication based on space-time block coding Download PDFInfo
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Abstract
The invention provides an error rate analysis method for NOMA short packet communication based on space-time block coding, which comprises the following steps: s1: establishing a downlink MIMO NOMA wireless cellular communication network system, wherein the system comprises a base station BS, a central user Uc and an edge user Ue; modeling a channel matrix of the system; s2: orthogonalizing a channel matrix of the MIMO using space-time block coding STBC; s3: decoding by adopting a continuous interference elimination method to obtain a general expression of the instantaneous block error rate; s4: and approximating the instantaneous block error rate by adopting a Gaussian-Chebyshev approximation algorithm to obtain an analysis expression of the average block error. The invention directly processes the product term, replaces the linear approximation in the existing work with Gaussian Chebyshev approximation, derives an accurate closed approximation solution and realizes accurate and efficient analysis.
Description
Technical Field
The invention relates to the technical field of wireless communication, in particular to an error rate analysis method for NOMA short packet communication based on space-time block coding.
Background
With the rapid development of portable intelligent terminals and 5G communication technologies, the non-orthogonal multiple access technology (NOMA) has been increasingly used in wireless communication because it can provide an efficient spectrum resource utilization scheme. Space-time block coding (STBC) represents a transmit diversity scheme for a multiple transmit antenna system that includes propagating information on the transmit antennas to maximize diversity advantage in fading channels, which is a great aid in improving system performance. Such as Chinese patent publication No.: CN110418297a, 2019-11-05, discloses a power domain NOMA cooperative transmission method and device based on bit error rate fairness, the method comprises the following steps: establishing a transmission system model; the boundary simplification processes the received signal of the destination node to obtain the upper boundary of the detection signal and the noise signal; respectively decomposing the upper boundaries of the detection signal and the noise signal into sub-signals containing two independent random variables, wherein the two independent random variables respectively obey the exponential distribution of preset parameters; firstly, calculating a moment mother function of a detection signal, simplifying the moment mother function, obtaining a bit error rate closed boundary formula according to the simplified moment mother function, and calculating a closed solution of an average bit error rate through the bit error rate closed boundary formula.
For increasingly popular internet of things (IoT) applications, there is a need for ultra-reliable and low-latency communication guarantees, such as short packet communications, where the impact of block length on system performance is not negligible.
Disclosure of Invention
The invention provides an error rate analysis method for NOMA short packet communication based on space-time block coding, which aims to solve the problem that the accurate and efficient analysis cannot be performed due to the complex error rate function in the existing wireless communication system.
In order to solve the technical problems, the technical scheme of the invention is as follows: an error rate analysis method for NOMA short packet communication based on space-time block coding comprises the following steps:
s1: establishing a downlink MIMO NOMA wireless cellular communication network system, wherein the system comprises a base station BS, a central user Uc and an edge user Ue; modeling a channel matrix of the system;
s2: orthogonalizing a channel matrix of the MIMO using space-time block coding STBC;
s3: decoding by adopting a continuous interference elimination method to obtain a general expression of the instantaneous block error rate;
s4: and approximating the instantaneous block error rate by adopting a Gaussian-Chebyshev approximation algorithm, obtaining an analysis expression of the average block error, and analyzing the error rate according to the analysis expression of the average block error.
Preferably, the base station BS configures n T The root antenna, the central user and the edge user are all configured with n R A root antenna; setting that central users are randomly and uniformly distributed in a disc taking a base station as a center and Dc as a radius; setting edge user followsThe machines are uniformly distributed in a circular ring with the base station as the center, the inner diameter Dc and the outer diameter De.
Further, the signal sent by the base station BS to the central user Uc isThe signal sent by the base station BS to the edge user Ue is +.>The signal satisfies the following condition:
wherein ,PT Representing the transmit power of the base station; alpha c A power allocation factor representing a central user; alpha e Representing the power division factor of the edge user, and alpha c +α e ＝1；
Therefore, the signal x to be transmitted by the base station is modeled as:
x＝x c +x e
setting channel matrix from base station to central user asSetting channel matrix from base station to edge user +.>The channel matrix is modeled as:
wherein ,dc Representing the distance from the base station to the central user; d, d e Representing the distance from the base station to the central user; beta is the path loss index;representing a small scale fading index from the base station to the central user;representing the small scale fading index of the MIMO channel from the base station to the edge user.
Still further, consider a flat uncorrelated rayleigh fading MIMO channel, channel parameter h i,j ，i＝1,2,…,n R And j=1, 2, …, n T Modeling into independent uncorrelated complex cyclic Gaussian random variables, each of which obeys the CN (0, 1) distribution; assuming that the channel parameters are fixed within one frame length, the channel parameters are independent from each other among different frames;
the signals received at the central user and the edge users, respectively, may be represented as follows:
y c ＝H c x+z c
y e ＝H c x+z e
wherein , and />Additive white gaussian noise vectors representing the center user and the edge user, respectively; sigma (sigma) 2 Representing the variance of additive gaussian noise.
Still further, step S2, in particular, maps R.ltoreq.T input signals to n T On orthogonal sequences of length T, then through n T Transmitting by the root transmitting antennas simultaneously, obtaining the transmitting diversity gain of the wireless link by using STBC, wherein the information code rate of the STBC is that
For a given channel implementation, the generated effective channel is equivalent to a channel in which two parts corresponding to the real part and the imaginary part of the transmitted signal respectively contain T sub-channels;
before maximum likelihood detection, each sub-channel is described as follows with a relationship between the input signal and the output signal:
wherein I F Representing a Frobenius matrix; x is x STBC Representing the real or imaginary part of the transmitted signal, the power being P T /2n T ；z c STBC and ze STBC Corresponding terms representing noise after STBC decoding, subject to respectivelyAnddistribution; /> and />Is K mutually independent χ 2 Sum of random variables->Is:
where Γ (x) is the gamma function.
Still further, step S3, specifically,
the central user first goes to x e STBC Decoding is carried out, and the signal-to-interference-and-noise ratio is as follows:
wherein ,
the central user decodes x e STBC The instantaneous block error rate of (a) is expressed as:
wherein ,C(γ)＝WR′log 2 (1+γ)，V(γ)＝(log 2 e) 2 ·(1-(1+γ) -2 ) The method comprises the steps of carrying out a first treatment on the surface of the W is the system bandwidth, nc is the number of bits of transmission data to be sent to the central user;
if the central user is able to successfully decode x e STBC Then the central user decodes x c STBC Is the signal to noise ratio of (A)
Central user decoding x c STBC The instantaneous block error rate of (a) is
∈ c ＝∈ c，e +(1-∈ c，e )∈ c，c
wherein ,
the edge user pair x e STBC Decoding is carried out, and the signal-to-interference-and-noise ratio is as follows:
the instantaneous block error rate decoded by the edge user is:
where Ne is the number of bits of transmission data to be sent to the edge user.
Still further, in step S4, the central user decodes x c STBC The average block error rate of (a) is:
wherein ,
still further, because the central user decodes x c STBC The form of the average block error rate is too complex, resulting in difficulty in finding an analytical expression of the average block error rate; performing effective approximation processing on the instantaneous block error rate by using Gaussian-Chebyshev approximation;
wherein Max is a number;beta is the path loss index; k meterA compromise parameter showing complexity-accuracy; dc is the radius of the disk where the central user is located; Γ () is a gamma function; k=n R *n T Is the diversity gain obtainable using STBC; /> Is an error function;C(θ k )＝WR′log 2 (1+θ k )；V(θ k )＝(log 2 c) 2 ·(1-(1+θ k ) -2 ) The method comprises the steps of carrying out a first treatment on the surface of the m is the block length in short packet communication; nc is the number of bits of transmission data to be sent to the central user; />
Still further, for gamma c,e The cumulative distribution function segment of (a) is represented as follows:
when y is less than or equal to alpha e /α c Time of day
Otherwise, f γc，e (y)＝0；
Thus, the first and second substrates are bonded together,expressed as:
further approximation processing is carried out on the obtained product:
wherein ,C(ξ k )＝WR′log 2 (1+ξ k )，V(ξ k )＝(log 2 e) 2 ·(1-(1+ξ k ) -2 ) M is the block length in short packet communication, nc is the number of bits of transmission data to be sent to the central user,/->
Meanwhile, the following relationship exists:
from this, the central user decoding x is determined c STBC An approximate analytical expression of the average block error rate of (c).
Still further, for the edge user, the edge user decoded signal x is calculated e STBC An analytical expression of the block error rate;
γ e,e the cumulative distribution function of (a) may be expressed in segments as follows:
when y is less than or equal to alpha e /α c Time of day
Otherwise, f γe，e (y)＝0
Thus, the edge user decoded signal x is found e STBC The analytical expression of the block error rate of (a) is:
wherein ,beta is the path loss index; k is a compromise parameter representing complexity-accuracy; dc is the radius of the disk where the central user is located; de is the outer diameter of the ring where the edge user is located; Γ () is a gamma function; k=n R *n T Is the diversity gain obtainable using STBC; /> Is an error function; /> C(ξ k )＝WR′log 2 (1+ξ k )，V(ξ k )＝(log 2 e) 2 ·(1-(1+ξ k ) -2 ) M is the block length in short packet communication, nc is the number of bits of transmission data to be sent to the central user,/->
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
the invention can obtain the accurate approximate expression of the block error rate of the MIMO-NOMA short packet communication system based on STBC, based on the expression, related researchers can directly utilize the existing MATLAB, CVX and other tools to analyze the system performance more conveniently, rapidly and accurately, and the complexity of the processing process is reduced.
The average block error rate processing scheme provided by the invention breaks through the defects in the existing processing method and reserves the product term in integration; meanwhile, the nonlinear approximation is used for replacing the linear approximation in the existing method, so that function characteristics can be reflected more, and the accuracy of approximation is ensured.
Drawings
Fig. 1 is a flowchart illustrating steps of a method according to the present embodiment.
FIG. 2 is a graph showing the average error rate of the user decoded signal as the SNR varies according to the present embodiment;
FIG. 3 shows the average error rate of the center user decoding with α according to the present embodiment c A graph of the change;
FIG. 4 shows the average error rate of edge user decoding with α according to the present embodiment e Graph of the variation.
Detailed Description
The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, which are only for illustration and not to be construed as limitations of the present patent. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The technical scheme of the invention is further described below with reference to the accompanying drawings and examples.
Example 1
As shown in fig. 1, a method for analyzing error rate of NOMA short packet communication based on space-time block coding includes the following steps:
step S1: establishing a downlink MIMO NOMA wireless cellular communication network system, wherein the system comprises a base station BS, a central user Uc and an edge user Ue; modeling a channel matrix of the system; as shown in fig. 2, the base station is provided with n T =4 antennas, the central user and the edge user configure n respectively R 4 antennas, the central users are set to be randomly and uniformly distributed in a circular disc with a base station as a center and Dc=100deg.M as a radius; the set edge users are randomly and uniformly distributed in a circular ring with the base station as the center, the inner diameter Dc=100deg.M and the outer diameter De=200m. By passing throughSTBC is used for encoding.
The signal sent by the base station BS to the central user Uc isThe signal sent by the base station BS to the edge user Ue is +.>The signal satisfies the following condition:
wherein ,PT Representing the transmit power of the base station; alpha c A power allocation factor representing a central user; alpha e Representing the power division factor of the edge user, and alpha c +α e =1; the present embodiment sets alpha c ＝0.2，α e ＝0.8。
Therefore, the signal x to be transmitted by the base station is modeled as:
x＝X c +x e
setting channel matrix from base station to central user asSetting channel matrix from base station to edge user +.>The channel matrix is modeled as:
wherein ,dc Representing the distance from the base station to the central user; d, d e Representing the distance from the base station to the central user; beta is the path loss index;representing a small scale fading index from the base station to the central user;representing the small scale fading index of the MIMO channel from the base station to the edge user.
In this embodiment, consider a flat uncorrelated rayleigh fading MIMO channel, channel parameter h i,j ，i＝1,2,…,n R And j=1, 2, …, n T Modeling into independent uncorrelated complex cyclic Gaussian random variables, each of which obeys the CN (0, 1) distribution; in addition, we assume that the channel parameters are fixed within one frame length, and are independent from each other between different frames;
according to the above settings, then, the signals received at the central user and the edge user, respectively, can be represented as follows:
y c ＝H c x+z c
y e ＝H e x+z e
wherein , and />Additive white gaussian noise vectors representing the center user and the edge user, respectively; sigma (sigma) 2 Representing the variance of additive gaussian noise.
Step S2: orthogonalizing a channel matrix of the MIMO using space-time block coding STBC;
specifically, R.ltoreq.T input signals are mapped to n T On orthogonal sequences of length T, then through n T Root transmission skyThe wires are transmitted simultaneously and the STBC is used to obtain the transmit diversity gain of the wireless link. Thus, the information code rate of STBC is
In this example, the normalized code rate is R' =1.
For a given channel implementation, the resulting effective channel may be equivalent to a channel in which the two parts corresponding to the real and imaginary parts of the transmitted signal, respectively, contain T sub-channels. Before maximum likelihood detection, each sub-channel may be described as follows with a relationship between the input signal and the output signal:
wherein I F Representing a Frobenius matrix; x is x STBC Representing the real or imaginary part of the transmitted signal, the power being P T /2n T ；z c STBC and ze STBC Corresponding terms representing noise after STBC decoding, subject to respectivelyAnddistribution. /> and />Is K mutually independent χ 2 Sum of random variables->Is:
where Γ (x) is the gamma function.
Step S3: decoding by adopting a continuous interference elimination method to obtain a general expression of the instantaneous block error rate; in particular, the method comprises the steps of,
the central user first goes to x e STBC Decoding with signal-to-interference-and-noise ratio of
wherein ,
then the central user decodes x e STBC The instantaneous block error rate of (a) can be expressed as:
wherein ,C(γ)＝WR′log 2 (1+γ)，V(γ)＝(log 2 e) 2 ·(1-(1+γ) -2 ). W is the system bandwidth, in this example set w=1; nc is the number of bits of transmission data to be sent to the central user, nc=80 being set in this example. We set the block length m ∈100 in short packet communications to be able to guarantee the accuracy of the instantaneous block error rate, in this example set m=100.
If the central user is able to successfully decode x e STBC Then the central user decodes x c STBC Is the signal to noise ratio of (A)
The central user decodes x c STBC The instantaneous block error rate of (a) is
∈ c ＝∈ c，e +(1-∈ c，e )∈ c，c
wherein ,
the edge user is directly opposite to x e STBC Decoding is carried out, and the signal-to-interference-and-noise ratio is as follows:
the instantaneous block error rate decoded by the edge user is:
where Ne is the number of bits of transmission data to be transmitted to the edge user, ne=80 is set in this example.
Step S4: and approximating the instantaneous block error rate by adopting a Gaussian-Chebyshev approximation algorithm, obtaining an analysis expression of the average block error, and analyzing the error rate according to the analysis expression of the average block error.
The central user decodes x c STBC The average block error rate of (a) is:
wherein ,
because this form of integration is too complex, it is difficult to find an analytical expression for the average block error rate. The instantaneous block error rate is effectively approximated by a Gaussian-Chebyshev approximation:
wherein ,max is a sufficiently large number, we set max=100.Is an error function, ++>K is a compromise parameter representing complexity-accuracy, in this example set k=10000.
γ c,e The cumulative distribution function of (a) may be expressed in segments as follows:
when y is less than or equal to alpha e /α c Time of day
Otherwise, f γe，e (y)＝0
Thus, the first and second substrates are bonded together,can be expressed as:
we can further approximate this:
wherein ,
meanwhile, the following relationship exists:
in summary, the central user decode x can be obtained c STBC An approximate analytical expression of the average block error rate of (c).
For the edge user, we can calculate the decoded signal x of the edge user in a similar way to the central user e STBC Is a block error rate analytical expression of (c).
γ e,e The cumulative distribution function of (a) may be expressed in segments as follows:
when y is less than or equal to alpha e /α c Time of day
Otherwise, f γe，e (y)＝0
Thus we find the edge user decoded signal x e STBC The analytical expression of the block error rate of (a) is:
the method in this embodiment performs block error rate (BLER) performance evaluation on a two-user downlink multiple-input multiple-output (MIMO) NOMA network with a finite block length by using space-time block coding, and compared with the previous work, proposes a more direct and more accurate error rate analysis method. In the network, by invoking random geometry, it is assumed that the central users are evenly distributed in the disk centered on the base station, and the cell edge users are evenly distributed in the ring. For the average BLER of the central user in the flat Rayleigh fading channel, unlike the process of neglecting the product term in the prior art, we directly process the product term and replace the linear approximation in the prior work with Gaussian Chebyshev approximation, thus leading to an accurate closed approximation solution.
To further verify the technical effect of this embodiment, the following simulation was performed:
in the simulation process, the system bandwidth and rate are normalized, w=1, and r' =1. The central users are randomly and uniformly distributed in an area with the base station as the center and the Dc=100$, and the edge users are randomly and uniformly distributed in a circle with the base station as the center, the inner diameter Dc=100 m and the outer diameter De=200m. The complexity-accuracy tradeoff parameter is set to k=10000, max=100.
Simulation example 1 results as shown in fig. 2, we demonstrate the average block error rate for the center user and the edge user for different signal-to-noise ratio values when using STBC for the downlink MIMO NOMA network. In the figure we set, alpha c ＝0.2,α e =0.8, nc=80, ne=80, m=100 and n T ＝n R =4. Computer simulation values and analytic values are denoted by "Simu" and "Theo", respectively. From FIG. 1, we can see that both the center user and the edge user, the derived error rate resolution is almost perfectly matched to the computer simulation.
Simulation example 2 results as shown in fig. 3 and 4, we show that the downlink MIMO NOMA network uses STBC for different α c Value, average block error rate for center user and edge user. In this example, we set that snr=40 db, nc=80, ne=80, m=100 and n T ＝n R =4. From fig. 2 and 3, we can find that the error rate analysis values derived by us are almost perfectly matched with the computer simulation values.
In summary, we have studied the average block error rate of a downlink MIMO NOMA short packet communication network when STBC is used under a rayleigh flat fading channel. In the deduction process, gaussian Chebyshev approximation is used, and through simulation results, the deducted analytic value can be almost perfectly attached to the computer simulation value. The scheme can greatly reduce the complexity of calculation and provide a portable means for researching the problems.
It is to be understood that the above examples of the present invention are provided by way of illustration only and not by way of limitation of the embodiments of the present invention. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the invention are desired to be protected by the following claims.
Claims (5)
1. A method for analyzing the error rate of NOMA short packet communication based on space-time block coding is characterized in that: the method comprises the following steps:
s1: establishing a downlink MIMO NOMA wireless cellular communication network system, wherein the system comprises a base station BS, a central user Uc and an edge user Ue; modeling a channel matrix of the system;
s2: orthogonalizing a channel matrix of the MIMO using space-time block coding STBC;
s3: decoding the output signal by adopting a continuous interference elimination method to obtain a general expression of the instantaneous block error rate;
s4: approximating the instantaneous block error rate by using a Gaussian-Chebyshev approximation algorithm, obtaining an analysis expression of the average block error, and analyzing the error rate according to the analysis expression of the average block error;
step S1, the base station BS configures n T The root antenna, the central user and the edge user are all configured with n R A root antenna; setting that central users are randomly and uniformly distributed in a disc taking a base station as a center and Dc as a radius; the method comprises the steps that edge users are arranged in a circle with a base station as a center, an inner diameter Dc and an outer diameter De uniformly at random;
the signal sent by the base station BS to the central user Uc isThe signal sent by the base station BS to the edge user Ue is +.>The signal satisfies the following condition:
wherein ,PT Representing the transmit power of the base station; alpha c A power allocation factor representing a central user; alpha e Representing the power division factor of the edge user, and alpha c +α e ＝1；
Therefore, the signal x to be transmitted by the base station is modeled as:
x＝x c +x e
setting channel matrix from base station to central user asSetting channel matrix from base station to edge userThe channel matrix is modeled as:
wherein ,dc Representing the distance from the base station to the central user; d, d e Representing the distance from the base station to the central user; beta is the path loss index;representing a small scale fading index from the base station to the central user;representing a small scale fading index of the MIMO channel from the base station to the edge user;
considering a flat uncorrelated rayleigh fading MIMO channel, channel parameter h i,j ，i＝1,2,…,n R And j=1, 2, …, n T Modeling into independent uncorrelated complex cyclic Gaussian random variables, each of which obeys the CN (0, 1) distribution; assuming that the channel parameters are fixed within one frame length, the channel parameters are independent from each other among different frames;
the signals received at the central user and the edge users, respectively, may be represented as follows:
y c ＝H c x+z c
y e ＝H e x+z e
wherein , and />Additive white gaussian noise vectors representing the center user and the edge user, respectively; sigma (sigma) 2 Representing the variance of additive gaussian noise;
step S2, in particular, mapping R.ltoreq.T input signals to n T On orthogonal sequences of length T, then through n T The transmission antennas transmit simultaneously, and the transmission diversity gain of the wireless link is obtained by using STBC, and the information code rate of the STBC is as follows:
for a given channel implementation, the generated effective channel is equivalent to a channel in which two parts corresponding to the real part and the imaginary part of the transmitted signal respectively contain T sub-channels;
before maximum likelihood detection, each sub-channel is described as follows with a relationship between the input signal and the output signal:
wherein I F Representing a Frobenius matrix; x is x STBC Representing the real or imaginary part of the transmitted signal, the power being P T /2n T ；z c STBC and ze STBC Corresponding terms representing noise after STBC decoding, subject to respectivelyAnddistribution; /> and />Is->Independent χ 2 Sum of random variables->Is:
wherein Γ (x) is a gamma function;
in step S3, in particular,
the central user first goes toDecoding is carried out, and the signal-to-interference-and-noise ratio is as follows:
wherein ,
then the central user decodesThe instantaneous block error rate of (a) is expressed as:
wherein ,C(γ)＝WR′log 2 (1+γ)，V(γ)＝(log 2 e) 2 ·(1-(1+γ) -2 ) The method comprises the steps of carrying out a first treatment on the surface of the W is the system bandwidth, nc is the number of bits of transmission data to be sent to the central user;
if the central user is able to decode successfullyThen the central user decodes +.>The signal to noise ratio of (2) is:
central user decodingThe instantaneous block error rate of (a) is:
∈ c ＝∈ c，e +(1-∈ c，e )∈ c，c
wherein ,
the edge user pairDecoding is carried out, and the signal-to-interference-and-noise ratio is as follows:
the instantaneous block error rate decoded by the edge user is:
where Ne is the number of bits of transmission data to be sent to the edge user.
2. The error rate analysis method for NOMA short packet communication based on space-time block coding according to claim 1, wherein: step S4, the centerUser decodingThe average block error rate of (a) is:
wherein ,
3. the error rate analysis method for NOMA short packet communication based on space-time block coding according to claim 2, wherein: because the central user decodesThe form of the average block error rate is too complex, resulting in difficulty in finding an analytical expression of the average block error rate; performing effective approximation processing on the instantaneous block error rate by using Gaussian-Chebyshev approximation;
wherein Max is a number;beta is the path loss index; k represents a complexity-accuracy tradeoff parameter; dc is the radius of the disk where the central user is located; Γ () is a gamma function; k=n R *n T Is the diversity gain obtainable using STBC; is an error function; />C(θ k )＝WR′log 2 (1+θ k )；V(θ k )＝(log 2 e) 2 ·(1-(1+θk) -2 ) The method comprises the steps of carrying out a first treatment on the surface of the m is the block length in short packet communication; nc is the number of bits of transmission data to be sent to the central user; />
4. A method for error rate analysis of NOMA short packet communication based on space-time block coding as claimed in claim 3, wherein: for yc ,e The cumulative distribution function segment of (a) is represented as follows:
when y is less than or equal to alpha e /α c In the time-course of which the first and second contact surfaces,
otherwise the first set of parameters is selected,
thus, the first and second substrates are bonded together,expressed as:
further approximation processing is carried out on the obtained product:
wherein ,C(ξ k )＝WR′log 2 (1+ξ k )，V(ξ k )＝(log 2 e) 2 ·(1-(1+ξ k ) -2 ) M is the block length in short packet communication, nc is the number of bits of transmission data to be sent to the central user,/->
Meanwhile, the following relationship exists:
from this, a central user decoding is determinedAn approximate analytical expression of the average block error rate of (c).
5. The error rate analysis method for NOMA short packet communication based on space-time block coding as claimed in claim 4, wherein: for the edge user, calculating to obtain the decoded signal of the edge userAn analytical expression of the block error rate;
γ c,e the cumulative distribution function of (a) may be expressed in segments as follows:
when y is less than or equal to alpha e /α c In the time-course of which the first and second contact surfaces,
otherwise the first set of parameters is selected,
thus, the edge user decoded signal is foundThe analytical expression of the block error rate of (a) is:
wherein ,beta is the path loss index; k is a compromise parameter representing complexity-accuracy; dc is the radius of the disk where the central user is located; de is the outer diameter of the ring where the edge user is located; Γ () is a gamma function; k=n R *n T Is the diversity gain obtainable using STBC; /> Is an error function; /> C(ξ k )＝WR′log 2 (1+ξ k )，V(ξ k )＝(log 2 e) 2 ·(1-(1+ξ k ) -2 ) M is the block length in short packet communication, nc is the number of bits of transmission data to be sent to the central user,/->
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