CN110233751B - Heterogeneous hybrid network performance analysis method based on interference equivalence - Google Patents

Heterogeneous hybrid network performance analysis method based on interference equivalence Download PDF

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CN110233751B
CN110233751B CN201910445461.2A CN201910445461A CN110233751B CN 110233751 B CN110233751 B CN 110233751B CN 201910445461 A CN201910445461 A CN 201910445461A CN 110233751 B CN110233751 B CN 110233751B
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孙玉红
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Qufu Normal University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
    • H—ELECTRICITY
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    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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    • H04L41/12—Discovery or management of network topologies
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
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Abstract

The invention discloses a heterogeneous hybrid network performance analysis method based on interference equivalence, and provides a method for analyzing network interference and analyzing successful transmission probability of a network by aiming at using a SIC (shared information channel) technology in a multilayer heterogeneous hybrid network. The multi-layer heterogeneous hybrid network nodes are equivalent to the nodes on the same layer by using the concept of interference equivalence through random geometry, so that the performance index of the network after the SIC technology is used is successfully analyzed. The heterogeneous hybrid network performance analysis method of the invention utilizes random geometry to perform interference equivalence according to the interference received by each receiving end in the network, thereby leading the network structure to be similar to a single-layer network, facilitating the analysis of SIC technology and obtaining some transmission performance indexes of the network.

Description

Heterogeneous hybrid network performance analysis method based on interference equivalence
Technical Field
The invention relates to a network performance analysis method, in particular to a network performance analysis method based on interference equivalence in a multilayer heterogeneous hybrid network.
Background
At present, high-speed wireless communication technology is rapidly developing and affects human lives step by step. As the demand for wireless network capacity increases, wireless systems become more dense and the interference becomes more severe, and advanced techniques are needed to reduce the impact of interference on transmission. Among the methods, interference cancellation techniques are well known. Among them, Serial Interference Cancellation (SIC) has received much attention as one of interference cancellation techniques. It can decode messages from the collision signal in turn according to the strength of the received signal, and remove the signal decoded first, so as to reduce the interference of the subsequent signal. Since the requirements of the SIC on the receiving end are similar to those of the conventional non-SIC receiving end in terms of complexity and cost of hardware, neither more complex decoders nor multi-antenna support are required, and the SIC can achieve the shannon capacity bound in some special cases, it has been widely studied and applied, as already implemented in ieee 802.15.4. Currently, most SIC research is focused on ad hoc networks and single-layer cellular networks. For heterogeneous networks, especially those with non-poisson distribution at the transmitting end, there is relatively little research on how SIC improves its performance.
A multi-layer heterogeneous network is composed of nodes with different transmission powers and coverage areas, and different networks (e.g., a conventional macro cell network and a small cell network) respectively form a network layer, and each single-layer (i.e., homogeneous) cellular network is regarded as a special case. In recent years, this isomerization has accelerated the evolution with the dramatic increase in traffic demand.
However, under the condition of a heterogeneous network, the power of each transmitting end and the density of the network layer where the transmitting end is located are inconsistent, which is inconsistent with the principle of serial elimination of interference signals required by the SIC technology, so that the analysis of the influence of the SIC technology in a multi-layer heterogeneous network is a problem to be solved.
Disclosure of Invention
The invention mainly aims to provide a network performance analysis method based on interference equivalence, which enables a multi-layer heterogeneous hybrid network to use a SIC technology.
The technical scheme adopted by the invention is as follows: a heterogeneous hybrid network performance analysis method based on interference equivalence comprises the following steps:
the hybrid network is a multilayer network based on spectrum sharing and embedded with a D2D link, the multilayer network has k layers in common, the topological distribution of the transmitting nodes of each layer is an independent poisson point process, namely HIP, and the density of the corresponding ith layer is lambda iWith a transmission power of mui(ii) a The distribution characteristics of the D2D link are: all transmitting nodes are distributed with a density of lambdadHaving a transmission power mu at the transmitting nodedThe receiving nodes are positioned at a distance of y, and the distribution of y satisfies
Figure GDA0003554574960000021
The fading of the signal propagation follows an exponential distribution with an average value of 1 and a path loss function of l (x) x-α(ii) a Receiving terminal xjReceiving sender xiThe signals are represented as: fij＝μihijl(||xj-xi| |) wherein hijIs a fading variable, | | xj-xi| is xjAnd xiThe Euclidean distance of; a successful transmission is conditioned by the signal-to-interference ratio being greater than a given threshold:
Figure GDA0003554574960000022
wherein:
k: the number of layers of the multi-layer heterogeneous network;
i, a certain layer of the multi-layer heterogeneous network;
λi: the distribution density of the ith layer of sending nodes in the multilayer heterogeneous network;
λd: the distribution density of the sending nodes of the D2D link;
μi: the transmission power of an ith layer of transmission nodes in the multilayer heterogeneous network;
μdthe transmission power of the transmitting node of the D2D link;
l(x)＝x-α: a path loss formula, wherein x is a distance and alpha is a path loss index;
xj: any receiving node of the hypothesis;
xi: a transmitting node of a hypothetical ith layer;
Fij＝μihijl(||xj-xi| |) is the power of the transmitting end is μ |)iThe power of the receiving end; h isijIs from xiTo xjA fading variable of the channel of (a);
Figure GDA0003554574960000031
conditions for successful transmission, i.e. signal-to-interference ratio, SIR >Theta, wherein theta is a threshold value for successful decoding by the receiving end; the molecule part is a receiving end xuReceived sender xiThe transmitted destination signal, the denominator part being xuThe sum of the received interference sent by other sending ends;
under the condition that the obtained interference signals are eliminated in sequence by using the SIC technology, all network layers with different powers and different densities are equivalent to the network layer with the same power, wherein:
in a heterogeneous hybrid network, obtaining the equivalent density of interference received by a target receiving end of a HIP part k-layer node as follows:
Figure GDA0003554574960000032
the C function is defined as:
Figure GDA0003554574960000033
wherein
Figure GDA0003554574960000035
Is a Gaussian hypergeometric function;
further, the equivalent density of interference suffered by the D2D link receiving end is:
Figure GDA0003554574960000034
λeq_k: to assume that all transmitters are at power μkUnder the condition of (1), receiving end x0Density of accumulated interference; lambda [ alpha ]eq_dD2D receiver assumes mu for all transmittersdThe density of the accumulated interference;
λithe distribution density of any layer of transmitting end of the HIP; mu.skAnd muiThe transmission power, mu, of the k-th layer and i-th layer transmitting terminals respectivelydTransmit power of a transmitting node for the D2D link; α is a path loss exponent; thetahIs the threshold for successful decoding at the receiving end.
Further, the method for analyzing the performance of the heterogeneous hybrid network based on the interference equivalence further comprises the following steps:
For the HIP part of the heterogeneous hybrid network, for the k-th layer sending end, if the receiving end can successfully eliminate n strongest interferences, the successful transmission probability is:
Figure GDA0003554574960000041
here, the number of the first and second electrodes,
Figure GDA0003554574960000042
for the D2D part of the heterogeneous hybrid network, if the receiving end can successfully cancel the n strongest interferences, the successful transmission probability is:
Figure GDA0003554574960000043
here, ynIndicating the distance of the nth strongest interference to the receiving end,
Figure GDA0003554574960000044
Figure GDA0003554574960000045
representing the successful receiving probability of the receiving node of the transmitting end of the kth layer of the HIP part after n maximum interferences can be successfully eliminated or the successful transmitting probability of the transmitting end of the kth layer;
Figure GDA0003554574960000046
for the D2D link, if the receiving end can successfully eliminate the probability of successful transmission after n maximum interferences;
λeq_kis based on the k-th layer equivalent interference equivalent density, λeq_dThe interference equivalent density of the D2D receiving end;
rnthe distance from the nth strongest interference sending end to the receiving end is represented;
rkindicating that x is away from receiving end in k-th layer sending node set0The closest distance;
a is a path loss exponent and,
Figure GDA0003554574960000047
θhis a threshold value of successful decoding of the HIP receiving end;
θda threshold for successful decoding at the receiver end of D2D;
c is a function defined as:
Figure GDA0003554574960000051
wherein
Figure GDA00035545749600000513
Is a gaussian hypergeometric function.
Further, the method for analyzing the performance of the heterogeneous hybrid network based on the interference equivalence further comprises the following steps:
Under the SIC capability that the receiving end can eliminate at most N (N belongs to [0, infinity)) strongest interference sources, the successful transmission performance of different layer networks of the HIP part is as follows:
Figure GDA0003554574960000052
wherein the content of the first and second substances,
Figure GDA00035545749600000514
representing the probability of success without eliminating any interfering signals, wherein
Figure GDA0003554574960000053
Figure GDA0003554574960000054
Indicating the successful transmission probability of the k-th layer sending end after the receiving end can successfully eliminate the n strongest interferences
Figure GDA0003554574960000055
Figure GDA0003554574960000056
Here, the first and second liquid crystal display panels are,
Figure GDA0003554574960000057
if i-1 strongest interferers have been cancelled, the probability of successfully cancelling the ith interference is
Figure GDA0003554574960000058
With the SIC capability of the receiving end to cancel at most N (N ∈ [0, ∞)) strongest interferers, the transmission performance of the D2D link is:
Figure GDA0003554574960000059
wherein the content of the first and second substances,
Figure GDA00035545749600000510
representing the probability of successful transmission without canceling any interfering signals,
Figure GDA00035545749600000511
the successful transmission probability after the receiving end successfully eliminates the n strongest interferences is shown as follows:
Figure GDA00035545749600000512
here, the first and second liquid crystal display panels are,
Figure GDA0003554574960000061
Figure GDA0003554574960000062
indicating that if i-1 strongest interferers have been cancelled, the probability of successfully cancelling the ith interference is
Figure GDA0003554574960000063
The invention has the advantages that:
the invention discloses an interference equivalence-based heterogeneous hybrid network performance analysis method, which is based on a random geometry method, and is used for equating a multi-layer heterogeneous network into a layer of network through random equivalent interference, so that the successful transmission probability of the network under the SIC technical condition is successfully analyzed. As wireless network technology develops, network systems are becoming more dense and diversified, and some low-power nodes, such as home cells, relay nodes, D2D devices, and the like, participate in network communication, so that the network tends to be heterogeneous. The complexity of the network makes it more and more difficult to analyze interference in the network and to evaluate and deploy network performance. Serial Interference Cancellation (SIC) technology is attracting attention in the industry as an effective technique for reducing and eliminating interference. The invention provides a method for analyzing the interference of a network and analyzing the successful transmission probability of the network by using a SIC technology in a multilayer heterogeneous network. By using the concept of interference equivalence in random geometry, multi-layer heterogeneous network nodes are regarded as network nodes of the same layer, and therefore the performance index of the network after the SIC technology is used is successfully analyzed.
In addition to the above-described objects, features and advantages, the present invention has other objects, features and advantages. The present invention will be described in further detail below with reference to the drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention.
Fig. 1 is a model diagram of a method for analyzing performance of a heterogeneous hybrid network based on interference equivalence according to the present invention (five stars and asterisks represent transmitting ends of different layers, squares represent some D2D links, solid arrows represent transmission links, dashed arrows represent interference links, and only part of the interference links are shown);
FIG. 2 is a trend graph of analysis values and simulation values of successful transmission probability analysis of HIP sending nodes under the condition that a receiving end of the interference equivalence-based heterogeneous hybrid network performance analysis method of the present invention uses SIC technology;
fig. 3 is a trend graph of analysis values and simulation values of successful transmission probability analysis of a D2D link under the condition that a receiving end of the interference equivalence-based heterogeneous hybrid network performance analysis method of the present invention uses the SIC technology.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1 to 3, as shown in fig. 1 to 3, a method for analyzing performance of a heterogeneous hybrid network based on interference equivalence according to the present invention includes:
the hybrid network is a multilayer network embedded with a D2D link based on spectrum sharing, the multilayer network has k layers in common, the topological distribution of the sending nodes of each layer is a Poisson point process (HIP part for short) which is independent from each other, and the density of the corresponding i-th layer is lambdaiWith a transmission power of mui(ii) a The distribution characteristics of the D2D link are: all transmitting nodes are distributed with a density of lambdadHaving a transmission power mu at the transmitting nodedThe receiving nodes are positioned at a distance of y, and the distribution of y satisfies
Figure GDA0003554574960000071
The fading of the signal propagation follows an exponential distribution with an average value of 1 and a path loss function of l (x) x-α(ii) a Receiving terminal xjReceiving sender xiThe signals are represented as: fij＝μihijl(||xj-xi| |) wherein hijIs a fading variable, | | x j-xi| | is xjAnd xiThe Euclidean distance of; a successful transmission is conditioned by the signal-to-interference ratio being greater than a given threshold:
Figure GDA0003554574960000072
wherein:
k: the number of layers of the multi-layer heterogeneous network;
i, a certain layer of the multi-layer heterogeneous network;
λi: the distribution density of the ith layer of sending nodes in the multilayer heterogeneous network;
λd: distribution density of the sending nodes of the D2D link;
μi: the transmission power of an ith layer of transmission nodes in the multilayer heterogeneous network;
μdthe transmission power of the transmitting node of the D2D link;
l (x) x- α: path loss (the equation for the change in signal power with increasing distance), x is the distance, and α is the path loss exponent;
xj: any receiving node of the hypothesis;
xi: a transmitting node of a hypothetical ith layer;
Fij＝μihijl(||xj-xi| l) is the power of the transmitting end is μiThe power of the receiving end; h isijIs from xiTo xjA fading variation of the channel of (1);
Figure GDA0003554574960000081
conditions for successful transmission, i.e. signal-to-interference ratio, SIR>θ, where θ is the threshold for successful decoding at the receiving end, and is generally a known condition; the molecule part is a receiving end xuReceived sender xiThe transmitted destination signal, the denominator part being xuAnd the sum of the received interference sent by other sending ends.
The heterogeneous hybrid network performance analysis method based on interference equivalence further comprises the following steps: under the condition that the obtained interference signals are eliminated in sequence by using the SIC technology, all network layers with different powers and different densities are equivalent to the network layer with the same power, wherein:
According to the meaning of interference equivalence, in a heterogeneous hybrid network, obtaining the equivalent density of interference received by a target receiving end of a HIP part k-layer node as follows:
Figure GDA0003554574960000082
the C function is defined as:
Figure GDA0003554574960000083
wherein the content of the first and second substances,
Figure GDA0003554574960000084
is a Gaussian hypergeometric function;
the equivalent density of interference suffered by the receiving end of the D2D link is as follows:
Figure GDA0003554574960000091
λeq_k: to assume that all transmitters (including HIP and D2D) are at power μkUnder the condition of (1), receiving end x0Density of accumulated interference; lambda [ alpha ]eq_dD2D receiver assumes mu for all transmittersdThe density of the accumulated interference;
λithe distribution density of any layer of transmitting end of the HIP; mu.skAnd muiThe transmission power, mu, of the k-th layer and i-th layer transmitting terminals respectivelydTransmit power of a transmitting node for the D2D link; α is a path loss exponent; thetahIs the threshold for successful decoding at the receiving end.
The heterogeneous hybrid network performance analysis method based on interference equivalence further comprises the following steps:
for the HIP part of the heterogeneous hybrid network, for the k-th layer transmitting end, if the receiving end can successfully eliminate n strongest interferences, the successful transmission probability is as follows:
Figure GDA0003554574960000092
here, the first and second liquid crystal display panels are,
Figure GDA0003554574960000093
for the D2D part of the heterogeneous hybrid network, if the receiving end can successfully cancel the n strongest interferences, the successful transmission probability is:
Figure GDA0003554574960000094
here, ynIndicating the distance of the nth strongest interference to the receiving end,
Figure GDA0003554574960000095
Figure GDA0003554574960000096
The successful receiving probability of the receiving node of the k-th layer sending end of the HIP part after n maximum interferences can be successfully eliminated or the successful sending probability of the k-th layer sending end is shown;
Figure GDA0003554574960000097
for the D2D link, if the receiving end can successfully eliminate the probability of successful transmission after n maximum interferences;
λeq_kis based on the k-th layer equivalent interference equivalent density, λeq_dThe interference equivalent density of the D2D receiving end;
rnthe distance from the nth strongest interference sending end to the receiving end is represented;
rkindicating that x is away from receiving end in k-th layer sending node set0The closest distance;
a is a path loss exponent and,
Figure GDA0003554574960000101
θhfor HIP receptionA threshold for successful decoding of the end;
θda threshold for successful decoding at the receiver end of D2D;
c is a function defined as:
Figure GDA0003554574960000102
Figure GDA0003554574960000103
is a gaussian hypergeometric function.
The heterogeneous hybrid network performance analysis method based on interference equivalence further comprises the following steps:
under the SIC capability that the receiving end can eliminate at most N (N belongs to [0, infinity)) strongest interference sources, the successful transmission performance of different layer networks of the HIP part is as follows:
Figure GDA0003554574960000104
wherein the content of the first and second substances,
Figure GDA0003554574960000105
representing the probability of success without removing any interfering signals, wherein,
Figure GDA0003554574960000106
Figure GDA0003554574960000107
indicating the successful transmission probability of the k-th layer sending end after the receiving end can successfully eliminate the n strongest interferences
Figure GDA0003554574960000108
Figure GDA0003554574960000109
Here, the first and second liquid crystal display panels are,
Figure GDA00035545749600001010
if i-1 strongest interferers have been cancelled, the probability of successfully cancelling the ith interference is
Figure GDA00035545749600001011
With the SIC capability of the receiving end to cancel at most N (N ∈ [0, ∞)) strongest interferers, the transmission performance of the D2D link is:
Figure GDA0003554574960000111
wherein the content of the first and second substances,
Figure GDA0003554574960000112
representing the probability of successful transmission without canceling any interfering signals,
Figure GDA0003554574960000113
the successful transmission probability after the receiving end successfully eliminates the n strongest interferences is shown as follows:
Figure GDA0003554574960000114
here, the first and second liquid crystal display panels are,
Figure GDA0003554574960000115
Figure GDA0003554574960000116
indicating that if i-1 strongest interferers have been cancelled, the probability of successfully cancelling the ith interference is
Figure GDA0003554574960000117
Example 1
A heterogeneous hybrid network performance analysis method based on interference equivalence adopts a two-layer network with density lambda1＝0.002，λ20.004, power μ1＝10，μ2The path loss index α is 1, 4. Due to the multi-layer network, the SIR threshold is specified to be greater than 1, i.e., greater than 0db, in order to ensure that the user has at least one serving base station. The successful probability is calculated by comparing the successful transmission probability of eliminating 1 interference and 2 interference sources for the nodes with uniform Poisson distribution of each layer. The trend for the SIR (in db) from 0 to 10 is shown in figure 1.
The invention relates to a heterogeneous hybrid network performance analysis method based on interference equivalence, which utilizes random geometry to perform interference equivalence according to interference received by each receiving end in a network, so that the network structure is identical with the analysis of SIC technology, and some performance indexes of the network are obtained.
The technical scheme adopted by the invention is that the equivalent interference density of a network receiving end is obtained according to network parameters, and then the successful transmission probability of a corresponding transmitting end is calculated according to a network layer where the receiving end is located.
The invention discloses an interference equivalence-based heterogeneous hybrid network performance analysis method, which is based on a random geometry method, and is used for equating a multi-layer heterogeneous network into a layer of network through random equivalent interference, so that the successful transmission probability of the network under the SIC technical condition is successfully analyzed. As wireless network technology develops, network systems are becoming more dense and diversified, and some low-power nodes, such as home cells, relay nodes, D2D devices, and the like, participate in network communication, so that the network tends to be heterogeneous. The complexity of the network makes it more and more difficult to analyze interference in the network and to evaluate and deploy network performance. Serial Interference Cancellation (SIC) technology is attracting attention in the industry as an effective technique for reducing and eliminating interference. The invention provides a method for analyzing the interference of a network and analyzing the successful transmission probability of the network by using a SIC technology in a multilayer heterogeneous network. By using the concept of interference equivalence in random geometry, multi-layer heterogeneous network nodes are regarded as network nodes of the same layer, and therefore the performance index of the network after the SIC technology is used is successfully analyzed.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (4)

1. A heterogeneous hybrid network performance analysis method based on interference equivalence is characterized by comprising the following steps:
the hybrid network is a multilayer network based on spectrum sharing and embedded with a D2D link, the multilayer network has k layers in common, the topological distribution of the transmitting nodes of each layer is an independent poisson point process, namely HIP, and the density of the corresponding ith layer is lambdaiWith a transmission power of mui(ii) a The distribution characteristics of the D2D link are: all transmitting nodes are distributed with a density of lambdadHaving a transmission power mu at the transmitting nodedThe receiving nodes are positioned at a distance of y, and the distribution of y satisfies
Figure FDA0003554574950000011
The fading of the signal propagation follows an exponential distribution with an average value of 1 and a path loss function of l (x) x-α(ii) a Receiving terminal xjReceiving sender xiThe signals are represented as: fij＝μihijl(||xj-xi| |) wherein hijIs a fading variable, | | xj-xi| is xjAnd xiThe Euclidean distance of; a successful transmission is conditioned by the signal-to-interference ratio being greater than a given threshold:
Figure FDA0003554574950000012
wherein:
k: the number of layers of the multi-layer heterogeneous network;
i, a certain layer of the multi-layer heterogeneous network;
λi: the distribution density of the ith layer of sending nodes in the multilayer heterogeneous network;
λd: distribution density of the sending nodes of the D2D link;
μi: the transmission power of an ith layer of transmission nodes in the multilayer heterogeneous network;
μdthe transmission power of the transmitting node of the D2D link;
l(x)＝x-α: a path loss formula, wherein x is a distance and alpha is a path loss index;
xj: any receiving node of the hypothesis;
xi: a transmitting node of a hypothetical ith layer;
Fij＝μihijl(||xj-xi| l) is the power of the transmitting end is μiThe power of the receiving end; h isijIs from xiTo xjA fading variation of the channel of (1);
Figure FDA0003554574950000021
conditions for successful transmission, i.e. signal-to-interference ratio, SIR>Theta, wherein theta is a threshold value for successful decoding by the receiving end; the molecule part is a receiving end xuReceived sender xiThe transmitted destination signal, the denominator part being xuThe sum of the received interference sent by other sending ends;
under the condition that the obtained interference signals are eliminated in sequence by using the SIC technology, all network layers with different powers and different densities are equivalent to the network layer with the same power, wherein:
in a heterogeneous hybrid network, obtaining the equivalent density of interference received by a target receiving end of a HIP part k-layer node as follows:
Figure FDA0003554574950000022
the C function is defined as:
Figure FDA0003554574950000023
wherein the content of the first and second substances,
Figure FDA0003554574950000024
is a gaussian hypergeometric function.
2. The method of claim 1, wherein the method comprises: the equivalent density of interference suffered by the receiving end of the D2D link is as follows:
Figure FDA0003554574950000025
λeq_k: to assume that all transmitters are at power mukUnder the condition of (1), receiving end x0Density of accumulated interference; lambda [ alpha ]eq_dD2D receiver assumes mu for all transmittersdThe density of the accumulated interference;
λithe distribution density of any layer of transmitting end of the HIP; mu.skAnd muiThe transmission power, mu, of the k-th layer and i-th layer transmitting terminals respectivelydTransmit power of a transmitting node for the D2D link; α is a path loss exponent; thetahIs the threshold for successful decoding at the receiving end.
3. The method of claim 1, further comprising:
for the HIP part of the heterogeneous hybrid network, for the k-th layer transmitting end, if the receiving end can successfully eliminate n strongest interferences, the successful transmission probability is as follows:
Figure FDA0003554574950000031
here, the first and second liquid crystal display panels are,
Figure FDA0003554574950000032
for the D2D part of the heterogeneous hybrid network, if the receiving end can successfully cancel the n strongest interferences, the successful transmission probability is:
Figure FDA0003554574950000033
here, ynIndicating the distance of the nth strongest interference to the receiving end,
Figure FDA0003554574950000034
Figure FDA0003554574950000035
the method comprises the steps that for a receiving node of a k-th layer sending end of an HIP part, if n maximum interferences can be successfully eliminated, the receiving probability is obtained, or the successful sending probability of the k-th layer sending end is obtained;
Figure FDA0003554574950000036
The successful transmission probability of the D2D link under the condition that the receiving end can successfully eliminate n maximum interferences is obtained;
λeq_kis based on the k-th layer equivalent interference equivalent density, λeq_dThe interference equivalent density of the D2D receiving end;
rnthe distance from the nth strongest interference sending end to the receiving end is represented;
rkindicating that x is away from receiving end in k-th layer sending node set0The closest distance;
a is a path loss exponent and,
Figure FDA0003554574950000037
θhis a threshold value of successful decoding of the HIP receiving end;
θdis D2DA threshold for successful decoding at the receiving end;
c is a function defined as:
Figure FDA0003554574950000041
Figure FDA0003554574950000042
is a gaussian hypergeometric function.
4. The method of claim 1, further comprising:
under the SIC capability that the receiving end can eliminate at most N (N belongs to [0, infinity)) strongest interference sources, the successful transmission performance of different layer networks of the HIP part is as follows:
Figure FDA0003554574950000043
wherein the content of the first and second substances,
Figure FDA0003554574950000044
representing the probability of success without eliminating any interfering signals, wherein
Figure FDA0003554574950000045
Figure FDA0003554574950000046
Indicating the successful transmission probability of the k-th layer sending end after the receiving end can successfully eliminate the n strongest interferences
Figure FDA0003554574950000047
Figure FDA0003554574950000048
Here, the first and second liquid crystal display panels are,
Figure FDA0003554574950000049
if i-1 strongest interferers have been cancelled, the probability of successfully cancelling the ith interference is
Figure FDA00035545749500000410
With the SIC capability of the receiving end to cancel at most N (N ∈ [0, ∞)) strongest interferers, the transmission performance of the D2D link is:
Figure FDA00035545749500000411
Wherein, the first and the second end of the pipe are connected with each other,
Figure FDA00035545749500000412
representing the probability of successful transmission without canceling any interfering signals,
Figure FDA00035545749500000413
the successful transmission probability after the receiving end successfully eliminates n strongest interferences is shown as follows:
Figure FDA00035545749500000414
here, the number of the first and second electrodes,
Figure FDA0003554574950000051
Figure FDA0003554574950000052
indicating that if i-1 strongest interferers have been cancelled, the probability of successfully cancelling the ith interference is
Figure FDA0003554574950000053
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