CN109890036B - Self-return method of heterogeneous network - Google Patents

Self-return method of heterogeneous network Download PDF

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CN109890036B
CN109890036B CN201910090821.1A CN201910090821A CN109890036B CN 109890036 B CN109890036 B CN 109890036B CN 201910090821 A CN201910090821 A CN 201910090821A CN 109890036 B CN109890036 B CN 109890036B
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base station
user equipment
small
small base
macro base
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CN109890036A (en
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贾向东
杨小蓉
纪澎善
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Northwest Normal University
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention discloses a self-return method of a heterogeneous network, which considers the influence of a multilayer heterogeneous network with high frequency spectrum and energy efficiency and the influence of NOMA technology on the signal-to-interference-plus-noise ratio of a system, the coverage probability and the energy efficiency in a small-sized base station. A single antenna small cell is covered by a macro cell using massive MIMO technology. NOMA is used at each small cell for backhaul and downlink access. By utilizing a full duplex technology, a small base station communicates with user equipment through an uplink and a downlink; meanwhile, by using a power domain NOMA technology, the small base station superposes a backhaul on a downlink access link based on a power sharing coefficient. Uplink and downlink transmission backhauls are performed simultaneously at each small cell. Meanwhile, the macro base station is composed of massive MIMO transmitting antennas and receiving antennas, and by using a full duplex technique, the macro base station communicates with the user equipment by using the massive MIMO transmitting antennas and receives a backhaul through the cascaded small base station receiving antennas. All transmissions on the macro base station and the small base station are performed on the same time-frequency resources.

Description

Self-return method of heterogeneous network
Technical Field
The invention relates to the technical field of wireless communication, in particular to an effective self-return transmission method for realizing a large-scale MIMO full-duplex heterogeneous network by using NOMA.
Background
Driven by the rapid growth of new applications and wireless communications, the demand for network performance is increasing, and the market demands that next generation networks should support higher system capacity (about 1000 times) than current generation networks, so that fifth generation (5G) communication systems become a hot spot of academic interest. Compared with the currently used 4G, the 5G network greatly improves the network performance in the aspects of system capacity, energy efficiency, spectrum efficiency, data rate and the like.
Massive MIMO, heterogeneous networks and full duplex are extremely important and potentially developing technologies in 5G networks. In the large-scale MIMO technology, a large number of antennas are deployed at a base station, so that spatial multiplexing gain and beamforming gain are realized, and more degrees of freedom are provided for a propagation channel. The heterogeneous network is to deploy ultra-dense small cells on macro cells to reduce the load of the macro cells, enlarge the coverage area and increase the area throughput. By deploying heterogeneous networks, the distance between the user equipment and the base station is reduced, resulting in reduced path loss, increased energy efficiency and spectral efficiency. Heterogeneous networks depend to a large extent on high speed backhaul link control, coordination between macro cell base stations and small cell base stations, and data transmission by small cell base stations. Traditionally, cellular networks are highly efficient in providing coverage, but as the number of user equipment increases, energy efficiency and spectral efficiency drop rapidly.
Heterogeneous networks are realized by embedding massive MIMO, and the frequency spectrum and energy efficiency can be greatly improved. In the novel large-scale MIMO auxiliary heterogeneous network, a large-scale MIMO antenna array is equipped for a high-power macro base station, and densely deployed low-power small base stations are covered by the antenna array. The large-scale MIMO is embedded in the heterogeneous network, the large-scale heterogeneous network is designed by combining the advantages of the large-scale MIMO and the heterogeneous network, and the large-scale MIMO antenna array is configured for the high-power macro base station in the novel heterogeneous network and covered by the densely deployed low-power small base stations, so that the novel heterogeneous network has better performance.
With the dense deployment of small cells, heavy traffic load on the core network can be solved through the backhaul link. Although conventional wired backhaul links have high reliability at high data rates, it is impractical and costly to make wired connections between all small base stations. Thus, a wireless backhaul link is a suitable and cost-effective solution. However, sometimes, the small base station cannot exchange backhaul with the macro base station on the same frequency band, and thus, wireless backhaul becomes one of the problems to be solved.
Disclosure of Invention
The invention aims to provide an effective self-return method for realizing a large-scale MIMO full-duplex heterogeneous network by utilizing a non-orthogonal multiple access technology, so as to solve the problem of simultaneously realizing uplink, downlink and return transmission.
In order to achieve the purpose, the invention adopts the following technical scheme: a self-backhauling method of a heterogeneous network, comprising the steps of:
s1 same frequency deploymentK+1 layer heterogeneous network, where the first layer is a macro cell, the restKThe layer is a small cell, the macro base station is located at an optical fiber point of presence or a high-capacity line-of-sight microwave link available for the core network, the small base station is connected to the core network through a return provided by the macro base station, the macro base station simultaneously sends downlink signals to the user equipment by using a full-duplex technology and receives the return from the small base station through the same resource block, the small base station using NOMA and the full-duplex technology firstly combines the downlink signals and the return signals to the macro base station by using power domain superposition codes with different power sharing coefficients, and then the small base station simultaneously sends the obtained superposition signals and receives uplink signals of the user equipment on the same resource block by using the full-duplex technology;
s2, selecting a user terminal cascade strategy for an uplink and a downlink of the user equipment and a backhaul link of the small cell by using the NOMA power sharing coefficient;
s3, modeling interference of a return link and an access link by using a random geometry and a Poisson point process, modeling an active small base station as a new Poisson point process, modeling uplink user equipment cascaded to the active small base station as another independent non-uniform Poisson point process, and calculating interference distribution;
s4, calculating the coverage probability of uplink and uplink backhaul transmission from the user equipment to the small base station by using the characteristics of the NOMA superposition coding and the channel state information and the interference distribution obtained in the step S3, and obtaining the coverage probability of the downlink of the user equipment;
and S5, providing a model of frequency spectrum and energy efficiency, analyzing the influence of NOMA and full-duplex technology on the heterogeneous network, and simultaneously analyzing the resolution of the analog-to-digital converter in a large-scale MIMO antenna array.
Further, a method for obtaining the downlink coverage probability is provided
Figure DEST_PATH_IMAGE002
The user equipment uses a user cascade based on a maximum bias received power rule, wherein the user terminal provides a maximum long-term average received powerBase station concatenation of rates, for downlink user equipment concatenation, at
Figure DEST_PATH_IMAGE004
At a macro base station
Figure DEST_PATH_IMAGE005
The average bias received power of the user equipment at (a) is:
Figure DEST_PATH_IMAGE007
(ii) a Wherein
Figure DEST_PATH_IMAGE009
Is the array gain of the zero-forcing beamforming transmission, and
Figure DEST_PATH_IMAGE011
，
Figure DEST_PATH_IMAGE013
is a macro base station bias factor, a backhaul signal and a downlink access signal are superposed in a power domain and have a power sharing coefficient
Figure DEST_PATH_IMAGE015
And
Figure DEST_PATH_IMAGE017
in the position of
Figure 185587DEST_PATH_IMAGE002
User equipment of (2) from layerkIs located atjThe average bias received power of the small base station is:
Figure DEST_PATH_IMAGE019
，
Figure DEST_PATH_IMAGE021
are the same bias factor for small base stations in layer k.
Further, there is a level of user equipment uplink and small cell backhaul links based on the small cell using NOMA and full duplex techniquesIn which the user equipment uplink concatenation is at
Figure DEST_PATH_IMAGE023
The user equipment is cascaded with a small base station, and the cascade of the backhaul links of the small base station is positioned
Figure DEST_PATH_IMAGE025
The small base station and the macro base station are cascaded for backhaul, and the cascade rule based on the nearest distance is used for cascading two user terminals, so that the signal-to-interference-plus-noise ratio of a downlink, the user equipment and the first user terminal are maximizedKLayer nearest to
Figure 929945DEST_PATH_IMAGE025
The probability of small base station concatenation is:
Figure DEST_PATH_IMAGE027
。
further, different interference aggregates exist under different distributed random variables, and the analysis process comprises the following steps:
s31, user equipment
Figure DEST_PATH_IMAGE029
Subject to interference from interfering terminals
Figure DEST_PATH_IMAGE031
Of which
Figure DEST_PATH_IMAGE033
Is a density of
Figure DEST_PATH_IMAGE035
Independent poisson point process of (1), random variables
Figure DEST_PATH_IMAGE037
And
Figure DEST_PATH_IMAGE039
respectively channel gain and terminal
Figure 984620DEST_PATH_IMAGE031
With specific receiver terminals
Figure 197427DEST_PATH_IMAGE029
Is the corresponding path loss exponent of
Figure DEST_PATH_IMAGE041
In small-scale fading channel, the gain follows the Rayleigh distribution of unit power and the distance
Figure DEST_PATH_IMAGE042
Satisfy the requirement of
Figure DEST_PATH_IMAGE044
In the case of (2), using the equivalent power parameter
Figure DEST_PATH_IMAGE046
And path loss exponent
Figure DEST_PATH_IMAGE047
From interfering terminals
Figure 464067DEST_PATH_IMAGE031
User equipment (2)
Figure 986184DEST_PATH_IMAGE029
Laplace transform of the received interference:
Figure DEST_PATH_IMAGE049
Figure DEST_PATH_IMAGE051
，
when distance is exceeded
Figure 652788DEST_PATH_IMAGE042
Satisfy the requirement of
Figure DEST_PATH_IMAGE053
The corresponding laplace transform is then:
Figure DEST_PATH_IMAGE055
；
s32, channel gain fading in equivalent small scale
Figure DEST_PATH_IMAGE057
Compliance parameter of
Figure DEST_PATH_IMAGE059
Gamma distribution of (2):
Figure DEST_PATH_IMAGE061
distance, distance
Figure 357702DEST_PATH_IMAGE042
Satisfy the requirement of
Figure 42630DEST_PATH_IMAGE044
Using equivalent power parameters
Figure 814277DEST_PATH_IMAGE046
And path loss exponent
Figure 764915DEST_PATH_IMAGE041
Receiving from the terminal
Figure DEST_PATH_IMAGE062
User equipment (2)
Figure 585104DEST_PATH_IMAGE029
Laplace transform of the interfering signal of (a):
Figure 640651DEST_PATH_IMAGE055
，
wherein
Figure DEST_PATH_IMAGE064
Is a binomial coefficient;
when distance is exceeded
Figure 583200DEST_PATH_IMAGE042
Satisfy the requirement of
Figure 958817DEST_PATH_IMAGE053
The corresponding laplace transform is then:
Figure DEST_PATH_IMAGE066
。
further, the coverage probability corresponding to the uplink backhaul transmission includes access transmission from the user equipment to the small base station and backhaul transmission from the small base station to the macro base station.
Further, when the user equipment is cascaded with the macro base station, the coverage probability is determined by a signal to interference plus noise ratio in downlink transmission from the macro base station to the user equipment; when the UE is cascaded with NOMA and a full-duplex small base station, the coverage probability is obtained by the signal-to-interference-plus-noise ratio in the downlink transmission from the small base station to the UE, and meanwhile, the coverage probability is influenced by the backhaul transmission from the small base station to the macro base station.
Further, power consumption models of the macro base station, the small base station and the user equipment are formulated, and the power consumption of the macro base station using the large-scale MIMO technology is as follows:
Figure DEST_PATH_IMAGE068
wherein
Figure DEST_PATH_IMAGE070
The reciprocal of the drain efficiency of the macro base station power amplifier represents a static circuit power consumption constant, and the power consumption of an analog-to-digital converter of each macro base station is calculated as follows:
Figure DEST_PATH_IMAGE072
wherein
Figure DEST_PATH_IMAGE074
A representative constant, b is the resolution of the analog-to-digital converter;
the downlink power consumption is analyzed as:
Figure DEST_PATH_IMAGE076
wherein
Figure DEST_PATH_IMAGE078
And
Figure DEST_PATH_IMAGE080
is the drain efficiency of the small base station power amplifier andKthe inverse of the static power consumption of the small base station.
Compared with the prior art, the invention provides a self-return method for realizing a large-scale MIMO full-duplex heterogeneous network by using NOMA, which has the following beneficial effects:
1) by using the full duplex technology at the small base station, the user equipment can be cascaded with the uplink small base station and can also be cascaded with the downlink small base station. The distance from the small base station to the macro base station is larger than the distance from the small base station to the user equipment, so that the macro base station is regarded as a remote user.
2) According to the invention, NOMA technology is used at a small base station, non-orthogonal transmission is used at a transmitting end, interference information is actively introduced, and demodulation is realized at a receiving end through a serial interference elimination technology receiver. Although the complexity of the receiver adopting the serial interference cancellation technology is improved to a certain extent, the spectral efficiency can be better improved.
3) In the backhaul transmission realized at the small base station in the invention, the small base station is cascaded to the macro base station, and the connected macro base station directly decodes the backhaul signal from the small base station by taking the message of the superposed downlink user equipment signal as interference to complete the backhaul transmission process.
4) For downlink transmission of the user equipment, the user equipment can be cascaded to a macro base station or a small base station, and when the user equipment is cascaded to the macro base station, downlink messages are received; however, unlike the uplink, when the user equipment is cascaded to the small cell, since the NOMA technique is enabled at the small cell, the received information contains two parts: downlink messages and backhaul messages and therefore performance also depends on the choice of both aspects.
5) In the heterogeneous network provided by the invention, the macro base station uses a large-scale MIMO technology to further enhance the cell throughput. Many orders of magnitude more antenna elements are deployed at a base station while providing high data rates for user equipment within its cell. In addition to the gain in the whole cell, the effect of multipath fading (using infinite antennas) theoretically disappears because the signal-to-interference-plus-noise ratio converges to the deterministic equivalence (the random channel vector between base station and user becomes a noise-free deterministic channel).
6) Uplink and downlink transmit power is reduced by an order of magnitude with the number of antenna elements, or even more (less energy to maintain a particular signal-to-interference ratio or quality of service), in a power efficient sense. For the uplink, a high array gain for coherent combining may allow the transmit power of each terminal to be significantly reduced. For the downlink, energy can be focused from the base station to the direction in which the user is located by high resolution beamforming.
7) The present invention proposes a heterogeneous network in which a full duplex technique is used at a small base station, and base transceiver stations transmit and receive simultaneously on the same frequency band, thereby theoretically doubling the achievable rate compared to a half duplex communication system. To enable full duplex communication at a base station, two different antenna configurations, namely shared and split antenna configurations, can be implemented. With a shared antenna configuration, a single antenna simultaneously receives and transmits signals through a three-port circulator. While separate antenna configurations use separate antennas for signal reception and transmission.
8) In the invention, a random geometry domain tool is used for analyzing the coverage probability of uplink backhaul of the small cell and downlink transmission of user equipment, and effective approximation is adopted for interference of the user equipment. The distance between two user equipments is approximately the distance between one of the two users and the access point (small cell or macro base station) of the interfering user equipment. On the other hand, for the user equipment and the corresponding density measurement function, an approximately uniform poisson point process is adopted, and the reasonable power distribution coefficient is designed to be crucial to the coverage area and the energy efficiency. In addition, since the number of antennas in the massive MIMO system is very large, the resolution of the massive MIMO antenna is also important, and the energy efficiency can be significantly improved using a low-resolution massive MIMO antenna.
Drawings
Fig. 1 is a diagram illustrating a heterogeneous network model of the self-backhaul method of the heterogeneous network according to the present invention.
Fig. 2 is a diagram of an interference model suffered by a specific macro base station in the self-backhaul method of the heterogeneous network of the present invention.
Fig. 3 is a diagram of an example of a tdd transmission protocol of the self-backhaul method of the heterogeneous network according to the present invention.
Fig. 4 is a diagram illustrating an interference model suffered by a specific user in the self-backhaul method of the heterogeneous network according to the present invention.
Fig. 5 is a process diagram of macro cell and small cell transmission using NOMA technology of the self-backhaul method of the heterogeneous network of the present invention.
Fig. 6 is a diagram of a single-user MIMO transmission channel of the self-backhaul method of the heterogeneous network according to the present invention.
Fig. 7 is a transmission process diagram of a small cell and a user equipment in the self-backhaul method of the heterogeneous network of the present invention.
Fig. 8 is a useful channel gain diagram for uplink transmission in two cells of the self-backhauling method of the heterogeneous network of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings.
The invention designs an effective self-return method for realizing a large-scale MIMO full-duplex heterogeneous network by using NOMA, analyzes a heterogeneous wireless network consisting of a macro base station, a small base station and user equipment, and provides a network model using large-scale MIMO, full-duplex and NOMA technologies. The uplink access, the backhaul transmission and the downlink are respectively analyzed in detail, and the power consumption model of the large-scale MIMO macro base station in the method is used for analyzing the structural frequency spectrum and the energy efficiency.
Example 1
The present invention proposes a heterogeneous network consisting of macro cells and small cells, considering uplink and backhaul transmission, as well as downlink, as shown in figure 1.
Same frequency deploymentK+1Layer heterogeneous network, the first layer is macro cell, the restKThe layer is a small cell. Densely deployed small base stations are connected to a core network through a backhaul provided by a macro base station. The macro base station and the small base station both adopt full duplex technology. The link is established between the small cell base station and the macro base station, the link is established between the user equipment and the small cell base station, and the link is established between the macro base station and the user equipment, and the link is accessed to the macro cell.
Full duplex technology is used for macro base stations using massive MIMO technology and single antenna small base stations using NOMA technology. When they receive the signal from their tandem terminal, they also receive self-interference from its transmitted signal, and also receive other interference from the surroundings, and for the convenience of analysis, a model of the interference experienced by a particular macro base station is given, as shown in fig. 2. A full duplex macro base station and a small base station take self-interference cancellation to reduce self-interference. Using a precompression technique, the channel matrix between the transmit and receive antennas is modeled as loop interference, and the loop interference link is modeled as a rayleigh fading channel. The large-scale MIMO full-duplex heterogeneous network in the method uses a time division duplex protocol to send signals to a full-duplex communication link. As shown in fig. 3, an example of a time division duplex protocol is given. Where the forward link is separated from the reverse link by allocating different time symbols in the same frequency band. This transmission mode allows for symmetric flow for downlink and uplink data transmission, and thus channel training overhead can be reduced by exploiting reciprocity between downlink and uplink channels. The uplink pilot sequence is utilized by both downlink and uplink data transmissions. In alltThe symbols are fully used for pilot and for massive MIMO antennas the same set of pilot sequences is reused in neighbouring cells. The remainder of the coherence interval is used to transmit useful numbers on either the forward link or the reverse link or bothAccordingly.
For a downlink transmission scenario from a macro base station to a user equipment, there are two types of user terminal concatenation. The first type is downlink concatenation of a user terminal with a base station on a downlink access link, and the second type is uplink concatenation of a small cell and a user terminal. A user concatenation based on a maximum offset received power rule is used, wherein a user terminal is concatenated with the base station providing the maximum long term average received power. Thus, for downlink user equipment concatenation, atM(
Figure DEST_PATH_IMAGE082
) In macro base station
Figure 130167DEST_PATH_IMAGE002
The average bias received power of the user equipment at (a) is:
Figure DEST_PATH_IMAGE084
wherein
Figure 789687DEST_PATH_IMAGE009
Is the array gain of the zero-forcing beamforming transmission, and
Figure 903137DEST_PATH_IMAGE011
，
Figure 828367DEST_PATH_IMAGE013
is a bias factor for the macro base station. It is assumed that all macro base stations use the same bias factor. Unlike user equipment downlink concatenation in macro base stations, NOMA techniques are used at small base stations, exploiting multiple access power sparsity. In the method, a backhaul signal and a downlink access signal are superimposed in a power domain with a power sharing factor
Figure DEST_PATH_IMAGE085
And
Figure DEST_PATH_IMAGE086
. Thus, is located at
Figure DEST_PATH_IMAGE087
User equipment of (2) from layerkIs located atjThe average bias received power of the small base station is
Figure DEST_PATH_IMAGE088
，
Figure DEST_PATH_IMAGE089
Is a layerkThe same offset factor for small and medium sized base stations.
Since small base stations using NOMA technology operate in full duplex mode, there is a concatenation of user equipment uplink and small base station backhaul links. The cascade of the uplink of the user equipment is the cascade of the user equipment and a small base station, and the cascade of the backhaul link of the small base station is the cascade of the small base station and a macro base station for backhaul. Coverage analysis is difficult due to the use of NOMA technology at small base stations. And regarding the macro base station cascaded by the small base stations as a far-end user terminal, and directly decoding the backhaul message by regarding the superposed downlink message as noise by the macro base station. By analyzing the example of S =4 as shown in fig. 4, the transmission procedure of the macro cell and the small cell using the NOMA technique can be explained in detail.
It is assumed that small cell access point 1 is behind small cell access point 2, small cell access point 2 is behind small cell access point 3, and small cell access point 3 is behind small cell access point 4. As received in the macro cell downlink transmission, small cell access point 1 can only decode user data in for small cell 1, small cell access point 2 decodes not only user data in small cell 2 but also user data in small cell 1 and small cell 2. Finally, the small cell access point 4 decodes all data of the users in small cells 1,2, 3 and 4. Since the small cell access point, 2, 3 and 4 all have data for user in small cell 1, they may cooperate with small cell access point 1 to send data s1 to user 1 in small cell 1. Similarly, since the small cell access point 3 also has data for user 2 in small cell 2, it can cooperate with small cell 1. Here, the cooperation between small cell access points 1,2, 3 and 4 is that small cell access point 2, small cell access point 3 and small cell access point 4 can simultaneously send message s1, and their own messages s2, s3 and s4, respectively. Similarly, small cell access points 3 and 4 may also simultaneously transmit message s2, and their own messages s3 and s4, respectively, to improve signal reception for small cell users 1 and 2. Without such cooperation, each small cell access point would only transmit its own signal.
Use of
Figure DEST_PATH_IMAGE091
Indicating the number of small base stations that are cascaded with the macro base station over the backhaul link by using the maximum bias received power strategy.
Figure 613527DEST_PATH_IMAGE091
Is a random variable and can exceed the maximum number of backhaul flow supports for the maximum layer k
Figure 861975DEST_PATH_IMAGE091
. Characterizing random variables using probability mass functions
Figure 146326DEST_PATH_IMAGE091
By their mean values, i.e.
Figure 146326DEST_PATH_IMAGE091
To approximate the number of layers K of cascaded small base stations. Layers cascaded with macro base stationskCannot perform backhaul at the same time, and thus it is considered that the macro base station randomly selects
Figure DEST_PATH_IMAGE095
Of (b), thus a layerkThe scheduling activity of the small cell in (1) can be given as
Figure DEST_PATH_IMAGE097
Is a firstkBackhaul access probability of small and medium base stations in the layer. By a macro base stationkThe number of backhaul flows of the layer service is
Figure DEST_PATH_IMAGE099
。
To facilitate analysis of the interference experienced by the user equipment, a particular user equipment is analyzed as shown in fig. 5. Is located at
Figure DEST_PATH_IMAGE100
User equipment and the secondkLayer is located at
Figure DEST_PATH_IMAGE101
When the small base station is cascaded, the received composite signal contains the required signal and the signals from the small base station to the base station
Figure 122634DEST_PATH_IMAGE101
The backhaul signal of the macro base station in the small base station cascade is regarded as a near user terminal, and according to the principle of NOMA, the transmission is successful under the following two conditions:
(1) the user equipment may decode a backhaul signal transmitted by its serving small cell;
(2) after performing the channel state information, the user equipment may decode its desired signal.
Example 2
Based on example 1, as shown in FIG. 1, the method is based onK+1Layered heterogeneous networks. As can be seen from the figure, the macro base station, the small base station and the user simultaneously implement receiving and sending information, while massive MIMO technology is used at both the macro base station and the small base station. As shown in fig. 6, signal power and link reliability are improved by coherently processing signals at multiple transceiver ports to achieve diversity gain. With massive MIMO technology, separate links can be created for transmitting independent data streams, providing more degrees of freedom for the propagation channel, and enabling multiplexing.
In addition, as shown in fig. 7, in the heterogeneous network of the method, the small cell applies a power domain NOMA, and for a user with a poor channel condition, a larger power is allocated when transmitting information, and vice versa for a user with a good channel condition. At the transmitting end, the base station communicates with all users through the same time-frequency resources, i.e. through superposition coding technology. At the receiving end, reception is performed by successive interference cancellation.
Example 3
As shown in FIG. 8, uplink transmissions in two cells have
Figure DEST_PATH_IMAGE103
Represent fromkThe available channel gain of an individual user to its serving massive MIMO base station. Assume i.i.d. Rayleigh fading channel model, base station in the first cell and the second cellkThe complex propagation coefficients between individual users can be calculated as:
Figure DEST_PATH_IMAGE105
Figure DEST_PATH_IMAGE107
is a complex fast fading factor representing the channel matrix of all userskColumn(s) of
Figure DEST_PATH_IMAGE109
，
Figure DEST_PATH_IMAGE111
Is an amplitude factor that affects ensemble attenuation and shadow fading, assuming that because geometrical attenuation and shadow fading vary very slowly with respect to the spatial dimensions, it remains constant over frequency and the index of the base station antenna, and gives:
Figure DEST_PATH_IMAGE113
，
within each cellKEach terminal sends the data stream to a corresponding base station, and the base station uses the channel state information to perform linear detection.
Regional spectral efficiency
The regional spectral efficiency takes into account the spatial properties of the heterogeneous network, and the unit is, when the downlink of the user equipment is taken into account, the average regional spectral efficiency of the downlink of the user equipment is:
Figure DEST_PATH_IMAGE115
。
s6, regional energy efficiency
In order to test the improvement of the method on the energy efficiency, firstly, power consumption models of a small base station, a macro base station and user equipment are formulated. In general, the power consumption of the system includes radiation power, circuit consumption power, and power consumption of signal processing. In a conventional antenna array, each antenna requires an analog-to-digital converter or a digital-to-analog converter, which is responsible for most of the circuit power consumption. Especially in massive MIMO systems, the power consumption of the analog-to-digital converter (digital-to-analog converter) circuit is very large due to the large number of antennas deployed. Thus, the power consumption of a macro base station using massive MIMO is
Figure DEST_PATH_IMAGE117
Figure DEST_PATH_IMAGE119
The reciprocal of the drain efficiency of the macro base station power amplifier represents a static circuit power consumption constant, and the power consumption of an analog-to-digital converter of each macro base station is calculated as follows:
Figure DEST_PATH_IMAGE120
wherein
Figure DEST_PATH_IMAGE121
A representative constant, b is the resolution (number of quantization bits) of the analog-to-digital converter; next, the downlink power consumption is analyzed as:
Figure DEST_PATH_IMAGE122
wherein
Figure DEST_PATH_IMAGE123
And
Figure DEST_PATH_IMAGE124
is the drain efficiency of the small base station power amplifier andKthe inverse of the static power consumption of the small base station.
In addition to the above embodiments, the present invention may have other embodiments, and any technical solutions formed by equivalent substitutions or equivalent transformations are within the scope of the present invention as claimed.

Claims (5)

1. A self-backhauling method of a heterogeneous network, comprising the steps of:
s1, deploying K +1 layer heterogeneous networks in the same frequency, wherein the first layer is a macro cell, the remaining K layers are small cells, the macro base station is located at an optical fiber point of presence or a high-capacity line-of-sight microwave link available for the core network, the small base station is connected to the core network through a return stroke provided by the macro base station, the macro base station simultaneously sends downlink signals to user equipment by using a full-duplex technology and receives the return stroke from the small base station through the same resource block, the small base station using NOMA and the full-duplex technology firstly combines the downlink signals and the return stroke signals to the macro base station by using power domain superposition codes with different power sharing coefficients, and then the small base station simultaneously sends the obtained superposition signals and receives uplink signals of the user equipment on the same resource block by using the full-duplex technology;
s2, selecting a user terminal cascade strategy for an uplink and a downlink of the user equipment and a backhaul link of the small cell by using the NOMA power sharing coefficient;
s3, modeling interference of a return link and an access link by using a random geometry and a Poisson point process, modeling an active small base station as a new Poisson point process, modeling uplink user equipment cascaded to the active small base station as another independent non-uniform Poisson point process, and calculating interference distribution;
s4, calculating the coverage probability of uplink and uplink backhaul transmission from the user equipment to the small base station by using the characteristics of the NOMA superposition coding and the channel state information and the interference distribution obtained in the step S3, and obtaining the coverage probability of the downlink of the user equipmentBy setting one at ODThe user equipment of (1) uses a user cascade based on a maximum bias received power rule, wherein the user terminal is cascaded with the base station providing the maximum long-term average received power and for the downlink user equipment cascade, is located at M (M is equal to phi)M) At a macro base station ofDThe average bias received power of the user equipment at (a) is:
Figure FDA0003401257200000011
wherein
Figure FDA0003401257200000012
Is the array gain of the zero-forcing beamforming transmission, and
Figure FDA0003401257200000013
ζMis a macro base station bias factor, a backhaul signal and a downlink access signal are superposed in a power domain and have a power sharing coefficient
Figure FDA0003401257200000021
And
Figure FDA0003401257200000022
at the position of ODThe average biased received power of the small base station at j from layer k is:
Figure FDA0003401257200000023
Figure FDA0003401257200000024
are the same bias factors of the small and medium base stations in layer k;
s5, providing a model of frequency spectrum and energy efficiency, analyzing the influence of NOMA and full-duplex technology on the heterogeneous network, and analyzing the resolution of the analog-to-digital converter in the large-scale MIMO antenna array, wherein the power consumption model of the macro base station, the small base station and the user equipment is formulated, and the power consumption of the macro base station using the large-scale MIMO technology is as follows:
Figure FDA0003401257200000025
wherein epsilonMThe reciprocal of the drain efficiency of the macro base station power amplifier represents a static circuit power consumption constant, and the power consumption of an analog-to-digital converter of each macro base station is calculated as follows:
Figure FDA0003401257200000026
wherein N is0A representative constant, b is the resolution of the analog-to-digital converter; the downlink power consumption is analyzed as:
Figure FDA0003401257200000027
wherein
Figure FDA0003401257200000028
And
Figure FDA0003401257200000029
is the inverse of the drain efficiency of the small base station power amplifier and the static power consumption of the kth small base station.
2. The self-backhauling method of the heterogeneous network of claim 1, wherein: based on small cell using NOMA and full duplex technology, there is a concatenation of user equipment uplink and small cell backhaul link, where the user equipment uplink concatenation is located at OUThe user equipment is cascaded with a small base station, and the cascade of the backhaul links of the small base station is positioned at
Figure FDA00034012572000000210
The small base station and the macro base station are cascaded for backhaul, the cascade of two user terminals is carried out by using a cascade rule based on the nearest distance, the signal-to-interference-plus-noise ratio of a downlink is maximized, and the user equipment is positioned closest to the K-th layer
Figure FDA00034012572000000211
The probability of small base station concatenation is:
Figure FDA0003401257200000031
3. the self-backhauling method of the heterogeneous network of claim 1, wherein: different interference aggregates exist under different distributed random variables, and the analysis process comprises the following steps:
s31, setting the interference terminal v e phi received by the user equipment uPOf where phiPIs a density of λPIndependent poisson point process of (1), random variable hv，uAnd | Xv，uL is the channel gain and the terminal v ∈ Φ respectivelyPDistance from receiver terminal u, corresponding path loss exponent αPIn small scale fading channel gain obeys rayleigh distribution of unit power and distance | Xv，u| satisfy | Xv，uUnder the condition that | ≧ 0, the equivalent power parameter A is utilizedPAnd path loss exponent αPFrom interfering terminal v e phiPThe laplacian transform of the interference received by user equipment u of (a) is:
Figure FDA0003401257200000032
when the distance | Xv，u| satisfy | Xv，uWhen | ≧ z, the corresponding laplace transform:
Figure FDA0003401257200000033
s32, equivalent small-scale fading channel gain gv，uObeying a gamma distribution with parameter (N, 1): g is a radical of formulav，uΓ (N, 1), distance | Xv，u| satisfy | Xv，u| ≧ 0, utilizing equivalent power parameter APAnd path loss exponent αPReceiving the information from the terminal v e phiPOf user equipment uLaplace transform of (a):
Figure FDA0003401257200000041
wherein
Figure FDA0003401257200000042
Is a binomial coefficient;
when the distance | Xv，u| satisfy | Xv，uWhen | ≧ z, the corresponding laplace transform:
Figure FDA0003401257200000043
4. the self-backhauling method of the heterogeneous network of claim 1, wherein: the coverage probability corresponding to the uplink backhaul transmission comprises access transmission from the user equipment to the small base station and backhaul transmission from the small base station to the macro base station.
5. The self-backhauling method of the heterogeneous network of claim 1, wherein: when the user equipment is cascaded with the macro base station, the coverage probability is determined by a signal to interference plus noise ratio in downlink transmission from the macro base station to the user equipment; when the UE is cascaded with NOMA and a full-duplex small base station, the coverage probability is obtained by the signal-to-interference-plus-noise ratio in the downlink transmission from the small base station to the UE, and meanwhile, the coverage probability is influenced by the backhaul transmission from the small base station to the macro base station.
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