Optimization method and device for interference alignment of heterogeneous networks and storage medium

Abstract

The embodiment of the present application discloses a kind of optimization methods and related equipment of heterogeneous network interference alignment, and heterogeneous network interference can be aligned optimization.The method comprises: determining the first position information of each user in target cell in current period;According to the position information of each user and the antenna scanning beam pattern corresponding to target base station, the first digital label corresponding to each user is determined, and the target base station corresponds to the target cell;According to the first digital label, each user is grouped, and the grouping information corresponding to each user is obtained;According to the grouping information corresponding to each user, the heterogeneous network is aligned and optimized.

Description

Technical Field

[0001] This application relates to the field of communications, and in particular to an optimization method, apparatus and storage medium for interference alignment in heterogeneous networks. Background Technology

[0002] Heterogeneous networks (HetNet), one of the ten key technologies of 5G (5th Generation Mobile Communication Technology), refer to networks based on macro base stations and low-power access nodes, such as micro base stations, pico base stations, and flying base stations, or coexisting with multiple access technologies such as WiFi and Long Term Evolution (LTE). To address the challenges posed by the massive increase in the number of devices and the accelerating demands of users for service speed, quality of service, and security, 5G network architecture is evolving towards ultra-dense, three-dimensional macro-micro collaborative networking, effectively improving system throughput and bandwidth utilization. However, with the increase in the number and types of heterogeneous nodes deployed, the network will experience complex and severe interference problems, leading to decreased data transmission quality, increased error rates, and reduced system capacity.

[0003] Interference Alignment (IA) technology fully utilizes precoding techniques and designs transmit / receive matrices at the transceiver ends to compress and align the spatial dimension of interference signals into a finite-dimensional subspace orthogonal to the desired signal. The goal is to achieve maximum system freedom, i.e., maximum multiplexing gain or signal dimension, thereby suppressing and eliminating interference. Current IA in heterogeneous networks primarily involves first grouping micro-users within a microcell, then aligning the interference generated by the macro base station to users within the group into a subspace along the same direction to eliminate cross-layer interference. Finally, distributed or iterative IA algorithms based on singular value decomposition are used to compress the signal space occupied by inter-cell interference.

[0004] This networking method performs an IA calculation every time data is transmitted. As the number of users increases, the computational complexity becomes high, resulting in excessive overhead and wasted resources. Summary of the Invention

[0005] This application provides an optimization method, apparatus, and storage medium for heterogeneous network interference alignment, which can optimize the alignment of heterogeneous network interference.

[0006] The first aspect of this application provides an optimization method for interference alignment in heterogeneous networks, which may include:

[0007] Determine the first location information of each user in the target cell within the current period;

[0008] The first digital tag corresponding to each user is determined based on the location information of each user and the antenna scanning beam pattern corresponding to the target base station, wherein the target base station corresponds to the target cell;

[0009] The users are grouped according to the first digital tag to obtain the group information corresponding to each user;

[0010] The heterogeneous network is optimized for interference alignment based on the group information corresponding to each user.

[0011] In one possible design, determining the first digital tag corresponding to each user based on the location information of each user and the antenna scanning beam pattern corresponding to the target base station includes:

[0012] The coverage area of ​​the target base station is divided into at least two regions based on the antenna scanning beam pattern.

[0013] If there is a target area in at least two regions where the number of users in the target area is greater than a preset threshold, the target area will be divided into two sub-regions.

[0014] The first digital tag is assigned to each user based on the area identifiers corresponding to other areas and the area identifiers corresponding to the two sub-areas, wherein the other areas are areas other than the target area among the at least two areas.

[0015] In one possible design, the target base station includes macro base stations and micro base stations, and the interference alignment optimization of the heterogeneous network based on the packet information corresponding to each user includes:

[0016] Construct the first transmit beamforming matrix corresponding to the macro base station;

[0017] Construct the second transmit beamforming matrix corresponding to the micro base station;

[0018] Construct the first receive beamforming matrix for the user corresponding to the macro base station;

[0019] Construct the second receive beamforming matrix for the user corresponding to the micro base station;

[0020] The first transmit beamforming matrix, the second transmit beamforming matrix, the first receive beamforming matrix, and the second receive beamforming matrix are used to perform interference alignment optimization on the heterogeneous network using the grouping information corresponding to each user.

[0021] In one possible design, the step of invoking at least one of the first transmit beamforming matrix, the second transmit beamforming matrix, the first receive beamforming matrix, and the second receive beamforming matrix to perform interference alignment optimization on the heterogeneous network using the grouping information corresponding to each user includes:

[0022] Determine the user group corresponding to the microcell, wherein the microcell corresponds to the micro base station;

[0023] By using the first digital tag corresponding to each user and the group information corresponding to each user, the cross-layer interference generated by the macro base station to the user in the user group is aligned to the same subspace.

[0024] In one possible design, determining the location information of each user within the target cell in the current period includes:

[0025] Determine the signal propagation time between a first target user and each of at least two base stations, wherein the first target user is any one of the users in the target cell;

[0026] The distance between the first target user and each of the at least two base stations is calculated based on the signal propagation time.

[0027] The location information of the first target user is determined based on the location of each of the at least two base stations and the distance between the first target user and each of the at least two base stations.

[0028] In one possible design, the method further includes:

[0029] Determine the second location information of each user in the target cell for the next cycle;

[0030] The second digital tag corresponding to each user is determined based on the second location information and the antenna scanning beam pattern;

[0031] If there is a third target user among the users whose second digital tag does not match the first digital tag, then the third target user is regrouped to obtain the grouping information corresponding to the third target user;

[0032] The heterogeneous network is subjected to interference alignment optimization based on the third target grouping information.

[0033] A second aspect of this application provides a heterogeneous network interference alignment optimization apparatus, comprising:

[0034] The first determining unit is used to determine the first location information of each user in the target cell within the current period;

[0035] The second determining unit is used to determine the first digital tag corresponding to each user based on the location information of each user and the antenna scanning beam pattern corresponding to the target base station, wherein the target base station corresponds to the target cell;

[0036] A segmentation unit is used to group the users according to the first digital tag to obtain the grouping information corresponding to each user;

[0037] The optimization unit is used to perform interference alignment optimization on the heterogeneous network based on the group information corresponding to each user.

[0038] In one possible design, the second determining unit is specifically used for:

[0039] The coverage area of ​​the target base station is divided into at least two regions based on the antenna scanning beam pattern.

[0040] If there is a target area in at least two regions where the number of users in the target area is greater than a preset threshold, the target area will be divided into two sub-regions.

[0041] The first digital tag is assigned to each user based on the area identifiers corresponding to other areas and the area identifiers corresponding to the two sub-areas, wherein the other areas are areas other than the target area among the at least two areas.

[0042] In one possible design, the target base station includes macro base stations and micro base stations, and the optimization unit is specifically used for:

[0043] Construct the first transmit beamforming matrix corresponding to the macro base station;

[0044] Construct the second transmit beamforming matrix corresponding to the micro base station;

[0045] Construct the first receive beamforming matrix for the user corresponding to the macro base station;

[0046] Construct the second receive beamforming matrix for the user corresponding to the micro base station;

[0047] The first transmit beamforming matrix, the second transmit beamforming matrix, the first receive beamforming matrix, and the second receive beamforming matrix are used to perform interference alignment optimization on the heterogeneous network using the grouping information corresponding to each user.

[0048] In one possible design, the optimization unit invokes at least one beamforming matrix from the first transmit beamforming matrix, the second transmit beamforming matrix, the first receive beamforming matrix, and the second receive beamforming matrix to perform interference alignment optimization on the heterogeneous network using the grouping information corresponding to each user, including:

[0049] Determine the user group corresponding to the microcell, wherein the microcell corresponds to the micro base station;

[0050] By using the first digital tag corresponding to each user and the group information corresponding to each user, the cross-layer interference generated by the macro base station to the user in the user group is aligned to the same subspace.

[0051] In one possible design, the first determining unit is specifically used for:

[0052] Determine the signal propagation time between a first target user and each of at least two base stations, wherein the first target user is any one of the users in the target cell;

[0053] The distance between the first target user and each of the at least two base stations is calculated based on the signal propagation time.

[0054] The location information of the first target user is determined based on the location of each of the at least two base stations and the distance between the first target user and each of the at least two base stations.

[0055] In one possible design,

[0056] The first determining unit is further configured to determine the second location information of each user in the target cell in the next cycle;

[0057] The second determining unit is further configured to determine the second digital tag corresponding to each user based on the second location information and the antenna scanning beam pattern;

[0058] The segmentation unit is further configured to, if among the users there is a third target user whose second digital label does not match the first digital label, regroup the third target user to obtain the grouping information corresponding to the third target user;

[0059] The optimization unit is further configured to perform interference alignment optimization on the heterogeneous network based on the third target grouping information.

[0060] A third aspect of this application provides a computer-readable storage medium storing at least one executable instruction that, when executed on a computing device, causes the computing device to perform the optimization method for heterogeneous network interference alignment as described in the first aspect of this application.

[0061] The fourth aspect of this application discloses a computer program product that, when run on a computer, causes the computer to execute the optimization method for heterogeneous network interference alignment described in the first aspect of this application.

[0062] The fifth aspect of this application discloses an application publishing platform for publishing computer program products, wherein when the computer program products are run on a computer, the computer executes the optimization method for heterogeneous network interference alignment described in the first aspect of this application.

[0063] As can be seen from the above technical solutions, the embodiments of this application have the following advantages:

[0064] In this embodiment, the location information of each user within the cell is acquired, and digital tags are assigned to each user based on the location information. Users are then flexibly and dynamically grouped based on these digital tags. A pre-constructed transmit / receive beamforming matrix is ​​then used and stored, and can be directly retrieved as needed. This achieves dynamic grouping interference alignment and avoids repetitive calculations within a cycle, effectively improving network flexibility, resource utilization, and interference handling efficiency, while ensuring correct data transmission. Attached Figure Description

[0065] The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0066] Figure 1 This is a network architecture diagram of the heterogeneous network interference alignment optimization system provided in the embodiments of this application;

[0067] Figure 2 A flowchart illustrating the optimization method for heterogeneous network interference alignment provided in an embodiment of this application;

[0068] Figure 3 This is a schematic diagram illustrating the determination of location information for each user in a target cell, provided in an embodiment of this application.

[0069] Figure 4 This is a schematic diagram of the coverage area division of a base station provided in an embodiment of this application;

[0070] Figure 5 This is a schematic diagram of the virtual structure of the heterogeneous network interference alignment optimization device provided in the embodiments of this application;

[0071] Figure 6 This is a schematic diagram of the hardware structure of the server provided in an embodiment of this application. Detailed Implementation

[0072] To enable those skilled in the art to better understand the present application, the technical solutions of the embodiments of the present application will be described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. All embodiments based on the present application should fall within the scope of protection of the present application.

[0073] Existing inter-user identification (IA) methods for heterogeneous networks statically group micro-users, either by grouping users within the same microcell or by grouping users from all microcells together, followed by interference alignment. Each time data is transmitted, the precoding interference suppression matrix at both the transceiver and receiver needs to be regenerated using the IA algorithm. This approach does not consider the impact of user location and mobility on the grouping method, resulting in significant resource waste due to the large amount of repetitive computation during each data transmission. Furthermore, this method struggles to cope with the ever-increasing number of users, requiring highly sophisticated antenna configurations and achieving high computational complexity. It also fails to fully leverage the interference suppression capabilities of IA, leading to a significant deterioration in transmission link quality.

[0074] Please see Figure 1 , Figure 1 The network architecture diagram of the heterogeneous network interference alignment optimization system provided in this application embodiment includes:

[0075] The target cell 100 includes a macro base station 101, a micro base station 102, and a micro base station 103. Each of the macro base station 101, micro base station 102, and micro base station 103 serves two user terminals. The interference signals in the target cell 100 mainly include cross-layer interference signals 104, inter-cell interference signals 105, and inter-user interference signals 106. The cross-layer interference signal 104 is the interference signal caused by the macro base station 101 to the users covered by the micro base station 102. The inter-cell interference signal 105 is the interference signal caused by the micro base station 103 to the users in the micro base station 102. The inter-user interference signal 106 is the interference signal caused by the base station to the users it covers.

[0076] In view of this, this application provides an optimized method for interference alignment in heterogeneous networks. After obtaining the real-time location of users from base stations, the edge server assigns specific digital tags to users and flexibly and dynamically groups users. Then, using the digital tags, the edge server performs inter-intelligence (IA) calculations to obtain the transmit / receive precoding matrix and stores the results. Finally, it can be directly accessed as needed. By incorporating user behavior and introducing digitization, this method significantly reduces the computational complexity of IA and the resource waste caused by redundant calculations, effectively improving network flexibility and interference handling efficiency, and ensuring the correct transmission of network data.

[0077] The following section provides a detailed explanation of the heterogeneous network interference alignment optimization method provided in this application from the perspective of a heterogeneous network interference alignment optimization device.

[0078] Please see Figure 2 , Figure 2 A flowchart illustrating the optimization method for heterogeneous network interference alignment provided in this application embodiment includes:

[0079] 201. Determine the first location information of each user in the target cell for the current period.

[0080] In this embodiment, the heterogeneous network interference alignment optimization device can determine the first location information of each user in the target cell of the current period through the base station. Specifically, the heterogeneous network interference alignment optimization device determines the first location information of each user in the target cell of the current period in the following manner:

[0081] Determine the signal propagation time between the first target user and each of at least two base stations, wherein the first target user is any one of the users in the target cell;

[0082] Calculate the distance between the first target user and each of the at least two base stations based on the signal propagation time;

[0083] The location information of the first target user is determined based on the location of each of the at least two base stations and the distance between the first target user and each of the at least two base stations.

[0084] That is, the signal propagation time between the terminal device and at least two base stations is measured, and the distance between the terminal device and the base stations is calculated based on the signal propagation time. Then, circles are drawn with each base station as the center and the distance between the base station and the terminal device as the radius. The intersection of these circles is the two-dimensional coordinate position of the terminal device. Assume the base station position coordinates are (x... i y i If the terminal device's location coordinates are (x0, y0), then:

[0085] (x i -x0) 2+(y i -y0) 2 =R i 2 i = 1, ..., M, Formula 1;

[0086] Where M represents the number of base stations used to locate terminal devices, please refer to [link / reference]. Figure 3 , Figure 3 Taking the location of a terminal device using three base stations as an example, where 301 is base station 1, 302 is base station 2, 303 is base station 3, R1 is the distance between the terminal device (UE) and base station 1, R2 is the distance between the UE and base station 2, and R3 is the distance between the UE and base station 3. Draw circles with each base station as the center and the distance between the base station and the UE as the radius. The intersection of these circles, 304, is the location of the UE.

[0087] Of course, there are other ways to determine the primary location information of each user within the target cell for the current period, which will be explained in detail below:

[0088] I. Time Difference of Arrivals (TDOA) Method

[0089] TDOA positioning measures the difference in TOA (Time of Arrival) between two different base stations and a terminal device. Each TDOA measurement corresponds to a pair of hyperbolas with the two base stations as foci. The more TDOA values ​​there are, the more hyperbolas intersect, and the estimated location of the terminal device is its intersection point. In a Cartesian coordinate system, assuming the base station coordinates are (x, y), and the coordinates of three terminal devices A, B, and C are (x1, y1), (x2, y2), and (x3, y3) respectively, and the arrival times of the signals emitted by the three terminal devices at the base station are t1, t2, and t3 respectively, the distance between the three terminal devices can be calculated using the following formula: [Formula omitted for brevity].

[0090]

[0091] R s 2 =(R s1 +R1) 2 =R s1 2 +2*R s1 *R1+R1 2 , formula 3

[0092] (xx s ) 2 +(yy s ) 2 =R s1 2 +2*R s1*R1+R1 2 , formula 4

[0093] 2*R s1 *R1+2*x s1 *x+2*y s1 *y=k s 2 -k1 2 -R s1 2 , formula 5

[0094] Where: k i =x i 2 +y i 2 It can locate terminal device A, and then obtain the location information of all terminal devices.

[0095] II. Angle of Arrival (AOA) Method

[0096] The AOA (Angle of Arrival) utilizes the base station's receiving antenna array to measure the angle of arrival (AOA) of the radio waves transmitted by the terminal device. This creates a radial azimuth line from the base station to the terminal device. Multiple base stations jointly measure the AOA, and the intersection of their azimuth lines represents the estimated location of the terminal device. Assuming... and ω1 and ω2 are the azimuth angles of users A and B relative to the horizontal plane, respectively, and the elevation angles of the terminal device are the elevation angles of the terminal device. Generally, in two-dimensional plane positioning, positioning can be achieved simply by measuring the received signal.

[0097]

[0098] Where x1 and y1 are the two-dimensional coordinates of the terminal device, and x and y are the coordinates of the base station.

[0099] 3. GPS or BeiDou is used to locate the terminal device;

[0100] The terminal device is positioned using satellite network assistance. The terminal device receives signals from GPS or BeiDou integrated within it, measures and obtains location data, and reports it to the base station. The base station calculates the relative estimated position of the terminal device based on its latitude and longitude information.

[0101] 202. Determine the first digital tag corresponding to each user based on the location information of each user and the antenna scanning beam pattern corresponding to the target base station.

[0102] In this embodiment, the heterogeneous network interference alignment optimization device can equally divide the target base station coverage area according to the antenna scanning beammap to obtain at least two regions. If there is a target region in the at least two regions where the number of users in the region is greater than a preset threshold, the target region is divided into two sub-regions. Based on the region identifiers corresponding to the regions other than the target region in the at least two regions and the region identifiers corresponding to the two sub-regions, each user is assigned a first digital tag corresponding to the region where they are located. That is, taking the beamforming phased array antenna direction of a 5G base station as an example, the horizontal beam half-power angle width is approximately 30°. The coverage area corresponding to a single base station can be equally divided into three regions, i.e., two horizontal beam coverage areas are set as one division region. When the number of users in a certain region is too large (i.e., the number of users in that region is greater than a preset threshold), the region can be dynamically divided into two single-beam coverage areas, i.e., the coverage area of ​​a single base station is divided into four regions. Figure 4 As shown, Figure 4 This application provides a schematic diagram of the coverage area division of a base station. In the initial state, the base station is divided into three equal areas. Initially, sub-areas b and c are one area. Since the number of users in this area is greater than a preset threshold, the area is divided into two sub-areas. The more areas are divided, the higher the computational overhead and complexity will be, but the stronger the interference suppression capability will be. In practical applications, it is also necessary to select and balance according to the network load. For example, when the cell network load is below 30%, the coverage area of ​​multiple beams can be divided into one area. When the network load is between 30% and 60%, the coverage area of ​​two beams can be divided into one area. When the network load is greater than 60%, due to the large number of users, the coverage area of ​​a single beam can be divided into one area. The above is only an example. Of course, there are other division methods, which are not limited to this one.

[0103] Subsequently, the heterogeneous network interference alignment optimization device, based on the first location information of each user within the target cell, rationally divides the base station coverage area into multiple regions and assigns corresponding digital tags to terminal devices within each region. The following will all use... Figure 4 Taking the four regions shown as an example, the digital tag of the terminal device is in the form of [T, Q, N], where T is the base station identifier, Q∈{a, b, c, d} represents the region identifier in the cell, and N is the terminal device identifier. If the base station antenna is a 64TR antenna, the maximum horizontal beam of a single cell is 16. When the network load is greater than 60%, the cell can be divided into a maximum of 16 regions, then Q∈{a, b, ..., p} has a total of 16 values. The digital tag of the base station is only related to the base station identifier, i.e., the base station ID.

[0104] 203. Group each user according to the first numerical label to obtain the group information corresponding to each user.

[0105] In this embodiment, the heterogeneous network interference alignment optimization device groups each user according to the first digital tag, obtains the group information corresponding to each user, that is, users with the same T and Q values ​​are grouped together, and stores the information of all groups.

[0106] 204. Perform interference alignment optimization on heterogeneous networks based on the group information corresponding to each user.

[0107] In this embodiment, the heterogeneous network interference alignment optimization device can perform interference alignment according to the grouping method of the current period, thereby solving the serious interference problem in heterogeneous networks:

[0108] The system has a set of base stations L = {0, 1, 2, ..., L}, where L = 0 represents a macro base station (MBS). The number of macro users (represented by MUEs) is K0. Each microcell (a technology developed based on macro cells, with a coverage radius of approximately 30m to 300m and low transmit power, generally below 1W) contains K micro users (PUEs). The number of antennas configured on the MBS is M0, and the number of antennas configured on the micro base station (PBS) is M. All users (including MUEs and PUEs) are configured with M′ antennas.

[0109] The signal transmitted to the i-th user UE [i, l] in the l-th cell of the network can be represented as:

[0110]

[0111] in, This indicates that the power constraint condition for the received signal of the j-th data stream of UE[i, l] must satisfy E[||x] [i，l] || 2 ]≤P [i，l] , Indicates bearing Beamforming vector, This represents the transmit beamforming matrix pointing to UE[i, l], and the corresponding data signal vector is...

[0112] The signal decoded by the receiving precoding matrix at the UE[i, l] end can be represented as:

[0113]

[0114] in, This represents the channel matrix from base station l′ to UE[i, l]. Assume the channel is a quasi-static flat fading channel, and its elements are independent and identically distributed random variables, n. [i，l]This indicates that the prescription difference in UE[i, l] is σ. 2 The additive white Gaussian noise vector.

[0115] To address cross-layer interference, a macro base station transmit beamforming matrix (first reflection beamforming matrix) is designed. Specifically, based on the concept of subspace alignment in the interference alignment algorithm, the space containing the macro base station transmit beamforming matrix needs to be independent of the space formed by the cross-layer interference channel to eliminate the impact of cross-layer interference on the desired signal.

[0116]

[0117] in, V MBS For the first transmit beamforming matrix corresponding to the macro base station, using the allocated hand-held tags and stored packet information, the cross-layer interference generated by MBS for users in each group under each microcell is aligned to the same subspace, that is:

[0118]

[0119]

[0120]

[0121]

[0122] Where l∈P, k∈N, after grouping interference alignment according to group labels, all cross-layer interference caused by MBS transmission signals is aligned into Q×(P-1) different signal subspaces, which reduces the computational complexity caused by a large number of calculations when calculating the receive beamforming matrix of each PUE.

[0123]

[0124] Design the transmit beamforming matrix for each micro base station to suppress inter-cell and inter-user interference experienced by the PUE. By solving equations 10 to 13, the receive beamforming matrix for the PUE can be obtained. The transmit matrix of the PBS can be designed as follows:

[0125]

[0126] in, The first K-1 terms in this combined matrix represent all inter-user interference within a PBS coverage area, and the subsequent K(L-1) terms represent inter-cell interference between all microcells within the same layer.

[0127] The design method for the MUE's receive beamforming matrix is ​​the same, and will not be elaborated here. The MUE's receive beamforming matrix can suppress interference between users on the same layer between MUEs. After obtaining each beamforming matrix, it can be stored for convenient subsequent use.

[0128] It should be noted that after storing each beamforming matrix, the second location information of each user in the target cell can be determined in the next cycle. Based on the second location information and the antenna scanning beammap, the second digital tag corresponding to each user is determined. If there is a third target user whose second digital tag does not match the first digital tag, the third target user is regrouped to obtain the grouping information corresponding to the third target user. Interference alignment optimization of the heterogeneous network is then performed based on the third target grouping information. In other words, interference alignment optimization of the heterogeneous network can be performed periodically. Considering the user's mobility, the size of the divided area, and the length of the user's measured received reference signal period, the user's location information is reacquired at a certain time period τ. The current user's digital tag is updated according to the method described in step 202 above. It is then determined whether the tag is consistent with the tag stored in the previous cycle. If consistent, the transmitted and received beamforming matrices of each network node after interference alignment in the previous cycle (i.e., the beamforming matrix constructed in step 204) are directly called. If inconsistent, the user whose tag has changed is simply reassigned to a new group, interference alignment is performed again, and the result is stored.

[0129] In summary, it can be seen that the embodiments provided in this application acquire the location information of each user within the cell, assign digital tags to each user based on the location information, and flexibly and dynamically group users based on the digital tags. Then, a pre-constructed transmit / receive beamforming matrix is ​​used and stored, which can be directly retrieved as needed. This achieves dynamic grouping interference alignment and avoids repetitive calculations within a cycle, effectively improving network flexibility, resource utilization, and interference handling efficiency, while ensuring correct data transmission.

[0130] The embodiments of this application have been described above from the perspective of the method for heterogeneous network interference alignment optimization. The embodiments of this application will now be described from the perspective of the heterogeneous network interference alignment optimization device:

[0131] Please see Figure 5 , Figure 5 This is a schematic diagram of an embodiment of the heterogeneous network interference alignment optimization device provided in this application. The heterogeneous network interference alignment optimization device includes:

[0132] The first determining unit 501 is used to determine the first location information of each user in the target cell within the current period;

[0133] The second determining unit 502 is used to determine the first digital tag corresponding to each user based on the location information of each user and the antenna scanning beam pattern corresponding to the target base station, wherein the target base station corresponds to the target cell;

[0134] The segmentation unit 503 is used to group the users according to the first digital tag to obtain the grouping information corresponding to each user;

[0135] The optimization unit 504 is used to perform interference alignment optimization on the heterogeneous network based on the group information corresponding to each user.

[0136] In one possible design, the second determining unit 502 is specifically used for:

[0137] The coverage area of ​​the target base station is divided into at least two regions based on the antenna scanning beam pattern.

[0138] If there is a target area in at least two regions where the number of users in the target area is greater than a preset threshold, the target area will be divided into two sub-regions.

[0139] The first digital tag is assigned to each user based on the area identifiers corresponding to other areas and the area identifiers corresponding to the two sub-areas, wherein the other areas are areas other than the target area among the at least two areas.

[0140] In one possible design, the target base station includes macro base stations and micro base stations, and the optimization unit 504 is specifically used for:

[0141] Construct the first transmit beamforming matrix corresponding to the macro base station;

[0142] Construct the second transmit beamforming matrix corresponding to the micro base station;

[0143] Construct the first receive beamforming matrix for the user corresponding to the macro base station;

[0144] Construct the second receive beamforming matrix for the user corresponding to the micro base station;

[0145] The first transmit beamforming matrix, the second transmit beamforming matrix, the first receive beamforming matrix, and the second receive beamforming matrix are used to perform interference alignment optimization on the heterogeneous network using the grouping information corresponding to each user.

[0146] In one possible design, the optimization unit 504 invokes at least one beamforming matrix from the first transmit beamforming matrix, the second transmit beamforming matrix, the first receive beamforming matrix, and the second receive beamforming matrix to perform interference alignment optimization on the heterogeneous network using the grouping information corresponding to each user, including:

[0147] Determine the user group corresponding to the microcell, wherein the microcell corresponds to the micro base station;

[0148] By using the first digital tag corresponding to each user and the group information corresponding to each user, the cross-layer interference generated by the macro base station to the user in the user group is aligned to the same subspace.

[0149] In one possible design, the first determining unit 501 is specifically used for:

[0150] Determine the signal propagation time between a first target user and each of at least two base stations, wherein the first target user is any one of the users in the target cell;

[0151] The distance between the first target user and each of the at least two base stations is calculated based on the signal propagation time.

[0152] The location information of the first target user is determined based on the location of each of the at least two base stations and the distance between the first target user and each of the at least two base stations.

[0153] In one possible design,

[0154] The first determining unit 501 is further configured to determine the second location information of each user in the target cell in the next cycle;

[0155] The second determining unit 502 is further configured to determine the second digital tag corresponding to each user based on the second location information and the antenna scanning beam pattern;

[0156] The segmentation unit 503 is further configured to regroup the third target users if there is a third target user among the users whose second digital tag does not match the first digital tag, and obtain the grouping information corresponding to the third target user.

[0157] The optimization unit 504 is further configured to perform interference alignment optimization on the heterogeneous network based on the third target grouping information.

[0158] This application also provides another heterogeneous network interference alignment optimization device, which is deployed on a server. Please refer to... Figure 6 , Figure 6 This is a schematic diagram of a server structure provided in an embodiment of this application. The server 600 can vary significantly due to different configurations or performance characteristics. It may include one or more central processing units (CPUs) 622 (e.g., one or more processors) and a memory 632, and one or more storage media 630 (e.g., one or more mass storage devices) for storing application programs 642 or data 644. The memory 632 and storage media 630 can be temporary or persistent storage. The program stored in the storage media 630 may include one or more modules (not shown in the diagram), each module including a series of instruction operations on the server. Furthermore, the CPU 622 may be configured to communicate with the storage media 630 and execute the series of instruction operations stored in the storage media 630 on the server 600.

[0159] Server 600 may also include one or more power supplies 626, one or more wired or wireless network interfaces 650, one or more input / output interfaces 658, and / or one or more operating systems 641, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, etc.

[0160] The steps performed by the heterogeneous network interference alignment optimization device in the above embodiments can be based on this. Figure 6 The server structure shown.

[0161] This application also provides a computer-readable storage medium storing at least one executable instruction, which, when executed on a computing device, causes the computing device to perform the optimization method for heterogeneous network interference alignment described in any of the above embodiments.

[0162] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0163] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0164] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0165] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0166] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0167] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0168] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0169] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. An optimization method for interference alignment in heterogeneous networks, characterized in that, include: Determine the first location information of each user in the target cell within the current period; Based on the first location information of each user in the target cell, the base station coverage area is divided into multiple areas, and the first digital tag corresponding to each user is determined according to the first location information of each user and the antenna scanning beam pattern corresponding to the target base station. The target base station corresponds to the target cell. The first digital tag is in the form of [T, Q, N], where T is the identifier of the base station, Q is the area identifier in the cell, and N is the identifier of the terminal device. The users are grouped according to the first digital tag to obtain the group information corresponding to each user; users with the same T and Q values ​​are grouped together. Interference alignment optimization is performed on the heterogeneous network based on the group information corresponding to each user; wherein, the user group corresponding to the micro cell is determined, and the micro cell corresponds to the micro base station; a pre-constructed transmit and receive beamforming matrix is ​​invoked, and the cross-layer interference generated by the macro base station to the users in the user group is aligned to the same subspace through the first digital tag corresponding to each user and the group information corresponding to each user.

2. The method according to claim 1, characterized in that, The step of dividing the base station coverage area into multiple regions based on the first location information of each user within the target cell, and determining the first digital tag corresponding to each user based on the first location information of each user and the antenna scanning beammap corresponding to the target base station includes: The coverage area of ​​the target base station is divided into at least two regions based on the antenna scanning beam pattern. If there is a target area in at least two regions where the number of users in the target area is greater than a preset threshold, the target area will be divided into two sub-regions. The first digital tag is assigned to each user based on the area identifiers corresponding to other areas and the area identifiers corresponding to the two sub-areas, wherein the other areas are areas other than the target area among the at least two areas.

3. The method according to claim 1, characterized in that, The target base station includes macro base stations and micro base stations, and the interference alignment optimization of the heterogeneous network based on the packet information corresponding to each user includes: Construct the first transmit beamforming matrix corresponding to the macro base station; Construct the second transmit beamforming matrix corresponding to the micro base station; Construct the first receive beamforming matrix for the user corresponding to the macro base station; Construct the second receive beamforming matrix for the user corresponding to the micro base station; The first transmit beamforming matrix, the second transmit beamforming matrix, the first receive beamforming matrix, and the second receive beamforming matrix are used to perform interference alignment optimization on the heterogeneous network using the grouping information corresponding to each user.

4. The method according to any one of claims 1 to 3, characterized in that, The determination of the first location information of each user within the target cell in the current period includes: Determine the signal propagation time between a first target user and each of at least two base stations, wherein the first target user is any one of the users in the target cell; The distance between the first target user and each of the at least two base stations is calculated based on the signal propagation time. The first location information of the first target user is determined based on the location of each of the at least two base stations and the distance between the first target user and each of the at least two base stations.

5. The method according to any one of claims 1 to 3, characterized in that, The method further includes: Determine the second location information of each user in the target cell for the next cycle; The second digital tag corresponding to each user is determined based on the second location information and the antenna scanning beam pattern; If there is a third target user among the users whose second digital tag does not match the first digital tag, then the third target user is regrouped to obtain the grouping information corresponding to the third target user; The heterogeneous network is subjected to interference alignment optimization based on the grouping information corresponding to the third target user.

6. A heterogeneous network interference alignment optimization device, characterized in that, include: The first determining unit is used to determine the first location information of each user in the target cell within the current period; The second determining unit is used to divide the base station coverage area into multiple areas based on the first location information of each user in the target cell, and to determine the first digital tag corresponding to each user based on the location information of each user and the antenna scanning beam pattern corresponding to the target base station. The target base station corresponds to the target cell. The first digital tag is in the form of [T, Q, N], where T is the identifier of the base station, Q is the area identifier in the cell, and N is the identifier of the terminal device. The segmentation unit is used to group the users according to the first digital tag to obtain the grouping information corresponding to each user; wherein users with the same T and Q values ​​are grouped together. An optimization unit is used to perform interference alignment optimization on the heterogeneous network based on the group information corresponding to each user; wherein, the user group corresponding to the micro cell is determined, the micro cell corresponds to the micro base station; a pre-constructed transmit and receive beamforming matrix is ​​invoked, and the cross-layer interference generated by the macro base station to the users in the user group is aligned to the same subspace through the first digital tag corresponding to each user and the group information corresponding to each user.

7. The apparatus according to claim 6, characterized in that, The second determining unit is specifically used for: The coverage area of ​​the target base station is divided into at least two regions based on the antenna scanning beam pattern. If there is a target area in at least two regions where the number of users in the target area is greater than a preset threshold, the target area will be divided into two sub-regions. The first digital tag is assigned to each user based on the area identifiers corresponding to other areas and the area identifiers corresponding to the two sub-areas, wherein the other areas are areas other than the target area among the at least two areas.

8. The apparatus according to claim 6, characterized in that, The target base station includes macro base stations and micro base stations, and the optimization unit is specifically used for: Construct the first transmit beamforming matrix corresponding to the macro base station; Construct the second transmit beamforming matrix corresponding to the micro base station; Construct the first receive beamforming matrix for the user corresponding to the macro base station; Construct the second receive beamforming matrix for the user corresponding to the micro base station; The first transmit beamforming matrix, the second transmit beamforming matrix, the first receive beamforming matrix, and the second receive beamforming matrix are used to perform interference alignment optimization on the heterogeneous network using the grouping information corresponding to each user.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one executable instruction, which, when executed on a computing device, causes the computing device to perform an optimization method for heterogeneous network interference alignment as described in any one of claims 1 to 5.

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