High-Energy-Efficient Deployment Method, System and Storage Medium for Wireless Access Points in Heterogeneous De-Cellular Networks

Abstract

The present invention provides a method, system, and storage medium for high-energy-efficiency deployment of wireless access points in a heterogeneous decellularized cell system. The method includes a user clustering step, a necessity determination step, and a wireless access point deployment step. The present invention has the following beneficial effects: the present invention utilizes user clusters and two types of energy efficiency gains to complete the deployment of wireless access points in a heterogeneous decellularized cell, thereby improving the average energy efficiency performance of the system. The first type of energy efficiency gain achieves coarse differentiation, allowing for rapid determination of the necessity of heterogeneous decellularized cells; the second type of energy efficiency gain achieves fine-grained deployment, allowing for the deployment of wireless access points serving different user clusters.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a method, system and storage medium for energy-efficient deployment of wireless access points in a heterogeneous decellularized cell system. Background Art

[0002] Green communications are a necessary prerequisite for sustainable development, and energy efficiency has become a key metric in the design and evaluation of communication systems. Unlike traditional cellular cells, heterogeneous, cell-free systems not only effectively improve system performance by leveraging macrodiversity gain, but also cost-effectively meet diverse service demands. Therefore, this is a hot research topic in 5G and Beyond.

[0003] Some research has been conducted on the energy efficiency of heterogeneous decellularized systems. However, this research primarily focuses on the instantaneous energy efficiency of these systems, specifically designing precoding and power allocation algorithms to improve instantaneous energy efficiency. This is primarily due to the fact that wireless communication systems typically utilize instantaneous channel state information (CSI) to design high-performance algorithms, making instantaneous performance metrics a key research focus. For heterogeneous decellularized systems, wireless access points are small and mobile, making their deployment to improve system performance an unavoidable challenge. Aside from the use of fast-moving platforms like drones as wireless access points, wireless access points are generally deployed not in real time but rather remain stationary over time. Therefore, it is inappropriate to continue to use instantaneous energy efficiency performance to guide wireless access point deployment. Effective wireless access point deployment solutions are still lacking. Summary of the Invention

[0004] The present invention provides a method for high energy efficiency deployment of wireless access points in a heterogeneous decellularized cell system, comprising the following steps:

[0005] Step 1: User clustering step: Divide users into T non-overlapping user clusters, so that the number of user clusters is equal to the number of types of wireless access points in the heterogeneous decellularized cell system, and define a sub-service area for each user cluster. The set of sub-service areas is recorded as the set of sub-service areas to be deployed.

[0006] Step 2, Necessity Judgment Step: Different types of wireless access points are sorted into sets S t In the set S, 1≤t≤T t Organize in collection In, that is is the set of wireless access points to be deployed; St The wireless access points in the t , maximum energy consumption P com，t ; According to the maximum transmission power, Sort the elements in ascending order, the first one is denoted as S min , the last one is denoted as S max ;

[0007] The CPU obtains the first type of energy efficiency gain ξ1 according to formula (1):

[0008]

[0009] In formula (1), P min 、P com，min 、|S min |Corresponding to S min The maximum transmission power, maximum energy consumption, and number of wireless access points, P max 、P com，max 、|S max |It is S max Maximum transmit power, maximum energy consumption, and number of wireless access points;

[0010] When η L ≤ξ1≤η H , using S min Provide services to K users in the entire service area, η L <1<η H , η L and η H They represent the lower bound and upper bound of energy efficiency gain, respectively, where it is unnecessary to deploy different types of wireless access points.

[0011] When 0≤ξ1<η L or η H <ξ1, using {S1,...,S T Provide services to K users in the entire service area;

[0012] Step 3, wireless access point deployment steps: If η L ≤ξ1≤η H , using S min Provide services to K users in the entire service area, and wireless access points are evenly deployed in the entire service area; if 0≤ξ1<η L or η H <ξ1, using {S1,...,S TProvide services to K users in the entire service area, calculate the second-category energy efficiency gain of each sub-service area, obtain the set of wireless access points used in the sub-service area of each user cluster, and evenly deploy the wireless access points in the wireless access point set in the sub-service area.

[0013] As a further improvement of the present invention, in the user clustering step, a clustering algorithm is used to divide users into T non-overlapping user clusters, so that the number of user clusters is equal to the number of types of wireless access points in the heterogeneous decellularized cell system, and a sub-service area is defined for each user cluster. The definition principle is that the sub-service area must be able to accommodate all users in the corresponding user cluster, and different sub-service areas do not overlap.

[0014] As a further improvement of the present invention, in the user clustering step, the clustering algorithm is a K-means clustering algorithm.

[0015] As a further improvement of the present invention, the shape of the sub-service area is regular or irregular.

[0016] As a further improvement of the present invention, the wireless access point deployment step includes:

[0017] Step a: The instantaneous energy efficiency is defined as the ratio of the sum of the instantaneous rates of all users to the sum of the energy consumption of all wireless access points. The value range of the instantaneous energy efficiency is [β min , β max ], set the discretization step size to (β max -β min ) / N, [β min , β max ] is divided into N energy efficiency sub-segments, and the instantaneous energy efficiency obtained by simulation is discretized. That is, when the instantaneous energy efficiency value obtained by simulation is within the nth energy efficiency sub-segment, the instantaneous energy efficiency is equal to the left endpoint of the nth energy efficiency sub-segment, which is recorded as β n ;

[0018] Step b: When the t′th sub-service area is composed of the wireless access point set S t When performing services, the average energy efficiency β is obtained t (t′), that is Where M is the number of simulations, 1≤t′≤T; when the instantaneous energy efficiency obtained by the mth simulation falls within the nth energy efficiency sub-segment, δ n (m) = 1; when the instantaneous energy efficiency obtained by the mth simulation does not fall within the nth energy efficiency sub-segment, δ n (m) = 0; the CPU obtains the second type of energy efficiency gain ξ2(t′) of the t′th sub-service area according to the following calculation formula, that is,

[0019]

[0020] In formula (2), β max (t′) and β mim (t′) are the wireless access point set S in the t′th sub-service area. max and S min Average energy efficiency when

[0021] Step c: Deploy wireless access points throughout the entire service area according to steps a and b.

[0022] As a further improvement of the present invention, in step a, the channel model of the t′th sub-service area is determined based on prior knowledge.

[0023] As a further improvement of the present invention, in the wireless access point deployment process in a single sub-service area in step b: for each sub-service area in A, a second type of energy efficiency gain can be obtained. If there exists t′ such that ξ2(t′)≥1, then ξ2(t * )=max t′ {ξ2(1),…,ξ2(T)}, then at the tth * A set of wireless access points S is deployed in each sub-service area max , the wireless access points in the set are evenly distributed in the tth * sub-service area; if ξ2(t′)<1 for any t′, then ξ2(t * )=min t′ {ξ2(1),…,ξ2(T)}, then at the tth * A set of wireless access points S is deployed in each sub-service area min , the wireless access points in the set are evenly distributed in the tth * within the sub-service area.

[0024] As a further improvement of the present invention, in step c, the sub-service area set to be deployed is initialized. The set of wireless access points to be deployed According to the maximum transmission power, Sort the elements in ascending order, with the last one being denoted as S max , the first one is denoted as S min ; According to step a and step b, get the tth * The wireless access points are deployed in the sub-service areas, and then the set of sub-service areas to be deployed is updated, that is, and the type of wireless access points to be deployed; if there exists t′ such that ξ2(t′)≥1, the set of wireless access points to be deployed is updated to According to the updated Update S max; If ξ2(t′)<1 for any t′, the set of wireless access points to be deployed is updated to According to the updated Update S min Repeat the AP deployment process and parameters within a single sub-service area Update process until and Each has only one element; at this time, The wireless access points in the wireless access point set corresponding to the element are evenly deployed in The sub-service area corresponding to the element in .

[0025] The present invention also provides a high-energy-efficiency deployment system for wireless access points in a heterogeneous decellularized cell system, comprising: a memory, a processor, and a computer program stored on the memory, wherein the computer program is configured to implement the steps of the high-energy-efficiency deployment method of the present invention when called by the processor.

[0026] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is configured to implement the steps of the high-energy-efficiency deployment method of the present invention when called by a processor.

[0027] The present invention achieves the following beneficial effects: It utilizes user clusters and two types of energy efficiency gains to deploy wireless access points in heterogeneous decellularized cells, thereby improving the system's average energy efficiency performance. The first type of energy efficiency gain enables coarse differentiation, quickly determining the necessity of heterogeneous decellularized cells; the second type of energy efficiency gain enables fine-grained deployment, enabling the deployment of wireless access points serving different user clusters. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 is a schematic diagram of a heterogeneous decellularized cell system;

[0029] Figure 2 This is a diagram of wireless access point deployment;

[0030] Figure 3 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0031] The present invention discloses a high-energy-efficiency deployment method for wireless access points in a heterogeneous decellularized cell system. Unlike existing practices, the present invention clusters users and uses prior knowledge to calculate two types of energy efficiency gains, thereby reducing real-time information interaction between users and wireless access points, and between wireless access points and CPUs, rapidly completing the deployment of wireless access points and improving the energy efficiency performance of the heterogeneous decellularized cell system.

[0032] The present invention uses prior knowledge to calculate two types of energy efficiency gains of a heterogeneous decellularized cell system, judges the necessity of adopting the heterogeneous decellularized cell system based on the first type of energy efficiency gain, and further provides the deployment of wireless access points based on the second type of energy efficiency gain.

[0033] like Figure 3 As shown, the present invention discloses a method for high energy efficiency deployment of wireless access points in a heterogeneous decellularized cell system, comprising the following steps:

[0034] Step 1, user clustering step: The number of types of wireless access points in the heterogeneous decellular cell is T (1<T), and K users need to be served in the service area. Since the CPU knows the distribution of users in advance, a clustering algorithm can be used to divide users into T non-overlapping clusters, so that the number of user clusters is equal to the number of types of wireless access points in the heterogeneous decellular cell. The choice of clustering algorithm needs to be determined according to the actual situation. For example, if fast computing speed and low complexity are required, the K-means clustering algorithm can be considered. However, the results of this algorithm are unstable, and the final result is related to the selection of the initial point, and it is easy to fall into local optimality. In addition, a sub-service area is delineated for each user cluster. The delineation principle is that the sub-service area must be able to accommodate all users in the corresponding user cluster, and different sub-service areas do not overlap. It is worth noting that the shape of the sub-service area can be regular or irregular. The set of these sub-service areas is recorded as the set of sub-service areas to be deployed

[0035] Step 2, Necessity Judgment Step: Different types of wireless access points are sorted into sets S t (1≤t≤T). These wireless access point sets S t (1≤t≤T) sorted in the set (denoted as the set of wireless access points to be deployed), that is, S t The wireless access points in the network have the same maximum transmission power (denoted as P t ), maximum energy consumption (denoted as P com，t ), and other hardware parameters. com，t It is determined by the hardware structure of the wireless access point's transmitter and the signal processing method. The elements in S t (1≤t≤T)) are sorted in ascending order, and the first one is recorded as S min , the last one is denoted as S max .

[0036] The CPU obtains the first type of energy efficiency gain (denoted as ξ1) according to the following calculation formula:

[0037]

[0038] In formula (1), P min 、P com，min 、|S min | respectively correspond to the wireless access point set S min The maximum transmit power, maximum energy consumption, and number of wireless access points. max 、P com，max 、|S max | is the wireless access point set S max The maximum transmit power, maximum energy consumption, and number of wireless access points.

[0039] When ξ1 is close to 1, that is, η L ≤ξ1≤η H (η L <1<η H ), it is not necessary to use heterogeneous decellularization cells, and homogeneous decellularization cells can be used, that is, the wireless access point set S min Provide services to K users in the entire service area. Otherwise, 0≤ξ1<η L or η H <ξ1, it is considered necessary to adopt heterogeneous decellularization cells, that is, to adopt a wireless access point set {S1, ..., S T} Provide services to K users in the entire service area. L and η H The specific value of η needs to be determined according to the actual situation. L and η H They represent the lower bound and upper bound of energy efficiency gain, respectively, where it is unnecessary to deploy different types of wireless access points. 1. When η is satisfied L ≤ξ1≤η H When it is deployed, it means that only one type of wireless access point needs to be deployed, and that type is S min Corresponding type. 2. When 0≤ξ1<η L or η H When ξ1 is less than ξ1, it means that different types of wireless access points need to be deployed, and these types are from S1 to S T The corresponding type.

[0040] Step 3, wireless access point deployment steps: If η L ≤ξ1≤η H , using wireless access point set S min To provide services to users in the entire service area, wireless access points can be evenly deployed throughout the service area.

[0041] If 0≤ξ1<η L or η H<ξ1, adopt wireless access point set {S1,...,S T} Provide services to users in the entire service area. Calculate the second-category energy efficiency gain of each sub-service area (see formula (2)) to obtain the set of wireless access points used in the sub-service area of each user cluster, and ensure that the wireless access points in the set are evenly deployed in the sub-service area. The detailed description is as follows:

[0042] (a) First, the channel model and signal processing method will affect the instantaneous energy efficiency obtained in the simulation, so they need to be determined in advance and, using prior knowledge, be as consistent as possible with the actual situation. For example, when determining the channel model for the t′th sub-service area based on prior knowledge, if there are many scattering clusters within the sub-service area, a Rayleigh channel model can be used. In practical applications, heterogeneous decellularized systems use signal processing methods to improve system performance. Here, it is necessary to determine which signal processing methods used by the system will affect the user's instantaneous rate and the energy consumption of the wireless access point. Common signal processing methods include channel estimation, precoding, power allocation, and pairing between users and wireless access points.

[0043] The instantaneous energy efficiency is defined as the ratio of the sum of the instantaneous rates of all users to the sum of the energy consumption of all wireless access points. The value range of the instantaneous energy efficiency is [β min , β max ], set the discretization step size to (β max -β min ) / N, and then [β min , β max ] is divided into N energy efficiency sub-segments. max and β min It needs to be set according to the specific situation. Discretize the instantaneous energy efficiency obtained by simulation, that is, when the instantaneous energy efficiency value obtained by simulation is within the nth energy efficiency sub-segment, let the instantaneous energy efficiency be equal to the left endpoint of the nth energy efficiency sub-segment (denoted as β n ).

[0044] (b) Secondly, when the t′(1≤t′≤T)th sub-service area is composed of the wireless access point set S t When performing services, the average energy efficiency β can be obtained t (t′), that is Where M is the number of simulations, which is set according to the actual situation. When the instantaneous energy efficiency obtained by the mth simulation falls within the nth energy efficiency sub-segment, δ n (m) = 1; when the instantaneous energy efficiency obtained by the mth simulation does not fall within the nth energy efficiency sub-segment, δ n (m) = 0. The CPU obtains the second type of energy efficiency gain (denoted as ξ2(t′)) of the t′th sub-service area according to the following calculation formula:

[0045]

[0046] In formula (2), β max (t′) and β min (t′) are the wireless access point set S in the t′th sub-service area. max and S min The average energy efficiency when

[0047] Wireless access point deployment process within a single sub-service area: Each sub-service area in can obtain a second-class energy efficiency gain. If there exists t′(1≤t′≤T) such that ξ2(t′)≥1, then ξ2(t * )=max t′ {ξ2(1),…,ξ2(T)}, then at the tth * A set of wireless access points S is deployed in each sub-service area max , the wireless access points in the set are evenly distributed in the tth * sub-service area; if for any t′(1≤t′≤T) ξ2(t′)<1, then ξ2(t * )=min t′ {ξ2(1),…,ξ2(T)}, then at the tth * A set of wireless access points S is deployed in each sub-service area min , the wireless access points in the set are evenly distributed in the tth * within the sub-service area.

[0048] (c) Finally, according to (a) and (b), wireless access points can be deployed in the entire service area. Initialize the set of sub-service areas to be deployed The set of wireless access points to be deployed According to the maximum transmission power, The elements in (elements are wireless access point sets) are sorted in ascending order, and the last one is recorded as S max , the first one is denoted as S min According to (a) and (b), we can get the tth * The wireless access points are deployed in the sub-service areas. Then the set of sub-service areas to be deployed is updated, i.e. and the type of wireless access points to be deployed. If there exists t′(1≤t′≤T) such that ξ2(t′)≥1, the set of wireless access points to be deployed is updated to According to the updated Update S max ; If ξ2(t′)<1 for any t′(1≤t′≤T), the set of wireless access points to be deployed is updated to According to the updated Update S min Repeat the AP deployment process and parameters within a single sub-service area Update process until and Each has only one element. At this time, The wireless access points in the wireless access point set corresponding to the element are evenly deployed in The sub-service area corresponding to the element in .

[0049] The technical solution of the present invention is described below with reference to specific embodiments:

[0050] like Figure 1 As shown, there are a total of 6 users that need to be served in the entire service area, that is, K = 6. The heterogeneous decellularized cell has two types of wireless access points, whose sets are denoted as S1 and S2, where S1 = {2#, 3#, 5#, 6#} and S2 = {1#, 4#}. The transmitters of the wireless access points all adopt a fully connected structure, equipped with a baseband processor, a phase shifter, a radio frequency link (mainly composed of a crystal oscillator, a filter and an amplifier), a power divider, a combiner, a power amplifier, and a radio frequency antenna. The simulation channel is selected as the Rayleigh channel model, and the signal processing method used is equal power allocation and normalized zero-forcing (ZF) hybrid precoding. Each user is served by all wireless access points. Set η L =0.8 and η H =2, number of simulations M = 100.

[0051] exist Figure 1 、 Figure 2 Based on the process Figure 3 , all steps of the specific implementation are as follows:

[0052] Step 1, user clustering step: Since the CPU knows the distribution of 6 users in advance, it uses the K-means clustering algorithm to divide the users into 2 non-overlapping clusters. Figure 2 As shown in the figure, a circular sub-service area is defined for each user cluster, which satisfies the requirement that "the sub-service area can accommodate all users in the corresponding user cluster and different sub-service areas do not overlap".

[0053] Step 2, necessity judgment step: Since the transmitter of the wireless access point adopts a fully connected structure, S t The maximum energy consumption P of any wireless access point com，t The power consumption of the transmitter's baseband processor, phase shifter, RF link, and power amplifier are denoted as P BB,t 、P PS,t 、PRF，t , and P PA,t In general, the power consumption of the baseband processor, phase shifter, and RF link is fixed and determined by the hardware components used. However, the power consumption of the power amplifier is determined by the output power and efficiency of the power amplifier, that is, it is not fixed, and the efficiency of the power amplifier is not necessarily linear. For the convenience of calculation, the linear fitting method is used to fit the functional relationship between the power amplifier power consumption and the output power of the power amplifier, which is expressed as P pA，t =P out ρ t +C t , where ρ t and C t are the slope and constant of the linear fit, P out is the output power of the power amplifier. Since the signal processing method is power normalized, the sum of the output power of all power amplifiers is less than or equal to the maximum transmission power. Therefore, the maximum energy consumption P com，t =P BB，t +R t P RF，t +R t N t P PS，t +P t ρ t +N t C t . R t is the number of RF chains, N t is the number of transmitting antennas, P t is the maximum transmit power.

[0054] According to the maximum transmission power Sort the elements in ascending order. If P2>P1, we can get {S1, S2}, and the first one is denoted as S min , that is, S min =S1, the last one is recorded as S max , that is, S max =S2.

[0055] The CPU obtains the first type of energy efficiency gain (denoted as ξ1) according to the following calculation formula:

[0056]

[0057] The parameters in the formula are set as ρ2=ρ1=4 / π, C2=C1=0, P2=2P1=100, R2=R1=6, N2=2N1=64, |S2|=(1 / 2)|S1|=2, P BB，2 =P BB，1 =200, P RF，2 =P RF，1 =120, P PS，2 =PPS，1 =20. Then we can get ξ1=0.553<η L ,It is necessary to adopt heterogeneous decellularization cells, that is, to use wireless access point sets S1 and S2 to serve the 6 users in the entire service area.

[0058] Step 3, wireless access point deployment step: Since 0≤ξ1<η L , using wireless access point sets S1 and S2 to serve users in the area. Calculate the second-category energy efficiency gain of each sub-service area, and obtain the wireless access point set used in the sub-service area of each user cluster, so that the wireless access points in the set are evenly deployed in the sub-service area. The detailed description is as follows:

[0059] (a) First, in a certain simulation, the channel matrix of the sth (1≤s≤|S1|+|S2|)th wireless access point is denoted as H s , the digital part of zero-forced hybrid precoding W s Expressed as

[0060]

[0061] in F s is the analog part of zero-forcing hybrid precoding, expressed as (·) -1 , and angle(·) are conjugate symmetry operation, matrix inversion operation, and phase extraction operation respectively. s It is used to normalize the power to ensure Where W s，k It's W s The kth column of is the two-norm operation.

[0062] Since instantaneous energy efficiency is defined as the ratio of the sum of the instantaneous rates of all users to the sum of the energy consumption of all wireless access points, the instantaneous energy efficiency is expressed as

[0063]

[0064] Where B is the bandwidth. When s∈S t When δ(s∈S t )=1; otherwise δ(s∈S t )=0. For example, wireless access point 1# belongs to the second category, that is, 1∈S2, then δ(1∈S1)=0,δ(1∈S2)=1. σ 2 represents the power of the noise, represents the power of the useful signal, and Indicates the power of interference. s，k (H s′，k ) is Hs (H s′ )'s kth row, and W s′，k′ It's W s′ The k′th column of .

[0065] The value range of instantaneous energy efficiency is set to [100, 1100], and the discretization step is set to 10, so that [100, 1100] can be divided into 100 energy efficiency sub-segments. The instantaneous energy efficiency obtained by simulation is discretized, that is, when the instantaneous energy efficiency value obtained by simulation is within the nth energy efficiency sub-segment, the instantaneous energy efficiency is set to be equal to the left endpoint of the nth energy efficiency sub-segment, which is recorded as β n For example, the instantaneous energy efficiency β = 108.83. Since 100≤β≤110, it is located in the first energy efficiency sub-segment, so the discretized energy efficiency β = β1 = 100.

[0066] (b) Secondly, when the t′(1≤t′≤2)th sub-service area is composed of the wireless access point set S t Average energy efficiency during service When the instantaneous energy efficiency obtained by the mth simulation falls within the nth energy efficiency sub-segment, δ n (m) = 1; when the instantaneous energy efficiency obtained by the mth simulation does not fall within the nth energy efficiency sub-segment, δ n (m) = 0. The CPU obtains the second type of energy efficiency gain (denoted as ξ2(t′)) of the t′th sub-service area according to the following calculation formula:

[0067]

[0068] Where β max (t′) and β min (t′) are the wireless access point set S in the t′th sub-service area. max and S min The second equation exists because S min =S1 and S max =S2.

[0069] Wireless access point deployment process within a single sub-service area: Each sub-service area in , can obtain a second type of energy efficiency gain, namely ξ2(1) and ξ2(2). Assuming ξ2(1) = 0.6 and ξ2(2) = 0.4, then ξ2(t * )=ξ2(2). This means that the wireless access point set S1 is deployed in the second sub-service area. The wireless access points in the set S1 (i.e., wireless access points 2#, 3#, 5#, and 6#) are evenly distributed in the second sub-service area.

[0070] (c) Finally, according to (a) and (b), wireless access points can be deployed in the entire service area. Initialize the set of sub-service areas to be deployed The set of wireless access points to be deployed According to the maximum transmission power Sort the elements in ascending order, and we get {S1, S2}, then S min =S1,S max =S2.

[0071] According to (a) and (b), the wireless access point deployment in the second sub-service area can be obtained. Then the set of sub-service areas to be deployed and the set of wireless access points to be deployed are updated, that is, and And T=2-1=1. and Each has only one element, and the wireless access points in set S2 (ie, wireless access points 1# and 4#) are evenly distributed in the first sub-service area.

[0072] In summary, the present invention proposes a novel, energy-efficient wireless access point deployment method suitable for heterogeneous decellularized cell systems. This solution can more quickly deploy wireless access points in heterogeneous decellularized cell systems, improving the average energy efficiency performance of the system.

[0073] The present invention is applicable to the deployment of wireless access points of a heterogeneous decellularized cell system. A single antenna is provided at the user location. The entire heterogeneous decellularized cell system is composed of a central processing unit (CPU) and different types of wireless access points. The CPU needs to know the distribution of users in advance, and can be connected to the wireless access points via a wired connection (such as optical fiber, etc.) or a wireless connection. Different types of wireless access points need to differ in hardware indicators such as the number of antennas equipped on the transmitter, the number of radio frequency links, the maximum transmission power, and the number of wireless access points. The wireless access point can perform signal processing such as channel estimation and precoding, and send the processed information to the CPU. The deployment of wireless access points is calculated by the CPU.

[0074] The above is a further detailed description of the present invention in conjunction with specific preferred embodiments, and the specific implementation of the present invention should not be considered to be limited to these descriptions. For those skilled in the art of the present invention, without departing from the concept of the present invention, several simple deductions or substitutions can be made, which should be considered to fall within the scope of protection of the present invention.

Claims

1. A method for energy-efficient deployment of wireless access points in a heterogeneous decellularized cell system, characterized in that: The steps include: Step 1: User clustering step: Divide users into T non-overlapping user clusters, so that the number of user clusters is equal to the number of types of wireless access points in the heterogeneous decellularized cell system, and define a sub-service area for each user cluster. The set of sub-service areas is recorded as the set of sub-service areas to be deployed. Step 2, Necessity Judgment Step: Different types of wireless access points are sorted into sets S t In the set S, 1≤t≤T t Organize in collection In, that is is the set of wireless access points to be deployed; S t The wireless access points in the t , maximum energy consumption P com，t ; According to the maximum transmission power, Sort the elements in ascending order, the first one is denoted as S min , the last one is denoted as S max ; The CPU obtains the first type of energy efficiency gain ξ1 according to formula (1): In formula (1), P min 、P com，min 、|S min |Corresponding to S min The maximum transmission power, maximum energy consumption, and number of wireless access points, P max 、P com，max 、|S max |It is S max Maximum transmit power, maximum energy consumption, and number of wireless access points; When η L ≤ξ1≤η H , using S min Provide services to K users in the entire service area, η L <1<η H , η L and η H They represent the lower bound and upper bound of energy efficiency gain, respectively, where it is unnecessary to deploy different types of wireless access points. When 0≤ξ1<η L or η H <ξ1,using {S1,…,S T Provide services to K users in the entire service area; Step 3, wireless access point deployment steps: If η L ≤ξ1≤η H , using S min To provide services to K users in the entire service area, wireless access points are evenly deployed in the entire service area; If 0≤ξ1<η L or η H <ξ1, using {S1,…,S T Serving K users in the entire service area, calculating the second-category energy efficiency gain of each sub-service area, obtaining a set of wireless access points used in the sub-service area of each user cluster, and ensuring that the wireless access points in the set of wireless access points are evenly deployed in the sub-service area; The wireless access point deployment step includes: Step a: The instantaneous energy efficiency is defined as the ratio of the sum of the instantaneous rates of all users to the sum of the energy consumption of all wireless access points. The value range of the instantaneous energy efficiency is [β min , β max ], set the discretization step size to (β max -β min ) / N, [β min , β max ] is divided into N energy efficiency sub-segments, and the instantaneous energy efficiency obtained by simulation is discretized. That is, when the instantaneous energy efficiency value obtained by simulation is within the nth energy efficiency sub-segment, the instantaneous energy efficiency is equal to the left endpoint of the nth energy efficiency sub-segment, which is recorded as β n ; Step b: When the t′th sub-service area is composed of the wireless access point set S t When performing services, the average energy efficiency β is obtained t (t′), that is Where M is the number of simulations, 1≤t′≤T; when the instantaneous energy efficiency obtained by the mth simulation falls within the nth energy efficiency sub-segment, δ n (m) = 1; when the instantaneous energy efficiency obtained by the mth simulation does not fall within the nth energy efficiency sub-segment, δ n (m) = 0; the CPU obtains the second type of energy efficiency gain ξ2(t′) of the t′th sub-service area according to the following calculation formula, that is, In formula (2), β max (t′) and β min (t′) are the wireless access point set S in the t′th sub-service area. max and S min Average energy efficiency when Step c: Deploy wireless access points throughout the entire service area according to steps a and b.

2. The energy-efficient deployment method according to claim 1, wherein: In the user clustering step, a clustering algorithm is used to divide users into T non-overlapping user clusters, so that the number of user clusters is equal to the number of types of wireless access points in the heterogeneous decellularized cell system, and a sub-service area is defined for each user cluster. The demarcation principle is that the sub-service area must be able to accommodate all users in the corresponding user cluster, and different sub-service areas do not overlap.

3. The energy-efficient deployment method according to claim 2, wherein: In the user clustering step, the clustering algorithm is a K-means clustering algorithm.

4. The energy-efficient deployment method according to claim 2, wherein: The shape of the sub-service area is regular or irregular.

5. The energy-efficient deployment method according to claim 1, wherein: In step a, the channel model of the t′th sub-service area is determined based on prior knowledge.

6. The energy-efficient deployment method according to claim 1, characterized in that: In step b, the wireless access point deployment process in a single sub-service area: Each sub-service area in can obtain a second-class energy efficiency gain. If there exists t′ such that ξ2(t′)≥1, then ξ2(t*)=max t′ {ξ2(1),…,ξ2(T)}, then at the tth * A set of wireless access points S is deployed in each sub-service area max , the wireless access points in the set are evenly distributed in the tth * sub-service area; if ξ2(t′)<1 for any t′, then ξ2(t*)=min t′ {ξ2(1),…,ξ2(T)}, then at the tth * A set of wireless access points S is deployed in each sub-service area min , the wireless access points in the set are evenly distributed in the tth * within the sub-service area.

7. The energy-efficient deployment method according to claim 6, characterized in that: In step c, initialize the set of sub-service areas to be deployed The set of wireless access points to be deployed According to the maximum transmission power, Sort the elements in ascending order, with the last one being denoted as S max , the first one is denoted as S min ; According to step a and step b, get the tth * The wireless access points are deployed in the sub-service areas, and then the set of sub-service areas to be deployed is updated, that is, and the type of wireless access points to be deployed; if there exists t′ such that ξ2(t′)≥1, the set of wireless access points to be deployed is updated to According to the updated Update S max ; If ξ2(t′)<1 for any t′, the set of wireless access points to be deployed is updated to According to the updated Update S min Repeat the AP deployment process and parameters within a single sub-service area Update process until and Each has only one element; at this time, The wireless access points in the wireless access point set corresponding to the element are evenly deployed in The sub-service area corresponding to the element in .

8. A high energy efficiency deployment system for wireless access points in a heterogeneous decellularized cell system, characterized in that: include: A memory, a processor, and a computer program stored on the memory, wherein the computer program is configured to implement the steps of the energy-efficient deployment method according to any one of claims 1 to 7 when called by the processor.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is configured to implement the steps of the high-energy-efficiency deployment method according to any one of claims 1 to 7 when called by a processor.

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