High-frequency channel data optimized propagation method and device, equipment and storage medium

Abstract

The invention provides a high-frequency channel data optimized propagation method and device, equipment and a storage medium, and relates to the field of high-frequency channel networking. The propagation method comprises the following steps: constructing a signal propagation coverage model and a penetration loss model; identifying the characteristics of the current signal transmission area by using a signal propagation coverage model, dividing the current signal transmission area into a plurality of different areas by combining the penetration loss model, and giving the electromagnetic wave transmission quality of each area; switching the area with the electromagnetic wave transmission quality smaller than a preset value into optical communication, and continuing to maintain electromagnetic wave communication in other areas; and checking the communication quality of the area switched to optical communication, taking an industrial standard light source value as a base line, and taking a light and shade index of luminous flux as a basis for judging whether a light source signal is normal or not. According to the method, for different high-frequency related application scenes, VLC receiving ends are densely deployed for application scenes without coverage areas and with large building penetration loss, existing wireless signals such as millimeter waves are converted into optical signals, and coverage blind spots are reduced.

Description

Technical Field

[0001] The present invention relates to the field of high-frequency channel networking, and in particular to a high-frequency channel data optimization propagation method, device, equipment and storage medium. Background Art

[0002] As mobile communication systems develop, innovative services need to meet the growing demand for data traffic, the processing power of smart devices, and the promotion of innovative applications. To meet these service requirements, the communications industry has integrated the performance requirements of 5G systems, including network speeds up to 10Gbit / s, cell edge rates greater than 100Mbit / s, and delays less than 1ms. In order to meet the above performance requirements, the industry is studying new frequency bands up to 100GHz to meet the spectrum requirements of 5GNR. In order to develop new 5G systems to operate in frequency bands up to 100GHz, accurate wireless propagation models of these frequency bands are required, which are different from existing wireless channel models.

[0003] The frequency range of 5G mobile communication system is 500MHz~100GHz. In order to deploy 5G system in high frequency band, it is necessary to fit the wireless propagation model of high frequency band. The 3GPP three-dimensional channel model provides additional flexibility for the elevation dimension, allowing the modeling of two-dimensional antenna system. The channel model will be verified in the frequency band up to 100GHz, and the system performance of these frequency bands can be evaluated in a set of sets.

[0004] When faced with application scenarios including indoor corridors, small meeting rooms, open offices, shopping malls, etc., high-frequency signal transmission faces the problem of greater propagation loss that needs to be solved. Summary of the invention

[0005] Purpose of the invention: To propose a method, device, equipment and storage medium for optimizing the propagation of high-frequency channel data, so as to effectively solve the above-mentioned problems existing in the prior art.

[0006] In the first aspect, a method for optimizing the propagation of high-frequency channel data is proposed, and the steps are as follows:

[0007] Construct signal propagation coverage model and penetration loss model;

[0008] The signal propagation coverage model is used to identify the characteristics of the current signal transmission area, and combined with the penetration loss model, the current signal transmission area is divided into multiple different areas, and the electromagnetic wave transmission quality of each area is given;

[0009] Switching the area where the electromagnetic wave transmission quality is less than a predetermined value to optical communication, and maintaining electromagnetic wave communication in the remaining areas;

[0010] Check the communication quality in the area switched to optical communication, using the industry standard light source value as the baseline and the brightness index of the luminous flux as the basis for whether the light source signal is normal.

[0011] In a further embodiment of the first aspect, for signal propagation between different buildings, the penetration loss model is composed of the total signal propagation loss PL of the buildings. buil express:

[0012]

[0013] Where PL b Represents the basic path loss outside the building; PL tw Represents building penetration loss; PL in represents the path loss inside the building; σ p represents the standard deviation of penetration loss; N(μ, *) represents normal distribution;

[0014] Among them, the building penetration loss PL tw The calculation expression is as follows:

[0015]

[0016] Where PL npi is the additional penetration loss of the building under non-vertical incidence; L i represents the permeation loss of material i; N is the number of materials; pi is the proportion of the i-th material;

[0017] For non-vertical incidence, an additional 5dB loss needs to be added to the outer wall loss; the indoor loss is 0.5dB / m.

[0018] In a further embodiment of the first aspect, for signal propagation between different vehicles, the penetration loss model is composed of vehicle penetration loss PL car express:

[0019]

[0020] Where PL0 represents the vehicle external path loss; σ p represents the standard deviation of penetration loss; N(μ, *) represents normal distribution.

[0021] In a further embodiment of the first aspect, the signal propagation coverage model divides the high-frequency electromagnetic wave propagation area into the following areas according to the sparsity of high-frequency electromagnetic wave propagation:

[0022] Near-end free loss zone: mainly free space propagation, the propagation path is the straight path;

[0023] LOS+scatterer: LOS propagation is dominant, and scatterers provide reflection and diffraction propagation paths for electromagnetic waves;

[0024] NLOS area: consists of reflection path and direct path;

[0025] DistantNLOS region: composed of reflection paths;

[0026] No coverage area: There is no reflection path or direct path, the electromagnetic waves are transmitted over a long distance, and the receiver cannot demodulate the signal normally.

[0027] In a further embodiment of the first aspect, the current signal transmission area is divided into a plurality of different areas, and the electromagnetic wave transmission quality of each area is given, where the electromagnetic wave transmission quality is determined by the channel attenuation h(t):

[0028]

[0029] Where X represents the log-normal shadow attenuation; L represents the total number of paths; K represents the total number of channels; t represents the total access time; T l Indicates the time of accessing the first path; T k，l represents the starting time of accessing the kth channel and the lth path; p k，l represents a discrete random variable with equal probability of taking +1 and -1; βk ， l represents the channel coefficient of the first path that follows the log-normal distribution;

[0030] The calculated channel attenuation h(t) and the threshold H min Comparison:

[0031] If h(t)>H min , it is determined that the electromagnetic wave transmission quality does not meet the standard and switches to optical communication;

[0032] If h(t)≤H min , it is determined that the electromagnetic wave transmission quality meets the standard and electromagnetic wave communication continues.

[0033] In a further embodiment of the first aspect, a Markov prediction model may be used to predict the blind spot signal coverage trend of the optical signal, and the expression is as follows:

[0034] X(k+1)=X(k)×P

[0035] Where X(k) represents the state vector of the trend analysis and prediction object at time t=k; P represents the one-step transition probability matrix, and X(k+1) represents the state vector of the trend analysis and prediction object at time t=k+1.

[0036] Calculated by analyzing the following rectangular data:

[0037] The probability matrix of abnormal and normal light source signals in the previous period is:

[0038] The abnormal probability matrix of normal transfer of light source signal in the current period is:

[0039] The probability matrix of abnormal light source signal transition to normal in the current period is:

[0040] The second aspect of the present invention provides a high-frequency signal propagation device, which can automatically execute the high-frequency channel data optimization propagation method as described in the first aspect. The device includes a regional feature recognition unit, a switching condition judgment unit, and a switching result inspection unit.

[0041] The regional feature recognition unit is used to recognize the features of the current signal transmission area, divide the current signal transmission area into a plurality of different areas, and give the electromagnetic wave transmission quality of each area;

[0042] The switching condition judgment unit is used to switch the area where the electromagnetic wave transmission quality is less than a predetermined value to optical communication, and the remaining areas continue to maintain electromagnetic wave communication;

[0043] The switching result inspection unit is used to inspect the communication quality of the area switched to optical communication, taking the industry standard light source value as the baseline and using the brightness index of the luminous flux as the basis for whether the light source signal is normal.

[0044] According to a third aspect of the present invention, an electronic device is provided, comprising: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the high-frequency channel data optimization propagation method as described in the first aspect is implemented.

[0045] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, wherein at least one executable instruction is stored in the storage medium. When the executable instruction is executed on an electronic device, the electronic device executes the high-frequency channel data optimization propagation method as described in the first aspect.

[0046] Beneficial effects: The high-frequency channel data optimization propagation method proposed in the present invention is targeted at different high-frequency related application scenarios. For application scenarios with no coverage and large building penetration loss, the VLC receiving end is densely deployed to convert existing millimeter-wave and other wireless signals into optical signals to reduce coverage blind spots. The IEEE 802.15.3a UWB channel model is deployed at the receiving end of the VLC, and its high-speed characteristics are used to solve the problem of poor signal quality caused by continuous changes in spatial channels due to continuous changes in position during signal propagation. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1It is a flow chart of the high-frequency channel data optimization propagation method in an embodiment of the present invention.

[0048] Figure 2 It is a schematic diagram of the structure of a high-frequency signal propagation device in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In the following description, a large number of specific details are provided to provide a more thorough understanding of the present invention. However, it is apparent to those skilled in the art that the present invention can be implemented without one or more of these details. In other examples, in order to avoid confusion with the present invention, some technical features well known in the art are not described.

[0050] See Figure 1 As shown, this embodiment discloses a method for optimizing the propagation of high-frequency channel data, and the steps are as follows:

[0051] Construct signal propagation coverage model (Multi-Zone) and penetration loss model (02I). The Multi-Zone model is based on the sparseness of high-frequency electromagnetic wave propagation. The high-frequency electromagnetic wave propagation area can be simply divided into four different propagation areas:

[0052] Zone 1: Near-end free loss zone

[0053] In this area, electromagnetic waves mainly propagate in free space, and the propagation path is the direct path.

[0054] Zone 2: LOS + scatterer

[0055] In this area, electromagnetic waves are mainly propagated by LOS, accompanied by a small number of scatterers that provide reflection, diffraction and other propagation paths for electromagnetic waves. Common ones include ground reflection paths, wall reflection paths, etc. In some scenarios, the "waveguide effect" can be observed in this area.

[0056] Zone 3: NLOS zone

[0057] Electromagnetic wave propagation in this area is mainly composed of reflection and a small amount of direct path. As the distance between transmission and reception increases, the probability of occlusion increases, causing electromagnetic waves to reach the receiver through reflection, diffraction, and a small amount of direct path. This area is mainly composed of a small amount of reflection path. As the distance between transmission and reception increases, some blind spots already exist, and only a small amount of multiple reflection paths can reach the receiver. The received signal energy in this area is very weak, and the communication quality is relatively poor.

[0058] Zone 4: Distant NLOS

[0059] This area is mainly composed of a small number of reflection paths. As the transmission and reception distance increases, some blind spots already exist, and only a small number of multiple reflection paths can reach the receiver. The received signal energy in this area is very weak, and the communication quality is relatively poor.

[0060] Zone 5: No coverage area

[0061] This area is a non-coverage area. In this area, the electromagnetic wave has a severe attenuation due to long-distance propagation, multiple reflections, etc., resulting in the receiver being unable to demodulate the signal normally.

[0062] The building penetration loss of the 02I model is sensitive to materials such as glass and cement walls due to the short wavelength of millimeter waves, large path loss, and whether the penetration ability can meet the outdoor to indoor coverage. The 02I model propagation loss consists of three parts: outdoor propagation loss, building penetration loss, and indoor propagation loss. The O2I loss can be calculated by the following formula:

[0063]

[0064] PL npi is the additional penetration loss of the building under non-vertical incidence; L i represents the penetration loss of material i; N is the number of materials; pi is the proportion of the i-th material; for non-vertical incidence, an additional loss of 5dB needs to be added to the outer wall loss; the indoor loss is 0.5dB / m.

[0065] The calculation of penetration loss under different materials can be seen in Table 1 below:

[0066] Table 1 Penetration loss under different materials

[0067] Material Penetration loss(dB) Standard multi-pane glass Lglant=2+0.2f Coated glass <h2 style=";text-align:left;direction:ltr"><![CDATA[L <h2 style=";text-align:left;direction:ltr"> Larylaut <h2 style=";text-align:left;direction:ltr"> =23+0.3f]]><h2 style=";text-align:left;direction:ltr"> Concrete <![CDATA[L eserest =5+4f]]> wood <![CDATA[L some =4.85+0.12f]]>

[0068] Composite penetration loss is obtained by the weighted average of the transmittance of two different materials, with the weights determined by the relative surface area of ​​each material on the building facade. Two forms of this model are given here, low loss and high loss models. For non-vertical incidence, an additional loss of 5dB is added to the outer wall loss; the indoor loss is 0.5dB / m.

[0069] 02I Vehicle penetration loss PL car It is expressed as follows:

[0070]

[0071] PL0 represents the path loss outside the vehicle; σ p represents the standard deviation of penetration loss; N(μ, *) represents normal distribution.

[0072] According to different actual application scenarios, building penetration loss is divided into high-loss model (High-Loss Model) and low-loss model (Low-Loss Model). The high-loss model is mainly used in old buildings, which are mainly composed of 70% cement exterior walls and 30% ordinary glass windows. The low-loss model is mainly used in new buildings in urban areas, which are mainly composed of 70% IRR glass and 30% cement walls.

[0073] The signal propagation coverage model is used to identify the characteristics of the current signal transmission area, and combined with the penetration loss model, the current signal transmission area is divided into multiple different areas, and the electromagnetic wave transmission quality of each area is given; the electromagnetic wave transmission quality is determined by the channel attenuation h(t):

[0074]

[0075] Where X represents the log-normal shadow attenuation; L represents the total number of paths; K represents the total number of channels; t represents the total access time; T l represents the time of accessing the lth path; T k，l represents the starting time of accessing the kth channel and the lth path; p k，l represents a discrete random variable with equal probability of taking +1 and -1; β k，l Indicates that the channel coefficient of the first path follows a log-normal distribution;

[0076] The calculated channel attenuation h(t) and the threshold H min Comparison:

[0077] If h(t)>H min , it is determined that the electromagnetic wave transmission quality does not meet the standard and switches to optical communication;

[0078] If h(t)≤H min , it is determined that the electromagnetic wave transmission quality meets the standard and electromagnetic wave communication continues.

[0079] According to the average distance between the transmitting and receiving nodes and whether there is line of sight, four different standard measurement channels are given, as shown in Table 2:

[0080] Table 2 Measurement channels of four different standards

[0081] Model Type Whether line of sight Distance / m CM1 LOS 0～4 CM2 NLOS 0～4 CM3 NLOS 4～10 CM4 NLOS Extreme ——

[0082] As a preferred embodiment, a Markov prediction model may also be used to predict the blind area signal coverage trend of the optical signal, and the expression is as follows:

[0083] X(k+1)=X(k)×P

[0084] Where X(k) represents the state vector of the trend analysis and prediction object at time t=k; P represents the one-step transition probability matrix, and X(k+1) represents the state vector of the trend analysis and prediction object at time t=k+1.

[0085] Calculated by analyzing the following rectangular data:

[0086] The probability matrix of abnormal and normal light source signals in the previous period is: The abnormal probability matrix of normal transfer of light source signal in the current period is: The probability matrix of abnormal light source signal transition to normal in the current period is:

[0087] Check the communication quality in the area switched to optical communication, using the industry standard light source value as the baseline and the brightness index of the luminous flux as the basis for whether the light source signal is normal.

[0088] After the above process, it is necessary to further judge the spatial consistency. Spatial consistency is mainly reflected in the process of signal propagation, because the continuous change of position brings about the continuous change of spatial channel. This continuous change of space is mainly reflected in the following four aspects in technical evaluation.

[0089] Channel non-correlation: When using massive MIMO, the channels measured by different antenna elements may differ, including low channel correlation and different multipath parameters.

[0090] Multipath changes with space: In high-frequency transmission, beamforming and beam tracking are required to ensure effective communication transmission. The existing model does not consider the changes in fast fading caused by changes in user positions. As the user position changes, the multipath angle will change, and the phenomenon of multipath generation and death is more likely to cause the channel to change from line-of-sight transmission to non-line-of-sight transmission.

[0091] Strong correlation of channels at adjacent locations: Continuous changes in location result in strong correlation of channels at adjacent locations. Although the existing model has a certain reflection of the correlation through the autocorrelation distance, the modeling of small-scale multipath is randomly generated. This random multipath will enhance the non-correlation between users, and in the evaluation of multi-user MIMO transmission, this non-correlation will optimize the spatial multiplexing performance. Since high-frequency channel models will be introduced in indoor deployment and ultra-dense networks, the strong correlation in space needs to be considered in the new model to ensure the accuracy of the new model and the objectivity of the technical evaluation.

[0092] Channel correlation under multi-site multi-user: In the multi-service site scenario, the continuous evolution of channel characteristics experienced by multiple users and the channel correlation between different users / links, such as the correlation of interconnection links between relays or sites in CoMP and UDN Distributed-MIMO systems.

[0093] The angle change caused by the user position in the existing model is mainly reflected in the mapping of the signal on the transmitting and receiving antennas in the formula, as shown in the following formula, F RX and F tX Both represent the antenna response when different multipaths arrive at the receiving end and are transmitted from the transmitting end at different angles. Without making major changes to the existing statistical model, the transformation of spatial characteristics will be reflected in the modeling of this parameter.

[0094]

[0095] As a preferred embodiment, a high-frequency signal propagation device 100 is also disclosed. Figure 2 . The high-frequency signal propagation device 100 can automatically execute the high-frequency channel data optimization propagation method disclosed in the above embodiment. The device includes a regional feature recognition unit 101, a switching condition judgment unit 102, and a switching result inspection unit 103. The regional feature recognition unit 101 is used to identify the characteristics of the current signal transmission area, divide the current signal transmission area into multiple different areas, and give the electromagnetic wave transmission quality of each area. The switching condition judgment unit 102 is used to switch the area where the electromagnetic wave transmission quality is less than a predetermined value to optical communication, and the remaining areas continue to maintain electromagnetic wave communication. The switching result inspection unit 103 is used to check the communication quality of the area switched to optical communication, taking the industry standard light source value as the baseline, and using the brightness index of the luminous flux as the basis for whether the light source signal is normal.

[0096] In practical applications, the operation logic of the high-frequency channel data optimization propagation method disclosed in the above embodiment can be written into a set of executable instructions, and the executable instructions are written into a storage medium and run on an electronic device. More specific examples of the computer-readable storage medium mentioned in this embodiment may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. The computer-readable storage medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable signal medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or device.

[0097] As described above, although the present invention has been shown and described with reference to specific preferred embodiments, it should not be construed as limiting the present invention itself. Various changes may be made to it in form and detail without departing from the spirit and scope of the present invention as defined in the appended claims.

Claims

1. A method for optimizing the propagation of high-frequency channel data, characterized in that: The steps include: Construct signal propagation coverage model and penetration loss model; The signal propagation coverage model is used to identify the characteristics of the current signal transmission area, and combined with the penetration loss model, the current signal transmission area is divided into multiple different areas, and the electromagnetic wave transmission quality of each area is given; Switching the area where the electromagnetic wave transmission quality is less than a predetermined value to optical communication, and maintaining electromagnetic wave communication in the remaining areas; Check the communication quality in the area switched to optical communication, using the industry standard light source value as the baseline and the brightness index of the luminous flux as the basis for whether the light source signal is normal.

2. The high frequency channel data optimization propagation method according to claim 1, characterized in that: For signal propagation between different buildings, the penetration loss model is composed of the total signal propagation loss PL of the building build express: Where PL b Represents the basic path loss outside the building; PL tw represents the building penetration loss; PL in represents the path loss inside the building; σ p represents the standard deviation of penetration loss; N(μ,*) represents normal distribution; Among them, the building penetration loss PL tw The calculation expression is as follows: Where PL npi is the additional penetration loss of the building under non-vertical incidence; L i represents the permeation loss of material i; N is the number of materials; pi is the proportion of the i-th material; For non-vertical incidence, the outer wall loss needs to increase by 5dB of additional loss; The indoor loss is 0.5dB / m.

3. The high frequency channel data optimization propagation method according to claim 1, characterized in that: For signal propagation between different vehicles, the penetration loss model is composed of vehicle penetration loss PL car express: Where PL0 represents the vehicle external path loss; σ p represents the standard deviation of penetration loss; N(μ,*) represents normal distribution.

4. The high frequency channel data optimization propagation method according to claim 3, characterized in that: The signal propagation coverage model divides the high-frequency electromagnetic wave propagation area into the following areas according to the sparseness of high-frequency electromagnetic wave propagation: Near-end free loss zone: mainly free space propagation, the propagation path is the straight path; LOS+scatterer: LOS propagation is dominant, and scatterers provide reflection and diffraction propagation paths for electromagnetic waves; NLOS area: consists of reflection path and direct path; Distant NLOS region: composed of reflection paths; No coverage area: There is no reflection path or direct path, the electromagnetic waves are transmitted over a long distance, and the receiver cannot demodulate the signal normally.

5. The high frequency channel data optimization propagation method according to claim 4, characterized in that: The current signal transmission area is divided into multiple different areas, and the electromagnetic wave transmission quality of each area is given. The electromagnetic wave transmission quality is determined by the channel attenuation h(t): Where X represents the log-normal shadow attenuation; L represents the total number of paths; K represents the total number of channels; t represents the total access time; T l Indicates the time of accessing the first path; τ k,l represents the starting time of accessing the kth channel and the first path; p k,l represents a discrete random variable with equal probability of taking +1 and -1; β k,l Indicates that the channel coefficient of the first path follows a log-normal distribution; The calculated channel attenuation h(t) and the threshold H min Comparison: If h(t)>H min , it is determined that the electromagnetic wave transmission quality does not meet the standard and switches to optical communication; If h(t)≤H min , it is determined that the electromagnetic wave transmission quality meets the standard and electromagnetic wave communication continues.

6. The high frequency channel data optimization propagation method according to claim 5, characterized in that: Also includes: The Markov prediction model is used to predict the blind area signal coverage trend of the optical signal. The expression is as follows: X(k+1)=X(k)×P Where X(k) represents the state vector of the trend analysis and prediction object at time t=k; P represents the one-step transition probability matrix, and X(k+1) represents the state vector of the trend analysis and prediction object at time t=k+1.

7. The high frequency channel data optimization propagation method according to claim 6, characterized in that: Calculated by analyzing the following rectangular data: The probability matrix of abnormal and normal light source signals in the previous period is: The abnormal probability matrix of normal transfer of light source signal in the current period is: The probability matrix of abnormal light source signal transition to normal in the current period is:

8. A high-frequency signal propagation device, characterized in that: include: Regional feature recognition unit; The regional feature recognition unit is used to recognize the features of the current signal transmission area, divide the current signal transmission area into a plurality of different areas, and provide the electromagnetic wave transmission quality of each area; Switching condition judgment unit; The switching condition judgment unit is used to switch the area where the electromagnetic wave transmission quality is less than a predetermined value to optical communication, and the remaining areas continue to maintain electromagnetic wave communication; Switching result checking unit; the switching result checking unit is used to check the communication quality of the area switched to optical communication, taking the industry standard light source value as the baseline, and using the brightness index of the luminous flux as the basis for whether the light source signal is normal; The high-frequency signal propagation device can automatically execute the high-frequency channel data optimization propagation method as described in any one of claims 1 to 7.

9. An electronic device, characterized in that: The device comprises: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the high-frequency channel data optimization propagation method as claimed in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The storage medium stores at least one executable instruction. When the executable instruction is executed on the electronic device, the electronic device executes the high-frequency channel data optimization propagation method according to any one of claims 1 to 7.

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