CN111162854B - Channel measuring method, device, computer equipment and storage medium - Google Patents
Channel measuring method, device, computer equipment and storage medium Download PDFInfo
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- CN111162854B CN111162854B CN201911415600.3A CN201911415600A CN111162854B CN 111162854 B CN111162854 B CN 111162854B CN 201911415600 A CN201911415600 A CN 201911415600A CN 111162854 B CN111162854 B CN 111162854B
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Abstract
The application relates to a channel measuring method, a device, a computer device and a storage medium, wherein corresponding channel models are constructed in advance according to service types of different channels, each channel model is constructed according to characteristic parameters of each channel, and parameter scheduling information is configured for the channel models of different types, so that when the device is actually used, the characteristic parameters of the current channel can be obtained in real time, the optimal channel model is matched, optimal parameter scheduling information is obtained, and reasonable upper-layer scheduling is carried out on the service of the current channel based on the information, so that the service rate and the performance of a base station are improved, and the rate of the whole base station system is also improved.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a channel measurement method, an apparatus, a computer device, and a storage medium.
Background
The indoor channel model is a model for simulating an indoor wireless channel.
In the current wireless channel simulation, a protocol tap Delay model is adopted to perform simulation according to a specific channel of 3GPP, for example, a Tapped Delay Line (TDL) model, and then the upper layer of a base station is guided to perform scheduling based on the simulation result of the channel. The channel information of the specific channel is relatively fixed, and the corresponding simulation result is relatively fixed. However, the indoor environment has diversity, and the diversity causes the signal transmission path and signal strength to be different, which is equivalent to higher requirements for the scheduling of the upper layer services, and once the channel is not matched with the corresponding services, the throughput is very bad.
Therefore, the upper layer is guided to carry out scheduling based on the simulation result of the specific channel, which is not in accordance with the indoor variable situation, so that the optimal scheduling configuration cannot be obtained during scheduling.
Disclosure of Invention
In view of the above, it is necessary to provide a channel measurement method, apparatus, computer device and storage medium for solving the above technical problems.
In a first aspect, an embodiment of the present application provides a channel measurement method, where the method includes:
acquiring channel characteristic parameters of a current channel;
matching a target channel model for the current channel from a preset channel model library according to the channel characteristic parameters of the current channel; the channel model library comprises channel models corresponding to channels of various service types;
acquiring parameter scheduling information corresponding to the target channel model from a preset channel database according to the target channel model; the channel database comprises parameter scheduling information corresponding to a plurality of channel models; the parameter scheduling information is used to indicate upper layer scheduling of the current channel.
In one embodiment, the parameter scheduling information at least includes a service corresponding to a current channel, a receiving power value corresponding to the service, a data stream corresponding to the service, a precoding matrix indication feedback period corresponding to the service, and subcarrier information.
In one embodiment, the modeling process of each channel model in the channel model library includes:
acquiring signal sampling point data of a plurality of indoor sampling points, wherein the signal sampling point data is signal sampling point data of a plurality of indoor channels measured at the sampling points;
analyzing each signal sampling point data to obtain a channel characteristic parameter corresponding to each signal sampling point data;
and constructing a channel model of each channel according to the characteristic parameters of each channel.
In one embodiment, the acquiring signal sample point data of a plurality of indoor sample points includes:
determining a plurality of indoor sampling point positions according to the networking distribution of the indoor base stations; the sampling point position is determined in an area which can be covered by the indoor base station signal;
and collecting signal sampling point data of each sampling point according to the position of each sampling point.
In one embodiment, each indoor sampling point is sampled according to N times of a preset minimum scheduling time; n is a positive integer.
In one embodiment, the analyzing the data of each signal sampling point to obtain the channel characteristic parameter corresponding to the data of each signal sampling point includes:
acquiring a channel estimation value from each sampling point data;
and acquiring multipath components, antenna correlation coefficients, time correlation coefficients and subcarrier correlation coefficients of each channel estimation value as channel characteristic parameters corresponding to each sampling point data.
In one embodiment, the process of constructing the channel database includes:
performing data link simulation on each channel model according to each channel characteristic parameter to obtain parameter scheduling information corresponding to each channel model;
and storing the parameter scheduling information corresponding to each channel model to obtain a channel database.
In one embodiment, the method further comprises:
performing data link simulation on each channel model to acquire the performance relationship between the time correlation coefficient of each channel and different service data streams and the performance relationship between the subcarrier correlation coefficient of each channel and different service data streams;
determining a threshold value of the time correlation coefficient of each channel according to the performance relation between the time correlation coefficient of each channel and different service data streams, and determining a threshold value of the subcarrier correlation coefficient of each channel according to the performance relation between the subcarrier correlation coefficient of each channel and different service data streams;
and evaluating the correlation degree of the subcarrier correlation coefficient of each channel according to the threshold value of the subcarrier correlation coefficient, and evaluating the time correlation coefficient of each channel according to the time correlation coefficient threshold.
In a second aspect, an embodiment of the present application provides a channel measurement apparatus, including:
the acquisition module is used for acquiring the channel characteristic parameters of the current channel;
the matching module is used for matching a target channel model for the current channel from a preset channel model library according to the channel characteristic parameters of the current channel; the channel model library comprises channel models corresponding to channels of various service types;
the parameter module is used for acquiring parameter scheduling information corresponding to the target channel model from a preset channel database according to the target channel model; the channel database comprises parameter scheduling information corresponding to a plurality of channel models; the parameter scheduling information is used to indicate upper layer scheduling of the current channel.
In a third aspect, an embodiment of the present application provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor implements the steps of any one of the channel measurement methods provided in the embodiments of the first aspect when executing the computer program.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of any one of the channel measurement methods provided in the foregoing embodiments of the first aspect.
According to the channel measuring method, the channel measuring device, the computer equipment and the storage medium, corresponding channel models are constructed in advance according to service types of different channels, each channel model is constructed according to characteristic parameters of each channel, and parameter scheduling information is configured for the channel models of different types, so that when the channel measuring method is actually used, the characteristic parameters of the current channel can be obtained in real time, the optimal channel model is matched, optimal parameter scheduling information is obtained, reasonable upper-layer scheduling is carried out on the service of the current channel based on the information, the service rate and performance of a base station are improved, and the rate of the whole base station system is also improved.
Drawings
Fig. 1 is a diagram of an application environment of a channel measurement method according to an embodiment;
fig. 2 is a flowchart illustrating a channel measurement method according to an embodiment;
fig. 3 is a schematic diagram of an indoor UE path according to an embodiment;
fig. 4 is a flowchart illustrating a channel measurement method according to another embodiment;
FIG. 5 is a plan view of an indoor environment and base stations according to one embodiment;
FIG. 6 is a schematic diagram of a channel transmit/receive model according to an embodiment;
fig. 7 is a flowchart illustrating a channel measurement method according to another embodiment;
fig. 8 is a block diagram of a channel measuring apparatus according to an embodiment;
fig. 9 is a block diagram of a channel measuring apparatus according to another embodiment;
fig. 10 is a block diagram of a channel measuring apparatus according to another embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The channel measurement method provided by the application can be applied to the application environment as shown in fig. 1, and the computer device is connected with the processor, the memory, the network interface and the database through the system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing data of a kind of channel measurement. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to perform a channel measurement. The computer device may be installed in a base station, and the base station may be a base station of any standard, such as a 5G base station, a 4G base station, and the like, where the internal structure shown in fig. 1 is only an example of the computer device in the base station and is not limited.
For 5G large-band bandwidth, most of the delay spread will cause severe frequency selective fading to the signal. And the impulse response of the channel is time-varying, different impulse responses h (t) will characterize different channels at different absolute time instants t. The actual value of this impulse response is determined by the value of the MPC (multi-path Component) complex fading at time t. This also places higher demands on the scheduling of the upper layer traffic, which throughput drops significantly if the channel does not match the corresponding traffic. In general simulation, a protocol tap delay model is adopted for simulation, and the simulation is performed according to a specific channel of 3GPP, such as TDL. The information of the channels is relatively fixed, but the indoor environment is variable because the size of each room in the indoor environment is different, the arrangement and the position of indoor devices are different, the materials of indoor objects are different, the positions of the objects to be inspected in the rooms are different, and the like; these factors determine the reflection, refraction, diffraction, scattering, etc. of the radio radiation in the room, resulting in varying paths and signal strengths. These factors present challenges for indoor base station applications. If the result is directly used to guide the upper layer scheduling without considering the variability of the indoor environment, the optimal scheduling configuration cannot be obtained during the upper layer scheduling.
Based on this, embodiments of the present application provide a channel measurement method, an apparatus, a computer device, and a storage medium, and a technical solution of the present application and how to solve the above technical problem will be specifically described in detail below by way of embodiments and with reference to the accompanying drawings. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. It should be noted that, in the channel measurement method provided in the present application, the execution main body of fig. 2 to fig. 7 is a base station, where the execution main body may also be a channel measurement apparatus, where the apparatus may be implemented as part or all of the base station by software, hardware, or a combination of software and hardware.
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments.
In an embodiment, fig. 2 provides a channel measurement method, and this embodiment relates to a specific process in which a base station performs upper layer scheduling on a current channel according to a pre-configured channel model and parameter scheduling information, as shown in fig. 2, the method includes:
s101, obtaining the channel characteristic parameters of the current channel.
The current channel refers to a channel that needs to be currently scheduled, and the embodiment of the position corresponding to the current channel is not limited. The channel characteristic parameter represents information such as multipath component MPC of the channel, power, time, and phase of each component. The base station receives signals of a plurality of multipath components (MPCs) sent by each user terminal, optionally, the base station may further determine an arrival angle and a time delay of the MPC, and based on the arrival angle and the time delay, the base station may determine the position of each user terminal.
S102, according to the channel characteristic parameters of the current channel, matching a target channel model for the current channel from a preset channel model library; the channel model library comprises channel models corresponding to various service type channels.
And based on the channel characteristic parameters of the current channel, the base station matches a target channel model for the current channel from a preset channel model base. The channel model library stores a plurality of channel models, and each channel model corresponds to one service type, or one channel model corresponds to a plurality of similar service types. The channel model is constructed based on channel parameters, and the base station can directly match with a target channel model after acquiring the channel characteristic parameters of the current channel.
S103, acquiring parameter scheduling information corresponding to the target channel model from a preset channel database according to the target channel model; the channel database comprises parameter scheduling information corresponding to a plurality of channel models; the parameter scheduling information is used to indicate upper layer scheduling of the current channel.
In this step, the base station obtains parameter scheduling information corresponding to the target channel model from a preset channel database. The parameter scheduling information indicates scheduling information that needs to be used when the base station performs upper-layer scheduling on the service of the channel, and is used for indicating the base station to perform upper-layer scheduling on the current channel. Optionally, the parameter scheduling information at least includes a service corresponding to the current channel, a receiving power value corresponding to the service, a data stream corresponding to the service, a precoding matrix indication feedback period corresponding to the service, and subcarrier information. The channel database stores parameter scheduling information corresponding to various channel models in advance, and the base station can directly acquire the parameter scheduling information from the channel database.
Illustratively, as shown in fig. 3, fig. 3 is a path diagram of a UE in an indoor environment. Taking the UE from point a to point D, passing through points B and C as an example, the base station or specifically a scheduler parameter correction module in the base station analyzes the information data channel characteristics of the real-time data, and selects the optimal matching parameter scheduling information of the real-time channel and the channel database. Specifically, when the UE is at point a, the base station is at a visible distance, and the MPC obtained by the base station is recorded as H1Is prepared from H1And matching the parameter scheduling information in the channel database, wherein the parameter scheduling information comprises corresponding scheduling parameters of power and service, and then performing upper-layer scheduling based on the matched parameters. After the matching is finished, the relevant information set of the position channel model can be recorded as { H }1,SNRi,MCSiAnd h, wherein, the SNR is the signal-to-noise ratio, and the MCS is different service types. Let the set of channel correlation coefficients and the best performance relationship for the data stream be { H }1,Pi,LayeriP represents an antenna correlation coefficient, and Layer represents a data stream. And according to H1Calculating the time correlation coefficient of channel, and selecting the scheduling time period T1And carrying out scheduling.
When the UE moves to the point B, the signal is blocked, the channel H changes, and in the absence of a visible distance, the MPC, power, phase, and the like all change, and if the UE selects to perform scheduling according to the scheduling parameters of the service, data stream, and the like of the point a, the throughput of the UE may decrease quickly, even drop 0. Then the scheduler parameter modification module in the base station needs to find the channel H of the point B at this time2And according to H2And acquiring corresponding scheduling parameters and performing corresponding parameter adjustment to obtain the optimal channel matching. Similarly, when the UE moves to the point C and the point D, the channel H changes correspondingly, and the H corresponding to the point C corresponds to the H3H corresponding to D point4And acquiring corresponding scheduling parameters and performing corresponding parameter adjustment to obtain the optimal channel matching. Therefore, the corresponding channel model is determined through the characteristic analysis of the real-time channel, the optimal matching parameter scheduling information of the real-time channel and the channel database information is selected, and scheduling is performed according to the optimal parameter scheduling information, so that the whole system can obtain the optimal throughput, and the user experience is improved.
In the channel measurement method provided by this embodiment, because corresponding channel models are constructed in advance for different service types of channels, each channel model is constructed according to the characteristic parameters of each channel, and parameter scheduling information is configured for the different types of channel models, in practical use, the characteristic parameters of the current channel can be obtained in real time, the optimal channel model is matched to obtain the optimal parameter scheduling information, and the service of the current channel is reasonably scheduled by the upper layer based on the information, so that the service rate and performance of the base station are improved, and the rate of the whole base station system is also improved.
The following describes several embodiments of the channel model building process in the above embodiments. On the basis of the above embodiment, there is provided an embodiment of channel model construction, as shown in fig. 4, the embodiment includes:
s201, obtaining signal sampling point data of a plurality of indoor sampling points, wherein the signal sampling point data are signal sampling point data of a plurality of indoor channels measured at the sampling points.
The present embodiment is a data acquisition process of a channel model building process, and signal sampling point data of a plurality of channels corresponding to each sampling point in a plurality of indoor sampling points is acquired, that is to say, the signal sampling point data here is a general name and is not limited in other aspects. The sampling points represent indoor positions needing to be dotted, for example, some common dotted positions can be selected from the indoor sampling points, such as visible points, shielding points and some special corners in the coverage area of the indoor base station signal, and certainly, different moments when people walk around some positions can also be used as the sampling points.
Optionally, an implementation manner of obtaining signal sample point data is provided: determining indoor sampling point positions according to networking distribution of indoor base stations; the sampling point position is determined in an area which can be covered by the indoor base station signal; and collecting signal sampling point data of a plurality of sampling points according to the position of each sampling point. Optionally, each indoor sampling point is sampled according to N times of a preset minimum scheduling time; n is a positive integer.
Referring to fig. 5, fig. 5 is a plan distribution diagram of an indoor environment and base stations, and specifically, according to the networking distribution of indoor base stations, information collection is performed on areas that can be covered by the indoor base stations, and a visual point, a blocking point, a special corner, a position where people flow, and the like in the covered area are collected, as shown in the middle area of fig. 5. And then dotting the lines in the dotting area, namely acquiring signal data of the channel. When signal data are collected, a minimum scheduling time can be preset, and when the signal data are collected specifically, the signal data can be collected according to the time length N times of the time of each scheduling period, so that the data collection is controlled according to the preset scheduling period, and the rule analysis of the signal data is facilitated.
S202, analyzing the data of each signal sampling point, and acquiring the channel characteristic parameter corresponding to the data of each signal sampling point.
And S203, constructing a channel model of each channel according to the characteristic parameters of each channel.
After the signal data of each indoor sampling point is collected in the steps, the base station analyzes the data of the sampling points. When the sampling point data is analyzed, the base station can analyze through the signal data analysis module. For example, the signal data analysis module obtains characteristics of each channel in the sampling point data, including information such as MPC, phase, amplitude, and the like of the channel, and further obtains information such as time correlation of the channel, antenna correlation of the transceiver, carrier correlation, and the like.
Optionally, an implementable manner of the analysis process is provided, including: acquiring a channel estimation value from each sampling point data; and acquiring multipath components, antenna correlation coefficients, time correlation coefficients and subcarrier correlation coefficients of each channel estimation value as channel characteristic parameters corresponding to each sampling point data.
Taking a signal data analysis module in the base station as an example, the signal data analysis module obtains a channel estimation value H through a reference signal in sampling point signal datam,n,tWhere n is the number of transmit antennas, m is the number of receive antennas, and t is the absolute time. Wherein H is obtainedm,n,tReference may be made to the channel transceiving model shown in fig. 6. The signal data analysis module then passes Hm,n,tObtaining H at each timem,n,tIn particular, the signal data analysis module will Hm,n,tConverting into time domain, converting into H in time domainm,n,tAnd taking the tap power larger than the threshold as a valid MPC, and recording the corresponding power and time domain position of the MPC, wherein the threshold is an initial threshold, and because the threshold required to be used in the analysis process is not accurate, an initial threshold can be defined in actual use, and then an accurate threshold can be further determined based on the initial threshold.
When analyzing the signal sampling data, a signal data analysis module in the base station needs to acquire the correlation of the antenna as a reference parameter of the scheduling service data stream. Specifically, the signal data analysis module counts antenna correlation coefficients at different time points t, and the antenna correlation coefficients are used as antenna correlation values corresponding to the channels, and the antenna correlation values can be used as reference parameters for determining the scheduling service data streams.
Wherein, the signal data analysis module in the base station acquires H of different time points when analyzing the signal sampling datam,n,tAnd the correlation coefficient of the time domain is used as a reference for scheduling the time period. In obtaining Hm,n,tAfter the time correlation coefficient is obtained, an initial threshold of the time correlation coefficient can be set, the initial threshold can be used for judging the time correlation coefficient, if the calculated time correlation coefficient is larger than a threshold value, the channel correlation is considered to be strong in the period of time, and the base station refers to the scheduling time period based on the judged correlation strength of different channels.
In a 5G large bandwidth scenario, when there is a large delay spread, the channel frequency fading is severe, and for the condition of Precoding Matrix Indicator (PMI) feedback, a subcarrier feedback mode may be adopted, and in order to better select the subcarrier size, it is further necessary to obtain Hm,n,tThe carrier correlation of (2) is used as a reference for selecting the size of the PMI selection subcarrier. Specifically, the signal data analysis module calculates H in the scheduling periodm,n,tAfter the correlation of the subcarriers is carried out, the correlation coefficient of the subcarriers can be judged by setting an initial threshold value, if the correlation coefficient is larger than Q, the correlation coefficient is used as a strong correlation subcarrier set, so that the size of the minimum carrier subset in the subcarrier set can be selected and used as a reference for feeding back the size of the PMI subcarriers.
And based on the characteristic parameters of the channels, the base station constructs a channel model of each channel. For example, a tapped delay model can be used for simulation modeling, and then each channel model set is recorded as Hi。
In this embodiment, the base station acquires the sampling point signal data of each indoor channel in advance, analyzes based on the sampling point signal data, and establishes the channel model according to the analysis result, so that different channel models are established for the service corresponding to each channel in a targeted manner, the matching between the channel service and the channel model can be improved, and the optimal parameter scheduling information is obtained, thereby the service rate and performance of upper layer scheduling
In addition, in an embodiment, as shown in fig. 7, the building process of the channel database includes:
s301, according to the characteristic parameters of each channel, performing data link simulation on each channel model to obtain parameter scheduling information corresponding to each channel model.
In this embodiment, the base station performs data link simulation on the channel models respectively based on the established channel models and using the channel characteristic parameters as input, and obtains parameter scheduling information corresponding to each channel model.
Illustratively, according to channel modeling simulation, a receiving power value corresponding to a corresponding service is obtained as a scheduling parameter corresponding to power and service, and the set is recorded as { H }i,SNRi,MCSiWhere SNR is the signal-to-noise ratio and MCS is different traffic type. And according to channel modeling simulation, obtaining the corresponding relation between the antenna correlation coefficient P and the performances of different service data streams. Specifically, according to the obtained correlation coefficient P of the channel and the channel model, different data streams are simulated, the optimal performance relationship between the channel antenna correlation coefficient and the data stream is obtained, and the set is marked as { H }i,Pi,LayeriP is the antenna correlation coefficient, and Layer is the data stream.
And S302, storing the parameter scheduling information corresponding to each channel model to obtain a channel database.
And storing the information based on the parameter scheduling information obtained by simulating the channel model to obtain a channel database.
In this embodiment, a corresponding channel database is established according to the channel model, where the channel database includes channel information, and a performance analysis result corresponding to the channel information corresponds to scheduling information corresponding to a corresponding performance, so that the base station determines a corresponding channel model according to a real-time characteristic parameter of a current channel, and further determines corresponding parameter scheduling information according to the corresponding channel model, so that the obtained parameter scheduling information is more targeted, and it can be ensured that an upper layer schedule obtains an optimal scheduling configuration.
In addition, when the parameter scheduling information is obtained, an optimal threshold value of each parameter may be obtained, where the optimal threshold value is a threshold value obtained by accurately updating the initial threshold value mentioned in the embodiment of fig. 3, and in an embodiment, the method further includes: performing data link simulation on each channel model to acquire the performance relationship between the time correlation coefficient of each channel and different service data streams and the performance relationship between the subcarrier correlation coefficient of each channel and different service data streams; determining a threshold value of the time correlation coefficient of each channel according to the performance relation between the time correlation coefficient of each channel and different service data streams, and determining a threshold value of the subcarrier correlation coefficient of each channel according to the performance relation between the subcarrier correlation coefficient of each channel and different service data streams; and evaluating the correlation degree of the subcarrier correlation coefficient of each channel according to the threshold value of the subcarrier correlation coefficient, and evaluating the time correlation coefficient of each channel according to the time correlation coefficient threshold.
In this embodiment, based on the above-described constructed channel models, the base station uses the characteristic parameters of each channel as input to perform simulation, so as to obtain the channel time correlation coefficient threshold. Illustratively, according to the obtained channel time correlation coefficient, service simulation is performed, performance relations between the channel time correlation coefficient and different data services are obtained, an optimal performance relation is obtained from the performance relations, and then a channel time correlation coefficient threshold is determined. Wherein, the time correlation coefficient threshold is the optimal threshold value of the time correlation coefficient. After obtaining the time correlation coefficient threshold, the correlation degree of the time correlation coefficient of each channel can be evaluated according to the threshold value. That is, when the time correlation coefficient obtained in the previous embodiment is greater than the threshold value, the channel correlation is considered to be strong in the period of time, otherwise, the correlation is considered to be weak.
Similarly, based on the above-constructed channel models, the base station takes the characteristic parameters of each channel as input for simulation, and can obtain the correlation coefficient threshold of the sub-carrier of the channel. Illustratively, according to the obtained channel subcarrier correlation coefficient, service simulation is performed to obtain the performance relationship between the channel subcarrier correlation coefficient and different data services, and also obtain the optimal performance relationship from each performance relationship, so as to determine the channel subcarrier correlation coefficient threshold. Similarly, the threshold of the correlation coefficient of the sub-carrier is the optimal threshold value of the correlation coefficient of the sub-carrier. After the threshold of the correlation coefficient of the sub-carrier is obtained, the degree of the correlation coefficient of the sub-carrier of each channel can be evaluated according to the threshold. That is, when the correlation of the sub-carrier obtained in the previous embodiment is greater than the threshold, the sub-carrier is considered as a strong correlation sub-carrier, otherwise, the correlation is considered as a weak correlation.
After the optimal threshold values of the parameters are obtained, the optimal threshold values may be stored in the channel database. In this embodiment, after the optimal threshold value of each parameter is determined based on the channel model, the correlation of each parameter may be evaluated through the optimal threshold value, so as to better refer to upper layer scheduling and ensure that better parameter scheduling information may be selected.
It should be understood that although the various steps in the flow charts of fig. 2-7 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-7 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 8, there is provided a channel measuring apparatus including: an acquisition module 10, a matching module 11 and a parameter module 12, wherein,
an obtaining module 10, configured to obtain a channel characteristic parameter of a current channel;
the matching module 11 is configured to match a target channel model for a current channel from a preset channel model library according to a channel characteristic parameter of the current channel; the channel model library comprises channel models corresponding to channels of various service types;
the parameter module 12 is configured to obtain, according to the target channel model, parameter scheduling information corresponding to the target channel model from a preset channel database; the channel database comprises parameter scheduling information corresponding to a plurality of channel models; the parameter scheduling information is used to indicate upper layer scheduling of the current channel.
In an embodiment, the parameter scheduling information at least includes a service corresponding to a current channel, a receiving power value corresponding to the service, a data stream corresponding to the service, a precoding matrix indication feedback period corresponding to the service, and subcarrier information.
In one embodiment, as shown in fig. 9, there is provided a channel measuring apparatus, further comprising:
the sampling module 13 is configured to obtain signal sampling point data of a plurality of indoor sampling points, where the signal sampling point data is signal sampling point data of a plurality of indoor channels measured at the sampling points;
the analysis module 14 is configured to analyze each signal sampling point data to obtain a channel characteristic parameter corresponding to each signal sampling point data;
and the building module 15 is configured to build a channel model of each channel according to the characteristic parameters of each channel.
In an embodiment, the sampling module 13 is configured to determine a plurality of indoor sampling point positions according to indoor base station networking distribution; the sampling point position is determined in an area which can be covered by the indoor base station signal; and collecting signal sampling point data of each sampling point according to the position of each sampling point.
In one embodiment, each sampling point in the room is sampled according to N times of a preset minimum scheduling time; n is a positive integer.
In an embodiment, the analyzing module 14 is configured to obtain a channel estimation value from each sampling point data; and acquiring multipath components, antenna correlation coefficients, time correlation coefficients and subcarrier correlation coefficients of each channel estimation value as channel characteristic parameters corresponding to each sampling point data.
In one embodiment, as shown in fig. 10, there is provided a channel measuring apparatus, further comprising:
the simulation module 16 is configured to perform data link simulation on each channel model according to each channel characteristic parameter, and obtain parameter scheduling information corresponding to each channel model;
and the database module 17 is used for storing the parameter scheduling information corresponding to each channel model to obtain a channel database.
In one embodiment, the apparatus further comprises:
the relation module is used for carrying out data link simulation on each channel model and acquiring the performance relation between the time correlation coefficient of each channel and different service data streams and the performance relation between the subcarrier correlation coefficient of each channel and different service data streams;
a threshold value module, configured to determine a threshold value of a time correlation coefficient of each channel according to the performance relationship between the time correlation coefficient of each channel and different service data streams, and determine a threshold of a subcarrier correlation coefficient of each channel according to the performance relationship between the subcarrier correlation coefficient of each channel and different service data streams;
and the evaluation module is used for evaluating the correlation degree of the subcarrier correlation coefficient of each channel according to the threshold value of the subcarrier correlation coefficient and evaluating the time correlation coefficient of each channel according to the time correlation coefficient threshold.
The implementation principle and technical effect of all the channel measurement apparatuses provided in the above embodiments are similar to those of the above embodiments of the channel measurement method, and are not described herein again.
For the specific definition of the channel measurement device, reference may be made to the above definition of the channel measurement method, which is not described herein again. The various modules in the channel measuring device described above may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, the internal structure of which may be as described above in fig. 1. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a channel measurement method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the above-described architecture shown in fig. 1 is merely a block diagram of some of the structures associated with the present solution, and does not constitute a limitation on the computing devices to which the present solution applies, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring channel characteristic parameters of a current channel;
matching a target channel model for the current channel from a preset channel model library according to the channel characteristic parameters of the current channel; the channel model library comprises channel models corresponding to channels of various service types;
acquiring parameter scheduling information corresponding to the target channel model from a preset channel database according to the target channel model; the channel database comprises parameter scheduling information corresponding to a plurality of channel models; the parameter scheduling information is used to indicate upper layer scheduling of the current channel.
The implementation principle and technical effect of the computer device provided by the above embodiment are similar to those of the above method embodiment, and are not described herein again.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring channel characteristic parameters of a current channel;
matching a target channel model for the current channel from a preset channel model library according to the channel characteristic parameters of the current channel; the channel model library comprises channel models corresponding to channels of various service types;
acquiring parameter scheduling information corresponding to the target channel model from a preset channel database according to the target channel model; the channel database comprises parameter scheduling information corresponding to a plurality of channel models; the parameter scheduling information is used to indicate upper layer scheduling of the current channel.
The implementation principle and technical effect of the computer-readable storage medium provided by the above embodiments are similar to those of the above method embodiments, and are not described herein again.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method of channel measurement, the method comprising:
acquiring signal sampling point data of a plurality of indoor sampling points, wherein the signal sampling point data is signal sampling point data of a plurality of indoor channels measured at the sampling points; acquiring a channel estimation value from each sampling point data;
acquiring multipath components, antenna correlation coefficients, time correlation coefficients and subcarrier correlation coefficients of each channel estimation value as channel characteristic parameters corresponding to each sampling point data;
according to the channel characteristic parameters of the current channel, matching a target channel model for the current channel from a preset channel model library; the channel model library comprises channel models corresponding to channels of various service types;
acquiring parameter scheduling information corresponding to the target channel model from a preset channel database according to the target channel model; the channel database comprises parameter scheduling information corresponding to a plurality of channel models; the parameter scheduling information is used for indicating the upper layer scheduling of the current channel.
2. The channel measurement method according to claim 1, wherein the parameter scheduling information at least includes a service corresponding to the current channel, a receiving power value corresponding to the service, a data stream corresponding to the service, and a precoding matrix indication feedback period and subcarrier information corresponding to the service.
3. The channel measurement method according to claim 1 or 2, wherein the modeling process of each channel model in the channel model library comprises:
analyzing the data of each signal sampling point to obtain a channel characteristic parameter corresponding to the data of each signal sampling point;
and constructing a channel model of each channel according to each channel characteristic parameter.
4. The channel measuring method according to claim 3, wherein said obtaining signal sample point data of a plurality of sample points in a room comprises:
determining a plurality of indoor sampling point positions according to the networking distribution of the indoor base stations; the sampling point position is determined in an area which can be covered by the indoor base station signal;
and collecting signal sampling point data of each sampling point according to the position of each sampling point.
5. The channel measuring method according to claim 4, wherein each sampling point in the room is sampled according to N times of a preset minimum scheduling time; and N is a positive integer.
6. The channel measurement method according to claim 3, wherein the construction process of the channel database comprises:
performing data link simulation on each channel model according to each channel characteristic parameter to acquire parameter scheduling information corresponding to each channel model;
and storing the parameter scheduling information corresponding to each channel model to obtain the channel database.
7. The channel measurement method of claim 6, further comprising:
performing data link simulation on each channel model to acquire the performance relationship between the time correlation coefficient of each channel and different service data streams and the performance relationship between the subcarrier correlation coefficient of each channel and different service data streams;
determining a threshold value of the time correlation coefficient of each channel according to the performance relation between the time correlation coefficient of each channel and different service data streams, and determining a threshold of the subcarrier correlation coefficient of each channel according to the performance relation between the subcarrier correlation coefficient of each channel and different service data streams;
and evaluating the correlation degree of the subcarrier correlation coefficient of each channel according to the threshold value of the subcarrier correlation coefficient, and evaluating the time correlation coefficient of each channel according to the time correlation coefficient threshold.
8. A channel measurement apparatus, characterized in that the apparatus comprises:
the device comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring signal sampling point data of a plurality of indoor sampling points, and the signal sampling point data is signal sampling point data of a plurality of indoor channels measured at the sampling points; acquiring a channel estimation value from each sampling point data; acquiring multipath components, antenna correlation coefficients, time correlation coefficients and subcarrier correlation coefficients of each channel estimation value as channel characteristic parameters corresponding to each sampling point data;
the matching module is used for matching a target channel model for the current channel from a preset channel model library according to the channel characteristic parameters of the current channel; the channel model library comprises channel models corresponding to channels of various service types;
the parameter module is used for acquiring parameter scheduling information corresponding to the target channel model from a preset channel database according to the target channel model; the channel database comprises parameter scheduling information corresponding to a plurality of channel models; the parameter scheduling information is used for indicating the upper layer scheduling of the current channel.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the channel measurement method of any of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the channel measurement method according to any one of claims 1 to 7.
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| CN114189302B (en) * | 2021-12-13 | 2023-10-20 | 国网山东省电力公司营销服务中心(计量中心) | Wireless communication channel modeling method for smart grid transmission of user decentralized scene |
| CN117200915A (en) * | 2022-05-31 | 2023-12-08 | 中兴通讯股份有限公司 | Data channel model transmitting method and device and information transmitting method and device |
| CN117353848A (en) * | 2022-06-28 | 2024-01-05 | 中兴通讯股份有限公司 | Physical channel simulation method, device, channel simulation system and storage medium |
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