CN114785439A - Method and device for improving time synchronization precision of industrial Internet of things terminal - Google Patents
Method and device for improving time synchronization precision of industrial Internet of things terminal Download PDFInfo
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Abstract
The invention discloses a method and a device for improving the time synchronization precision of an industrial Internet of things terminal. And the intelligent reflecting surface is introduced into the wireless communication environment, and the optimal time precision is determined based on the different phase angles of the intelligent reflecting surface, the transmitting power distributed to the terminal by the base station and the steady-state error covariance by acquiring the different phase angles of the intelligent reflecting surface, so that the information accessibility of the two-way timestamp between the base station and the terminal is improved by introducing the intelligent reflecting surface, the reliability of a wireless channel is ensured, and the time synchronization precision is further improved.
Description
Technical Field
The invention relates to the field of time synchronization, in particular to a method and a device for improving the time synchronization precision of an industrial Internet of things terminal.
Background
The fifth generation mobile communication network (5G) meets the strict requirements of the industrial Internet of things on network characteristics such as large bandwidth, massive connection, flexible deployment and the like. Meanwhile, the introduction of the wireless network eliminates a large number of complex wired lines in a factory, and reduces the network deployment cost. However, the wireless network has poor interference resistance, and noise interference in the environment may cause disorder, delay or even packet loss of data packets carrying information in wireless link transmission.
There are a large number of terminals working in coordination in the industrial internet of things scenario, and these industrial terminals have extremely strict requirements for global time synchronization, and the time synchronization error is usually in ns level. And the time service is finished between the base station and each terminal based on a bidirectional timestamp information packet exchange mechanism. However, the reliability of the wireless channel has a great influence on the reachable rate of the timestamp information packet, and the loss of the information packet due to the unreliability of the wireless link causes the increase of the time synchronization error, and finally causes the time synchronization failure. Therefore, it is important to improve the reliability of the wireless network, ensure the arrival rate of the timestamp packets, and improve the accuracy of the clock synchronization. The intelligent reflecting surface is a plane formed by a large number of passive reflecting elements, and a new line-of-sight path is created by adjusting the phase of each reflecting element to change the transmission direction of signals, so that the wireless signal transmission environment is improved, and the channel reliability is enhanced. Meanwhile, the intelligent reflecting surface draws wide attention in the industry due to the characteristics of low energy consumption, low cost and flexible deployment. Therefore, the intelligent reflecting surface can be applied to the scene of the industrial internet of things with a complex field environment and is used for improving the reliability of a wireless transmission link, and further achieving the purpose of improving the time synchronization precision.
Patent No. CN201910335042.3 discloses a time synchronization method, apparatus, device and medium. The method is used for intelligent clock terminal equipment for time setting through a network time protocol, and comprises the following steps: when the current clock time of the time synchronization server is successfully acquired, taking the current clock time of the time synchronization server as the local clock time, wherein the time synchronization server is used for providing time reference for all terminal equipment in a network through a network time protocol; and when the current clock time of the time synchronization server fails to be obtained, obtaining the current clock time of a transfer server, and taking the current clock time of the transfer server as the local clock time, wherein the transfer server is used for providing information interacted with a user for the intelligent clock terminal equipment. The technical scheme of the embodiment of the invention can improve the accuracy of the local clock. Patent No. CN202010877365.8 discloses a time-synchronized real-time adaptive convergence estimation system, which includes a synchronization error estimation unit, a synchronization error feature estimation model, and a real-time convergence detection model. The method can be used in a distributed system or a wireless network with time synchronization requirements, is integrated into a time synchronization algorithm adopted by an application object, and further calculates the synchronization error convergence probability by using the time offset estimation obtained by the time synchronization algorithm. The obtained synchronization error convergence probability can be used as the basis for judging the system time synchronization precision and convergence state by other applications or time synchronization algorithms. The patent No. CN202121075649.1 discloses a real-time synchronization device of a wireless ad hoc network, which includes a networking and a communication protocol, and the real-time synchronization device includes a PC server, a BLE host and a BLE slave, wherein a command sending component of the PC server sends a time synchronization message to the BLE host, a command transparent transmission component of the BLE host updates a local time stamp T2 to be a time stamp T1 of the time synchronization message, and sends the time synchronization message with a local time stamp T2 to the BLE slave according to the communication protocol, the BLE slave obtains a local real-time stamp T3, adds a difference T4 between the stored local time stamp T3 and a time stamp T2 attached to the time synchronization message, calculates a new time stamp T5(═ T4+ T3), forms a data packet and sends the data packet to the BLE host, and the data packet is transparent transmitted to the PC server through the BLE host, and the PC server processes and detects a difference of time stamps T5 of each slave. The invention realizes high unification of time of each node in each group network through two-stage synchronous messages, has a closed loop feedback mechanism of data packet return, and can correct the synchronization success in time by the PC server.
At present, the above patents mainly improve the time synchronization precision by improving the time synchronization mechanism, but do not solve the problem of poor reliability of the wireless link, and the time synchronization precision of each terminal is not guaranteed.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to overcome the defects that the reliability of a wireless link is not solved and the time synchronization precision of each terminal is not guaranteed in the prior art, so that the method and the device for improving the time synchronization precision of the industrial internet of things terminal are provided.
The embodiment of the invention provides a method for improving the time synchronization precision of an industrial Internet of things terminal, which comprises the following steps:
constructing a wireless channel according to the position relationship among the base station, the terminal and the intelligent reflecting surface;
acquiring a line-of-sight path component, a non-line-of-sight path component and an intelligent reflecting surface phase angle of the wireless channel, and generating an equivalent channel based on the line-of-sight path component, the non-line-of-sight path component and the intelligent reflecting surface phase angle of the wireless channel;
acquiring the transmitting power distributed to the terminal by the base station and the line-of-sight path component of the equivalent channel, and determining the reliability evaluation index of the wireless channel based on the transmitting power and the line-of-sight path component of the equivalent channel;
acquiring timestamp information received by the terminal and the base station in a bidirectional information interaction process, and determining a current clock synchronization state estimation value based on the timestamp information;
inputting the estimated value of the current clock synchronization state and the reliability evaluation index of the wireless channel into a linear estimation model to generate an estimation error covariance of the current clock synchronization state;
iteration is carried out on the estimation error covariance of the current clock synchronization state, and a steady-state error covariance is generated;
and determining the optimal time synchronization precision based on the transmitting power distributed to the terminal by the base station, the steady-state error covariance and the intelligent reflecting surface phase angle.
Optionally, the determining a reliability evaluation indicator of the wireless channel based on the transmission power and the equivalent channel includes:
calculating a beam forming vector based on the line-of-sight path component of the equivalent channel, and generating an effective channel based on the wireless channel and the beam forming vector;
and acquiring a signal-to-noise ratio threshold value of the terminal, and calculating a reliability evaluation index based on the effective channel, the transmission power distributed to the terminal by the base station and the signal-to-noise ratio threshold value of the terminal.
Optionally, in the calculating a reliability evaluation indicator based on the effective channel, the transmission power allocated to the terminal by the base station, and the terminal signal-to-noise ratio threshold value, a calculation formula of the reliability evaluation indicator is as follows:
in the above formula, gu(k)(Θ) represents an effective channel,
indicating the threshold value, sigma, of the signal-to-noise ratio of the terminal2Representing Gaussian white noise, pu(k)Represents the transmit power allocated to the terminal by the base station.
Optionally, the determining the current clock synchronization state estimation value based on the timestamp information includes:
acquiring random time delay, fixed time delay and clock offset of the wireless channel, and constructing a time synchronization measurement equation based on the timestamp information, the clock frequency deviation, the random time delay of the wireless channel, the fixed time delay and the clock offset;
solving the time synchronization measurement equation to generate the actual value of the clock synchronization state and the error measurement noise;
and acquiring a clock synchronization state estimation value of a previous time node, and generating a current clock synchronization state estimation value based on the clock synchronization measurement value and the clock synchronization state estimation value of the previous time node.
Optionally, in the calculating the clock synchronization measurement value based on the clock synchronization state actual value, the error measurement noise, and the clock frequency deviation, a calculation formula of the clock synchronization measurement value is as follows:
yq＝ηq(Dxq+vq)
in the above formula, yqRepresenting clock-synchronous measurements, etaqRepresenting a binary Bernoulli random variable, D representing a clock frequency deviation, xqIndicating the actual value of the clock synchronization status, vqRepresenting error measurement noise.
Optionally, the determining the optimal time synchronization accuracy based on the transmission power allocated to the terminal by the base station, the steady-state error covariance, and the intelligent reflecting surface phase angle includes:
constructing a multi-target problem according to the steady-state error covariance and the fairness factor, and taking the transmitting power distributed to the terminal by the base station and the phase angle of the intelligent reflecting surface as constraint conditions;
solving the multi-target problem by using a genetic algorithm, generating a plurality of pareto front solutions, and selecting the optimal time synchronization precision from the pareto front solutions; the multiple pareto front solutions include multiple time synchronization precisions
Optionally, the multi-objective problem is represented as follows:
in the above equation, χ represents the fairness factor,
representing steady state error covariance，pu(k)And representing the transmitting power distributed to the terminal by the base station, U representing a terminal set, and theta representing the phase angle of the intelligent reflecting surface.
In the second aspect of this application, still provide a device that improves industry thing networking terminal time synchronization precision, include:
the building module is used for building a wireless channel according to the position relation among the base station, the terminal and the intelligent reflecting surface;
the generating module is used for acquiring a line-of-sight path component, a non-line-of-sight path component and an intelligent reflecting surface phase angle of the wireless channel and generating an equivalent channel based on the line-of-sight path component, the non-line-of-sight path component and the intelligent reflecting surface phase angle of the wireless channel;
an obtaining module, configured to obtain a line-of-sight path component of the equivalent channel and a transmission power allocated to the terminal by the base station, and determine a reliability evaluation index of the wireless channel based on the transmission power and the equivalent channel;
the calculation module is used for acquiring timestamp information received by the terminal and the base station in a bidirectional information interaction process and determining a current clock synchronization state estimation value based on the timestamp information;
the generating module is used for inputting the estimated value of the current clock synchronization state and the reliability evaluation index of the wireless channel into a linear estimation model to generate an estimation error covariance of the current clock synchronization state;
the iteration module is used for iterating the estimation error covariance of the current clock synchronization state to generate a steady-state error covariance;
and the determining module is used for determining the optimal time synchronization precision based on the transmitting power distributed to the terminal by the base station, the steady-state error covariance and the intelligent reflecting surface phase angle.
In a third aspect of the present application, a computer device is also presented, comprising a processor and a memory, wherein the memory is used for storing a computer program, the computer program comprises a program, and the processor is configured to invoke the computer program to execute the method of the first aspect.
In a fourth aspect of the present application, an embodiment of the present invention provides a computer-readable storage medium, in which a computer program is stored, and the computer program is executed by a processor to implement the method of the first aspect.
The technical scheme of the invention has the following advantages:
1. according to the method for improving the time synchronization precision of the industrial Internet of things terminal, the estimation value of the current clock synchronization state and the reliability evaluation index of a wireless channel are calculated, the estimation value of the current clock synchronization state and the reliability evaluation index of the wireless channel are input into a linear estimation model, the estimation error covariance of the current clock synchronization state is generated, the estimation error covariance at different moments is converged, and the steady-state error covariance is generated. And the intelligent reflecting surface is introduced into the wireless communication environment, and the optimal time precision is determined based on the different phase angles of the intelligent reflecting surface, the transmitting power distributed to the terminal by the base station and the steady-state error covariance by acquiring the different phase angles of the intelligent reflecting surface, so that the information accessibility of the two-way timestamp between the base station and the terminal is improved by introducing the intelligent reflecting surface, the reliability of a wireless channel is ensured, and the time synchronization precision is further improved.
2. The multi-target problem is solved by adopting a genetic algorithm, a plurality of pareto leading edge solutions are generated, time synchronization precision fairness of each terminal is considered besides time synchronization precision is guaranteed, time precision maximization is pursued while fairness is considered, and different requirements of different industrial applications on time precision and fairness are met.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a method for improving time synchronization accuracy of an industrial internet of things terminal in embodiment 1 of the present invention;
fig. 2 is a schematic diagram of a wireless channel formed by an intelligent reflective surface, a base station and a terminal in embodiment 1 of the present invention;
FIG. 3 is a flowchart of step S103 in embodiment 1 of the present invention;
FIG. 4 is a flowchart of step S104 in embodiment 1 of the present invention;
fig. 5 is a schematic diagram of a multi-terminal time synchronization guaranteeing method in embodiment 1 of the present invention;
fig. 6 is a schematic diagram of a bidirectional timestamp packet switching mechanism in embodiment 1 of the present invention;
FIG. 7 is a flowchart of step S107 in embodiment 1 of the present invention;
fig. 8 is a schematic block diagram of a device for improving the time synchronization precision of an industrial internet of things terminal in embodiment 2 of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it is to be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplification of description, but do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Furthermore, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Example 1
The embodiment provides a method for improving the time synchronization precision of an industrial internet of things terminal, as shown in fig. 1, the method includes the following steps:
s101, a wireless channel is constructed according to the position relation among the base station, the terminal and the intelligent reflecting surface.
As shown in fig. 2, a downlink multi-input single-output system assisted by an Intelligent Reflecting Surface (IRS) is formed between the base station, the terminal and the intelligent reflecting surface, and includes a multi-antenna Base Station (BS), a multi-element intelligent reflecting surface and | U | single-antenna industrial terminals, where the set of terminals is denoted as U ═ { U (k) | k ═ 1, 2., | U | }. The base station has MbLine NbColumn root antenna, Intelligent Reflector (IRS) by MiLine NiThe antenna and the reflecting elements are in Uniform Rectangular Arrangement (URA), and each reflecting element can independently adjust the phase of the reflecting element and create a new line-of-sight path.
S102, a line-of-sight path component, a non-line-of-sight path component and an intelligent reflector phase angle of the wireless channel are obtained, and an equivalent channel is generated based on the line-of-sight path component, the non-line-of-sight path component and the intelligent reflector phase angle of the wireless channel.
The wireless channel between the base station and the terminal and the wireless channel between the intelligent reflecting surface and the terminal follow rice fading, u (k) is selected as the terminal, and a path between the base station and the intelligent reflecting surface is represented as HbiThe path between the base station and the terminal u (k) is denoted hbu(k)The path between the intelligent reflecting surface and the terminal u (k) is denoted as hiu(k)。
Further, assume that the wireless channel between the base station and the intelligent reflecting surface is represented as
Wherein the content of the first and second substances,
in the above formula, abiRepresenting the path loss between the base station and the intelligent reflecting surface,
representing a normalized line-of-sight path component between the base station and the intelligent reflecting surface.
Wherein the normalized line-of-sight path component between the base station and the intelligent reflecting surface
The calculation formula of (c) is as follows:
in the above-mentioned formula, the compound has the following structure,
representing the horizontal angle of arrival from the base station to the intelligent reflecting surface,
representing the vertical angle of arrival from the base station to the intelligent reflecting surface,
representing the horizontal departure angle from the base station to the intelligent reflective surface,
denotes the vertical departure angle from the base station to the intelligent reflecting surface, δ denotes the wavelength of the transmission signal, l denotes the distance between two adjacent elements in each row and each column of a uniform rectangular arrangement, S ∈ {1, 2.. multidot.s },. T ∈ {1, 2.. multidot.t }, and rvec (·) denotes the matrix row vectorization.
Further, the channel between the base station and the terminal u (k) is denoted as
Wherein, the first and the second end of the pipe are connected with each other,
in the above formula, abu(k)Representing the path loss between the base station and the terminal, Kbu(k)≥0，Kbu(k)Representing the rice factor in the radio channel between the base station and the terminal,
represents a normalized line-of-sight path component between the base station and the terminal,
representing a normalized non-line-of-sight path component between the base station and the terminal.
Wherein the normalized line-of-sight path component between the base station and the terminal
The calculation formula of (a) is as follows:
in the above-mentioned formula, the compound has the following structure,
representing the horizontal departure angle from the base station to terminal u (k),
indicating the vertical departure angle from the base station to terminal u (k).
Further, the wireless channel between the intelligent reflecting surface and the terminal u (k) is represented as
In the above formula, aiu(k)Indicating the path loss between the intelligent reflecting surface and the terminal, Kiu(k)≥0，Kiu(k)Representing the rice factor in the wireless channel between the intelligent reflecting surface and the terminal,
represents the normalized line-of-sight path component between the intelligent reflecting surface and the terminal u (k),
representing a normalized non-line-of-sight path component between the base station and the terminal.
Wherein the normalized line-of-sight path component between the intelligent reflecting surface and the terminal u (k)
The calculation formula of (a) is as follows:
in the above-mentioned formula, the compound has the following structure,
representing the exit angle in the horizontal plane from the intelligent reflecting surface to the terminal u (k),
indicating the exit angle in the vertical plane from the intelligent reflective surface to the terminal u (k).
Further, Kbu(k)And Kiu(k)Non-line-of-sight path components are not zero at the same time, and follow the CN (0, 1) distribution.
Further, the intelligent reflector phase angle can be expressed as:
wherein, thetam，nThe phase of the element in the m-th row and n-th column of the intelligent reflecting surface is shown.
The calculation formula of the equivalent channel is as follows:
hu(k)(Θ)＝hbu(k)+hiu(k)Φ(Θ)Hbi
wherein
diag (·) represents a diagonal matrix with only the main diagonal having elements.
Further, by introducing the intelligent reflective surface in the wireless environment, each terminal can accept signals from two paths, i.e. the base station-terminal path and the base station-intelligent reflective surface-terminal path, and then the total signal received at terminal u (k) is represented as:
in the above formula, pu(k)Denotes the transmit power assigned by the base station to the terminal u (k),
representing the beamforming vector, su(k)CN (0, 1) represents a signal of the terminal u (k), nu(k)CN (0, 1) represents terminal noise.
S103, acquiring the transmitting power distributed to the terminal by the base station and the line-of-sight path component of the equivalent channel, and determining the reliability evaluation index of the wireless channel based on the transmitting power and the line-of-sight path component of the equivalent channel.
S104, obtaining timestamp information received by the terminal and the base station in the bidirectional information interaction process, and determining the current clock synchronization state estimated value based on the timestamp information.
And S105, inputting the estimated value of the current clock synchronization state and the reliability evaluation index of the wireless channel into a linear estimation model, and generating the estimation error covariance of the current clock synchronization state.
Specifically, the linear estimation model adopts improved Kalman filtering, and P is generated by utilizing the improved Kalman filteringqThe recurrence formula of (c) is as follows:
in the above formula, Pq|q-1＝APq-1AT+Q，Pq|q-1Representing the state estimation error variance P corresponding to the node at the previous time due to the unreliable state of the channelqWith randomness, packet loss also occurs randomly.
And S106, iterating the estimation error covariance of the current clock synchronization state to generate a steady-state error covariance.
The method comprises the following steps of generating a state estimation error covariance based on a current clock synchronization state estimation value, generating an error covariance of Kalman filtering in a steady state through multiple iterations, wherein a calculation formula of the steady state error covariance is as follows:
wherein, the first and the second end of the pipe are connected with each other,
the matrix A is an identity matrix, E [ w ]qwq T]Q denotes a Gaussian distribution, KkalRepresenting the kalman gain.
S105, obtaining the phase angle of the intelligent reflecting surface, and determining the optimal time synchronization precision based on the transmitting power distributed to the terminal by the base station, the steady-state error covariance and the phase angle of the intelligent reflecting surface.
According to the method for improving the time synchronization precision of the industrial Internet of things terminal, the error covariance of the current clock synchronization state is generated by calculating the reliability evaluation index of the current clock synchronization state estimation value and the wireless channel and inputting the current clock synchronization state estimation value and the reliability evaluation index of the wireless channel into the linear estimation model, and the steady-state error covariance is obtained by iterative solution of a plurality of time error covariances. And the intelligent reflecting surface is introduced into a wireless communication environment, the reliability of a wireless channel and the steady-state error covariance are obtained through obtaining different phase angles of the intelligent reflecting surface and the transmitting power distributed to the terminal by the base station, and the optimal time precision is determined.
Preferably, as shown in fig. 3, the determining the reliability evaluation index of the wireless channel based on the transmission power and the equivalent channel in step S103 includes:
and S1031, calculating a beam forming vector based on the line-of-sight path component of the equivalent channel, and generating an effective channel based on the equivalent channel and the beam forming vector.
Wherein, in order to enhance the signal received at the user, the maximum ratio transmission is adopted at the base station, based on the equivalent channel hu(k)(Θ) line-of-sight path component
Is known to the user of the wireless communication device,
the calculation formula of (c) is as follows:
further, the calculation formula of the beamforming vector based on maximum ratio transmission is as follows:
further, the effective channel is represented as:
wherein the content of the first and second substances,
to represent
The conjugate transpose matrix of (a) is,
represents omegau(k)The conjugate transpose matrix of (2).
Further, the signal-to-noise ratio of the terminal is calculated based on the effective channel and the transmission power allocated to the terminal by the base station, and the calculation formula is as follows:
in the above formula, σ2Is gaussian white noise received by the terminal.
S1032, acquiring a terminal signal-to-noise ratio threshold value, and calculating a reliability evaluation index based on the effective channel, the transmission power distributed to the terminal by the base station and the terminal signal-to-noise ratio threshold value.
Wherein, the calculation formula of the reliability evaluation index is as follows:
in the above formula, gu(k)(Θ) represents an effective channel,
representing the threshold value, σ, of the signal-to-noise ratio of the terminal2Representing Gaussian white noise, pu(k)Represents the transmit power allocated by the base station to the terminal.
Further, the interruption probability is selected as the channel reliability evaluation index, that is, the probability distribution of the loss variable value is reflected by the probability that the signal-to-noise ratio of the terminal is greater than a threshold value, and is expressed as etaq～(1，pc) Packet reachability pcCan be expressed as:
wherein, the first and the second end of the pipe are connected with each other,
signal-to-noise ratio (minimum) threshold value for terminal u (k), packet reachability rate pcIt may also represent the probability of non-interruption, pcIs equal to the terminal signal-to-noise ratio of the terminal u (k) is greater than the threshold value
The probability value of (a) is determined,
wherein the content of the first and second substances,
further, solve for pcIs equivalent to solving for variable | gu(k)(Θ)|2A probability density function and a cumulative distribution function of (2), wherein the probability density function fg＝Pr{|gu(k)(Θ)|2＝Ψ(pu(k)) And cumulative distribution function
The probability of (d) can be expressed as:
wherein the cumulative distribution function Fg＝Pr{|gu(k)(Θ)|2＜Ψ(pu(k)) The probability of the channel is a probability of interruption, and the probability of interruption is used as a channel reliability evaluation index.
Preferably, as shown in fig. 4 to 5, the acquiring, in step S104, timestamp information received by the terminal and the base station in a bidirectional information interaction process, and determining an estimated value of a current clock synchronization state based on the timestamp information includes:
s1041, acquiring a random time delay, a fixed time delay and a clock offset of the wireless channel, and constructing a time synchronization measurement equation based on the timestamp information, the clock frequency deviation, the random time delay of the wireless channel, the fixed time delay and the clock offset.
As shown in fig. 6, in a wireless communication environment formed by a base station, an intelligent reflector and an industrial time service terminal, where alignment of a terminal clock to a base station reference clock is completed between the base station and the terminal through a bidirectional timestamp packet exchange mechanism, it is assumed that in a clock synchronization process, the base station and the terminal u (k) complete N times of positioning information exchange, and in a q-th time information exchange period, the terminal u (k) is at T1，qTransmitting the time containing T to the base station1，qThe synchronization packet of (2); base station at T2，qThe synchronization packet is received at time T3，qSending a reply packet back at any time, wherein the reply packet comprises T2，qTime and T3，qTime of day; finally the terminal u (k) is at T4，qReceiving a reply information packet from the base station all the time, and finishing the information exchange process of the q-th cycle; four time information generated in the process, wherein T1，qAnd T4，qIs the local clock information, T, of terminal u (k)2，qAnd T3，qIs the local clock information of the base station, after N times of positioning information exchange, the terminal u (k) will receive a series of time stamps, which are recorded as
Further, based on the timestamp information, a time synchronization measurement equation is constructed as follows:
T2，q＝f(T1，q+τ+Xq)+θ
T3，q＝f(T4，q-τ-Yq)+θ
in the above formula, Xq，YqRepresenting random time delays due to the randomness of the radio channel, τ represents a fixed time delay between two synchronization nodes, assuming that the uplink and downlink are symmetric and the distance between the terminal u (k) and the base station is constant, therefore the fixed delay τ can be considered as a fixed variable in a round of time stamp exchange and assuming that the clock frequency deviation f is known and does not change during a round of time stamp exchange, θ represents the clock offset between two time synchronization nodes.
S1042, solving the time synchronization measurement equation, and generating the clock synchronization state actual value and the error measurement noise.
Wherein, the local clock information T of the base station is used2，qAnd T3，qThe following formula is obtained by sorting:
wherein the time-synchronized measurement equation is generated based on the equation:
yq＝Dxq+vq
wherein the content of the first and second substances,
representing the current clock synchronization state estimate,
represents the actual value of the clock synchronization state between the synchronization node (terminal u (k)) and the reference node (base station),
representing random delays subject to an independent, identically distributed gaussian distribution, also called error measurement noise, E v assuming its mean value is zeroqvq T]＝R。
Further, after exchanging the time stamp information between the two synchronization nodes,
the measurement information representing the clock synchronization state x may also be written as y1，y2，...，yN}; because variable time delay exists between nodes, a certain error exists between a measurement result and a true value, the measurement result cannot accurately reflect fixed time delay and relative clock offset information, and the error measurement noise is represented as vq。
And S1043, calculating the clock synchronization measured value based on the clock synchronization state actual value, the error measurement noise and the clock frequency deviation.
Since the clock synchronization state between the base station and the terminal u (k) changes slowly and the current state is linearly related to the previous time state, the estimated value of the clock synchronization state transition measurement can also be expressed as:
xq＝Axq-1+wq-1
in the above formula, the matrix A is a unit matrix, wq-1Is indicative of the noise of the system and,
further, the actual value of the clock synchronization state may be modeled as a mean of zero and a covariance matrix of E [ w ]qwq T]Gaussian distribution of Q.
Further, in the wireless transmission network, due to the influence of the random variable of the wireless channel fading, the transmission of the link is no longer reliable, that is, in the process of bidirectional information exchange of clock synchronization, neither the clock information sent by the base station to the terminal u (k) nor the clock information of the reply base station of the terminal u (k) can be guaranteed to arrive certainly, therefore, the time synchronization measurement equation is considered to be corrected so as to be matched with the modeling of the time synchronization mechanism in the wireless network transmission scene, and the corrected time synchronization measurement equation is as follows:
yq＝ηq(Dxq+vq)
in the above formula, yqRepresenting a measure of clock synchronisation, ηqRepresenting a binary Bernoulli random variable, D representing a clock frequency deviation, xqRepresenting the actual value of the clock synchronization state, vqRepresenting error measurement noise, whenqWhen the value is 1, indicating that the target node receives the clock synchronization information of the source node; when etaqWhen the value is 0, it indicates that the clock synchronization information is lost during transmission, that is, the clock synchronization process in which the observation value is lost.
S1044, acquiring a clock synchronization state estimation value of a previous time node, and generating a current clock synchronization state estimation value based on the clock synchronization measurement value and the clock synchronization state estimation value of the previous time node.
Specifically, the synchronization state property of the synchronization node is defined as:
therein, the watch
The estimation of the clock synchronization state based on the received measurement message, i.e. the estimated value of the clock synchronization state, is shown.
Further, a state estimation error covariance is calculated based on the current clock synchronization state estimation value, and the expression is as follows:
in the above formula, the matrix PqRepresenting state estimation error covariance, wherein the state estimation value is synchronized with the clock
Closer to the actual value x of the clock synchronization stateqThe smaller the estimated error value of the clock state, and therefore, the state estimation error variance PqThe clock synchronization accuracy can be reflected.
Further, a current clock synchronization state estimated value is generated based on the clock synchronization measured value and the clock synchronization state estimated value of the previous time node, and a calculation formula is as follows:
in the above formula, the first and second carbon atoms are,
representing the current clock synchronization state estimate, a representing an identity matrix,
an estimate of the clock synchronisation state, η, representing the last time nodeqRepresenting binary Bernoulli random variable, yqA measurement value representing the synchronization of the clocks,
minimum threshold value, K, representing the signal-to-noise ratio of the terminalkalRepresents the Kalman gain, wherein the Kalman gain KkalThe calculation formula of (c) is as follows:
Kkal＝Pq|q-1DT(DPq|q-1DT+R)-1
further, the calculation formula of the estimated value of the state transition at the current time obtained based on the estimated value of the clock synchronization state at the previous time node is as follows:
further, a clock synchronization error is calculated based on the actual value of the clock synchronization state and the estimated value of the current clock synchronization state, and the calculation formula is as follows:
in this embodiment, the timestamp packet has a certain loss probability when transmitted in an unreliable wireless environment due to unpredictable noise interference and non-line-of-sight path components of the channel. The terminal u (k) estimates the base station clock parameters based on the received timestamp information, and the more the received timestamps are, the more accurate the estimation is, and the smaller the estimation error is, that is, the synchronization precision is reduced along with the loss of the timestamp information, so that an intelligent reflecting surface is introduced into a wireless downlink transmission environment, a new line-of-sight path is added, the wireless transmission environment is improved, and the channel reliability is improved.
Preferably, as shown in fig. 7, the determining the optimal time synchronization accuracy based on the transmission power allocated to the terminal by the base station, the steady-state error covariance, and the intelligent reflecting surface phase angle in step S107 includes:
s1071, constructing a multi-target problem according to the steady-state error covariance and the fairness factor, and taking the transmitting power distributed to the terminal by the base station and the phase angle of the intelligent reflecting surface as constraint conditions.
Wherein the multi-objective problem is represented as follows:
in the above equation, χ represents the fairness factor,
representing the steady state error covariance, Pu(k)And representing the transmitting power distributed to the terminal by the base station, U representing a terminal set, and theta representing the phase angle of the intelligent reflecting surface.
Wherein, the first and the second end of the pipe are connected with each other,
further, the constraint conditions include:
(1) the constraint of the transmission power allocated to the terminal by the base station (the sum of the transmission power allocated to all terminals does not exceed the maximum transmission power available by the base station) is expressed as follows:
in the above formula, pmaxRepresenting the maximum transmit power that the base station can provide.
(2) And the phase angle of the intelligent reflecting surface is constrained according to the following expression:
|θm，n|＝1，m＝1，2，...，Mi，n＝1，2，...，Ni
s1072, solving the multi-target problem by using a genetic algorithm, generating a plurality of pareto front solutions, and selecting the optimal time synchronization precision from the pareto front solutions; the plurality of pareto front solutions includes a plurality of time synchronization precisions.
Specifically, a constructed multi-target problem is solved by adopting a non-dominated sorting genetic algorithm NSGA-II, a series of pareto leading-edge solutions are obtained through solving, and in practical application, an optimal solution can be reasonably selected according to different industrial application requirements; in NSGA-II, a certain number of candidate solutions can be abstracted into chromosomes, so that the population evolves towards a better direction, the evolution starts from a group of random individuals, and the cross variation is performed one generation after another, and finally, suitable individuals are obtained; the NSGA-II algorithm comprises coding, population initialization, objective function evaluation, non-dominant sorting, selection, crossing, variation, population iteration and the like.
Further, in NSGA-II, the chromosome represents the result of the intelligent reflecting surface phase and the transmission power distribution; assuming that the phase and the transmit power of the intelligent reflective surface are both discrete, X and Y are defined as the number of selectable values of transmit power and intelligent reflective surface phase shift, respectively. Therefore, front log2X bits represent the transmit power allocated to the first terminal, and there is a total of | U |. log2X bits to represent a power allocation scheme; miNi·log2Y bit represents MiColumn NiOptimization of the phase of the rows of intelligent reflective surface elements, where each log2The Y bits are a set representing the phase state of a reflective element, and thus, the size of each chromosome is represented by | U |. log2 X+MiNi·log2Y bit.
Further, the pareto leading edge solutions also include fairness indexes, the pareto leading edge solutions are represented in a distribution graph, time synchronization accuracy and the fairness indexes are mutually exclusive data, when time synchronization accuracy is required to be the highest, the fairness index is the lowest, and otherwise, when the fairness index is required to be the highest, the time synchronization accuracy is the lowest.
In this embodiment, the base station transmission power and the phase angle of the intelligent reflection surface may affect the reliability of the wireless channel, that is, the reachable rate p of the timestamp information packet at the terminal side is affectedcFurther changing the steady state error covariance of the current time synchronization state of the terminal in the Kalman filtering steady state
The time synchronization precision of wireless time service is maximized by jointly optimizing the transmitting power of the base station and the phase of the intelligent reflecting surface, namely the time service error covariance is minimized, the fairness of the precision of each terminal of the system is considered, and the performance indexes of all the terminals in the system are ensured.
Example 2
This embodiment provides a device for improving industry thing networking terminal time synchronization precision, as shown in fig. 8, includes:
and the building module 81 is configured to build a wireless channel according to the position relationship among the base station, the terminal, and the intelligent reflecting surface.
The system comprises a Base Station (BS), a multi-element intelligent reflecting surface and | U | single-antenna industrial terminals, wherein a downlink multi-input single-output system assisted by the Intelligent Reflecting Surface (IRS) is formed among the base station, the terminals and the intelligent reflecting surface, and the terminal set is expressed as U ═ { U (k) | k ═ 1, 2., | U | }. The base station has MbLine NbRow root antenna, Intelligent Reflector (IRS) by MiLine NiThe antenna and the reflecting elements are in Uniform Rectangular Arrangement (URA), and each reflecting element can independently adjust the phase of the reflecting element and create a new line-of-sight path.
The generating module 82 obtains a line-of-sight path component, a non-line-of-sight path component, and an intelligent reflector phase angle of the wireless channel, and generates an equivalent channel based on the line-of-sight path component, the non-line-of-sight path component, and the intelligent reflector phase angle of the wireless channel.
The wireless channel between the base station and the terminal and the wireless channel between the intelligent reflecting surface and the terminal follow rice fading, u (k) is selected as the terminal, and a path between the base station and the intelligent reflecting surface is represented as HbiThe path between the base station and the terminal u (k) is denoted hbu(k)The path between the intelligent reflecting surface and the terminal u (k) is denoted as hiu(k)。
Further, assume that the wireless channel between the base station and the intelligent reflecting surface is represented as
Wherein the content of the first and second substances,
the upper typeIn (a)biRepresenting the path loss between the base station and the intelligent reflecting surface,
representing a normalized line-of-sight path component between the base station and the intelligent reflecting surface.
Wherein the normalized line-of-sight path component between the base station and the intelligent reflecting surface
The calculation formula of (c) is as follows:
in the above formula, the first and second carbon atoms are,
representing the horizontal angle of arrival from the base station to the intelligent reflecting surface,
representing the vertical angle of arrival from the base station to the intelligent reflecting surface,
representing the horizontal departure angle from the base station to the intelligent reflective surface,
denotes the vertical departure angle from the base station to the intelligent reflecting surface, δ denotes the wavelength of the transmission signal, l denotes the distance between two adjacent elements in each row and each column of a uniform rectangular arrangement, S ∈ {1, 2.. multidot.s },. T ∈ {1, 2.. multidot.t }, and rvec (·) denotes the matrix row vectorization.
Further, the channel between the base station and the terminal u (k) is denoted as
Wherein, the first and the second end of the pipe are connected with each other,
in the above formula, abu(k)Representing the path loss between the base station and the terminal, Kbu(k)≥0，Kbu(k)Indicating the rice factor in the radio channel between the base station and the terminal,
represents a normalized line-of-sight path component between the base station and the terminal,
representing a normalized non-line-of-sight path component between the base station and the terminal.
Wherein the normalized line-of-sight path component between the base station and the terminal
The formula (c) is as follows:
in the above formula, the first and second carbon atoms are,
representing the horizontal departure angle from the base station to terminal u (k),
indicating the vertical departure angle from the base station to terminal u (k).
Further, the wireless channel between the intelligent reflecting surface and the terminal u (k) is represented as
In the above formula, the first and second carbon atoms are,aiu(k)indicating the path loss between the intelligent reflecting surface and the terminal, Kiu(k)≥0，Kiu(k)Representing the rice factor in the wireless channel between the intelligent reflecting surface and the terminal,
represents the normalized line-of-sight path component between the intelligent reflecting surface and the terminal u (k),
representing a normalized non-line-of-sight path component between the base station and the terminal.
Wherein the normalized line-of-sight path component between the intelligent reflecting surface and the terminal u (k)
The calculation formula of (a) is as follows:
in the above-mentioned formula, the compound has the following structure,
indicating the exit angle in the horizontal plane from the intelligent reflective surface to the terminal u (k),
indicating the exit angle in the vertical plane from the intelligent reflective surface to the terminal u (k).
Further, Kbu(k)And Kiu(k)Not simultaneously zero, the non-line-of-sight path components follow the CN (0, 1) distribution.
Further, the intelligent reflector phase angle can be expressed as:
wherein, thetam，nPhase for representing m row and n column elements of intelligent reflecting surfaceA bit.
The calculation formula of the equivalent channel is as follows:
hu(k)(Θ)＝hbu(k)+hiu(k)Φ(Θ)Hbi
wherein
diag (·) represents a diagonal matrix with only the principal diagonals having elements.
Further, by introducing the intelligent reflective surface in the wireless environment, each terminal can accept signals from two paths, i.e. the base station-terminal path and the base station-intelligent reflective surface-terminal path, and then the total signal received at terminal u (k) is represented as:
in the above formula, pu(k)Denotes the transmit power assigned by the base station to the terminal u (k),
representing a beamforming vector, su(k)CN (0, 1) represents a signal of terminal u (k), nu(k)CN (0, 1) represents terminal noise.
An obtaining module 83, configured to obtain the transmit power allocated to the terminal by the base station and the line-of-sight path component of the equivalent channel, and determine the reliability evaluation index of the wireless channel based on the transmit power and the line-of-sight path component of the equivalent channel.
And a calculating module 84, configured to obtain timestamp information received by the terminal and the base station in a bidirectional information interaction process, and determine an estimated value of a current clock synchronization state based on the timestamp information.
And the generating module 85 is configured to input the current clock synchronization state estimation value and the reliability evaluation index of the wireless channel into a linear estimation model, and generate an estimation error covariance of the current clock synchronization state.
In particularThe linear estimation model adopts improved Kalman filtering, and P is generated by utilizing the improved Kalman filteringqThe recurrence formula of (c) is as follows:
in the above formula, Pq|q-1＝APq-1AT+Q，Pq|q-1Representing the state estimation error variance P corresponding to the previous time node due to the unreliable state of the channelqWith randomness, packet loss also occurs randomly.
An iteration module 86, configured to iterate the estimated error covariance of the current clock synchronization state to generate a steady-state error covariance;
the method comprises the following steps of generating a state estimation error covariance based on a current clock synchronization state estimation value, generating an error covariance of Kalman filtering in a steady state through multiple iterations, wherein a calculation formula of the steady state error covariance is as follows:
wherein λ ═ E [ η [ ]q]＝pc(pu(k)，Θ)，
The matrix A is an identity matrix, E [ w ]qwq T]Q denotes a Gaussian distribution, KkalRepresenting the kalman gain.
A determining module 87, configured to determine the time synchronization accuracy based on the transmission power allocated to the terminal by the base station, the steady-state error covariance, and the intelligent reflecting surface phase angle.
According to the device for improving the time synchronization precision of the industrial Internet of things terminal, the estimation value of the current clock synchronization state and the reliability evaluation index of the wireless channel are calculated, the estimation value of the current clock synchronization state and the reliability evaluation index of the wireless channel are input into the linear estimation model, the estimation error covariance of the current clock synchronization state is generated, the estimation error covariance at different moments is converged, and the steady-state error covariance is generated. And the intelligent reflecting surface is introduced into the wireless communication environment, and the optimal time precision is determined based on the different phase angles of the intelligent reflecting surface, the transmitting power distributed to the terminal by the base station and the steady-state error covariance by acquiring the different phase angles of the intelligent reflecting surface, so that the information accessibility of the two-way timestamp between the base station and the terminal is improved by introducing the intelligent reflecting surface, the reliability of a wireless channel is ensured, and the time synchronization precision is further improved.
Example 3
The embodiment provides a computer device, which comprises a memory and a processor, wherein the processor is used for reading an instruction stored in the memory, and the instruction can execute a method for improving the time synchronization precision of the industrial internet of things terminal in any method embodiment.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Example 4
The embodiment provides a computer-readable storage medium, which stores computer-executable instructions, where the computer-executable instructions may execute a method for improving time synchronization accuracy of an industrial internet of things terminal in any of the above method embodiments. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (10)
1. A method for improving the time synchronization precision of an industrial Internet of things terminal is characterized by comprising the following steps:
constructing a wireless channel according to the position relationship among the base station, the terminal and the intelligent reflecting surface;
acquiring a line-of-sight path component, a non-line-of-sight path component and an intelligent reflecting surface phase angle of the wireless channel, and generating an equivalent channel based on the line-of-sight path component, the non-line-of-sight path component and the intelligent reflecting surface phase angle of the wireless channel;
acquiring the transmitting power distributed to the terminal by the base station and the line-of-sight path component of the equivalent channel, and determining the reliability evaluation index of the wireless channel based on the transmitting power and the line-of-sight path component of the equivalent channel;
acquiring timestamp information received by the terminal and the base station in a bidirectional information interaction process, and determining a current clock synchronization state estimation value based on the timestamp information;
inputting the estimated value of the current clock synchronization state and the reliability evaluation index of the wireless channel into a linear estimation model to generate an estimation error covariance of the current clock synchronization state;
iteration is carried out on the estimation error covariance of the current clock synchronization state, and a steady-state error covariance is generated;
and determining the optimal time synchronization precision based on the transmitting power distributed to the terminal by the base station, the steady-state error covariance and the intelligent reflecting surface phase angle.
2. The method for improving the time synchronization accuracy of the industrial internet of things terminal according to claim 1, wherein the determining the reliability evaluation index of the wireless channel based on the transmission power and the line-of-sight path component of the equivalent channel comprises:
calculating a beam forming vector based on the line-of-sight path component of the equivalent channel, and generating an effective channel based on the equivalent channel and the beam forming vector;
and acquiring a signal-to-noise ratio threshold value of the terminal, and calculating a reliability evaluation index based on the effective channel, the transmission power distributed to the terminal by the base station and the signal-to-noise ratio threshold value of the terminal.
3. The method for improving the time synchronization precision of the industrial internet of things terminal according to claim 2, wherein the reliability evaluation index is calculated according to the following formula:
in the above formula, gu(k)(Θ) represents an effective channel,
indicating the threshold value, sigma, of the signal-to-noise ratio of the terminal2Representing white Gaussian noise, pu(k)Represents the transmit power allocated to the terminal by the base station.
4. The method for improving the time synchronization accuracy of the industrial internet of things terminal according to claim 1, wherein the determining the current clock synchronization state estimation value based on the timestamp information comprises:
acquiring random time delay, fixed time delay and clock offset of the wireless channel, and constructing a time synchronization measurement equation based on the timestamp information, the clock frequency deviation, the random time delay of the wireless channel, the fixed time delay and the clock offset;
solving the time synchronization measurement equation to generate the actual value of the clock synchronization state and the error measurement noise;
calculating the clock synchronization measurement value based on the clock synchronization state actual value, the error measurement noise and the clock frequency deviation;
and acquiring a clock synchronization state estimation value of a last time node, and generating a current clock synchronization state estimation value based on the clock synchronization measurement value and the clock synchronization state estimation value of the last time node.
5. The method for improving the time synchronization accuracy of the terminals of the industrial internet of things as claimed in claim 4, wherein in the calculating the clock synchronization measurement value based on the actual value of the clock synchronization state, the error measurement noise and the clock frequency deviation, the calculation formula of the clock synchronization measurement value is as follows:
yq＝ηq(Dxq+vq)
in the above formula, yqRepresenting clock-synchronous measurements, etaqRepresenting a binary Bernoulli random variable, D representing a clock frequency deviation, xqRepresenting the actual value of the clock synchronization state, vqRepresenting error measurement noise.
6. The method for improving the time synchronization accuracy of the industrial internet of things terminal according to claim 1, wherein the determining the optimal time synchronization accuracy based on the transmission power allocated to the terminal by the base station, the steady-state error covariance and the intelligent reflecting surface phase angle comprises:
constructing a multi-target problem according to the transmitting power distributed to the terminal by the base station, the steady-state error covariance and a fairness factor, and taking the transmitting power distributed to the terminal by the base station and the phase angle of the intelligent reflecting surface as constraint conditions;
solving the multi-target problem by using a genetic algorithm, generating a plurality of pareto leading edge solutions, and selecting the optimal time synchronization precision from the pareto leading edge solutions; the plurality of pareto front solutions includes a plurality of time synchronization precisions.
7. The method for improving the time synchronization accuracy of the industrial internet of things terminal according to claim 6, wherein the multi-objective problem is expressed as follows:
in the above equation, χ represents the fairness factor,
representing the steady state error covariance, pu(k)And representing the transmitting power distributed to the terminal by the base station, U representing a terminal set, and theta representing the phase angle of the intelligent reflecting surface.
8. The utility model provides an improve device of industry thing networking terminal time synchronization precision which characterized in that includes:
the building module is used for building a wireless channel according to the position relationship among the base station, the terminal and the intelligent reflecting surface;
the generating module is used for acquiring a line-of-sight path component, a non-line-of-sight path component and an intelligent reflecting surface phase angle of the wireless channel and generating an equivalent channel based on the line-of-sight path component, the non-line-of-sight path component and the intelligent reflecting surface phase angle of the wireless channel;
an obtaining module, configured to obtain a transmit power allocated to the terminal by the base station and a line-of-sight path component of the equivalent channel, and determine a reliability evaluation index of the wireless channel based on the transmit power and the equivalent channel;
the calculation module is used for acquiring timestamp information received by the terminal and the base station in the bidirectional information interaction process and determining the estimated value of the current clock synchronization state based on the timestamp information;
the generating module is used for inputting the estimated value of the current clock synchronization state and the reliability evaluation index of the wireless channel into a linear estimation model to generate an estimation error covariance of the current clock synchronization state;
the iteration module is used for iterating the estimation error covariance of the current clock synchronization state to generate a steady-state error covariance;
and the determining module is used for determining the optimal time synchronization precision based on the transmitting power distributed to the terminal by the base station, the steady-state error covariance and the intelligent reflecting surface phase angle.
9. A computer device comprising a processor and a memory, wherein the memory is configured to store a computer program and the processor is configured to invoke the computer program to perform the steps of the method of any of claims 1-7.
10. A computer-readable storage medium having stored thereon computer instructions, which, when executed by a processor, carry out the steps of the method according to any one of claims 1-7.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015049478A1 (en) * | 2013-10-01 | 2015-04-09 | Khalifa University of Science, Technology, and Research | Method and devices for synchronization |
| CN110174104A (en) * | 2019-05-30 | 2019-08-27 | 北京邮电大学 | A kind of Combinated navigation method, device, electronic equipment and readable storage medium storing program for executing |
| CN113133014A (en) * | 2021-03-23 | 2021-07-16 | 清华大学 | Generalized electromagnetic wave orbital angular momentum transmission system based on intelligent reflecting surface |
| CN113225276A (en) * | 2021-05-08 | 2021-08-06 | 东南大学 | Semi-blind channel estimation method for intelligent reflector-oriented auxiliary communication system |
| CN114071485A (en) * | 2021-11-15 | 2022-02-18 | 重庆邮电大学 | Intelligent reflecting surface safe communication energy efficiency optimization method based on imperfect channel |
| CN114124264A (en) * | 2021-11-26 | 2022-03-01 | 江苏科技大学 | Unmanned aerial vehicle channel model building method based on variable reflection phase at intelligent reflection surface |
-
2022
- 2022-03-30 CN CN202210333636.2A patent/CN114785439B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015049478A1 (en) * | 2013-10-01 | 2015-04-09 | Khalifa University of Science, Technology, and Research | Method and devices for synchronization |
| CN110174104A (en) * | 2019-05-30 | 2019-08-27 | 北京邮电大学 | A kind of Combinated navigation method, device, electronic equipment and readable storage medium storing program for executing |
| CN113133014A (en) * | 2021-03-23 | 2021-07-16 | 清华大学 | Generalized electromagnetic wave orbital angular momentum transmission system based on intelligent reflecting surface |
| CN113225276A (en) * | 2021-05-08 | 2021-08-06 | 东南大学 | Semi-blind channel estimation method for intelligent reflector-oriented auxiliary communication system |
| CN114071485A (en) * | 2021-11-15 | 2022-02-18 | 重庆邮电大学 | Intelligent reflecting surface safe communication energy efficiency optimization method based on imperfect channel |
| CN114124264A (en) * | 2021-11-26 | 2022-03-01 | 江苏科技大学 | Unmanned aerial vehicle channel model building method based on variable reflection phase at intelligent reflection surface |
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