CN117675460B - Anti-interference method, equipment and storage medium of wireless communication system - Google Patents
Anti-interference method, equipment and storage medium of wireless communication system Download PDFInfo
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Abstract
The application discloses an anti-interference method, equipment and a storage medium of a wireless communication system, which determine a target coding mode based on a target transmission rate; determining a target communication channel based on the interference power of each channel; constructing an optimization model based on nonlinear generalized control in a continuous time domain; constructing a sliding mode interference observer to estimate the system state and the interference state to obtain a control error estimated value and a total interference estimated value; calculating a control error estimated value and a lumped interference estimated value to obtain a control error predicted value, a control input predicted value and a target input predicted value; and carrying out weighted combination on the control error predicted value, the control input predicted value and the target input predicted value to obtain a target control law. The anti-interference method of the wireless communication system provided by the application can quickly converge without pre-predicting or sensing the characteristics of unknown interference, and reduce the influence of the unknown interference, so that the wireless communication system can stably communicate.
Description
Technical Field
The present application relates to the field of wireless communication technologies, and in particular, to an anti-interference method, apparatus, and storage medium for a wireless communication system.
Background
In recent 20 years, wireless communication technologies such as software radio and cognitive radio are developed rapidly, so that a wireless communication system gradually has the capability of sensing electromagnetic environment and adjusting communication parameters such as self-transmitting power and communication frequency according to requirements, and the capability of adapting to complex severe interference environments of the wireless communication system is greatly enhanced. However, the interference patterns are various, and new interference layers are endless. Wireless communication systems may be subject to unknown interference that has never been encountered, making it difficult to maintain reliability of communication information transmissions.
The unknown interference experienced by a wireless communication system is generally characterized as follows: the characteristics of unknown disturbances are often difficult to predict in advance or perceive in real time; the time-varying speed of unknown interference tends to be much faster than the wireless communication system parameter adjustment speed; unknown interference is bounded towards general energy or power, and is piecewise continuous in the time domain; wireless communication systems often face different unknown interferences from multiple sources.
The prior wireless communication system anti-interference is mostly based on machine learning technologies such as reinforcement learning, deep learning and the like, when the system is interfered, a model obtained by training or learning is based on the characteristics of interference, system parameters of the communication system are determined, and then the adjustment is carried out based on the system parameters. The model needs to be iterated and trained in the early stage. Since the model is required to iterate or train based on the interference experienced, the sensing and adaptation speed for the unknown interference is slower when the communication system is experiencing the unknown interference. Thus, it is difficult for a communication system to maintain stable communication under unknown interference with unknown characteristics, rapid changes, and multiple sources. The reliability and validity of the communication cannot be guaranteed in the case of unknown interference.
Disclosure of Invention
In view of the above, the present application provides an anti-interference method for a wireless communication system, which is used for solving the problem that the communication system is difficult to maintain stable communication when unknown interference is received.
In order to achieve the above object, the following schemes are proposed:
An anti-interference method of a wireless communication system, comprising:
Acquiring a target transmission rate of a wireless communication system and interference power of each channel;
determining a target coding mode based on the target transmission rate;
Determining a target communication channel based on the interference power of each channel;
constructing an optimization model of the wireless communication system based on continuous time domain nonlinear generalized control;
the sliding mode interference observer estimates the system state of the wireless communication system and the interference state of unknown interference to obtain a control error estimated value and a total interference estimated value;
Calculating the control error estimated value and the lumped interference estimated value to obtain a control error predicted value, a control input predicted value and a target input predicted value;
Substituting the control error predicted value, the control input predicted value and the target input predicted value into the optimization model for weighted combination to obtain a target control law.
Preferably, the constructing an optimization model of the wireless communication system based on continuous time domain nonlinear generalized control includes:
modeling a state equation of the wireless communication system according to the linear relation between the signal-to-interference-plus-noise ratio of each channel and the error rate of each channel to obtain the state equation:
Wherein x n (t) is a system state variable of an nth channel of the wireless communication system at a time t, y n,BER (t) is a time t, error rates of the nth channel of the wireless communication system, C i and D i are constants in an ith modulation coding mode, u 1(t)＝up(t)-PJn(t)(5),uP (t) is a transmission power control output, and P Jn (t) is interference plus noise power in a passband of the nth channel;
Constructing a control error equation: e (t) =y r,BER(t)-yn,BER(t),ei(t)＝e(i)(t),i∈N(9),yr,BER (t) is the target error rate, e (t) is the control error, e (i) (t) is the i-th derivative of e (t);
Constructing a lumped interference equation set:
Where w (t) is the lumped interference of the unknown interference and the uncertainty of the wireless communication system, b (t) is the control gain, bmin < b (t) < bmax, bmin and bmax are positive constants, b 0 is the nominal value of b (t), Is the n 1 th order derivative of the bit error rate,As the first derivative of the bit error rate y n,BER (t),N 1 derivative of the target bit error rate y r,BER (t) and is calculated byA representation;
Based on continuous time domain nonlinear generalized control, constructing an optimization model of the wireless communication system:
wherein T >0 is the control period, Q >0 is the weight of the control error, R >0 is the weight of the control input, and u r,P (T) is the steady-state control output.
Preferably, the sliding mode interference observer estimates a system state and an interference state to obtain a control error estimated value and a total interference estimated value, and includes:
The sliding mode interference observer is represented by the formula:
estimating the error to obtain a control error estimated value, AndEstimates of the derivatives of the n 1 -1 and i orders of e (t), respectively,For an estimate of wn 1 (t) at n 1 =0,For the estimated value of the i+1 derivative of e (t), u 1 * (t) is the target control law, v i (t) is the sliding mode interference observer gain;
Assuming that there are known constants L.gtoreq.0 and m.epsilon.N + such that |w (m) (t) |.ltoreq.L, the sliding mode disturbance observer passes the formula:
estimating to obtain a lumped interference estimated value, wherein, AndRespectively lumped interferenceAn estimated value at n 1 =j and n 1 =m-1,Is thatEstimate at n 1 = j + 1.
Preferably, the calculating the control error estimated value and the lumped interference estimated value to obtain a control error predicted value, a control input predicted value and a target input predicted value includes:
Substituting the control error estimation value into a taylor series of the control error:
the predicted value is calculated to obtain:
defining decision variables:
U(t)＝[u1(t) u1 (1)(t) … u1 (r)(t)]T (26)
when the relative order of the wireless communication system is low, selecting any controller parameter (Q, R, R, T), enabling the wireless communication system to be always asymptotically stable, and substituting r=0 into a control error Taylor series to obtain a control error prediction value:
when r=0, the decision variable U (t) =u 1 (t), let the following variables be:
Wherein:
W2(t)＝w2(t) (29)
Obtaining a control error predicted value: r epsilon N is the control order for the predicted value of the control error;
The control input and the predicted value of the target input can be obtained based on the Taylor series of the control input and the Taylor series of the target input
Wherein,In order to control the predicted value of the input,A predicted value input for the target.
Preferably, the substituting the control error predicted value, the control input predicted value and the target input predicted value into the optimization model for weighted combination to obtain a target control law includes:
substituting the control error predicted value, the control input predicted value and the target input predicted value into the following formula:
The target control law is obtained as follows:
Where k 0 and k 1 are the optimal gains when the control order r is zero, respectively.
Preferably, the determining the target communication channel based on the interference power of each channel includes:
And taking the channel with the minimum interference power as the target communication channel.
An anti-interference device of a wireless communication system, comprising: a memory and a processor;
The memory is used for storing programs;
the processor is configured to execute the program to implement the steps of the anti-interference method of the wireless communication system as described above.
A storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of an anti-interference method of a wireless communication system as described above.
As can be seen from the above technical solution, in the anti-interference method for a wireless communication system provided by the embodiment of the present application, the target transmission rate of the wireless communication system and the interference power of each channel are obtained; then determining a target coding mode based on the target transmission rate; determining a target communication channel based on the signal-to-noise ratio of each channel; constructing an optimization model of the communication system based on the nonlinear generalized control of the continuous time domain; constructing a sliding mode interference observer to estimate the system state and the interference state to obtain a control error estimated value and a total interference estimated value; calculating a control error estimated value and a lumped interference estimated value to obtain a control error predicted value, a control input predicted value and a target input predicted value; substituting the control error predicted value, the control input predicted value and the target input predicted value into an optimization model for weighted combination to obtain a target control law. The anti-interference method of the wireless communication system provided by the application adopts a sliding mode interference observer to generate an estimated value of the system state affected by interference. The optimization model then optimizes the control strategy of the system by predicting future tracking errors and steady-state control inputs using the estimates. The characteristics of the unknown interference do not need to be predicted or perceived in advance, and the time-varying nature of the unknown interference is not particularly required. When interference is bounded, the method can quickly converge, reduce the influence of unknown interference and enable the wireless communication system to stably communicate.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present application, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of an anti-interference method of a wireless communication system according to an embodiment of the present application;
FIG. 2 is a graph showing the variation of error rate with the signal-to-interference-and-noise ratio according to an embodiment of the present application;
fig. 3 is a hardware block diagram of an anti-interference device of a wireless communication system according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The wireless communication system comprises a transmitter and a receiver, and is provided with power, modulation coding mode and channel self-adaptive adjustment capability. Wherein, the wireless communication frequency band is divided into n mutually non-overlapping channels. the transmit power of the wireless system at time t P s(t)∈[Psmin,Psmax ], where P smin and P smax are the maximum and minimum transmit powers of the wireless communication system, respectively. The wireless communication system has M modulation coding modes corresponding to M transmission rates. Before each communication, the wireless communication system can set up communication by giving out a target communication channel, a modulation coding mode and a transmitting power according to the technical scheme of the application.
First, an anti-interference method of a wireless communication system according to an embodiment of the present application is described with reference to fig. 1, where, as shown in fig. 1, the method may include:
step S01, a target transmission rate of the wireless communication system and interference power of each channel are obtained.
Specifically, the target transmission rate y r,Rate (t) of the wireless communication system is determined, and the interference plus noise power of each channel of the wireless communication system is obtained through broadband spectrum sensing, so as to obtain the interference power P Jn (t) of each channel.
Step S02, determining a target coding scheme based on the target transmission rate.
Specifically, a modulation and coding scheme having a transmission rate that matches the target transmission rate is selected as the target coding scheme.
Step S03, determining a target communication channel based on the interference power of each channel.
Specifically, a channel with least unknown interference may be selected as the communication channel. Therefore, the channel with the smallest interference power can be selected as the target communication channel from among the interference powers of the channels perceived by the broadband spectrum, and the target communication channel outputs u ch (t).
And S04, constructing an optimization model of the communication system based on the nonlinear generalized control of the continuous time domain.
Specifically, a curve of the variation of the error rate with the signal-to-interference-and-noise ratio in different modulation and coding modes of the wireless communication system is shown in fig. 2. When the bit error rate P e≤10-3 is, the general bit error rate curve will enter into the "waterfall region", and the relationship between the bit error rate and the signal-to-interference-and-noise ratio of the channel can be approximated as a linear relationship, so that a linear equation can be used to approximated the relationship between the signal-to-interference-and-noise ratio of the channel and the bit error rate in a certain modulation coding mode. The signal-to-interference-and-noise ratio SJNR of the nth channel is a system state variable x n (t); the relation between the signal-to-interference-plus-noise ratio SJNR and the bit error rate BER in the nth channel M modulation and coding modes at the time t can be approximated as:
Wherein i ε {1, …, M }, C i and D i are constants under the ith modulation coding scheme, and X i is a SJNR threshold under the ith modulation coding scheme. If at time t, the transmission power P s (t) of the communication signal and the interference plus noise power P Jn (t) in the nth channel are both in dBm, and the free space propagation loss is not considered, then at time t, SJNR of the nth channel may be expressed as:
xn(t)＝SJNRn(t)＝Ps(t)-PJn(t) (2)
When the target communication channel control output u ch (t) =n, the change of the wireless communication system state in the ith modulation and coding scheme can be expressed by the following formula:
Where u P (t) is the transmit power control output variable and B p is the control parameter of u P (t). According to equation (2), the dynamic characteristic parameter a= -1, the control parameter B P = 1. Thus, in combination with equation (1) and equation (3), the state equation of the wireless communication system can be modeled as follows:
Order the
u1(t)＝up(t)-PJn(t) (5)
Further, according to the linear relation between the signal-to-interference-and-noise ratio of each channel and the error rate of each channel, the state equation (4) of the obtained communication system is simplified as follows:
obtainable according to formula (6):
wherein, Is the second derivative of y n,BER (t),U 1 (t) is defined by formula (5) as the first derivative of u 1 (t). And (3) making:
wherein, Is the 1 st derivative of y n,BER (t).
Constructing a control error equation:
e(t)＝yr,BER(t)-yn,BER(t),ei(t)＝e(i)(t),i∈N (9)
Wherein y r,BER (t) is the target bit error rate, e (t) is the control error, and e (i) (t) is the i-th derivative of e (t).
Since the target bit error rate y r,BER (t) of a wireless communication system is generally constant, the n 1 derivative of the control error e (t) must exist and be bounded, and then the control error satisfies:
wherein, Representing the first derivative of e i (t), w (t) is the lumped disturbance of the unknown disturbance and system uncertainty,Is the derivative of the n 1 th order of w (t).
Constructing a lumped interference equation set:
Wherein b (t) is the control gain, b min＜b(t)＜bmax,bmin and b max are the normal numbers, b (t) is the upper and lower bounds, b 0 is the nominal value of b (t), Is the n 1 th order derivative of the bit error rate,As the first derivative of the bit error rate y n,BER (t),N 1 derivative of the target bit error rate y r,BER (t) and is calculated byAnd (3) representing.
Based on the nonlinear generalized control of the continuous time domain, an optimization model of the communication system is constructed:
wherein T >0 is the control period, Q >0 is the weight of the control error, R >0 is the weight of the control input, and u r,P (T) is the steady-state control output.
In step S05, the sliding mode interference observer estimates a system state of the wireless communication system and an interference state of the unknown interference.
Specifically, the sliding mode interference observer can observe the system state of the wireless communication system and the interference state of unknown interference to obtain a control error estimated value and a total interference estimated value. Assuming that there are known constants L.gtoreq.0 and m.epsilon.N + such that |w (m) (t) |.ltoreq.L, the sliding mode disturbance observer passes the formula:
Estimating a control error to obtain a control error estimated value, wherein, AndEstimates of the derivatives of the n 1 -1 and i orders of e (t), respectively,Is thatAn estimate at n 1 =0,For the estimate of the i+1 derivative of e (t), u 1 * (t) is the target control law and v i (t) is the sliding mode disturbance observer gain.
Assuming that there are known constants L.gtoreq.0 and m.epsilon.N + such that |w (m) (t) |.ltoreq.L, the sliding mode disturbance observer passes the formula:
Further, the method comprises the steps of,
vi(t)＝K(t)sign[vi-1(t)] (20)
Wherein the method comprises the steps ofIs the system outputCan be expressed asEstimating the lumped interference to obtain a lumped interference estimated value,For lumped interference estimates, K (t) is the switching gain,
When i=0, formula (14) is simplified as:
When n 1 =2, m=1, formula (15) is simplified as:
the formula (17) is simplified as:
wherein, To control the estimates of the derivatives of the error and the estimates of the aggregate interference,Is a target control law.
Step S06, calculating the control error estimated value and the lumped interference estimated value.
Specifically, the control error prediction value, the control input prediction value, and the target input prediction value may be calculated based on the taylor series.
Substituting the control error estimate into a taylor series of control errors:
The calculation can be carried out:
defining decision variables:
U(t)＝[u1(t) u1 (1)(t) … u1 (r)(t)]T (26)
Considering that the relative order of the wireless communication system is relatively low, for arbitrarily selected controller parameters (Q, R, T), the wireless communication system is always asymptotically stable, and r=0 is substituted into the control error taylor series to obtain a control error predicted value:
when r=0, the decision variable U (t) =u 1 (t), let the following variables be:
Wherein:
W2(t)＝w2(t) (29)
In summary, the calculated control error prediction value is:
Considering the existence of external unknown disturbances and system uncertainties, W (t) is a correction to the traditional prediction approach based on Taylor series expansion. Similar to the solve control error predictors steps (24) - (31), the control input, target input predictors are obtained based on the taylor series of the control input and the taylor series of the target input:
wherein, In order to control the predicted value of the input,A predicted value input for the target.
And S07, substituting the control error predicted value, the control input predicted value and the target input predicted value into the optimization model for weighted combination.
Specifically, substituting the control error predicted value, the control input predicted value and the target input predicted value into the optimization model can obtain:
wherein,
For a pair ofRegarding U-biasing, it is possible to obtain:
wherein, Can make theThus, the decision change becomes:
Taking the first row of decision variable U * (t) as the target control law, the target control law can be obtained as:
Where u 1 * (t) represents the target control law in an interfering environment. k 0 and k 1 are the optimal gains when r=0, respectively.
The anti-interference method of the wireless communication system provided by the embodiment of the application is characterized in that the target transmission rate of the wireless communication system and the interference power of each channel are obtained; then determining a target coding mode based on the target transmission rate; determining a target communication channel based on the signal-to-noise ratio of each channel; constructing an optimization model of the communication system based on the nonlinear generalized control of the continuous time domain; constructing a sliding mode interference observer to estimate the system state and the interference state to obtain a control error estimated value and a total interference estimated value; calculating a control error estimated value and a lumped interference estimated value to obtain a control error predicted value, a control input predicted value and a target input predicted value; substituting the control error predicted value, the control input predicted value and the target input predicted value into an optimization model for weighted combination to obtain a target control law. The anti-interference method of the wireless communication system provided by the application adopts a sliding mode interference observer to generate an estimated value of the system state affected by interference. The optimization model then optimizes the control strategy of the system by predicting future tracking errors and steady-state control inputs using the estimates. The characteristics of the unknown interference do not need to be predicted or perceived in advance, and the time-varying nature of the unknown interference is not particularly required. When interference is bounded, the method can quickly converge, reduce the influence of unknown interference and enable the wireless communication system to stably communicate.
The anti-interference method of the wireless communication system provided by the embodiment of the application can be applied to anti-interference equipment of the wireless communication system. Fig. 3 shows a block diagram of a hardware structure of an anti-interference device of a wireless communication system, and referring to fig. 3, the hardware structure of the device may include: at least one processor 1, at least one communication interface 2, at least one memory 3 and at least one communication bus 4;
In the embodiment of the application, the number of the processor 1, the communication interface 2, the memory 3 and the communication bus 4 is at least one, and the processor 1, the communication interface 2 and the memory 3 complete the communication with each other through the communication bus 4;
The processor 1 may be a central processing unit CPU, or an Application-specific integrated Circuit ASIC (Application SPECIFIC INTEGRATED Circuit), or one or more integrated circuits configured to implement embodiments of the present invention, etc.;
The memory 3 may comprise a high-speed RAM memory, and may further comprise a non-volatile memory (non-volatile memory) or the like, such as at least one magnetic disk memory;
Wherein the memory stores a program, and the processor can call the program stored in the memory, wherein the program is used for realizing each processing flow in the anti-interference scheme of the wireless communication system
The embodiment of the application also provides a storage medium, which can store a program suitable for being executed by a processor, wherein the program is used for realizing each processing flow in the anti-interference scheme of the wireless communication system.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (4)
1. An anti-interference method for a wireless communication system, comprising:
Acquiring a target transmission rate of a wireless communication system and interference power of each channel;
determining a target coding mode based on the target transmission rate;
Determining a target communication channel based on the interference power of each channel;
constructing an optimization model of the wireless communication system based on continuous time domain nonlinear generalized control;
the sliding mode interference observer estimates the system state of the wireless communication system and the interference state of unknown interference to obtain a control error estimated value and a total interference estimated value;
Calculating the control error estimated value and the lumped interference estimated value to obtain a control error predicted value, a control input predicted value and a target input predicted value;
Substituting the control error predicted value, the control input predicted value and the target input predicted value into the optimization model for weighted combination to obtain a target control law;
the constructing an optimization model of the wireless communication system based on the continuous time domain nonlinear generalized control comprises the following steps:
modeling a state equation of the wireless communication system according to the linear relation between the signal-to-interference-plus-noise ratio of each channel and the error rate of each channel to obtain the state equation:
Wherein x n (t) is a system state variable of an nth channel of the wireless communication system at a time t, y n,BER (t) is a time t, error rates of the nth channel of the wireless communication system, C i and D i are constants in an ith modulation coding mode, u 1(t)＝up(t)-PJn(t)(5),uP (t) is a transmission power control output, and P Jn (t) is interference plus noise power in a passband of the nth channel;
Constructing a control error equation: e (t) =y r,BER(t)-yn,BER(t),ei(t)＝e(i)(t),i∈N (9),yr,BER (t) is the target error rate, e (t) is the control error, e (i) (t) is the i-th derivative of e (t);
Constructing a lumped interference equation set:
Where w (t) is the lumped interference of the unknown interference and the uncertainty of the wireless communication system, b (t) is the control gain, b min＜b(t)＜bmax,bmin and b max are normal numbers, b 0 is the nominal value of b (t), Is the n 1 th order derivative of the bit error rate,As the first derivative of the bit error rate y n,BER (t),N 1 derivative of the target bit error rate y r,BER (t) and is calculated byA representation;
Based on continuous time domain nonlinear generalized control, constructing an optimization model of the wireless communication system:
Wherein T > 0 is a control period, Q > 0 is the weight of a control error, R is more than or equal to 0 is the weight of a control input, and u γ,P (T) is a steady-state control output;
The sliding mode interference observer estimates the system state and the interference state to obtain a control error estimated value and a total interference estimated value, and the method comprises the following steps:
The sliding mode interference observer is represented by the formula:
estimating the error to obtain a control error estimated value, AndEstimates of the derivatives of the n 1 -1 and i orders of e (t), respectively,Is thatAn estimate at n 1 =0,For the estimated value of the i+1 derivative of e (t), u 1 * (t) is the target control law, v i (t) is the sliding mode interference observer gain;
Assuming that there are known constants L.gtoreq.0 and m.epsilon.N + such that |w (m) (t) |.ltoreq.L, the sliding mode disturbance observer passes the formula:
estimating to obtain a lumped interference estimated value, wherein, AndRespectively lumped interferenceAn estimated value at n 1 =j and n 1 =m-1,Is thatAn estimated value at n 1 =j+1;
The calculating the control error estimated value and the lumped interference estimated value to obtain a control error predicted value, a control input predicted value and a target input predicted value includes:
Substituting the control error estimation value into a taylor series of the control error:
the predicted value is calculated to obtain:
defining decision variables:
When the relative order of the wireless communication system is low, selecting any controller parameter (Q, R, R, T), enabling the wireless communication system to be always asymptotically stable, and substituting r=0 into a control error Taylor series to obtain a control error prediction value:
when r=0, the decision variable U (t) =u 1 (t), let the following variables be:
Wherein:
W2(t)＝w2(t) (29)
Obtaining a control error predicted value: r epsilon N is the control order for the predicted value of the control error;
The control input Qin Le series and the target input Qin Le series can be used for obtaining the predicted value of the target input as follows
Wherein, In order to control the predicted value of the input,A predicted value input for the target;
Substituting the control error predicted value, the control input predicted value and the target input predicted value into the optimization model for weighted combination to obtain a target control law, wherein the method comprises the following steps:
substituting the control error predicted value, the control input predicted value and the target input predicted value into the following formula:
The target control law is obtained as follows:
Where k 0 and k 1 are the optimal gains when the control order r is zero, respectively.
2. The method of interference avoidance in a wireless communication system according to claim 1 wherein said determining a target communication channel based on the interference power of said channels comprises:
And taking the channel with the minimum interference power as the target communication channel.
3. An anti-interference device for a wireless communication system, comprising: a memory and a processor;
The memory is used for storing programs;
the processor configured to execute the program to implement the steps of the anti-interference method of the wireless communication system according to any one of claims 1-2.
4. A storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the interference suppression method of a wireless communication system according to any of claims 1-2.
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