Time hopping code estimation and multi-hop coherent combining method and device for satellite communication

Abstract

The application discloses a time-hopping code estimation and multi-hop coherent combination method and device for satellite communication, and belongs to the field of digital signal processing. The sending end disperses information symbols in designated time slots of different time frames for repeated transmission, and the time slot of the sending signal is determined by a time-hopping code. The time-hopping code is randomly changed within a predetermined range according to an agreement between the two communication parties. The receiving end uses a cross-entropy iteration method to perform joint estimation of the time-hopping code and the carrier phase of the time-hopping signal transmitted through an AWGN channel. The time-hopping code and the carrier phase are binary quantized, the estimation values of the time-hopping code and the carrier phase are obtained from the probability generated by the binary quantization bits, the time slot of the signal is selected and the carrier phase is compensated, the multi-hop signals are coherently combined, the sample with small SNR loss is selected to update the probability generated by the binary quantization bits, and the global optimal vector group is obtained through iteration. According to the global optimal vector group, the multi-hop coherent combination is realized to improve the demodulation SNR, and the reliability of the time-hopping communication is effectively improved with low complexity.

Description

TECHNICAL FIELD

[0001] The application relates to a cross-entropy iterative auxiliary time-hopping code estimation and multi-hop coherent combination method and device, and belongs to the field of digital signal processing. BACKGROUND

[0002] In the field of satellite communication, the broadcast characteristics of wireless signals pose a risk of interception, thereby seriously threatening information security. Starting from the idea of suppressing and eliminating detectable and attackable features existing in communication signals, a random process is introduced to randomly control signal transmission time. In a time-hopping communication system, signals are sent in time-hopping time segments, which destroys the continuity of signals in the time domain in the communication process and increases the difficulty of signal interception. For a satellite-ground uplink, in addition to the requirement that information content is not detected, the signal itself is also required not to be perceived, otherwise a non-cooperative party can detect the existence of the uplink signal to find the terminal position and attack the terminal. In order to improve the concealment of the satellite-ground uplink, the transmitting end further reduces the signal power, disperses the information symbols to be sent in multiple time slots of different time frames for repeated transmission, and each time of transmission adopts a randomly changed time-hopping code to control the movement of the signal in time, which creates a very low signal-to-noise ratio condition for the uplink and increases the uncertainty of time. In order to recover the information symbols, the receiving end needs to combine the multi-hop signals scattered in different time slots of each time frame and having a very low signal-to-noise ratio, so as to obtain a signal-to-noise ratio gain. Since the signal carrier phase of each frame is random to the receiving end, in order to reduce the loss of the combined signal-to-noise ratio, the receiving end is required to accurately estimate and compensate the signal carrier phase of each frame, and since the time-hopping code is random, the time-hopping code of each time frame needs to be searched, and finally the coherent combination and demodulation of the multi-hop signal are completed. The above problem is a multi-dimensional nonlinear optimization problem about the estimation of multi-dimensional parameters of the multi-hop carrier phase and the time-hopping code under the condition of a very low signal-to-noise ratio. From the perspective of maximum likelihood estimation, it is very difficult to directly solve the problem, and the traditional traversal method has high complexity.

[0003] Cross-entropy, as a global random optimization algorithm, is widely used in multi-dimensional, large-scale and nonlinear optimization problems. The optimization problem is converted into a probability estimation problem of a small probability event, that is, the occurrence of the optimal solution is a small probability event. An adaptive key sampling strategy is adopted to select samples with better effects according to the objective function for updating the probability distribution. New samples are generated by using the updated probability distribution, and iteration is performed in sequence so that the optimal solution is more likely to occur. The application of cross-entropy to joint estimation of multi-hop carrier phase and time-hopping code can reduce the complexity of parameter estimation. Based on this, a cross-entropy iterative auxiliary time-hopping code estimation and multi-hop coherent combination method is proposed. SUMMARY

[0004] The application aims to provide a cross-entropy iteration assisted time hopping code estimation and multi-hop coherent combining method and device, which can improve the demodulation signal-to-noise ratio through coherent combining at a low complexity, and effectively improve the reliability of time hopping communication.

[0005] The application aims to achieve the above-mentioned purpose through the following technical solutions.

[0006] The application discloses a time hopping code estimation and multi-hop coherent combining method for satellite communication, wherein a sending end disperses information symbols in designated time slots of different time frames for repeated transmission, and the time slot of the sending signal is determined by a time hopping code; and the time hopping code is randomly changed within a predetermined range according to an agreement between the two communication parties.

[0007] The application discloses a time hopping code estimation and multi-hop coherent combining method for satellite communication, and comprises the following steps.

[0008] Step one: divide a communication time window into multiple time frames, each time frame includes multiple time slots, and the information symbols to be sent are repeatedly transmitted in the designated time slots of the multiple time frames after BPSK modulation; the time slot position of the sending signal in each time frame is determined by the time hopping code corresponding to the frame; the time hopping code is randomly changed within a predetermined range according to an agreement between the two communication parties, and a BPSK modulated time hopping signal with random time hopping code is generated.

[0009] The BPSK modulated time hopping signal with random time hopping code is shown in the following formula:

[0010]

[0011] The N symbols to be sent are repeatedly transmitted in N time frames, the duration of a single time frame is T, b represents the kth BPSK modulated symbol, and b represents the kth BPSK modulated symbol. s f f k k ​​​​∈ {-1, +1}, w(t) denotes a single pulse waveform, c m denotes the time-hopping code of the mth time frame, c m ∈ {0, 1,..., N h -1}, the time-hopping code c m is added to the signal of the mth time frame m T c , N h T c = T f , T s is a single symbol duration, T c = N s T s , f0 is the carrier frequency of the transmitted signal, and φ 0,m is the initial phase of the carrier of the transmitted signal in the mth time frame.

[0012] Step two: the BPSK modulated time-hopping signal obtained in step one is sent into an AWGN channel, and a signal transmitted through the AWGN channel is received.

[0013] The received signal after the AWGN channel is denoted as

[0014]

[0015] wherein A is the amplitude of the transmitted signal when it reaches the receiver, τ is the time delay of the receiving end relative to the sending end, f d is the frequency offset of the received signal relative to the transmitted signal, φ m is the initial phase of the carrier of the received signal in the mth time frame, and n(t) denotes additive complex Gaussian white noise with a mean of 0 and a variance of The time delay τ and the frequency offset f d of the receiving end are ideally synchronized.

[0016] Step three: the search range of the initial phase of the carrier of each frame of the received signal is [0, 2π), and the search range of c m is agreed by the two parties of communication as {0, 1,..., N h -1}, and the search parameters of the initial phase of the carrier of the mth frame of the received signal and the time-hopping code are respectively wherein The search values are mapped to binary codes, D1 and D2 are the numbers of binary quantization bits, each carrier phase search value corresponds to a D1-bit binary number, and each time-hopping code search value corresponds to a D2-bit binary number, that is, the parameter quantization of the time-hopping code and the carrier phase of each time signal is realized.

[0017] φ m,d denotes the dth carrier initial phase estimation value of the mth frame, d ∈ {1, 2,..., N1}, and there are

[0018]

[0019] Let d-1 be a D1bit binary number, then the φ m,d is established by the above formula.

[0020] c m,u denotes the u-th hop-time code estimate of the m-th frame, u∈{1, 2, …, N2}, and N2=N h , and

[0021] c m,u = u-1 (4)

[0022] Let u-1 be a D2bit binary number, then the c m,u is established by the above formula.

[0023] Step four: initialize the binary quantization bit generation probability as the input of the first cross-entropy iteration, and obtain N c group binary codes according to the binary quantization bit generation probability, which are called candidate groups. The hop-time code estimate and the carrier phase estimate are obtained by mapping the binary codes, the time slot where the signal is located is selected according to the hop-time code estimate, the carrier phase of the signal in the selected time slot is compensated according to the carrier phase estimate, and the multi-hop signal after compensation is coherently combined. The signal-to-noise ratio of the combined signal is estimated, the difference between the estimated signal-to-noise ratio and the theoretical signal-to-noise ratio is calculated, the combined signal-to-noise ratio loss is obtained, and the combined signal-to-noise ratio loss is taken as the objective function of the cross-entropy iteration.

[0024] N f frame hop-time code and carrier phase estimate binary quantization bits are N f (D1+D2)bit, and the binary quantization bit generation probability of the i-th cross-entropy iteration is wherein denotes the probability that the j-th quantization bit is 1, which is generated by The binary quantization bits generated are denoted as wherein denotes the j-th quantization bit, b i The hop-time code and carrier phase estimate obtained by mapping are denoted as Initialize the binary quantization bit generation probability as wherein denotes a 1×N f(D1+D2) is a vector with all elements being 1. A binary code is generated based on this probability to obtain the time-hopping code and the estimated carrier phase. The time slot where the signal is located is selected based on the estimated time-hopping code. The carrier phase of the signal in the selected time slot is compensated based on the estimated carrier phase. The compensated multi-hop signals are then coherently combined.

[0025] The time shift in the m-th frame is v. m T c The k-th data in a time slot is represented as

[0026]

[0027] Where C m (v m ) is the time-skip code indicator function

[0028]

[0029] Based on time-skip code estimation value Select the time slot location of the m-th frame signal, based on the carrier phase estimate. Compensate the carrier phase of the selected time slot in the m-th frame, N f The signal after combining the kth data from the selected time slot of each time frame is represented as follows:

[0030]

[0031] Let γ1 represent the single-hop signal-to-noise ratio, then the theoretical signal-to-noise ratio after combining is:

[0032] γ comb =γ1+10log 10 (N f (8)

[0033] The difference between the estimated signal-to-noise ratio and the theoretical signal-to-noise ratio is calculated using the following formula, yielding the combined signal-to-noise ratio loss:

[0034]

[0035] in, The signal-to-noise ratio (SNR) estimation method used to estimate the actual combined SNR is as follows:

[0036]

[0037] Here, mean() means to take the mean, and var() means to take the variance.

[0038] The combined signal-to-noise ratio (SNR) is calculated by substituting the estimated results of the theoretical and actual combined SNR into the combined SNR loss formula. This calculated combined SNR loss is then used as the objective function for cross-entropy iteration, with N... c The parameters are used to obtain Nc The combined signal-to-noise ratio loss estimation results.

[0039] Step 5: Iteratively update the parameter estimation results using cross-entropy, and update the N obtained in Step 4. c Sort the combined signal-to-noise ratio (SNR) losses from smallest to largest, and select the top N SNR losses with the smallest combined SNR losses. e The time-hopping code and carrier phase quantization parameters corresponding to the group are used as the preferred group. The probability of each bit in the binary quantization bits of the preferred group being 0 or 1 is calculated. Based on the probability obtained from the statistics of the preferred group, the binary quantization bit generation probability of the next cross-entropy iteration is obtained.

[0040] N c The combined signal-to-noise ratio (SNR) loss estimates are sorted from smallest to largest, and the sorted SNR loss obtained from the i-th cross-entropy iteration is denoted as . The corresponding time-hopping code and carrier phase binary quantization bits are denoted as: Depend on The estimated value obtained by mapping is denoted as l∈{1, 2, ..., N} c}. Select the top N pairs of samples with the smallest combined signal-to-noise ratio loss. e Group of binary quantized bits form the preferred group The corresponding time-hopping code and carrier phase estimate are Calculate the probability p that each quantized bit of the preferred group is 1. i+1

[0041]

[0042] For p i+1 Perform smoothing and update the generation probability for the next iteration.

[0043]

[0044] Where α is the smoothing coefficient, α∈(0,1], the larger α is, the faster the convergence speed.

[0045] Step Six: To avoid getting trapped in local optima, a globally optimal vector set is established. The time-hopping code and carrier phase estimate that minimize the signal-to-noise ratio loss during the cross-entropy iteration process are selected as the globally optimal vector set. When each element in the algorithm becomes 0 or 1, or when the number of iterations reaches the set maximum number of iterations, the cross-entropy iteration stops, and the globally optimal vector set is output. Based on the globally optimal vector set obtained through random search, time slot selection and carrier phase compensation are performed on the received signal. Multi-hop coherent combining is used to improve the demodulation signal-to-noise ratio, effectively improving the reliability of time-hop communication with low complexity.

[0046] set up Used to record the minimum combined signal-to-noise ratio loss from the 1st iteration to the i-th iteration, set As a means of recording The corresponding time-hopping code and carrier phase estimate, when N is obtained in the i-th iteration in step five. c The minimum value of the combined signal-to-noise ratio loss satisfies At that time, The value is updated to and The value is updated to otherwise and Unchanged. Calculation The number of elements M that are 0 or 1, when M < N f When (D1+D2) and the current iteration number is less than the set maximum iteration number, As the input condition for the next cross-entropy iteration, repeat steps four through six. When M = N f When (D1+D2) or the current iteration count equals the set maximum iteration count, the cross-entropy iteration stops, and the globally optimal vector set is output.

[0047] Based on the time-hopping code and carrier phase estimate in the globally optimal vector set obtained by the above random search process, time slot selection and carrier phase compensation are performed on the received signal, and coherent merging is performed on the compensated multi-hop signal to improve the demodulation signal-to-noise ratio, thereby effectively improving communication reliability with low complexity.

[0048] This invention also discloses a time-hop code estimation and multi-hop coherent merging apparatus for satellite communication, used to implement a time-hop code estimation and multi-hop coherent merging method for satellite communication. The time-hop code estimation and multi-hop coherent merging apparatus for satellite communication includes a parameter quantization unit, a parameter compensation and multi-hop merging unit, a signal-to-noise ratio estimation unit, and a cross-entropy iteration unit.

[0049] The parameter quantization unit is used to establish the mapping relationship between the time-hopping code and the carrier phase search value and the binary quantization bits.

[0050] The parameter compensation and multi-hop merging unit performs parameter compensation and multi-hop merging based on the estimation results obtained from the cross-entropy iteration unit. It selects the time slot where the signal is located based on the time hop code estimation value, compensates the carrier phase of the selected time slot signal based on the carrier phase estimation value, and performs coherent merging on the compensated multi-hop signal.

[0051] The signal-to-noise ratio (SNR) estimation unit estimates the SNR of the merged signal obtained by the parameter compensation and merging unit, calculates the difference between the estimated SNR and the theoretical SNR, and obtains the merged SNR loss.

[0052] The cross entropy iteration unit generates a probability generation binary code from the binary quantization bit, generates a time hopping code and a carrier phase estimation value according to the binary code and a mapping relationship obtained by the parameter quantization unit, outputs the estimation value to the parameter compensation and multi-hop combination unit, takes the combined signal-to-noise ratio loss calculated by the signal-to-noise ratio estimation unit as a target function, selects a sample with smaller combined signal-to-noise ratio loss as an optimal group, regenerates the binary quantization bit generation probability according to the optimal group for the next iteration, records the time hopping code and the carrier phase estimation value corresponding to the minimum combined signal-to-noise ratio loss in the iteration process as a global optimal vector group, and outputs the global optimal vector group after the iteration is stopped.

[0053] Advantages:

[0054] 1. The cross entropy iteration auxiliary time hopping code estimation and coherent combination method and device disclosed by the application adopts an adaptive key sampling strategy, takes minimizing the combined signal-to-noise ratio loss as a target function, converges to an optimal solution through random search and fast iteration, has higher complexity compared with a traditional traversal method which needs to search all possible parameter values one by one, and can significantly reduce the search times and reduce the complexity of parameter estimation by using the cross entropy iteration method to assist time hopping code estimation and coherent combination.

[0055] 2. The cross entropy iteration auxiliary time hopping code estimation and coherent combination method and device disclosed by the application accurately estimates the time hopping code and the multi-hop carrier phase through cross entropy iteration, obtains a signal-to-noise ratio gain through multi-hop coherent combination, and reduces the required single-hop signal-to-noise ratio for achieving the same demodulation bit error rate as the number of hops increases, thereby reducing the requirement for single-hop signal transmission power.

[0056] 3. In the open channel of satellite communication, the wireless signal has the risk of being intercepted by a non-cooperative party, the cross entropy iteration auxiliary time hopping code estimation and coherent combination method and device disclosed by the application determines the communication signal transmission time by a randomly changed time hopping code, adopts the cross entropy iteration method to obtain a global optimal vector group for time slot selection and carrier phase compensation, performs time slot selection and carrier phase compensation on the received signal according to the global optimal vector group obtained through random search, and improves the signal-to-noise ratio through multi-hop coherent combination. By increasing the uncertainty of the communication signal in the time domain, the risk of satellite communication signal being intercepted by a non-cooperative party is reduced, and the communication security is improved. BRIEF DESCRIPTION OF DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0058] Figure 1 Flow chart for cross-entropy iteration aided joint estimation of time-hopping code and carrier phase.

[0059] Figure 2 Block diagram for cross-entropy iteration aided time-hopping code estimation and multi-hop coherent combining.

[0060] Figure 3 Diagram for time-hopping code.

[0061] Figure 4 Iteration curve for combining signal-to-noise ratio loss.

[0062] Figure 5 Combining bit error rate for cross-entropy iteration aided. DETAILED DESCRIPTION

[0063] The application will be further described and detailed below in combination with the drawings and examples.

[0064] As shown in the drawings, Figure 1 the cross-entropy iteration aided time-hopping code estimation and multi-hop coherent combining method disclosed in the embodiment has the following implementation steps:

[0065] Step one: based on the time-hopping signal time slot structure of the time-hopping code, as shown in the drawings, Figure 2 in the embodiment, N f = 8, N h = 4, N s = 1000, a BPSK modulated time-hopping signal is generated as shown in formula (1), 1000 BPSK modulated symbols to be transmitted are repeatedly transmitted in 8 time frames, each time frame is divided into 4 time slots, and the time slot position of the signal transmitted in each time frame is determined by the time-hopping code, and the communication parties agree that the time-hopping code value range is c m ∈ {0, 1, 2, 3}, the time-hopping code c m is added to the signal of the mth time frame. m T c .

[0066] Step two: the BPSK modulated time-hopping signal obtained in step one is sent into an AWGN channel, and a signal transmitted through the AWGN channel is received, the received signal after the AWGN channel is as shown in formula (2), and the receiving end time delay τ and frequency offset f d have ideal synchronization.

[0067] Step three: the carrier initial phase search range of each frame of the received signal is [0, 2π), the communication parties agree that the search range of c m is {0, 1, 2, 3}, in the embodiment, D1 = 5, D2 = 2, N1 = 32, N2 = 4, the carrier initial phase and time-hopping code search parameters of the mth frame of the received signal are respectively The search value is mapped with the binary code, each carrier phase search value corresponds to a 5-bit binary number, and each time-hopping code search value corresponds to a 2-bit binary number, that is, the parameter quantization of the time-hopping code and the carrier phase of each hop signal is realized.

[0068] The dth carrier initial phase estimation value of the mth frame is shown in formula (3), d-1 is expressed as a 5-bit binary number, for example, d-1=10 is expressed as a binary number 01010, thereby establishing φ m,d The mapping relationship with the 5-bit binary number. The u-th time-hopping code estimation value of the mth frame is shown in formula (4), u-1 is expressed as a 2-bit binary number, for example, u-1=2 is expressed as a binary number 10, thereby establishing c m,u The mapping relationship with the 2-bit binary number.

[0069] Step four: initialize the binary quantization bit generation probability as the input of the first cross-entropy iteration, the number of candidate groups N c =300 in this embodiment, 300 groups of binary codes are obtained according to the binary quantization bit generation probability, which are called candidate groups. The time-hopping code estimation value and the carrier phase estimation value are obtained by mapping the binary code, the time slot where the signal is located is selected according to the time-hopping code estimation value, the carrier phase of the selected time slot is compensated according to the carrier phase estimation value, and the coherent combination of the compensated multi-hop signal is performed. The signal-to-noise ratio of the combined signal is estimated, the difference between the estimated signal-to-noise ratio and the theoretical signal-to-noise ratio is calculated, and the combined signal-to-noise ratio loss is obtained, which is used as the objective function of the cross-entropy iteration.

[0070] In this embodiment, the binary quantization bits of the 8-frame time-hopping code and carrier phase estimation value are 56 bits, and the binary quantization bit generation probability of the i-th cross-entropy iteration is wherein represents the probability that the jth quantization bit is 1, and is generated by The generated binary quantization bits are represented as wherein represents the jth quantization bit, b i The time-hopping code and carrier phase estimation values obtained by mapping are denoted as The binary quantization bit generation probability is initialized as The binary code is generated according to the probability, the time-hopping code and carrier phase estimation values are obtained, the time slot where the signal is located is selected according to the time-hopping code estimation value, the carrier phase of the selected time slot is compensated according to the carrier phase estimation value, and the coherent combination of the compensated multi-hop signal is performed. According to formula (8), the theoretical signal-to-noise ratio of the combined signal is γ1+10log 10 8≈γ1+9, the combined signal-to-noise ratio loss is calculated according to formulas (9) and (10), and 300 combined signal-to-noise ratio loss estimation results of the candidate groups are obtained.

[0071] Step five: update the parameter estimation result by cross-entropy iteration, sort the 300 combined SNR losses obtained in step four from small to large to select the optimal group N e Take N = 60 for example, select the first 60 groups corresponding to the time-hop code and carrier phase quantization parameters with the smallest combined SNR loss as the optimal group, calculate the probability of each bit of the binary quantization bits of the optimal group taking 0 or 1, and obtain the binary code generation probability of the next cross-entropy iteration according to the probability obtained by the optimal group statistics.

[0072] Sort the 300 combined SNR loss estimation results from small to large, and record the combined SNR loss sorting result obtained by the i th cross-entropy iteration as The corresponding time-hop code and carrier phase binary quantization bits are recorded as l∈{1,2,...,N c Take the first 60 groups of binary quantization bits with the smallest combined SNR loss as the optimal group The corresponding time-hop code and carrier phase estimation values are According to formula (11), calculate the probability p of each bit of the optimal group taking 1 i+1 , and update the generation probability of the next iteration according to formula (12) In this embodiment, α = 1, that is,

[0073] Step six: avoid falling into a local optimal solution by setting a global optimal vector group, select the time-hop code and carrier phase estimation values with the smallest combined SNR loss in the cross-entropy iteration process as the global optimal vector group, and when each element in the global optimal vector group becomes 0 or 1, or the iteration number reaches the maximum iteration number set, the cross-entropy iteration stops, and the global optimal vector group is output. According to the global optimal vector group obtained by random search, perform time slot selection and carrier phase compensation on the received signal, and obtain demodulation SNR gain by multi-hop coherent combination.

[0074] Set to record the minimum combined SNR loss from the first iteration to the i th iteration, and set as a variable used to record the corresponding time-hop code and carrier phase estimation values, when the minimum value of the N c combined SNR losses obtained in the i th iteration in step five satisfies , update the value of to and update the value of to Otherwise, and remain unchanged. Calculate M is the number of elements with value 0 or 1, when M < 56 and the current iteration number is less than the set maximum iteration number, then As the input condition of the next cross-entropy iteration, steps four to six are repeated. When M = 56 or the current iteration number is equal to the set maximum iteration number, the cross-entropy iteration stops and the global optimal vector group

[0075] As shown in Figure 4 , when N c = 300, the ratio of the preferred group number to the candidate group number N e / N c is changed, the simulation iteration convergence curve is obtained, and the relationship between the average combined SNR loss and the iteration number is obtained. When N e / N c = 0.01, the iteration converges in 5 times, and the combined SNR loss is about 2.3 dB. When N e / N c = 0.3, the combined SNR loss is reduced to about 0.1 dB, and the iteration converges in about 25 times. When N e / N c is small, the convergence speed is fast, but it is easy to converge to a local optimal solution. As N e / N c increases, it is easy to obtain a global optimal solution, but the iteration number increases and the complexity increases.

[0076] Figure 5 The cross-entropy iteration auxiliary method is compared with the exhaustive method and the theoretical combined bit error rate. The exhaustive method performs point-by-point search on the two-dimensional grid of the time hopping code and the carrier phase. In an ideal case, this method can accurately estimate the discrete time hopping code, and the performance loss comes from the grid search step of the carrier phase. The cross-entropy iteration auxiliary method randomly searches the two-dimensional grid of the time hopping code and the carrier phase using an adaptive key sampling strategy, reducing the number of grid searches. In this embodiment, the number of grids in the time hopping code dimension is 2 16 , the number of grids in the carrier phase dimension is 2 24 , and the search number of the exhaustive method is 2 16 × 2 24 = 2 40 . In the cross-entropy iteration auxiliary method, N c = 300 and N e / N c = 0.2, and the iteration converges after about 20 times, so the search number of the cross-entropy iteration is about 300 × 20 = 6000, which is significantly reduced compared with the exhaustive method. The received signal carrier phase is set at the middle position of the grid, and the demodulation bit error rate is simulated under the condition that the single-hop E b / N0 range is -6 dB to 1 dB, as shown in Figure 5As shown, the cross-entropy iterative aided method has about 0.5dB improvement in demodulation performance compared with the exhaustive method (@BER=1x10 -4 ), and about 0.2dB performance loss compared with the theoretical combining (@BER=1x10 -4 ). Compared with the exhaustive method, the cross-entropy iterative aided method can improve the demodulation signal-to-noise ratio by multi-hop coherent combining with lower complexity, and has less loss compared with the theoretical combining, effectively improving the reliability of the time hopping communication.

[0077] The above detailed description further describes the purpose, technical scheme and beneficial effects of the application. It should be understood that the above description is only a specific embodiment of the application and is not used to limit the protection scope of the application. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the application should be included in the protection scope of the application.

Claims

1. A method for time hopping code estimation and multi-hop coherent combining for satellite communications, characterized by: The method comprises the following steps: Step one: divide the communication time window into multiple time frames, each time frame comprising multiple time slots, and repeatedly transmit the information symbols to be transmitted in the designated time slots of the multiple time frames after BPSK modulation, the time slot position of the signal transmitted in each time frame being determined by the time hopping code corresponding to the frame, and the time hopping codes being agreed by the two communication parties to randomly change within a predetermined range to generate the BPSK modulation time hopping signal with random time hopping codes; Step two: send the BPSK modulation time hopping signal obtained in step one into an AWGN channel, and receive the signal transmitted through the AWGN channel; Step three: the search range of the carrier initial phase of each frame signal is [0, 2π), and the communication parties agree that c m The search range of the time hopping code is {0, 1,..., N h The search parameters of the carrier initial phase and the time hopping code of the mth frame received signal are respectively Wherein The search value is mapped with the binary code, D1 and D2 are the binary quantization bit numbers, each carrier phase search value corresponds to a D1 bit binary number, and each time hopping code search value corresponds to a D2 bit binary number, that is, the parameter quantization of the time hopping code and the carrier phase of each hop signal is realized. Step four: initialize the binary quantization bit generation probability as the input of the first cross-entropy iteration, obtain N c The binary code is mapped to obtain a hop code estimate value and a carrier phase estimate value, a time slot where the signal is located is selected according to the hop code estimate value, the carrier phase of the signal in the selected time slot is compensated according to the carrier phase estimate value, and the compensated multi-hop signal is coherently combined; the signal-to-noise ratio of the combined signal is estimated, the difference between the estimated signal-to-noise ratio and the theoretical signal-to-noise ratio is calculated to obtain a combined signal-to-noise ratio loss, and the combined signal-to-noise ratio loss is taken as an objective function of cross-entropy iteration; Step five: update the parameter estimation result by cross-entropy iteration, sort the N c combined SNR losses obtained in step four from small to large, select the time hop code and carrier phase quantization parameters corresponding to the first N e groups with the minimum combined SNR loss as the preferred groups, calculate the probability of each bit taking 0 or 1 in the binary quantization bits of the preferred groups, and obtain the binary quantization bit generation probability of the next cross-entropy iteration according to the probability obtained by the preferred group statistics. Step six: avoid falling into a local optimal solution by setting a global optimal vector group, select the time hopping code and carrier phase estimation value with the minimum time hopping code and carrier phase estimation value in the cross entropy iteration process as the global optimal vector group, stop the cross entropy iteration when each element in the generated probability becomes 0 or 1 or the iteration number reaches the maximum iteration number set, and output the global optimal vector group; select the time slot and compensate the carrier phase of the received signal according to the global optimal vector group obtained through the random search, improve the demodulation signal-to-noise ratio through multi-hop coherent combination, and effectively improve the reliability of the time hopping communication with low complexity.

2. The method of time hopping code estimation and multi-hop coherent combining for satellite communication of claim 1, wherein: In step one, The BPSK modulation time hopping signal with random time hopping codes is as follows: N s symbols to be transmitted are repeated in N f time frames, the duration of a single time frame is T f , b k denotes the k-th BPSK modulated symbol, b k ∈ {-1, +1}, w(t) denotes a single pulse waveform, c m denotes the m-th time frame's time hopping code, c m ∈ {0, 1,..., N h - 1}, the time hopping code c m adds a time shift c m T c to the signal of the m-th time frame, N h T c = T f , T s is the duration of a single symbol, T c = N s T s , f0is the transmitted signal carrier frequency, φ 0,m is the initial phase of the transmitted signal carrier in the m-th time frame.

3. The method of time hopping code estimation and multi-hop coherent combining for satellite communication of claim 2, wherein: In step two, The received signal after the AWGN channel is represented as where A is the amplitude of the transmitted signal when it reaches the receiver, τ is the time delay of the receiver relative to the transmitter, f d is the frequency offset of the received signal relative to the transmitted signal, φ m is the initial phase of the carrier of the received signal in the mth time frame, and n(t) represents additive complex white Gaussian noise with a mean of 0 and a variance of the time delay τ and the frequency offset f d has been ideally synchronized.

4. The method of time hopping code estimation and multi-hop coherent combining for satellite communication of claim 3, wherein: In step three, φ m,d φd,m represents the initial phase estimation value of the dth carrier of the mth frame, d e {1, 2,..., N1}, and has Let d - 1 be represented as a Dlbit binary number, so that φ is established by the above equation m,d Mapping relationship with Dlbit binary number; c m,u denotes the u-th hop-time code estimate of the m-th frame, u e {1, 2,..., N2}, and N2= N h , has c m,u = u - 1 (4) expressing u - 1 as a D2bit binary number, so that the mapping relationship of c m,u with the D2bit binary number is established by the above equation.

5. The method of time hopping code estimation and multi-hop coherent combining for satellite communication of claim 4, wherein: In step four, N f frame-hopping code and carrier phase estimation value, the binary quantization bits of which are N f (D1+D2) bits, the binary quantization bit generation probability of the i-th cross-entropy iteration is wherein denotes the probability of the j-th quantization bit taking 1, and is generated by The generated binary quantization bits are denoted as wherein denotes the j-th quantization bit, b i The obtained frame-hopping code and carrier phase estimation value are denoted as The binary quantization bit generation probability is initialized as wherein denotes a 1×N f (D1+D2) vector with all elements being 1, the binary code is generated according to the probability, the frame-hopping code and carrier phase estimation value are obtained, the signal is selected according to the frame-hopping code estimation value, the signal carrier phase of the selected time slot is compensated according to the carrier phase estimation value, and the compensated multi-hop signal is coherently combined. the time shift in the mth frame is v m T c the kth data in one time slot is represented as where C m (v m ) is a function of the time-of-flight code According to the time hop code estimate value The time slot position of the mth frame signal is selected, and a carrier phase estimate value is obtained The carrier phase of the selected time slot in the mth frame is compensated, and the kth data of the selected time slot of N f frame is represented as Let γ1 represent the single-hop signal-to-noise ratio, and the theoretical signal-to-noise ratio after combination is γ comb = γ1+ 10 log 10 (N f ) (8) The difference between the estimated signal-to-noise ratio and the theoretical signal-to-noise ratio is calculated according to the following formula, and the combination signal-to-noise ratio loss is wherein The actual combined signal-to-noise ratio is estimated, and the signal-to-noise ratio estimation method used is: Wherein, mean() represents taking the mean value, and var() represents taking the variance. The combined theoretical signal-to-noise ratio, the estimation result of the actual combined signal-to-noise ratio, and the loss formula of the combined signal-to-noise ratio are brought into the loss formula of the combined signal-to-noise ratio to obtain the loss of the combined signal-to-noise ratio. The calculated loss of the combined signal-to-noise ratio is used as the target function of the cross-entropy iteration, and N c group parameters are obtained. c combined signal-to-noise ratio loss estimation results.

6. The method of time hopping code estimation and multi-hop coherent combining for satellite communication of claim 5, wherein: In step five, N c The N The corresponding binary quantization bits of the time-of-flight code and the carrier phase are denoted as The estimated value obtained by the mapping is denoted as The estimated value obtained by the mapping is denoted as The first N e groups of binary quantization bits with the smallest combined SNR loss are taken to form the preferred group The corresponding time-of-flight code and carrier phase estimated values are The probability p that each bit quantization bit of the preferred group is 1 is calculated i+1 p i+1 Smoothed, update the generating probabilities for the next iteration Wherein, α is a smoothing coefficient, α ∈ (0, 1], the larger α is, the faster the convergence speed is.

7. The method of time hopping code estimation and multi-hop coherent combining for satellite communication of claim 6, wherein: The implementation method of step six is Setting For recording the minimum combined SNR loss from the first iteration to the i-th iteration, set As for recording The corresponding time-hopping code and carrier phase estimation value, when the minimum value of the N c combined SNR loss obtained in the i-th iteration in step five satisfies , update the value of to and update the value of to Otherwise and unchanged; calculate the number M of elements in 0 or 1, when M < N f (D1+D2) and the current iteration number is less than the set maximum iteration number, set as the input condition for the next cross-entropy iteration, repeat steps four to six; when M = N f (D1+D2) or the current iteration number is equal to the set maximum iteration number, the cross-entropy iteration stops, and the global optimal vector group is output According to the time hopping code and carrier phase estimation value in the global optimal vector group obtained through the above random search process, the time slot is selected and the carrier phase is compensated, the multi-hop signal after compensation is coherently combined to improve the demodulation signal-to-noise ratio, and the communication reliability is effectively improved with low complexity.

8. A satellite communication oriented time hopping code estimation and multi-hop coherent combining apparatus for implementing the satellite communication oriented time hopping code estimation and multi-hop coherent combining method as claimed in claim 1, 2, 3, 4, 5, 6 or 7, characterized by: The method comprises a parameter quantization unit, a parameter compensation and multi-hop combination unit, a signal-to-noise ratio estimation unit, and a cross entropy iteration unit. The parameter quantization unit is configured to establish a mapping relationship between the time hopping code and carrier phase search value and the binary quantization bits. The parameter compensation and multi-hop combination unit performs parameter compensation and multi-hop combination on the estimation result obtained by the cross entropy iteration unit, selects the time slot of the signal according to the time hopping code estimation value, compensates the carrier phase of the selected time slot signal according to the carrier phase estimation value, and coherently combines the multi-hop signal after compensation. The signal-to-noise ratio estimation unit estimates the signal-to-noise ratio of the combined signal obtained by the parameter compensation and combination unit, calculates the difference between the estimated signal-to-noise ratio and the theoretical signal-to-noise ratio, and obtains the combination signal-to-noise ratio loss. The cross entropy iteration unit generates a probability generation binary code from the binary quantization bit, generates a time hopping code and a carrier phase estimation value according to the binary code and a mapping relationship obtained by the parameter quantization unit, outputs the estimation value to the parameter compensation and multi-hop combination unit, takes the combined SNR loss calculated by the SNR estimation unit as a target function, selects a sample with a smaller combined SNR loss as an optimal group, regenerates the binary quantization bit generation probability according to the optimal group for the next iteration, records the time hopping code and the carrier phase estimation value corresponding to the minimum combined SNR loss as a global optimal vector group during the iteration, and outputs the global optimal vector group after the iteration is stopped.

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