End-to-end voice transmission method based on low-orbit satellite communication vocoder channel

Abstract

The invention provides an end-to-end voice transmission method based on a low-orbit satellite communication vocoder channel, which has efficient data compression: a G.729 coding algorithm and a linear predictive coding technology are adopted, so that the bit rate of voice data is reduced to 8kbps; encryption processing is introduced after voice coding, and confidentiality and integrity of data in the transmission process are ensured. The anti-interference capability is excellent: by using the QPSK modulation technology, the anti-interference performance of the signal in long-distance transmission is improved, the QPSK modulation can transmit 2-bit information in each symbol, and the frequency spectrum utilization rate is higher; in the real-time feedback mechanism, under the support of the channel state feedback mechanism, the receiving end can report channel quality information to the sending end regularly, and the modulation mode and power setting are adjusted in real time according to feedback so as to optimize the transmission quality; and comprehensive signal processing: through soft decision decoding and a combined signal processing technology, the signal recovery capability is obviously enhanced, so that the decoding process is more accurate.

Description

Technical Field

[0001] This patent belongs to the field of low-orbit satellite communications and signal anti-interference, specifically an end-to-end voice transmission method based on a low-orbit satellite communication vocoder channel. Background Art

[0002] With the rapid development of communication technology, low-orbit satellite communications have gradually become an important means to meet the demand for efficient data transmission on a global scale. However, existing voice transmission technologies face multiple challenges in practical applications, especially in terms of bandwidth limitations, data security, and signal quality. Traditional voice coding technologies such as G.711 and G.726 perform well in high-bandwidth environments, but their transmission efficiency is low under low-bandwidth conditions, resulting in degraded call quality and poor user experience. In addition, the deficiencies of existing technologies in data encryption make it difficult to effectively protect user privacy and data security. In addition, traditional modulation methods have weak anti-interference capabilities and are easily affected by multipath propagation and signal interference, resulting in high bit error rates (BER). Summary of the invention

[0003] The present invention proposes an end-to-end voice transmission method based on a low-orbit satellite communication vocoder channel, aiming to improve the efficiency, security and reliability of voice communication.

[0004] To achieve the above object, the technical solution adopted by the present invention is:

[0005] The end-to-end voice transmission method based on a low-orbit satellite communication vocoder channel is characterized in that it comprises the following steps:

[0006] Step S1: Voice signal collection

[0007] Through the microphone, the user's voice input is converted into an electrical signal, which becomes the basis of voice data;

[0008] Step S2: Digitization of speech signal

[0009] The collected speech signal is digitized through sampling and quantization;

[0010] Step S3: Speech encoding

[0011] S31, voice encoding is performed via a voice encoding module

[0012] The digitized speech signal is compressed and G.729 is selected as the coding algorithm. The G.729 algorithm extracts the characteristics of the speech signal by using linear predictive coding technology. The following are the specific steps of the process:

[0013] S311, signal framing:

[0014] The continuous speech signal is divided into multiple short time frames, each frame is 20 milliseconds long and overlaps 10 milliseconds;

[0015] S312, Linear Prediction Analysis:

[0016] Apply linear prediction analysis to each frame and calculate the prediction coefficients. LPC predicts the current sample value by building a linear model, using the weighted sum of the previous N samples. These weighted coefficients reflect the short-term characteristics of the signal.

[0017] Assume that the audio signal of a frame is Then the LPC model can be expressed as:

[0018]

[0019] Among them, ak is the prediction coefficient, P is the prediction order, and e[n] is the prediction error;

[0020] S313, Quantization and Coding:

[0021] The prediction coefficients are quantized using the number of bits, and at the same time, the prediction error signal of the LPC model is also quantized and encoded;

[0022] S32, Data Compression

[0023] After encoding using the G.729 algorithm, the amount of compressed voice data is reduced;

[0024] Step S4: Encryption processing by encryption module

[0025] After voice encoding is completed, voice data encryption is performed to ensure the security of voice transmission. The specific steps of encryption are as follows:

[0026] S41. Encryption algorithm selection

[0027] A symmetric encryption algorithm is used. AES in the symmetric encryption algorithm supports keys of different lengths. The appropriate key length can be selected according to specific security requirements.

[0028] S42. Key Management

[0029] Key management strategies include the following aspects:

[0030] Key generation: Generate keys using a strong random number generator;

[0031] Key exchange: To ensure that only the communicating parties can obtain the encryption key, a key exchange protocol is used. The key exchange protocol allows the two parties to securely share the key without directly transmitting the key;

[0032] Key storage: Use secure hardware modules or software encryption libraries to encrypt and store keys;

[0033] S43. Data encryption implementation

[0034] When encrypting the encoded voice data, the AES encryption algorithm needs to be applied to the data stream. This process includes the following steps:

[0035] Initialize the encryptor: create an AES encryption instance, select CBC mode, and introduce the initial vector (IV).

[0036] Encrypted data: Encrypt the encoded G.729 data using the AES cipher. The data needs to be padded to ensure that its length is a multiple of the block size.

[0037] Data formatting: The encrypted data needs to be packaged into packets, which contain the ciphertext, initialization vector (IV), and necessary metadata to ensure that the same IV is used when the receiving end can decrypt it;

[0038] S44. Data integrity verification

[0039] By performing a hash operation on the ciphertext and the key, a unique MAC value is generated. This value is sent together with the ciphertext. The receiving end can verify the MAC value when decrypting the data to ensure the integrity of the data.

[0040] Step S5: Modulate the signal through the signal modulation module

[0041] After completing the voice coding and encryption processing, the processed voice data is converted into a radio frequency signal suitable for transmission in low-orbit satellite communications through channel modulation. The specific steps are as follows:

[0042] S51, modulation mode selection

[0043] Select QPSK, or quadrature phase shift keying, which is an efficient phase modulation technique that can convey 2 bits of information per symbol;

[0044] S52, Band Selection

[0045] Select the L band suitable for mobile communication and low-speed data transmission as the carrier frequency;

[0046] S53, Signal Generation and Modulation

[0047] After determining the modulation mode and carrier frequency, the encrypted data stream is then QPSK modulated. The specific steps are as follows:

[0048] S531, bit stream grouping:

[0049] Divide the encrypted voice data stream into multiple bit groups, each group contains 2 bits of data, so as to correspond to the QPSK modulation symbols;

[0050] S532, mapping to symbols:

[0051] Each bit group corresponds to a specific modulation symbol. In QPSK, the four phases correspond to four symbols, expressed as:

[0052] 00→0° sine wave

[0053] 01→90° The first quadrant of the sine wave

[0054] 10→180° sine wave in the third quadrant

[0055] 11→270° sine wave in the second quadrant

[0056] According to the above bit group, it can be mapped as:

[0057] 11→270°|00→0°|10→180°|10→180°|01→90°|10→180°

[0058] S533, signal waveform generation:

[0059] The mapped symbols are used to generate the corresponding modulated signal waveform. The QPSK modulated signal can be represented by a sine wave, and each symbol corresponds to a sine wave signal with a phase.

[0060] The mathematical expression of the modulated signal is as follows:

[0061]

[0062] Where A is the amplitude and fc. is the carrier frequency φ n . is the phase. Assuming the selected carrier frequency is 1.5 GHz, the signal expression can be obtained;

[0063] S534, generate sample signal:

[0064] Assuming that the amplitude of the generated signal is 1 and the duration is the time interval of each symbol, it can be calculated:

[0065] For the symbol "00", the signal is:

[0066] s0(t)=cos(2π×1.5×10 9 t)

[0067] For symbol "01", the signal is:

[0068]

[0069] For symbol "10", the signal is:

[0070] s2(t)=cos(2π×1.5×10 9 t+π)

[0071] For symbol "11", the signal is:

[0072]

[0073] S54, signal power control

[0074] According to the changes in channel conditions, the power of the transmitted signal is adjusted in real time to offset possible signal attenuation and interference. When adjusting the power of the transmitted signal, a feedback mechanism is used to monitor the quality of the received signal in real time and make power adjustments;

[0075] S55, Signal Transmission

[0076] After modulation and power control, the modulated signal will be sent to the low-orbit satellite through the L-band antenna, which uses a parabolic antenna. The satellite will forward the received signal to the target receiving end to ensure the effective transmission of data from the transmitter to the receiver;

[0077] Step S6: Satellite communication transmission

[0078] Combined with soft-decision-based joint signal processing and adaptive power control system, anti-interference in low-orbit satellite communications is achieved.

[0079] S61, soft decision decoding

[0080] At the signal receiving end, soft decision decoding technology is used to improve the signal recovery capability;

[0081] S62, Joint Signal Processing

[0082] The receiving end optimizes the received signal through frequency domain equalization and time domain equalization to offset multipath effects and other interference sources;

[0083] S63, Adaptive Power Control

[0084] Adaptive power control is performed based on real-time channel status to achieve optimized signal transmission. By monitoring channel quality, the transmit power is reduced when interference is high, and the power is increased when channel conditions are good.

[0085] S64, channel status feedback

[0086] Establish a channel status feedback mechanism between the transmitter and the receiver, where the receiver periodically reports channel quality information to the transmitter to help the transmitter optimize the modulation mode and power setting;

[0087] Step S7: Demodulation by demodulation module

[0088] After the receiving end successfully receives the satellite signal, the RF signal is converted into a digital signal through signal demodulation, as follows:

[0089] The receiving end successfully receives the satellite signal through the receiving antenna and low noise amplifier, which is manifested by the received signal strength reaching the preset threshold.

[0090] Extract the features of the modulated signal and convert it into a corresponding digital bit stream. For QPSK modulated signals, the demodulation technology includes:

[0091] Phase demodulation: QPSK modulation relies on the phase change of the signal, so the demodulator needs to accurately identify the phase of the received signal.

[0092] Sampling and symbol decision: By sampling the signal and determining the phase position of each symbol, it is mapped back to the corresponding bit group.

[0093] The process of converting the satellite signal into a digital data stream using a QPSK demodulator in a receiver is as follows:

[0094] Amplification and down-conversion of received signals: The received high-frequency RF signal is first amplified by a low-noise amplifier and then down-converted to a baseband signal for subsequent demodulation processing;

[0095] Phase synchronization: Using a phase-locked loop, the phase of the received signal is aligned with the phase of the demodulator's local oscillator.

[0096] Demodulation process: The down-converted baseband signal is input into the QPSK demodulator, which converts each symbol into a corresponding bit group by analyzing the phase information of the signal;

[0097] Bit stream reassembly: reassemble the demodulated bit groups into a complete digital bit stream in preparation for subsequent signal decryption processing;

[0098] Step S8: Decryption by decryption module

[0099] After the signal demodulation is completed, the demodulated digital data stream is restored to the original voice data. The premise of signal decryption processing is that the received digital data stream has been demodulated. In addition, the receiving end needs to have the same decryption key and algorithm as the sending end.

[0100] The details are as follows:

[0101] Using a symmetric encryption algorithm, the encryption and decryption processes use the same key.

[0102] Key and Initialization Vector (IV): The decryption process requires the key and IV generated during encryption. IV is used to ensure that the same plaintext generates different ciphertext each time it is encrypted.

[0103] Decryption process: Use the AES decryption algorithm to decrypt the received ciphertext and convert it into original voice data; Step S9: Perform voice decoding through the voice decoding module

[0104] After decryption is completed, the recovered digital data stream is decoded to generate a playable audio signal;

[0105] The condition for voice decoding is that the decrypted digital data stream is complete and undamaged original voice data, using the G.729 audio coding format.

[0106] The decoding process is as follows:

[0107] Decoder: Use the G.729 decoder to convert the bit stream into an audio signal in pulse code modulation format;

[0108] Reconstruct audio waveform: convert PCM signal into analog signal;

[0109] Step S10: Performance monitoring and user feedback

[0110] After completing the voice playback, conduct performance monitoring and collect user feedback.

[0111] The prerequisite for performance monitoring is that the system can collect relevant data during operation and can effectively interact with users to obtain feedback. Through user feedback, we can understand the system's user experience and existing problems, and make necessary adjustments and improvements.

[0112] Performance monitoring can be done in the following ways:

[0113] Real-time data monitoring: Use monitoring tools to record system performance indicators.

[0114] User feedback collection: Collect user opinions and suggestions through questionnaires or feedback mechanisms.

[0115] Data analysis: Analyze the collected data to identify potential problems and perform targeted optimization.

[0116] As a preferred technical solution of the present invention: in step S2, the voice signal is digitized by adopting a 16-bit PCM format and a sampling frequency of 44.1 kHz.

[0117] As a preferred technical solution of the present invention: in step S3, the G.729 algorithm effectively compresses the voice signal to a bit rate of 8 kbps per second, while ensuring clear sound quality.

[0118] As a preferred technical solution of the present invention: in step S4, the key lengths supported by AES include 128 bits, 192 bits and 256 bits, and the user selects a suitable key length according to specific security requirements.

[0119] Compared with the prior art, the present invention has the following beneficial effects:

[0120] 1. The present invention has efficient data compression: the G.729 coding algorithm and linear predictive coding (LPC) technology are used to reduce the bit rate of voice data from the traditional 64kbps to 8kbps. This significant compression not only saves bandwidth resources, but also reduces transmission costs. In low-bandwidth environments, this method can effectively improve the efficiency of voice transmission, ensuring that users can still enjoy a clear call experience when data traffic is limited.

[0121] 2. Enhanced security: This method introduces encryption processing after voice encoding, especially the use of the Advanced Encryption Standard (AES) algorithm, to ensure the confidentiality and integrity of data during transmission. By encrypting voice data, it can effectively prevent unauthorized access and data theft, and protect user privacy. This security measure is becoming increasingly important in modern communications, especially in situations involving sensitive information.

[0122] 3. The present invention has excellent anti-interference ability: By using QPSK modulation technology, the method improves the anti-interference performance of the signal in long-distance transmission. QPSK modulation can transmit 2 bits of information in each symbol, which has higher spectrum utilization than traditional BPSK modulation. In addition, the introduction of adaptive power control strategy enables the signal to dynamically adjust the transmission power when facing various interferences, thereby improving the signal quality and ensuring the stability of transmission.

[0123] 4. The present invention has a real-time feedback mechanism: With the support of the channel status feedback mechanism, the receiving end can regularly report channel quality information to the sending end. Based on these feedbacks, the sending end adjusts the modulation mode and power setting in real time to optimize the transmission quality. This dynamic adjustment mechanism not only improves the reliability of transmission, but also reduces the bit error rate (BER), ensuring that users can get a high-quality call experience under various conditions.

[0124] 5. The present invention has comprehensive signal processing: The method adopts soft decision decoding and joint signal processing technology, which significantly enhances the signal recovery ability. Compared with traditional hard decision decoding, soft decision decoding can take into account the strength and noise influence of the signal, making the decoding process more accurate. In addition, joint signal processing can effectively offset multipath propagation and other interference sources, ensuring that the signal maintains high clarity and quality in complex environments.

[0125] 6. User experience optimization: Performance monitoring and user feedback collection mechanisms enable the system to evaluate the quality of voice transmission in real time and make timely adjustments. By monitoring system performance indicators (such as bit error rate, signal-to-noise ratio, etc.) and combining user feedback, the development team can identify potential problems and make targeted optimizations. This mechanism not only improves the user's call quality, but also enhances user satisfaction, making the communication experience smoother. BRIEF DESCRIPTION OF THE DRAWINGS

[0126] Figure 1 This is a system architecture view of the present invention.

[0127] Figure 2 It is a signal processing flow view.

[0128] Figure 3 This is the flow chart of anti-interference technology. DETAILED DESCRIPTION

[0129] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments:

[0130] like Figure 1-3 As shown, the present invention proposes an end-to-end voice transmission method based on a low-orbit satellite communication vocoder channel, comprising the following steps:

[0131] Step S1: Voice signal collection

[0132] The collection of voice signals is the first step of this method. Through the microphone, the user's voice input is converted into electrical signals, which constitute the basis of voice data. The core of this stage is to ensure the clarity and accuracy of the signal, laying a good foundation for subsequent processing.

[0133] Step S2: Digitization of speech signal

[0134] To achieve subsequent encoding and compression, the collected analog signal needs to be digitized through sampling and quantization. The 16-bit PCM format is used for digitization at a sampling frequency of 44.1kHz to ensure that the quality and details of the signal are preserved.

[0135] Step S3: Speech encoding by the speech encoding module

[0136] In the confidential voice transmission method, voice coding and encryption processing are the core steps to ensure data security and transmission efficiency. This step will introduce in detail how to process voice signals using the G.729 coding algorithm and linear predictive coding (LPC) technology, and how to encrypt the encoded data to ensure the confidentiality of the voice content.

[0137] Speech Coding

[0138] The primary task of speech coding is to compress the digitized speech signal to reduce the bandwidth requirements for data transmission. Choosing G.729 as the coding algorithm has significant advantages, especially in low-bandwidth environments. The G.729 algorithm extracts the characteristics of the speech signal by using linear predictive coding (LPC) technology. The following are the specific steps of the process:

[0139] Signal framing: First, the continuous speech signal is divided into multiple short time frames, usually each frame is 20 milliseconds long and overlaps 10 milliseconds. This framing technology can ensure the effective capture of instantaneous speech features.

[0140] For example, a speech signal lasting 1 second can be divided into 50 frames, each frame containing 160 sampling points (assuming the sampling frequency is 8000 Hz).

[0141] Linear Prediction Analysis: Linear prediction analysis is applied to each frame and prediction coefficients are calculated. LPC works by building a linear model to predict the current sample value, using the weighted sum of the previous N samples. These weighted coefficients reflect the short-term characteristics of the signal.

[0142] Assume that the audio signal of a frame is The LPC model can be expressed as:

[0143]

[0144] Among them, ak is the prediction coefficient, P is the prediction order, and e[n] is the prediction error.

[0145] Quantization and coding: The prediction coefficients are quantized using an appropriate number of bits, for example, G.729 uses 8 bits for quantization to reduce the amount of data stored and transmitted. At the same time, the LPC prediction error signal is also quantized and coded to further improve the compression rate.

[0146] Through the above steps, the G.729 algorithm can effectively compress the voice signal to a bit rate of 8kbps per second while maintaining high sound quality.

[0147] Data Compression

[0148] After encoding with the G.729 algorithm, the compressed voice data significantly reduces the data volume, making it easier to transmit in limited bandwidth conditions. For example, the original PCM signal may require 64kbps, while the G.729 algorithm allows the same quality voice to only require 8kbps, greatly improving transmission efficiency.

[0149] Step S4: Encryption processing by encryption module

[0150] After voice coding is completed, encryption processing is an important step to ensure the security of voice transmission. This step is to protect the encoded voice data from being accessed and stolen by unauthorized users, and to ensure the confidentiality and integrity of the data during the entire transmission process. The following is a detailed process of encryption processing:

[0151] Encryption algorithm selection

[0152] Choosing a suitable encryption algorithm is the first step to achieve data security. For real-time voice transmission, symmetric encryption algorithms are usually used, among which the Advanced Encryption Standard (AES) is widely used due to its efficiency and security. AES supports keys of different lengths (such as 128 bits, 192 bits, and 256 bits), and the appropriate key length can be selected according to specific security requirements.

[0153] AES Algorithm Overview: AES is a block-based encryption algorithm that divides the input plaintext into fixed-size blocks (usually 128 bits) and applies a series of encryption transformations to each block. Its main advantages are:

[0154] Fast speed: The AES algorithm performs well in both hardware and software and is suitable for real-time voice transmission.

[0155] High security: AES is widely recognized as a secure encryption standard and has been adopted by multiple international standards organizations.

[0156] Key Management

[0157] The security of encryption is closely related to key management. An effective key management strategy includes the following aspects:

[0158] Key generation: Generate keys using a strong random number generator to ensure they are unpredictable. For AES, a key of 128 bits or longer is recommended.

[0159] Key exchange: To ensure that only the communicating parties have access to the encryption key, key exchange protocols (such as Diffie-Hellman or RSA) can be used. These protocols allow two parties to securely share a key without directly transmitting the key.

[0160] Key storage: The generated keys must be stored securely to prevent unauthorized users from obtaining them. Secure hardware modules (such as HSM) or software encryption libraries can be used to encrypt and store keys.

[0161] Data encryption implementation

[0162] When encrypting the encoded voice data, the AES encryption algorithm needs to be applied to the data stream. This process includes the following steps:

[0163] Initialize the cipher: Create an AES encryption instance and select the appropriate mode (such as CBC mode or GCM mode). CBC mode enhances security by introducing an initial vector (IV).

[0164] Code example:

[0165] fromCrypto.CipherimportAES

[0166] fromCrypto.Util.Paddingimportpad

[0167] importos

[0168] #Generate AES key and initial vector

[0169] key = os.urandom(16) # 128-bit random key

[0170] iv = os.urandom(16) # 128-bit random initialization vector

[0171] # Initialize the AES encryptor

[0172] cipher=AES.new(key,AES.MODE_CBC,iv)

[0173] Encrypted data: Encrypt the encoded G.729 data using the AES cipher. The data first needs to be padded to ensure that its length is a multiple of the block size.

[0174] #Example: Encrypted data

[0175] #G.729 data that needs to be encrypted

[0176] encoded_data = b'...G.729 encoded data...'

[0177] #encryption

[0178] ciphertext=cipher.encrypt(pad(encoded_data,AES.block_size))

[0179] Data formatting: The encrypted data needs to be packaged into packets, which contain the ciphertext, initialization vector (IV) and necessary metadata (such as timestamp, sequence number). This ensures that the same IV is used when the receiving end can decrypt.

[0180] Code example:

[0181] packet={

[0182] 'iv':iv,

[0183] 'ciphertext':ciphertext,

[0184] 'timestamp':time.time(),

[0185] #Other metadata

[0186] }

[0187] Data integrity verification

[0188] In order to ensure that the data has not been tampered with during transmission, the message authentication code (MAC) technology can be used. By performing a hash operation on the ciphertext and the key, a unique MAC value is generated, which is sent together with the ciphertext. The receiving end can verify the MAC value when decrypting the data to ensure the integrity of the data.

[0189] Code example:

[0190] fromCrypto.HashimportSHA256

[0191] # Calculate the message authentication code

[0192] mac=SHA256.new(ciphertext).digest()

[0193] packet['mac'] = mac

[0194] Step S5: Modulate the signal through the signal modulation module

[0195] After voice coding and encryption, channel modulation is a key step to convert the processed voice data into RF signals suitable for transmission in low-orbit satellite communications. This process ensures that the signal can be effectively transmitted over long distances through satellite links while minimizing signal distortion and interference. The following is a detailed process of channel modulation, using QPSK (quadrature phase shift keying) modulation and transmitting in the L band.

[0196] Modulation mode selection

[0197] QPSK is an efficient phase modulation technology that can transmit 2 bits of information per symbol. This method improves spectrum utilization compared to traditional BPSK (transmitting 1 bit per symbol) and is suitable for use in bandwidth-limited satellite communications. The main advantages of QPSK modulation include:

[0198] Strong anti-interference ability: QPSK is highly resistant to signal distortion and interference and is suitable for long-distance transmission.

[0199] High spectrum efficiency: Each symbol carries a large amount of information, which improves transmission efficiency.

[0200] Band Selection

[0201] When choosing a carrier frequency, the L band (1-2 GHz) is widely used in satellite communications and is particularly suitable for mobile communications and low-rate data transmission. The advantages of the L band include:

[0202] Strong signal penetration: L-band signals have less attenuation in the atmosphere and can better penetrate obstacles.

[0203] Strong anti-interference ability: Compared with higher frequency bands, L-band signals are more resistant to climatic conditions such as rain attenuation.

[0204] Signal Generation and Modulation

[0205] After determining the modulation mode and carrier frequency, the encrypted data stream is then QPSK modulated. The specific steps are as follows:

[0206] 1. Bit stream grouping: Divide the encrypted voice data stream (such as ciphertext) into several bit groups, each containing 2 bits of data, so as to correspond to the QPSK modulation symbols.

[0207] For example, suppose the encrypted data stream is: 11001010101011011110001101010100

[0209] The groups can be:

[0210] 11|00|10|10|10|11|01|00|11|10|10|10

[0211] 2. Mapping to symbols: Each bit group corresponds to a specific modulation symbol. In QPSK, four phases correspond to four symbols, usually expressed as:

[0212] 00→0°(sine wave)

[0213] 01→90° (the first quadrant of a sine wave)

[0214] 10→180° (the third quadrant of the sine wave)

[0215] 11→270° (the second quadrant of the sine wave)

[0216] According to the above bit group, it can be mapped as:

[0217] 11→270°|00→0°|10→180°|10→180°|01→90°|10→180°

[0218] 3. Signal waveform generation: Use the mapped symbols to generate the corresponding modulated signal waveform. The QPSK modulated signal can be represented by a sine wave, and each symbol corresponds to a sine wave signal with a phase.

[0219] The mathematical expression of the modulated signal can be expressed as:

[0220]

[0221] Where A is the amplitude and fc. is the carrier frequency φ n . is the phase. Assuming the selected carrier frequency is 1.5 GHz (L-band middle frequency), the signal expression can be obtained.

[0222] 4. Generate a sample signal: Assuming that the amplitude of the generated signal is 1 and the duration is the time interval of each symbol (such as 1ms), it can be calculated:

[0223] For the symbol "00", the signal is:

[0224] s0(t)=cos(2π×1.5×10 9 t).

[0226] For symbol "01", the signal is:

[0227]

[0228] For symbol "10", the signal is:

[0229] s2(t)=cos(2π×1.5×10 9 t+π).

[0231] For symbol "11", the signal is:

[0232]

[0233] Signal Power Control

[0234] In order to ensure that the signal has sufficient strength during transmission, signal power control is necessary. According to the changes in channel conditions, the power of the transmitted signal is adjusted in real time to offset possible signal attenuation and interference. The goal of power control is to maximize the quality of the signal at the receiving end and reduce the bit error rate (BER). A feedback mechanism can be used to monitor the quality of the received signal in real time and adjust the power.

[0235] Signal Transmission

[0236] After modulation and power control, the modulated signal will be sent to the low-orbit satellite through the antenna. L-band antennas usually use parabolic antennas to ensure the centralized transmission and directionality of the signal. The satellite forwards the received signal to the target receiving end to ensure the effective transmission of data from the transmitter to the receiver. This process involves complex satellite tracking and scheduling technology to ensure reliable transmission of signals in a dynamic environment.

[0237] Step S6: Satellite communication transmission

[0238] like Figure 3 As shown in the figure, in low-orbit satellite communications, anti-interference technology is crucial because the signal may be affected by a variety of interference sources. This step will combine the joint signal processing based on soft decision and the adaptive power control system to introduce its application in anti-interference in detail.

[0239] Soft decision decoding

[0240] At the signal receiving end, soft decision decoding technology is used to improve the signal recovery capability. Unlike hard decision decoding, soft decision decoding not only considers the 0 and 1 of the bit, but also comprehensively evaluates the received signal strength of each bit. This method can better cope with noise and interference in the signal.

[0241] Example: Assume that the received signal contains interference, resulting in some bit errors. Traditional hard decision decoding may only decide the bit value based on a certain threshold, such as:

[0242] The received signal is 0.7, which is considered to be bit 1;

[0243] The received signal is 0.3 which is considered to be bit 0.

[0244] In soft decision decoding, the received signal is converted into a probability distribution. For example, the signal strengths of 0.7 and 0.3 are represented by:

[0245] P(1)=0.7

[0246] P(0)=0.3

[0247] This processing allows the decoder to take all signal information into account, improving its ability to recover the original data, especially in poor signal quality situations.

[0248] Joint signal processing

[0249] Combining multiple signal processing technologies can effectively offset multipath effects and other interference sources. The receiving end optimizes the received signal through frequency domain equalization and time domain equalization.

[0250] Example: Assume that at the receiving end, the signal is affected by multipath propagation, resulting in distortion of the received signal. Through frequency domain equalization, the system can analyze the spectral characteristics of the signal and adjust the gain of each frequency component to restore the original signal. For example, by analyzing the frequency components of the signal through FFT, it is found that some frequency bands are interfered. The system can reduce the gain of these frequency bands and increase the gain of other frequency bands, thereby improving the overall signal quality.

[0251] Adaptive Power Control

[0252] Adaptive power control based on real-time channel status is an important means of optimizing transmission. By monitoring channel quality, the system can reduce the transmit power when interference is high to reduce the impact on adjacent frequency signals, and increase the power when channel conditions are good to increase the transmission rate.

[0253] Example: Assume that during a certain period of time, the system detects that the channel signal-to-noise ratio (SNR) is 8dB, and the system decides to reduce the transmit power to a certain level to avoid interference with other channels. When the SNR rises to 15dB, the system increases the transmit power to maximize data transmission efficiency.

[0254] Channel Status Feedback

[0255] A channel status feedback mechanism is established between the transmitter and the receiver, whereby the receiver periodically reports channel quality information to the transmitter to help the transmitter optimize the modulation mode and power setting.

[0256] Example: After receiving each data packet, the receiver sends a feedback signal containing the channel quality, for example:

[0257] “Current channel quality: good (SNR = 15dB)”

[0258] "Current channel quality: poor (SNR = 6dB)"

[0259] Based on this feedback information, the transmitter can adjust its signal processing strategy, for example, selecting a lower modulation method (such as QPSK) and a higher FEC coding rate when the channel quality is poor, to ensure reliable data transmission.

[0260] Step S7: demodulate the signal through the signal demodulation module

[0261] After the receiver successfully receives the satellite signal, signal demodulation is the key process to convert the RF signal into a digital signal. This process not only ensures the integrity of the information, but also lays the foundation for subsequent decryption and audio reconstruction. The following is the details of signal demodulation:

[0262] The receiver successfully receives the satellite signal, which is usually manifested by the received signal strength reaching a preset threshold. This process relies on efficient receiving antennas and low-noise amplifiers that can extract valid signals in a noisy and interfering environment.

[0263] The main purpose of signal demodulation is to convert the received RF signal into a processable digital data stream. Only through demodulation can the information carried on the RF signal be recovered for subsequent decryption and decoding.

[0264] The theoretical basis of signal demodulation is to extract the characteristics of the modulated signal (such as phase, frequency or amplitude) and convert it into a corresponding digital bit stream. For QPSK modulated signals, demodulation technology mainly includes:

[0265] Phase demodulation: QPSK modulation relies on the phase change of the signal, so the demodulator needs to accurately identify the phase of the received signal.

[0266] Sampling and symbol decision: The signal is sampled and the phase position of each symbol is determined, and then mapped back to the corresponding bit group.

[0267] The process of converting the satellite signal into a digital data stream using a QPSK demodulator in a receiver is as follows:

[0268] Amplification and down-conversion of received signals: The received high-frequency RF signal is first amplified by a low-noise amplifier and then down-converted to a baseband signal (lower frequency signal) for subsequent demodulation processing.

[0269] Phase synchronization: Use a phase-locked loop (PLL) or other phase synchronization techniques to align the phase of the received signal with the phase of the demodulator's local oscillator. Phase synchronization ensures that the demodulator can accurately identify the phase information of each symbol.

[0270] Demodulation process: The down-converted baseband signal is input to the QPSK demodulator. The demodulator converts each symbol into a corresponding bit group by analyzing the phase information of the signal. For example:

[0271] If the received signal phase is 0°, the corresponding bit is "00";

[0272] If the received signal phase is 90°, it corresponds to bit “01”;

[0273] If the received signal phase is 180°, it corresponds to bit “10”;

[0274] If the received signal phase is 270°, it corresponds to bit "11".

[0275] Assume that the received signal phase sequence is:

[0276] 0°|270°|90°|180°

[0277] The corresponding decoding result is:

[0278] 00|11|01|10

[0279] Bit stream reassembly: The demodulated bit groups are reassembled into a complete digital bit stream in preparation for subsequent decryption processing.

[0280] Step S8: Decryption by decryption module

[0281] After the signal demodulation is completed, the next step is the signal decryption process. This step aims to restore the demodulated digital data stream to the original voice data to ensure the security and confidentiality of the information.

[0282] The premise of signal decryption processing is that the received digital data stream has been demodulated to ensure the integrity and accuracy of the data stream. In addition, the receiving end must have the same decryption key and algorithm as the sending end.

[0283] The main purpose of decryption is to restore the encrypted digital data stream to the original voice data to ensure the confidentiality of information and the security of transmission. Only after decryption can the user hear the real voice content.

[0284] Signal decryption usually uses a symmetric encryption algorithm (such as AES, DES, etc.), and the encryption and decryption processes use the same key. AES (Advanced Encryption Standard) is a widely used encryption algorithm with high security and efficiency.

[0285] Key and Initialization Vector (IV): The decryption process requires the key and IV generated during encryption. IV is used to ensure that the same plaintext generates a different ciphertext each time it is encrypted.

[0286] Decryption process: Use the AES decryption algorithm to decrypt the received ciphertext and convert it into original voice data.

[0287] Assuming that the received digital data stream is ciphertext, the decryption process can be represented by the following sample code:

[0288] fromCrypto.CipherimportAES

[0289] fromCrypto.Util.Paddingimportunpad

[0290] #Assume there is a shared key and received ciphertext

[0291] #The key shared by the sender and receiver

[0292] key=b'ThisIsASecretKey'

[0293] #Extract the IV from the packet

[0294] iv = received_packet['iv']

[0295] #Ciphertext extracted from the data packet

[0296] ciphertext=received_packet['ciphertext']

[0297] # Initialize the AES decryptor

[0298] cipher=AES.new(key,AES.MODE_CBC,iv)

[0299] #Decrypt and remove padding

[0300] decrypted_data=unpad(cipher.decrypt(ciphertext),AES.block_size)

[0301] Step S9: Speech decoding by the speech coding module

[0302] Once decryption is complete, the recovered digital data stream must then be decoded to produce a playable audio signal. This process ensures that the decrypted voice data can be restored to an audible audio format.

[0303] The condition for voice decoding is that the decrypted digital data stream is complete and undamaged original voice data, using the G.729 audio coding format.

[0304] The main purpose of decoding is to convert the encoded voice data into an audio signal audible to the human ear so that the user can hear the voice content clearly.

[0305] G.729 coding is a widely used audio coding standard, mainly used for low bit rate speech coding. Its decoding process involves the following steps:

[0306] Decoder: Use the G.729 decoder to convert the bit stream into an audio signal in pulse code modulation (PCM) format.

[0307] Reconstruct the audio waveform: Convert the PCM signal to an analog signal for output through the speaker.

[0308] Assuming that the decrypted data is a bit stream in G.729 format, the decoding process can be represented by the following pseudo code:

[0309] #Use the G.729 decoder to convert the decrypted data into a PCM audio signal

[0310] pcm_audio = g729_decoder (decrypted_data) #decode to PCM format

[0311] #Play the PCM audio signal to the speaker

[0312] play_audio(pcm_audio)#play audio

[0313] Step S10: Performance monitoring and user feedback

[0314] After voice playback is completed, performance monitoring and user feedback collection are required to ensure system reliability and user experience.

[0315] The condition for performance monitoring is that the system can collect relevant data during operation and can effectively interact with users to obtain feedback.

[0316] The purpose of performance monitoring is to evaluate the quality of voice transmission and system performance in real time, understand the system experience and existing problems through user feedback, and make necessary adjustments and improvements.

[0317] Performance monitoring can be done in the following ways:

[0318] Real-time data monitoring: Use monitoring tools to record system performance indicators, such as bit error rate (BER), signal-to-noise ratio (SNR), latency, etc.

[0319] User feedback collection: Collect users' opinions and suggestions on audio quality, call clarity, etc. through questionnaires or feedback mechanisms.

[0320] Data analysis: Analyze the collected data to identify potential problems and perform targeted optimization.

[0321] Through the above method, the present invention can achieve the following effects:

[0322] 1. The present invention has efficient data compression: the G.729 coding algorithm and linear predictive coding (LPC) technology are used to reduce the bit rate of voice data from the traditional 64kbps to 8kbps. This significant compression not only saves bandwidth resources, but also reduces transmission costs. In low-bandwidth environments, this method can effectively improve the efficiency of voice transmission, ensuring that users can still enjoy a clear call experience when data traffic is limited.

[0323] 2. Enhanced security: This method introduces encryption processing after voice encoding, especially the use of the Advanced Encryption Standard (AES) algorithm, to ensure the confidentiality and integrity of data during transmission. By encrypting voice data, it can effectively prevent unauthorized access and data theft, and protect user privacy. This security measure is becoming increasingly important in modern communications, especially in situations involving sensitive information.

[0324] 3. The present invention has excellent anti-interference ability: By using QPSK modulation technology, the method improves the anti-interference performance of the signal in long-distance transmission. QPSK modulation can transmit 2 bits of information in each symbol, which has higher spectrum utilization than traditional BPSK modulation. In addition, the introduction of adaptive power control strategy enables the signal to dynamically adjust the transmission power when facing various interferences, thereby improving the signal quality and ensuring the stability of transmission.

[0325] 4. The present invention has a real-time feedback mechanism: With the support of the channel status feedback mechanism, the receiving end can regularly report channel quality information to the sending end. Based on these feedbacks, the sending end adjusts the modulation mode and power setting in real time to optimize the transmission quality. This dynamic adjustment mechanism not only improves the reliability of transmission, but also reduces the bit error rate (BER), ensuring that users can get a high-quality call experience under various conditions.

[0326] 5. The present invention has comprehensive signal processing: The method adopts soft decision decoding and joint signal processing technology, which significantly enhances the signal recovery ability. Compared with traditional hard decision decoding, soft decision decoding can take into account the strength and noise influence of the signal, making the decoding process more accurate. In addition, joint signal processing can effectively offset multipath propagation and other interference sources, ensuring that the signal maintains high clarity and quality in complex environments.

[0327] 6. User experience optimization: Performance monitoring and user feedback collection mechanisms enable the system to evaluate the quality of voice transmission in real time and make timely adjustments. By monitoring system performance indicators (such as bit error rate, signal-to-noise ratio, etc.) and combining user feedback, the development team can identify potential problems and make targeted optimizations. This mechanism not only improves the user's call quality, but also enhances user satisfaction, making the communication experience smoother.

[0328] The above description is only a preferred embodiment of the present invention and does not constitute any other form of limitation to the present invention. Any modification or equivalent change made based on the technical essence of the present invention still falls within the scope of protection required by the present invention.

Claims

1. An end-to-end voice transmission method based on a low-orbit satellite communication vocoder channel, characterized in that: The steps include: Step S1: Voice signal collection Through the microphone, the user's voice input is converted into an electrical signal, which becomes the basis of voice data; Step S2: Digitization of speech signal The collected speech signal is digitized through sampling and quantization; Step S3: Speech encoding S31, voice encoding is performed via a voice encoding module The digitized speech signal is compressed and G.729 is selected as the coding algorithm. The G.729 algorithm extracts the characteristics of the speech signal by using linear predictive coding technology. The following are the specific steps of the process: S311, signal framing: The continuous speech signal is divided into multiple short time frames, each frame is 20 milliseconds long and overlaps 10 milliseconds; S312, Linear Prediction Analysis: Apply linear prediction analysis to each frame and calculate the prediction coefficients. LPC predicts the current sample value by building a linear model, using the weighted sum of the previous N samples. These weighted coefficients reflect the short-term characteristics of the signal. Assume that the audio signal of a frame is Then the LPC model can be expressed as: Among them, ak is the prediction coefficient, P is the prediction order, and e[n] is the prediction error; S313, Quantization and Coding: The prediction coefficients are quantized using the number of bits, and at the same time, the prediction error signal of the LPC model is also quantized and encoded; S32, Data Compression After encoding using the G.729 algorithm, the amount of compressed voice data is reduced; Step S4: Encryption processing by encryption module After voice encoding is completed, voice data encryption is performed to ensure the security of voice transmission. The specific steps of encryption are as follows: S41, encryption algorithm selection A symmetric encryption algorithm is used. AES in the symmetric encryption algorithm supports keys of different lengths. The appropriate key length can be selected according to specific security requirements. S42. Key Management Key management strategies include the following aspects: Key generation: Generate keys using a strong random number generator; Key exchange: To ensure that only the communicating parties can obtain the encryption key, a key exchange protocol is used. The key exchange protocol allows the two parties to securely share the key without directly transmitting the key; Key storage: Use secure hardware modules or software encryption libraries to encrypt and store keys; S43. Data encryption implementation When encrypting the encoded voice data, the AES encryption algorithm needs to be applied to the data stream. This process includes the following steps: Initialize the encryptor: create an AES encryption instance, select the CBC mode, and introduce the initial vector (IV). Encrypted data: Encrypt the encoded G.729 data using the AES cipher. The data needs to be padded to ensure that its length is a multiple of the block size. Data formatting: The encrypted data needs to be packaged into packets, which contain the ciphertext, initialization vector (IV), and necessary metadata to ensure that the same IV is used when the receiving end can decrypt it; S44. Data integrity verification By performing a hash operation on the ciphertext and the key, a unique MAC value is generated. This value is sent together with the ciphertext. The receiving end can verify the MAC value when decrypting the data to ensure the integrity of the data. Step S5: Modulate the signal through the signal modulation module After completing the voice coding and encryption processing, the processed voice data is converted into a radio frequency signal suitable for transmission in low-orbit satellite communications through channel modulation. The specific steps are as follows: S51, modulation mode selection Select QPSK, or quadrature phase shift keying, which is an efficient phase modulation technique that can convey 2 bits of information per symbol; S52, Band Selection Select the L band suitable for mobile communication and low-speed data transmission as the carrier frequency; S53, Signal Generation and Modulation After the modulation mode and carrier frequency are determined, the encrypted data stream is then subjected to QPSK modulation. The specific steps are as follows: S531, bit stream grouping: Divide the encrypted voice data stream into multiple bit groups, each group containing 2 bits of data, so as to correspond to the QPSK modulation symbols; S532, map to symbols: Each bit group corresponds to a specific modulation symbol. In QPSK, the four phases correspond to four symbols, expressed as: 00→0° sine wave 01→90° The first quadrant of the sine wave 10→180° sine wave in the third quadrant 11→270° sine wave in the second quadrant According to the above bit group, it can be mapped as: 11→270°|00→0°|10→180°|10→180°|01→90°|10→180° S533, signal waveform generation: The mapped symbols are used to generate the corresponding modulated signal waveform. The QPSK modulated signal can be represented by a sine wave, and each symbol corresponds to a sine wave signal with a phase. The mathematical expression of the modulated signal is as follows: Where A is the amplitude and fc. is the carrier frequency φ n . is the phase. Assuming the selected carrier frequency is 1.5 GHz, the signal expression can be obtained; S534, generate sample signal: Assuming that the amplitude of the generated signal is 1 and the duration is the time interval of each symbol, it can be calculated: For symbol "00", the signal is: s0(t)=cos(2π×1.5×10 9 t) For symbol "01", the signal is: For symbol "10", the signal is: s2(t)=cos(2π×1.5×10 9 t+π) For symbol "11", the signal is: S54, signal power control According to the changes in channel conditions, the power of the transmitted signal is adjusted in real time to offset possible signal attenuation and interference. When adjusting the power of the transmitted signal, a feedback mechanism is used to monitor the quality of the received signal in real time and make power adjustments; S55, Signal Transmission After modulation and power control, the modulated signal will be sent to the low-orbit satellite through the L-band antenna, which uses a parabolic antenna. The satellite will forward the received signal to the target receiving end to ensure the effective transmission of data from the transmitter to the receiver; Step S6: Satellite communication transmission Combined with soft-decision-based joint signal processing and adaptive power control system, anti-interference in low-orbit satellite communications, S61, soft decision decoding At the signal receiving end, soft decision decoding technology is used to improve the signal recovery capability; S62, Joint Signal Processing The receiving end optimizes the received signal through frequency domain equalization and time domain equalization to offset multipath effects and other interference sources; S63, Adaptive Power Control Adaptive power control is performed based on real-time channel status to achieve optimized signal transmission. By monitoring channel quality, the transmit power is reduced when interference is high, and the power is increased when channel conditions are good. S64, channel status feedback Establish a channel status feedback mechanism between the transmitter and the receiver, where the receiver periodically reports channel quality information to the transmitter to help the transmitter optimize the modulation mode and power setting; Step S7: Demodulation by demodulation module After the receiving end successfully receives the satellite signal, the RF signal is converted into a digital signal through signal demodulation, as follows: The receiving end successfully receives the satellite signal through the receiving antenna and low noise amplifier, which is manifested by the received signal strength reaching the preset threshold. Extract the features of the modulated signal and convert it into a corresponding digital bit stream. For QPSK modulated signals, the demodulation technology includes: Phase demodulation: QPSK modulation relies on the phase change of the signal, so the demodulator needs to accurately identify the phase of the received signal. Sampling and symbol decision: By sampling the signal and determining the phase position of each symbol, it is mapped back to the corresponding bit group. The process of converting the satellite signal into a digital data stream using a QPSK demodulator in a receiver is as follows: Amplification and down-conversion of received signals: The received high-frequency RF signal is first amplified by a low-noise amplifier and then down-converted to a baseband signal for subsequent demodulation processing; Phase synchronization: Using a phase-locked loop, the phase of the received signal is aligned with the phase of the demodulator's local oscillator. Demodulation process: The down-converted baseband signal is input into the QPSK demodulator, which converts each symbol into a corresponding bit group by analyzing the phase information of the signal; Bit stream reassembly: reassemble the demodulated bit groups into a complete digital bit stream in preparation for subsequent signal decryption processing; Step S8: Decryption by decryption module After the signal demodulation is completed, the demodulated digital data stream is restored to the original voice data. The premise of signal decryption processing is that the received digital data stream has been demodulated. In addition, the receiving end needs to have the same decryption key and algorithm as the sending end. The details are as follows: Using a symmetric encryption algorithm, the encryption and decryption processes use the same key. Key and Initialization Vector (IV): The decryption process requires the key and IV generated during encryption. IV is used to ensure that the same plaintext generates different ciphertext each time it is encrypted. Decryption process: Use the AES decryption algorithm to decrypt the received ciphertext and convert it into original voice data; Step S9: Speech decoding by the speech decoding module After decryption is completed, the recovered digital data stream is decoded to generate a playable audio signal; The condition for voice decoding is that the decrypted digital data stream is complete and undamaged original voice data, using the G.729 audio coding format. The decoding process is as follows: Decoder: Use the G.729 decoder to convert the bit stream into an audio signal in pulse code modulation format; Reconstruct audio waveform: convert PCM signal into analog signal; Step S10: Performance monitoring and user feedback After completing the voice playback, conduct performance monitoring and collect user feedback. The prerequisite for performance monitoring is that the system can collect relevant data during operation and can effectively interact with users to obtain feedback. Through user feedback, we can understand the system's user experience and existing problems, and make necessary adjustments and improvements. Performance monitoring can be carried out in the following ways: Real-time data monitoring: Use monitoring tools to record system performance indicators. User feedback collection: Collect user opinions and suggestions through questionnaires or feedback mechanisms. Data analysis: Analyze the collected data to identify potential problems and perform targeted optimization.

2. The end-to-end voice transmission method based on a low-orbit satellite communication vocoder channel according to claim 1, characterized in that: In step S2, the speech signal is digitized by adopting a 16-bit PCM format at a sampling frequency of 44.1 kHz.

3. The end-to-end voice transmission method based on a low-orbit satellite communication vocoder channel according to claim 1, characterized in that: In step S3, the G.729 algorithm effectively compresses the voice signal to a bit rate of 8 kbps per second while ensuring clear sound quality.

4. The end-to-end voice transmission method based on a low-orbit satellite communication vocoder channel according to claim 1, characterized in that: In step S4, the key lengths supported by AES include 128 bits, 192 bits, and 256 bits. The user selects the appropriate key length based on specific security requirements.

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