Method of adaptive switching of siso / mimo mode for fso communication

Abstract

The application discloses a FSO communication method of adaptive switching of SISO / MIMO modes, which comprises the following steps: establishing a FSO composite atmospheric channel model; based on a GNURadio platform, writing a laser module, a modulation and demodulation module and a real-time error code rate monitoring feedback module, setting an oscilloscope module to observe a signal waveform, and building an adaptive SISO / MIMO-FSO link model; obtaining error code rate data of SISO and MIMO modes under different influences, and determining a threshold value based on a switching criterion of an upper bound of an FEC error code rate, and selecting a suitable best signal transmission mode. The transmission end of the application realizes dynamic switching of transmission modes according to feedback information, adopts a SISO link when channel quality is good to reduce energy consumption, and switches to a MIMO link when channel quality is poor to enhance signal strength and reliability, thereby providing a theoretical basis for maintaining robustness and stability of a FSO system in a changeable environment.

Description

Technical Field

[0001] This invention belongs to the field of free space optical communication (FSO) technology, specifically relating to an FSO communication method with adaptive switching between SISO / MIMO modes. Background Technology

[0002] One of the most important and fundamental issues in wireless communication is the scarcity of radio frequency (RF) spectrum. Due to the insufficiency of RF spectrum, additional RF bandwidth allocation is insufficient to meet the demands of high data transmission rates. Compared to traditional RF communication, fiber optic communication (FSO) has become a research hotspot in the future of communications due to its advantages of high bandwidth, no spectrum limitations, and high security. In urban communications, FSO can supplement or replace fiber optic communication, particularly suitable for areas where fiber optic laying is difficult, enabling high-bandwidth data transmission between buildings, such as high-speed internet access and local area network (LAN) interconnection. In military communications, FSO, due to its high confidentiality and anti-jamming capabilities, is suitable for tactical data transmission on the battlefield, supporting the interconnection of command and control, reconnaissance and surveillance, and combat systems. Furthermore, in scenarios requiring rapid deployment of communication systems, such as disaster relief, emergency response, and large-scale events, FSO can quickly establish temporary communication links, providing reliable data transmission services.

[0003] Generally, the performance of an FSO communication link depends primarily on the climate and physical characteristics of its installation location. Key factors affecting performance include atmospheric attenuation, scintillation caused by turbulence, pointing errors due to aperture alignment or building movement, solar interference, and line-of-sight obstructions. These factors often lead to fluctuations in signal strength and degraded signal quality, thus impacting the stability and performance of the communication system. Turbulence is one of the major challenges in free-space optical communication, causing strong intensity fluctuations in the optical signal during transmission, thereby affecting the signal quality at the receiver. Pointing errors are also a significant issue; thermal expansion and minor vibrations of buildings can cause inaccurate beam pointing between the transmitter and receiver, resulting in signal loss and reduced signal strength received at the receiver. The energy attenuation of the optical signal during transmission is called link loss. Link loss increases with transmission distance, limiting the transmission distance and reliability of FSO systems. This is especially true under adverse weather conditions such as heavy fog, where water molecules and suspended particles in the atmosphere absorb and scatter the optical signal, further attenuating the signal and significantly reducing transmission throughput.

[0004] In existing technologies, MIMO is a reliable technique for achieving spatial diversity and mitigating fading caused by atmospheric turbulence and attenuation caused by fog in long-distance data transmission. Adaptive transmission techniques (such as adaptive modulation, adaptive rate, and adaptive power) provide a feasible solution for suppressing the impact of atmospheric turbulence on laser signal transmission and improving the system's communication performance under various channel conditions. This allows for the selection of different MIMO transmission modes—diversity, multiplexing, or hybrid modes—based on channel conditions, achieving maximum average channel capacity while maintaining a reliable average bit error rate (BER).

[0005] In FSO (Fiber Optic Sort), the beam can be modulated using analog or digital signals. SDR (Software-Defined Radio) provides a reusable and future-proof platform by combining the RF-to-baseband transceiver physical layer with a digital intelligent processor. This offers several advantages. First, as an open-source software and hardware co-development platform, GNURadio provides a wealth of modules and tools to support rapid prototyping. Through GNURadio's graphical interface and Python programming interface, researchers can flexibly iterate and optimize the design of FSO systems quickly, making the design and testing process more efficient. Second, compared to traditional hardware implementations, researchers can use GNURadio for preliminary system design and performance evaluation without the need for expensive hardware, significantly reducing development costs. Finally, GNURadio allows researchers to perform system simulation and actual hardware testing on the same platform. Through integration with hardware devices such as USRP (United States Reliable Components), system designs can be verified in simulation environments and seamlessly transitioned to actual hardware environments for further testing and verification. Summary of the Invention

[0006] The purpose of this invention is to provide an FSO communication method with adaptive switching between SISO / MIMO modes, which solves the problem of low communication reliability of existing free-space optical communication systems in composite atmospheric channels.

[0007] The technical solution adopted in this invention is: an FSO communication method with SISO / MIMO mode adaptive switching, comprising the following steps:

[0008] Step 1: Establish an FSO composite atmospheric channel model that considers the combined effects of atmospheric turbulence, pointing error, and fog loss;

[0009] Step 2: Based on the FSO composite atmospheric channel model obtained in Step 1, construct an adaptive SISO / MIMO-FSO communication system model and generate signals;

[0010] Step 3: Based on the communication system model obtained in Step 2, obtain the bit error rate data of the signal under SISO and MIMO modes under different turbulence intensities, pointing errors and visibility ranges, and establish a threshold lookup table for mode switching based on the bit error rate data.

[0011] Step 4: The transmitter sends the signal into the atmospheric composite channel. After receiving the signal, the receiver compares the channel state information with the available thresholds in the threshold lookup table and selects the best signal transmission mode from the SISO and MIMO modes.

[0012] The invention is further characterized in that,

[0013] The FSO composite atmospheric channel model established in step 1 is expressed as follows:

[0014] (1)

[0015] In the formula, This refers to the optical power at the receiving end. It is the optical power at the transmitting end; Indicates the receiver's responsivity; It is additive white Gaussian noise; It is the normalized channel fading coefficient, expressed as , Represents the random components of atmospheric turbulence. This represents the random component pointing to the error. This represents the random component of fog loss.

[0016] random components of fog loss It's about wavelength. Functions:

[0017] (2)

[0018] In the formula, It is the transmission distance. It is the attenuation coefficient, expressed as:

[0019] (3)

[0020] In the formula, and These are the molecular absorption coefficient and the aerosol absorption coefficient, respectively. The molecular scattering coefficient is... The aerosol scattering coefficient after fog attenuation is given by the Kim model:

[0021] (4)

[0022] In the formula, Visibility level, The wavelength of the light source, This represents the size distribution of scattered fog particles in the Kim model.

[0023] random components of atmospheric turbulence The probability density function is characterized using the Gamma-Gamma turbulence model:

[0024] (11)

[0025] In the formula, For the Gamma function, This indicates it is of the second category. The modified Bessel function of order 1 and These are parameters related to small-scale and large-scale turbulent eddies, expressed as:

[0026] (12)

[0027] (13)

[0028] In the formula, The Rytov variance is expressed as:

[0029] (8)

[0030] In the formula, It is the wave number. It is the transmission distance. Let be the refractive index structure constant, expressed as:

[0031] (9)

[0032] In the formula, It's atmospheric pressure. It's temperature. The distance between them is Temperature difference.

[0033] Random component of pointing error Represented as:

[0034] (14)

[0035] In the formula, This represents the radial displacement of the light spot. express Received power at =0; It is the equivalent beam waist radius and , , Represents the error function. It is the beam waist radius. The receiver radius is given.

[0036] The adaptive SISO / MIMO-FSO communication system model built in step 2 includes a laser module, a modulation module, a channel module encapsulating the FSO composite atmospheric channel model, a demodulation module, and a real-time bit error rate monitoring and feedback module. When generating the signal, the laser power and wavelength of the laser module are set, the DBPSK modulation format is adopted, clock recovery is performed, and a receiver matched filter is provided to eliminate inter-symbol interference. At the same time, the signal is downsampled to restore the phase and frequency synchronization of the digital modulation signal.

[0037] The process of establishing the threshold lookup table in step 3 is as follows: Keeping the fog loss, pointing error, and geometric loss parameters constant, changing the atmospheric turbulence, and based on the upper bound of the FEC bit error rate, establish a lookup table for switching between different modes of transmission based on different atmospheric turbulence at various link distances; keeping the pointing error, atmospheric turbulence, and geometric loss parameters constant, changing the fog loss, and based on the upper bound of the FEC bit error rate, establish a lookup table for switching between different modes of transmission based on different visibility at various link distances; keeping the fog loss, atmospheric turbulence, and geometric loss parameters constant, changing the pointing error, and based on the upper bound of the FEC bit error rate, establish a lookup table for switching between different modes of transmission based on different pointing errors at various link distances.

[0038] Step 4 specifically involves the transmitting antennas TA and TB transmitting the optical signal generated by the laser module into the atmospheric composite channel, which is then received by the receiving antennas RA and RB. The transmitting antenna TB is selected to be on or off based on the Channel State Information (CSI). When the atmospheric visibility of the channel is greater than the visibility threshold, or the refractive index structure constant is less than the refractive index structure constant threshold, or the jitter standard deviation of the pointing error is less than the jitter standard deviation threshold (i.e., the bit error rate is below the upper limit of the FEC bit error rate), the transmitting antenna TB is turned off, and a SISO link is used for transmission to save transmission power. When the atmospheric visibility of the channel is less than the visibility threshold, or the refractive index structure constant is greater than the refractive index structure constant threshold, or the jitter standard deviation of the pointing error is greater than the jitter standard deviation threshold (i.e., the bit error rate is above the upper limit of the FEC bit error rate), the transmitting antenna TB is turned on, and a MIMO link is used for transmission to obtain diversity gain.

[0039] The beneficial effects of this invention are: the SISO / MIMO mode adaptive switching FSO communication method of this invention enables the transmitter to dynamically switch the transmission mode based on feedback information. When the channel quality is good, the SISO link is used to reduce energy consumption, and when the channel quality is poor, the MIMO link is switched to enhance signal strength and reliability, providing a theoretical basis for the FSO system to maintain robustness and stability in a variable environment. Attached Figure Description

[0040] Figure 1 This is a schematic diagram illustrating the principle of the SISO / MIMO mode adaptive switching FSO communication method of the present invention.

[0041] Figure 2(a) shows the system bit error rate as a function of turbulence when L=300m, visibility V=1000m, and pointing error jit=0.02m in this invention.

[0042] Figure 2(b) shows the system bit error rate as a function of turbulence when L=500m, visibility V=1000m, and pointing error jit=0.02m in this invention.

[0043] Figure 2(c) shows the system bit error rate as a function of turbulence when L=1500m, visibility V=1000m, and pointing error jit=0.02m in this invention.

[0044] Figure 3(a) shows the turbulence intensity at a link distance L=300m in this invention. =10 -15 The system bit error rate as a function of visibility when the pointing error jit = 0.02m;

[0045] Figure 3(b) shows the turbulence intensity at a link distance L=500m in this invention. =10 -15 The system bit error rate as a function of visibility when the pointing error jit = 0.02m;

[0046] Figure 3(c) shows the turbulence intensity at a link distance L=1500m in this invention. =10 -15 The system bit error rate as a function of visibility when the pointing error jit = 0.02m;

[0047] Figure 4(a) shows the turbulence intensity at a link distance L=300m in this invention. =-15, the curve of system bit error rate as a function of pointing error when visibility V=1000m;

[0048] Figure 4(b) shows the turbulence intensity at a link distance L=500m in this invention. =-15, the curve of system bit error rate as a function of pointing error when visibility V=1000m;

[0049] Figure 4(c) shows the turbulence intensity at a link distance L=1500m in this invention. =-15, the curve of the system bit error rate as a function of pointing error when visibility V=1000m. Detailed Implementation

[0050] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0051] Example 1

[0052] This invention provides an FSO communication method with SISO / MIMO mode adaptive switching, implemented according to the following steps:

[0053] Step 1: Establish an FSO composite atmospheric channel model that considers the combined effects of atmospheric turbulence, pointing error, and fog loss;

[0054] Step 2: Based on the FSO composite atmospheric channel model obtained in Step 1, construct an adaptive SISO / MIMO-FSO communication system model and generate signals;

[0055] Step 3: Based on the communication system model obtained in Step 2, obtain the bit error rate data of the signal under SISO and MIMO modes under different turbulence intensities, pointing errors and visibility ranges, and establish a threshold lookup table for mode switching based on the bit error rate data.

[0056] Step 4: The transmitter sends the signal into the atmospheric composite channel. After receiving the signal, the receiver compares the channel state information with the available thresholds in the threshold lookup table and selects the best signal transmission mode from the SISO and MIMO modes.

[0057] Example 2

[0058] This invention provides an FSO communication method with adaptive switching between SISO / MIMO modes, such as... Figure 1 As shown, the specific steps are as follows:

[0059] Step 1: Develop system modules based on the GNURadio platform. These modules are connected in series. The signal sequentially passes through the established laser module, modulation module, channel module (including atmospheric turbulence, pointing error, and fog loss modules to simulate the impact of atmospheric conditions on the signal), demodulation module, and real-time bit error rate monitoring and feedback module. An oscilloscope module is then used to observe the signal waveform. The channel module encapsulates an FSO composite atmospheric channel model that considers the combined effects of atmospheric turbulence, pointing error, and fog loss.

[0060] In an FSO communication system, when a light beam propagates along a horizontal path in an atmospheric channel, it is affected by atmospheric fading, which impacts the optical power at the receiver. Represented as:

[0061] (1)

[0062] In the formula, It is the optical power at the transmitting end. Indicates the receiver's responsivity. It is additive white Gaussian noise. This is the normalized channel fading coefficient. Due to the combined effect of three influencing factors, the channel model consists of three parts, which can be expressed as follows: , Represents the random components of atmospheric turbulence. This represents the random component pointing to the error. This represents the random component of fog loss.

[0063] 1) For FSO links, the random component of fog loss It's about wavelength. Functions:

[0064] (2)

[0065] In the formula, It is the transmission distance. It is the attenuation coefficient, expressed as:

[0066] (3)

[0067] In the formula, and These are the molecular absorption coefficient and the aerosol absorption coefficient, respectively. The molecular scattering coefficient is... The aerosol scattering coefficient after fog attenuation is given by the Kim model:

[0068] (4)

[0069] In the formula, Visibility level, The wavelength of the light source, Table 1 shows the size distribution of scattered fog particles in the Kim model. Visibility levels for foggy days are as follows: Horizontal visibility less than 1 km is classified as fog; horizontal visibility between 200 and 500 meters is classified as dense fog; horizontal visibility between 50 and 200 meters is classified as heavy fog; and horizontal visibility less than 50 meters is classified as very dense fog.

[0070] Table 1 Fog Visibility Levels

[0071]

[0072] (5)

[0073] 2) Atmospheric turbulence is caused by the uneven distribution of air density due to temperature and pressure differences in different regions of the air. Atmospheric turbulence leads to rapid fluctuations in light intensity, a phenomenon known as scintillation. Scintillation causes temporal and spatial variations in light intensity on the receiving plane of the FSO system. For different thermal expansions within the channel, the scintillation index used to estimate the turbulence effect is:

[0074] (6)

[0075] In the formula, This represents the average value. It's light intensity, assuming plane wave propagation. Represented as:

[0076] (7)

[0077] In the formula, The diameter of the circular aperture after scaling down the Fresnel zone. It is the wave number. For the receiving aperture diameter, It refers to the transmission distance.

[0078] In laser transmission, the transmission distance is In the Kolmogorov turbulence spectrum, strong and weak undulations of plane waves are typically described by the Rytov variance value:

[0079] (8)

[0080] In the formula, Let be the refractive index structure constant, expressed as:

[0081] (9)

[0082] In the formula, It's atmospheric pressure. It's temperature. The distance between them is Temperature difference.

[0083] The turbulence intensity levels corresponding to different values ​​of the refractive index structure constant are:

[0084] (10)

[0085] For the turbulence module, random numbers are generated using a Gamma-Gamma distribution within the module, and its probability density function is:

[0086] (11)

[0087] In the formula, For the Gamma function, This indicates it is of the second category. The modified Bessel function of order 1 and These are parameters related to small-scale and large-scale turbulent eddies, expressed as:

[0088] (12)

[0089] (13)

[0090] The input signal, after being processed by Gamma-Gamma random numbers, is output as a signal attenuated by turbulence. A Gamma-Gamma turbulence model is used to characterize the random components of atmospheric turbulence. .

[0091] 3) Pointing error is also a key factor affecting FSO systems. FSO transceivers transmit highly directional, narrow beams that must be precisely aligned with the receiver's aperture. However, buildings are constantly in slight motion, a result of various factors including thermal expansion, wind swaying, and vibration. Due to the narrow transmit beam and the receiver's limited field of view, building swaying can affect transceiver alignment, leading to communication interruptions. Random components of pointing error... The expression is:

[0092] (14)

[0093] In the formula, This represents the radial displacement of the light spot. express Received power at =0; It is the equivalent beam waist radius and , , Represents the error function. It is the beam waist radius. The receiver radius is given.

[0094] Considering zero line-of-sight pointing error, the elevation angle and horizontal displacement both follow independent and identical Gaussian distributions, and the receiver radial displacement... Follows Rayleigh distribution:

[0095] (15)

[0096] In the formula, This represents the jitter variance of the receiver. From equations (14) and (15), we can see that... The probability density function can be expressed as:

[0097] (16)

[0098] In the formula, Indicates the receiver's equivalent beam radius With the standard deviation of pointing error jitter The ratio of .

[0099] Step 2: Based on the FSO composite atmospheric channel model established in Step 1, build an adaptive SISO / MIMO-FSO link model. The generated signal passes through the laser module, modulation module, channel module, demodulation module, and real-time bit error rate monitoring feedback module. Set up an oscilloscope module to observe the signal waveform.

[0100] The laser module has a laser power of 300mW and a wavelength of 1500nm. After passing through the laser module, the signal is modulated by a DBPSK modulation module. The modulated DBPSK signal then passes through a series of turbulence, fog loss, geometric loss, and pointing error modules before being input to the demodulation module for demodulation. The demodulation module uses a PolyphaseClock Sync module for signal optimization. This module performs clock recovery and provides a receiver matched filter to eliminate ISI, while also downsampling the signal. Even after passing through the PolyphaseClock Sync module, the signal still has phase and frequency offset issues. The output signal then passes through the Costas Loop module to restore the phase and frequency synchronization of the digitally modulated signal. The Costas Loop first performs a complex multiplication of the received signal with a copy that has a different phase. Based on the result of the complex multiplier, it estimates the phase error of the signal and then adjusts the phase of the signal through a feedback loop to minimize the error. Furthermore, the Costas Loop can also estimate the frequency error caused by carrier drift during signal transmission and adjust the signal frequency based on the frequency error to ensure that the received signal is synchronized with the local reference signal. In this way, the Costas loop can synchronize the phase and frequency of the digital modulated signal at the receiving end, thereby effectively demodulating the signal and restoring the original digital data. The signal after passing through the Costas Loop module finally passes through the differential demodulation module, successfully recovering the original signal.

[0101] Step 3: After executing Step 2, the bit error rate data of the SISO system and MIMO system under different visibility ranges, different turbulence intensities, and different pointing errors are obtained. A threshold lookup table for mode switching is established based on the data.

[0102] Step 4: The transmitting antennas TA and TB transmit the optical signal generated by the laser into the atmospheric composite channel, which is then received by the receiving antennas RA and RB. The transmitting antenna TB is selected to be turned on or off according to the threshold obtained in step 2, so as to realize the switching between adaptive SISO and 2×2 MIMO modes and complete the adaptive FSO communication.

[0103] When the atmospheric visibility V in the channel is greater than the visibility threshold V (Threshold), or the refractive index structure constant... Less than the refractive index structural constant threshold (Threshold), or the jitter standard deviation Jit is less than the jitter standard deviation threshold Jit(Threshold), that is, the system bit error rate is lower than the upper bound of the FEC bit error rate (3.8×10). -3 When the transmit antenna TB is turned off, the system uses a SISO link for transmission to save transmit power, provided that the atmospheric visibility V of the channel is below the visibility threshold V(Threshold), or the refractive index structure constant is within a certain range. Greater than the refractive index structural constant threshold (Threshold), or the jitter standard deviation Jit is greater than the jitter standard deviation threshold Jit(Threshold), that is, the system bit error rate is higher than the upper bound of the FEC bit error rate (3.8×10). -3 With the transmit antenna TB activated, the system employs a MIMO link for transmission to achieve diversity gain, thereby mitigating signal loss caused by atmospheric composite channels. Under varying visibility ranges, turbulence intensities, and pointing errors, the base feedback mode continues to operate, enabling the system to continuously perform adaptive mode switching.

[0104] Example 3

[0105] Figures 2(a) to (c) show the bit error rate of SISO and MIMO links using DBPSK modulation format as a function of the refractive index structure constant at link distances of 300m, 500m, and 1500m, with a fixed visibility of 1000m and a pointing error jitter of 0.03m. The change curve. The upper limit of mode switching, using FEC forward error correction codes, is the maximum bit error rate that can be corrected, which is 3.8 × 10⁻⁶. -3 That is, before the bit error rate of the SISO link reaches the upper limit of FEC, the system needs to switch to the MIMO link with a bit error rate lower than the upper limit of FEC to ensure normal communication of the system, until the MIMO link can no longer meet the communication requirements.

[0106] At a link distance of 300m, channel conditions are good and link loss is low. The bit error rate of the MIMO link is slightly better than that of the SISO link. Using the SISO system saves power and eliminates the need for handover. When the link distance increases to 500m, the MIMO link performs better under turbulence intensity 10. -13 < <10 -11 Within the specified range, the bit error rate is better than that of the SISO link, and the system handover interval is 10. -12 < <10 -11 However, when the link length continues to increase to 1500m, the MIMO link operates under turbulence intensity of 10... -15 < <10 -12 Within the range, the bit error rate is better than that of the SISO link, and the switching interval is 10.-14 < <10 -13 As transmission distance increases and losses increase, the range of refractive index structure constants between the MIMO link and the SISO link widens, making the advantages of the MIMO system more pronounced. The handover visibility threshold lookup table is shown in Table 2.

[0107] Table 2 Turbulence Switching Threshold Lookup Table

[0108]

[0109] Example 4

[0110] Figures 3(a) to (c) show the results at link distances of 300m, 500m, and 1500m, respectively, with fixed visibility and weak turbulence intensity. =10 -15 The pointing error jitter is set to 0.03m. The bit error rate (BER) curves for SISO and MIMO links using DBPSK signal format are shown as a function of visibility. The handover strategy is: the handover upper limit is set to the maximum BER that can be corrected by FEC forward error correction codes, which is 3.8 × 10⁻⁶. -3 That is, before the bit error rate of the SISO link reaches the upper limit of the FEC, the system needs to switch to a MIMO link with a bit error rate lower than the upper limit of the FEC to resist channel fading and ensure normal communication of the system, until the MIMO link can no longer meet the communication requirements. The four gray ranges represent different levels of fog (see Table 1).

[0111] For a 300m link, when the visibility V > 300m, the performance of the SISO link is nearly the same as that of the MIMO link, and the SISO link can be adopted by the system. The MIMO link has a lower bit error rate than the SISO link within the visibility range of 140m < V < 200m, and the switching point of the system is V = 190m. However, under the conditions of strong dense fog and partial dense fog (V < 170m), due to the extremely poor channel, the MIMO system cannot meet the communication requirements either. For a 500m link, when the visibility V > 500m, the performance of the SISO link is close to that of the MIMO link, and the SISO link can be adopted by the system. The MIMO link has a lower bit error rate than the SISO link within the visibility range of 200m < V < 500m, and the switching point of the system is V = 360m. However, under the conditions of "strong dense fog", "dense fog" and partial "heavy fog" (V < 330m), due to the extremely poor channel, the MIMO system cannot meet the communication requirements either. For a 1500m link, when the visibility V > 800m, the performance of the SISO link is similar to that of the MIMO link, and the SISO link can be adopted by the system. The MIMO link has a lower bit error rate than the SISO link within the visibility range of 500m < V < 800m, and the switching point of the system is V = 580m. However, under the conditions of "strong dense fog", "dense fog", "heavy fog" and partial "fog" (V < 530m), due to the extremely poor channel and the influence of detector noise, the MIMO system cannot meet the communication requirements either. The switching visibility threshold lookup table is shown in Table 3:

[0112] Table 3 Switching Visibility Threshold Lookup Table

[0113]

[0114] Example 5

[0115] Figures 4(a) to 4(c) show the curves of the bit error rates of the SISO and MIMO links with the DBPSK signal format varying with the pointing error jitter Jit at the fixed visibility of 1000m, the fixed pointing error jitter of 0.03m, and the fixed weak turbulence intensity =10 -15 , for the 300m, 500m and 1500m link distances. The switching strategy is: the upper switching limit adopts the maximum bit error rate of 3.8×10 -3 that can be corrected by the FEC forward error correction code. That is, before the bit error rate of the SISO link reaches the FEC upper bound, the system needs to switch to the MIMO link with a bit error rate lower than the FEC upper bound to ensure the normal communication of the system until the MIMO link can no longer meet the communication requirements.

[0116] For a 300m link, when the pointing error jitter Jit > 0.06m, the SISO link cannot meet the communication requirements, while the MIMO link can always meet the system communication requirements within the pointing error jitter Jit < 0.08m. The system switching point is Jit = 0.06m. For a 500m link, when the pointing error jitter Jit > 0.04m, the SISO link cannot meet the communication requirements, and the MIMO link cannot meet the system communication requirements when the pointing error jitter Jit > 0.07m. The system switching point is Jit = 0.04m. For a 1500m link, due to the extremely poor link conditions, both SISO and MIMO links cannot meet the system communication requirements. The switching threshold lookup table is shown in Table 4.

[0117] Table 4 Pointing Error Switching Threshold Lookup Table

[0118]

[0119] Example 6

[0120] The SISO / MIMO mode adaptive switching FSO communication method of this invention employs DBPSK encoding. The receiver feeds back the instantaneous atmospheric channel state estimation information to the transmitter. The transmitter compares this information with a switching threshold to achieve dynamic switching of transmission modes. When channel quality is good, a SISO link is used to simplify the system and reduce energy consumption; when channel quality is poor, a MIMO link is switched to enhance signal strength and reliability. Considering the effects of fog loss, pointing error, and atmospheric fading caused by atmospheric turbulence, simulation analysis based on the upper bound of the FEC bit error rate was conducted to investigate the impact of different visibility levels, turbulence intensities, and pointing error jitter on the performance of the adaptive switching system at various link distances. A lookup table for different mode transmission switching was established, providing a theoretical basis for maintaining the robustness and stability of the FSO system in variable environments.

Claims

1. A method of FSO communication with adaptive switching between SISO / MIMO modes, characterized in that, The method comprises the following steps: Step 1, establishing a FSO composite atmospheric channel model considering the joint influence of atmospheric turbulence, pointing error and fog loss; Step 2, based on the FSO composite atmospheric channel model obtained in step 1, building a communication system model of adaptive SISO / MIMO-FSO and generating a signal; Step 3, based on the communication system model obtained in step 2, obtaining the bit error rate data of the signal under SISO and MIMO modes under different turbulence intensity, pointing error and visibility range, and establishing a threshold lookup table for mode switching according to the bit error rate data; Step 4, the transmitting end transmits the signal into the atmospheric composite channel, and the receiving end compares the channel state information with the available threshold in the threshold lookup table, and selects the best signal transmission mode in SISO and MIMO modes.

2. The FSO communication method of adaptive switching of SISO / MIMO modes as claimed in claim 1 wherein, The FSO composite atmospheric channel model established in step 1 is represented as: （1） wherein is the received optical power; is the transmitted optical power; denotes the responsivity of the receiver; is the additive white Gaussian noise; is the normalized channel fading coefficient, denoted as , denotes the random component of the atmospheric turbulence, denotes the random component of the pointing error, denotes the random component of the fog loss.

3. The FSO communication method of adaptive switching of SISO / MIMO modes as claimed in claim 2 wherein, The random component of the fog loss is a function of the wavelength of the light （2） wherein is the transmission distance, is the attenuation coefficient, expressed as: （3） where and are the molecular absorption coefficient and the aerosol absorption coefficient, respectively, is the molecular scattering coefficient, is the aerosol scattering coefficient after fog attenuation, given by the Kim model: （4） wherein is the visibility class, is the light source wavelength, is the size distribution of the scattering fog particles of the Kim model.

4. The FSO communication method of adaptive switching of SISO / MIMO modes as claimed in claim 2 wherein, Random components of the atmospheric turbulence The Gamma-Gamma turbulence model is used for the characterization, with the probability density function being: （11） where is the Gamma function, denotes the second kind modified Bessel function of order and are parameters related to small-scale and large-scale turbulent eddies, respectively, and are given by （12） （13） wherein Rytov variance value, denoted as: （8） wherein is the wave number, is the transmission distance, is the refractive index structure constant, expressed as: （9） wherein is the atmospheric pressure, is the temperature, is the temperature difference with a distance of is the temperature difference with a distance of 5. The FSO communication method of adaptive switching of SISO / MIMO modes as claimed in claim 2 wherein, a random component of the pointing error is represented as: （14） wherein is the radial displacement of the spot; denotes the received power at = 0; is the equivalent beam waist radius and , , denotes the error function, is the beam waist radius, is the receiver radius.

6. The FSO communication method of adaptive switching of SISO / MIMO modes as claimed in claim 1 wherein, The communication system model of adaptive SISO / MIMO-FSO built in step 2 comprises a laser module, a modulation module, a channel module encapsulating the FSO composite atmospheric channel model, a demodulation module and a real-time bit error rate monitoring feedback module. When generating the signal, the laser power and wavelength of the laser module are set, DBPSK modulation format is adopted, clock recovery is performed and a receiver matched filter is provided to eliminate inter-symbol interference, and the signal is down-sampled to recover the phase and frequency synchronization of the digital modulation signal.

7. The FSO communication method of adaptive switching of SISO / MIMO modes as claimed in claim 1 wherein, The threshold lookup table is established by keeping the fog loss, pointing error and geometric loss parameters unchanged, changing the atmospheric turbulence, based on the FEC bit error rate upper bound, and establishing different mode transmission switching lookup tables based on different atmospheric turbulence under multiple link distances; keeping the pointing error, atmospheric turbulence and geometric loss parameters unchanged, changing the fog loss, based on the FEC bit error rate upper bound, and establishing different mode transmission switching lookup tables based on different visibility under multiple link distances; keeping the fog loss, atmospheric turbulence and geometric loss parameters unchanged, changing the pointing error, based on the FEC bit error rate upper bound, and establishing different mode transmission switching lookup tables based on different pointing error under multiple link distances.

8. The FSO communication method of adaptive switching of SISO / MIMO modes as claimed in claim 1 wherein, Step 4 specifically comprises: the transmitting antennas TA and TB transmit the optical signal generated by the laser module into the atmospheric composite channel, and then the receiving antennas RA and RB receive it. When the atmospheric visibility of the channel is greater than the visibility threshold, or the refractive index structure constant is less than the refractive index structure constant threshold, or the pointing error jitter standard deviation is less than the jitter standard deviation threshold, i.e. the bit error rate is lower than the FEC bit error rate upper bound, the transmitting antenna TB is closed, and SISO link is used for transmission to save transmitting power; when the atmospheric visibility of the channel is less than the visibility threshold, or the refractive index structure constant is greater than the refractive index structure constant threshold, or the pointing error jitter standard deviation is greater than the jitter standard deviation threshold, i.e. the bit error rate is higher than the FEC bit error rate upper bound, the transmitting antenna TB is opened, and MIMO link is used for transmission to obtain diversity gain.

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