A method for power adaptive transmission of ultraviolet light communication

Abstract

This invention discloses a method for adaptive transmission power in ultraviolet (UV) optical communication. By simulating the frame error rate of the system's modulation and coding scheme, the signal strength required for successful decoding under different background noise intensities is obtained. The transmitter sends several data frames to the receiver and records the current link's transmission power. The receiver obtains the current link's signal strength and noise intensity data using channel estimation, quantizes it, and feeds it back to the transmitter. The transmitter judges the noise intensity; if the noise intensity is within a set noise intensity range, it determines that the background noise is in the i-th quantization interval, thus obtaining the signal strength required for successful decoding. Based on the current transmission power and the signal strength required for successful decoding, the feedback transmission power is obtained, and the corresponding UV LED power is selected to transmit the signal, achieving adjustable transmission power. This method can select different transmission powers at different transmission distances, achieving reliable data transmission with low power consumption.

Description

Technical Field

[0001] This invention relates to the field of wireless ultraviolet light communication technology, and in particular to a method for adaptive transmission of ultraviolet light communication power. Background Technology

[0002] Wireless optical communication is a communication technology that uses light waves to transmit information in free space. Depending on the type of light wave used, it can be divided into visible light communication, infrared light communication, and ultraviolet light communication. Ultraviolet light communication generally uses ultraviolet light with wavelengths of 200-280nm. This band of ultraviolet radiation in sunlight is absorbed by the ozone layer and rarely reaches the ground; therefore, this band of ultraviolet light is also known as the "solar blind zone" ultraviolet light. Ultraviolet light communication features non-line-of-sight communication, high security, and low background noise.

[0003] Ultraviolet (UV) communication, as a fallback communication method, can achieve a certain transmission rate in environments with strong electromagnetic interference and possesses good safety characteristics due to its strong attenuation. Under different transmission power and distance, the received signal and noise exhibit varying intensities, resulting in different achievable transmission rates. Currently, common UV communication systems simply use a fixed transmit power to send data, which causes significant power loss over short transmission distances. Therefore, it is necessary to design a power-adaptive transmission scheme for UV communication that can achieve different transmission power at different distances, thus meeting the low-power consumption requirement of UV communication. Summary of the Invention

[0004] The purpose of this invention is to provide a method for adaptive transmission of ultraviolet light communication power. This method can select different transmission powers at different transmission distances to achieve reliable data transmission with low power consumption and solve the problem of excessive power consumption in existing fixed transmission power systems.

[0005] The objective of this invention is achieved through the following technical solution:

[0006] A method for adaptive power transmission in ultraviolet light communication, the method comprising:

[0007] Step 1: By simulating the frame error rate of the system modulation and coding scheme, the system frame error rate curves under different background noise intensities are obtained, and the signal strength required for successful decoding under different background noise intensities is obtained.

[0008] Step 2: The transmitting end sends several data frames to the receiving end and records the current transmission power P of the link. t ′;

[0009] Step 3: The receiver obtains the signal strength of the current link using the channel estimation method. and noise intensity The data will be used to determine the signal strength of the current link. and noise intensity The quantized data is then fed back to the transmitting end.

[0010] Step 4: The transmitter receives the feedback signal strength. and noise intensity After determining the noise intensity range parameters, the signal strength required for successful decoding is obtained.

[0011] Step 5: The transmitting end uses the current link transmission power P recorded in Step 2. t The signal strength required for successful decoding obtained in step 4 is used to calculate the transmit power after feedback. Represented as:

[0012] Step 6: Transmit power after receiving feedback Then, the corresponding ultraviolet LED power is selected to send the signal, so that the transmission power is adjustable.

[0013] As can be seen from the technical solution provided by the present invention, the above method can select different transmission power at different transmission distances, realize reliable data transmission under low power consumption, and solve the problem of excessive power consumption in existing fixed transmission power systems. Attached Figure Description

[0014] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic flowchart of a method for adaptive transmission of ultraviolet light communication power provided in an embodiment of the present invention;

[0016] Figure 2 This is a schematic diagram showing the results of frame error rate simulation under different signal strengths and noise intensities in the example of this invention.

[0017] Figure 3 This is a schematic diagram of the frame error rate simulation results of the example system described in this invention;

[0018] Figure 4 This is a schematic diagram showing the average output power of the example system of the present invention at different transmission distances. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments, and do not constitute a limitation of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0020] like Figure 1 The diagram shown is a flowchart of an ultraviolet light communication power adaptive transmission method provided in an embodiment of the present invention. The method includes:

[0021] Step 1: By simulating the frame error rate of the system modulation and coding scheme, the system frame error rate curves under different background noise intensities are obtained, and the signal strength required for successful decoding under different background noise intensities is obtained.

[0022] In this step, in ultraviolet communication using on / off keying, when the transmitter sends bits "0" and "1" respectively, the number of photons received by the receiver conforms to the Poisson distribution model shown below:

[0023]

[0024] Where N i =n|s i =1 indicates that when the transmitter sends a bit "1", the receiver receives n photons, where N is the number of photons received. i =n|s i =0 indicates that when the transmitter sends bit "0", the receiver receives n photons; λ s λ represents the average signal strength, i.e., the average number of photons received by the receiver when a bit "1" is transmitted; b This represents the background noise intensity, i.e., the average number of photons received by the receiver when a bit "0" is transmitted.

[0025] It can be seen that the received signal is related to two parameters: noise intensity and signal strength. During channel decoding, a belief propagation decoding algorithm based on log-likelihood ratio is used to decode LDPC. The input information of this decoding algorithm is represented by the following formula:

[0026]

[0027] Among them, z i =N indicates that the number of photons in one symbol received by the receiver is N; and These represent the signal strength and noise intensity values ​​obtained by the receiver after channel estimation;

[0028] Therefore, the same set of channel codes will have different performance under different noise and signal strengths. In order to investigate the receiver signal strength required for successful decoding under different noise intensities, this study aims to explore the different noise intensities. By simulating the frame error rate of the modulation and coding scheme of the system, the signal strength required for successful decoding under different background noise intensities is obtained. That is, the signal strength required for channel coding to achieve a certain frame error rate under different noise intensities. Since the background noise in the atmosphere is a continuous value, the background noise is first quantized for system implementation. The quantization level of the noise intensity is defined as {λ}. b1 ,λ b2 ,...,λ bm}, each noise intensity quantization level λ bi The signal strength required for successful decoding corresponding to (1≤i≤m) is represented by Th. i .

[0029] Step 2: The transmitting end sends several data frames to the receiving end and records the current transmission power P of the link. t ′;

[0030] Step 3: The receiver obtains the signal strength of the current link using the channel estimation method. and noise intensity The data will be used to determine the signal strength of the current link. and noise intensity The quantized data is then fed back to the transmitting end.

[0031] In this step, the receiver estimates the channel parameters by adding a set of pilot sequences before transmitting the data frame. The pilot sequence is assumed to be a pseudo-random sequence of length L, s = {s1, s2, ..., s...}. L}, and the pseudo-random sequence s is known at the receiving end, define the set Z1 = {z i |s i =1} and Z0={z i |s i =0} represents the set of photons received by the receiver when 1 and 0 are transmitted in the pilot sequence, respectively. Then, the receiver obtains the signal strength of the current link through a channel estimation algorithm. and noise intensity The data is represented as:

[0032]

[0033] After completing channel estimation, the receiver will obtain the signal strength of the current link. and noise intensity After quantization, the data is fed back to the transmitting end. Specifically:

[0034] First, the noise intensity is divided into m orders of magnitude. If the channel estimation yields... Located in the interval (λ) bi-1 ,λ bi When the current channel background noise intensity is considered to be within the i-th order of magnitude, the background noise is divided into 10 orders of magnitude, and the receiver uses 4 bits of information to feed back the noise intensity interval; while the system transmission rate is 1Mbps and the receiver sampling rate is 100MHz, the maximum estimated value of the signal strength is 100, and 7 bits of information are used to feed back the signal strength.

[0035] The 11 bits of the feedback link are padded with 19 bits from 0 to 30, and then LDPC code (150, 30) is applied. The encoded information is then quadrupled in frequency, and the spread data is repeatedly encoded. In other words, the information sequence is transmitted at a rate that is a fraction of that of the forward link. The specific process is as follows:

[0036] For a set of (n,k) block codes C = [c1,c2,c3,…,c…] k ,c k+1 ,…,c n The channel coding rate is defined as follows: That is, the ratio of the information bit length to the codeword length in the code group. During the encoding process, k information bits are encoded by the encoder to obtain (nk) parity bits, which are then appended to the information bits to form the encoded codeword. The encoding process is represented as follows:

[0037]

[0038] u = [u1, u2, u3, ..., u k ]

[0039] C = u * G = [c1, c2, c3, ..., c k ,c k+1 ,…,c n ]

[0040] Where G represents the generating matrix, obtained through the verification matrix, and the elements g in matrix G. ij , 1≤i≤k, 1≤j≤

[0041] n, which takes the value of 0 or 1, is determined by the parameters and construction method of the parity check matrix; u represents the information bits before encoding, and the elements in matrix u are... k C represents the information to be encoded; C represents the encoded sequence, and the elements c in matrix C are... k 1≤k≤n represents the encoded information, which takes the value 1 or 0;

[0042] As shown above, the encoded codeword is obtained by multiplying the information bits by the matrix G. Assuming a symbol is spread by a spreading code, the resulting sequence is represented as follows: Taking either 0 or 1, specifically, it means spreading a single 1 bit encoded at the transmitting end into a code block of length four. The encoded bit 0 is spread into a code block. Based on the joint probability distribution, the spread spectrum sequence conforms to the Poisson distribution model shown below:

[0043]

[0044] i = 0, 1,

[0045] j = 1, 2, 3, 4, where N j Indicates that the sending end sends The number of photons received by the receiver at that time; s t Represents the channel-coded bits; Indicates that the sending end sends The channel-related parameters are obtained after the receiver performs channel estimation; i and j are just indexes here, different To distinguish them, i=0 indicates that the transmitted code block is a 0-spread code block; i=1 indicates that the transmitted code block is a 1-spread code block. Each spread code block consists of four symbols, and j is used to distinguish them.

[0046] Obtain the log-likelihood ratio information L(P) of the spread code block. t ) is represented as:

[0047]

[0048] In this case, the receiver transmits at its maximum power when sending feedback information, i.e., P. t =P max In the formula, P t and P max These represent the system's current transmit power and the system's maximum transmit power, respectively.

[0049] Step 4: The transmitter receives the feedback signal strength. and noise intensity After determining the noise intensity range parameters, the signal strength required for successful decoding is obtained.

[0050] Step 5: The transmitting end uses the current link transmission power P recorded in Step 2. t The signal strength required for successful decoding obtained in step 4 is used to calculate the transmit power after feedback. Represented as:

[0051] Step 6: Transmit power after receiving feedback Then, the corresponding ultraviolet LED power is selected to send the signal, so that the transmission power is adjustable.

[0052] In this step, if Then P t =P max ;

[0053] like Then P t =P min ;

[0054] In other cases,

[0055] In the formula P t P represents the system's current transmit power. max P represents the maximum power that the system can transmit; min This indicates the minimum power that the system can emit.

[0056] In practice, both the transmitter and receiver are composed of ultraviolet LEDs and photomultiplier tubes, forming an integrated transmitting and receiving device.

[0057] The method described in this embodiment of the invention will be explained in detail below with a specific example. In this example, due to the good encoding and decoding performance of 5G-NR-LDPC code, a 5G-NR-LDPC code with a code rate of (2176, 1280) is adopted. To decode the LDPC code, a minimum-sum decoding algorithm based on LLR information is used at the decoding end, with 20 decoding iterations. Considering the system transmission rate as R... s =1Mbps, noise intensity is:

[0058] λ b = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]

[0059] First, the frame error rate of the LDPC code with a code rate of (2176, 1280) is simulated under different signal strengths and noise levels. Figure 2 The diagram shown illustrates the results of frame error rate simulation under different signal and noise intensities in the example described in this invention. (The data is obtained by reading...) Figure 2 The data in the dataset yields the signal strength Th required for successful decoding under different noise intensities. i As shown in Table 1 below:

[0060] Table 1

[0061] <![CDATA[λ b ]]> 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Th 4 4 4 5 5 5 5 5 6 6

[0062] After obtaining the signal strength thresholds required for successful decoding under different noise intensities, the transmission power is adjusted according to the method described in this embodiment of the invention, and the system is simulated and tested. Here, we set the maximum power of the transmitting end to 100mW, and the adjustable transmission power set is [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]mW. Since the signal strength at different transmission powers and transmission distances in a line-of-sight link scenario can be calculated using the following formula:

[0063]

[0064] In the formula λ s Represents signal strength; η represents the quantum efficiency of the optical receiving antenna; g t P represents the path loss at the transmitting and receiving ends; out Represents the transmitting power; h represents Planck's constant; v represents the frequency of the transmitted signal; R s This indicates the transmitted symbol rate.

[0065] The path loss at the transmitting and receiving ends can be calculated using the following formula:

[0066]

[0067] In the formula, k e =k s +k a Represents the scattering coefficient k s With absorption coefficient k a The sum; r represents the distance between the transmitter and receiver; r Rx φ represents the radius of the optical receiving antenna. t Indicates the beam divergence angle at the transmitting end;

[0068] The parameter settings for the simulation test are shown in Table 2 below:

[0069] Table 2

[0070]

[0071] like Figure 3 The diagram shown is a simulation result of the frame error rate of the example system described in this invention. Figure 4 The diagram shows the average output power of the example system of the present invention at different transmission distances. The simulation results show that, according to the method described in the embodiments of the present invention, the system can automatically adjust the transmission power at different transmission distances, so that the system can reduce the transmission power of the system while meeting the communication requirements, thereby achieving the need for low-power communication.

[0072] It is worth noting that the contents not described in detail in the embodiments of the present invention belong to the prior art known to those skilled in the art.

[0073] In summary, compared with traditional ultraviolet light communication physical layer transmission technology, the method described in this embodiment of the invention can effectively reduce the power consumption of the system and effectively improve the communication reliability of the system in different application scenarios.

[0074] Furthermore, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware, and the corresponding program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0075] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims. The information disclosed in the background section is intended only to enhance the understanding of the overall background technology of the present invention and should not be construed as an admission or implication in any way that such information constitutes prior art known to those skilled in the art.

Claims

1. A method for adaptive power transmission in ultraviolet light communication, characterized in that, The method includes: Step 1: By simulating the frame error rate of the system modulation and coding scheme, the system frame error rate curves under different background noise intensities are obtained, and the signal strength required for successful decoding under different background noise intensities is obtained. Step 2: The transmitting end sends several data frames to the receiving end and records the current transmission power P of the link. t ′; Step 3: The receiver obtains the signal strength of the current link using the channel estimation method. and noise intensity The data will be used to determine the signal strength of the current link. and noise intensity The quantized data is then fed back to the transmitting end. Step 4: The transmitter receives the feedback signal strength. and noise intensity After determining the noise intensity range parameters, the signal strength required for successful decoding is obtained. Step 5: The transmitting end uses the current link transmission power P recorded in Step 2. t The signal strength required for successful decoding obtained in step 4 is used to calculate the transmit power after feedback. Represented as: Step 6: Transmit power after receiving feedback Then, the corresponding ultraviolet LED power is selected to send the signal, so that the transmission power is adjustable.

2. The method for adaptive transmission of ultraviolet light communication power according to claim 1, characterized in that, In step 1, in ultraviolet communication using on / off keying, when the transmitter sends bits "0" and "1" respectively, the number of photons received by the receiver conforms to the Poisson distribution model shown below: Where N i =n|s i =1 indicates that when the transmitter sends a bit "1", the receiver receives n photons; N i =n|s i =0 indicates that when the transmitter sends bit "0", the receiver receives n photons; λ s λ represents the average signal strength, i.e., the average number of photons received by the receiver when a bit "1" is transmitted; b This represents the background noise intensity, i.e., the average number of photons received by the receiver when a bit "0" is transmitted; When performing channel decoding, a confidence propagation decoding algorithm based on log-likelihood ratio is used to decode LDPC. The input information of this decoding algorithm is represented by the following formula: Among them, z i =N indicates that the number of photons in one symbol received by the receiver is N; and These represent the signal strength and noise intensity values ​​obtained by the receiver after channel estimation; By simulating the frame error rate of the modulation and coding scheme of the system, the signal strength required for successful decoding under different background noise intensities is obtained, that is, the signal strength required for channel coding to achieve a certain frame error rate under different noise intensities. First, the background noise is quantized, and the quantization level of the noise intensity is defined as {λ}. b1 ,λ b2 ,…,λ bm }, each noise intensity quantization level λ bi The signal strength required for successful decoding corresponding to (1≤i≤m) is represented by Th. i .

3. The ultraviolet light communication power adaptive transmission method according to claim 1, characterized in that, In step 3, The receiver estimates channel parameters by adding a set of pilot sequences before transmitting data frames. The pilot sequences are assumed to be pseudo-random sequences of length L, s = {s1, s2, ..., s...}. L }, and the pseudo-random sequence s is known at the receiving end, define the set Z1 = {z i |s i =1} and Z0={z i |s i =0} represents the set of photons received by the receiver when 1 and 0 are transmitted in the pilot sequence, respectively. Then, the receiver obtains the signal strength of the current link through a channel estimation algorithm. and noise intensity The data is represented as follows: After completing channel estimation, the receiver will obtain the signal strength of the current link. and noise intensity After quantization, the data is fed back to the transmitting end. Specifically: First, the noise intensity is divided into m orders of magnitude. If the channel estimation yields... Located in the interval (λ) bi-1 ,λ bi When the current channel background noise intensity is considered to be within the i-th order of magnitude, the background noise is divided into 10 orders of magnitude, and the receiver uses 4 bits of information to feed back the noise intensity interval. The system's transmission rate is 1Mbps, and the receiving end's sampling rate is 100MHz. Therefore, the maximum estimated signal strength is 100, and 7 bits of information are used to feed back the signal strength. The 11 bits of the feedback link are padded with 19 bits from 0 to 30, and then LDPC code (150, 30) is applied. The encoded information is then quadrupled in frequency spread, and the spread data is repeatedly encoded. That is, the information sequence is transmitted at a rate that is a fraction of that of the forward link. The specific process is as follows: For a set of (n,k) block codes C = [c1,c2,c3,…,c…] k ,c k+1 ,…,c n The channel coding rate is defined as follows: That is, the ratio of the information bit length to the codeword length in the code group. During the encoding process, k information bits are encoded by the encoder to obtain (nk) parity bits, which are then appended to the information bits to form the encoded codeword. The encoding process is represented as follows: u=[u1,u2,u3,…,u k ] C=u*G=[c1,c2,c3,…,c k ,c k+1 ,…,c n ] Here, G represents the generating matrix, obtained through the verification matrix, and the elements g in matrix G are... ij , 1≤i≤k, 1≤j≤n, takes the value 0 or 1, the specific value is determined by the parameters and construction method of the check matrix; u represents the information bits before encoding, and the elements in matrix u are... k C represents the information to be encoded; C represents the encoded sequence, and the elements c in matrix C are... k 1≤k≤n represents the encoded information, which takes the value 1 or 0; The encoded codeword is obtained by multiplying the information bits by the matrix G. Assume that the sequence after spreading a symbol using a spreading code is represented as follows: Taking either 0 or 1, specifically, it means spreading a single 1 bit encoded at the transmitting end into a code block of length four. The encoded bit 0 is spread into a code block. Based on the joint probability distribution, the spread spectrum sequence conforms to the Poisson distribution model shown below: Here N j Indicates that the sending end sends The number of photons received by the receiver at that time; s t Represents the channel-coded bits; Indicates that the sending end sends The channel correlation parameters are obtained after the receiver performs channel estimation; i and j represent the index, which is different for different... To distinguish them, i=0 indicates that the transmitted code block is a 0-spread code block; i=1 indicates that the transmitted code block is a 1-spread code block. Each spread code block consists of four symbols, and j is used to distinguish them. The log-likelihood ratio L(P) of the spread code block is obtained. t ) is represented as: In this case, the receiver transmits at its maximum power when sending feedback information, i.e., P. t =P max In the formula P t and P max These represent the system's current transmit power and the system's maximum transmit power, respectively.

4. The ultraviolet light communication power adaptive transmission method according to claim 1, characterized in that, In step 6, like Then P t =P max ; like Then P t =P min ; In other cases, In the formula P t P represents the system's current transmit power. max P represents the maximum power that the system can transmit; min This indicates the minimum power that the system can emit.

5. The ultraviolet light communication power adaptive transmission method according to claim 1, characterized in that, Both the transmitter and receiver are composed of ultraviolet LEDs and photomultiplier tubes, forming an integrated transmitting and receiving device.

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