A current distribution method, device and medium for cross-layer underwater magnetic induction communication

Abstract

The present invention discloses a current distribution method, device and medium for cross-layer underwater magnetic induction communication, belonging to the field of digital information transmission. The method comprises: establishing a magnetic induction communication system circuit model, including a transmitter and a receiver; calculating the probability density function of mutual inductance, received power, transmitted current and transmitted power based on the probability density function of the misalignment factor between the transmitting coil of the transmitter and the receiving coil of the receiver, and taking limited channel capacity and limited average power as constraints; calculating the effective capacity expression of the magnetic induction communication according to the probability density function of the mutual inductance and the received power; establishing a mathematical optimization problem based on the effective capacity expression and the constraints; solving the optimization problem using convex optimization theory to obtain the current distribution method for cross-layer underwater magnetic induction communication; the device and medium are used to implement the method; the present invention reduces hardware cost and volume, better meets the needs of delay-sensitive services, and improves universality and application value.

Description

Technical Field

[0001] The present invention belongs to the technical field of digital information transmission, and in particular relates to a current distribution method, equipment and medium for cross-layer underwater magnetic induction communication. Background Art

[0002] Electromagnetic wave communication technology has made significant progress, significantly improving transmission rates, bit error rates, and bandwidth utilization. However, in underwater environments, dynamic underwater conditions and harsh propagation environments can severely hinder electromagnetic wave transmission. In such scenarios, magnetic induction (MI) communication technology, based on the mutual inductance of coils, demonstrates advantages such as high penetration efficiency, stable channel conditions, and compact antenna size.

[0003] The basic principle of magnetic induction communication is to induce an electromotive force in the receiving coil through changes in current in the transmitting coil, thereby achieving signal transmission. Unlike traditional electromagnetic wave communication, magnetic induction communication relies on near-field magnetic field coupling and has advantages such as high penetration, strong channel stability, low power consumption, and small antenna size. These characteristics make it particularly suitable for complex environments and harsh scenarios. In underground wireless sensor networks (WUSNs), magnetic induction communication is widely used in agricultural monitoring, underground resource exploration, and earthquake early warning; in underwater environments, it is used for marine resource surveys, ecological monitoring, and submarine communications; and in the industrial field, it is used for equipment monitoring and control in mines, pipelines, and other environments.

[0004] In their paper, "Quality-of-Service Driven Power and Rate Adaptation for Multichannel Communications over Wireless Links," Jia Tang and Xi Zhang proposed a statistical quality of service (QoS)-driven power and rate adaptation mechanism to optimize the performance of multichannel wireless communication systems. The method first establishes a mathematical model of the multichannel communication system through theoretical analysis, clarifying the relationship between QoS objectives (such as user rate, delay, and false alarm rate) and channel conditions. Next, they design a power and rate adaptation algorithm based on QoS requirements to meet user quality of service expectations by optimizing power allocation and rate adjustment. In terms of system architecture, a multi-channel collaborative optimization strategy was proposed, combining channel switching and resource allocation mechanisms to ensure efficient utilization of channels. This method has three shortcomings: First, the model directly determines the value of the average received power. However, in practice, the average received power is affected by the performance of the transceiver and the environment, so what can be determined is often the average power of the transmitter; second, it assumes that the channel conditions are infinitely good. However, in reality, the maximum channel capacity is limited by various factors; third, the model directly allocates power without modeling the specific circuit, ignoring the power loss in the circuit.

[0005] Jianyu Wang, Wenchi Cheng, and Hailin Zhang proposed an optimal current control scheme for a MISO-OFDM-based magnetic induction ground communication system in their paper, “Optimal Current Control for MISO-OFDM Based Through-the-Earth Communications with Magnetic Induction” (J. Wang, W. Cheng and H. Zhang, "Optimal Current Control for MISO-OFDM BasedThrough-the-Earth Communications with Magnetic Induction," 2021 IEEE / CICInternational Conference on Communications in China (ICCC), Xiamen, China, 2021, pp. 133-138, doi: 10.1109 / ICCC52777.2021.9580360.). The implementation process begins by establishing a system model and analyzing the characteristics of the magnetic induction channel, then combining OFDM technology to construct a frequency domain channel matrix. Subsequently, with the goal of maximizing the system channel capacity, a constrained optimization problem is constructed, and the Lagrange dual decomposition method is used to design an optimal current distribution algorithm. The optimal current amplitude distribution for each transmitting antenna on each subcarrier is achieved through iterative solution. Simultaneously, a water injection algorithm is combined to dynamically adjust subcarrier power, prioritizing power allocation to subcarriers with better channel conditions to improve spectral efficiency. This method has two shortcomings: First, it only considers channel capacity as the optimization function. However, actual communications require consideration of both real-time and efficiency, and using channel capacity as the information transmission rate is inappropriate. Second, the model ignores the dynamic changes in channel conditions caused by changes in the coil's orientation. Summary of the Invention

[0006] To overcome the shortcomings of the prior art, the present invention provides a current distribution method, device, and medium for cross-layer underwater magnetic induction communication. By establishing an actual magnetic induction communication circuit model, information is transmitted using the mutual inductance of the coils. The circuit model parameters are used to obtain a communication-related signal model and power model. The randomness of the transmitting and receiving coil directions is simulated using the probability density function of the mutual inductance between the two coils. A statistical quality of service framework is introduced into the magnetic induction communication circuit to ensure limited communication latency and queue length, effectively improving link layer performance. This framework is used to establish an effective capacity model for magnetic induction communication. A mathematical optimization model is established with the effective capacity of the communication system as the optimization goal, and with the limited average power of the transmitter and the limited channel capacity as constraints. The KKT condition is used to obtain a closed-form solution for the optimal current distribution method. Current is used as the optimization variable, which is closer to the actual circuit than the power variable, and the current distribution strategy is adjusted at the circuit level. When the communication quality of service requirement is high, more current is allocated when the channel is poor to ensure that the receiver queue length does not overflow, reducing the probability of congestion, thereby increasing the information transmission rate under limited latency conditions and improving the effectiveness and reliability of the communication system.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is:

[0008] A current distribution method for cross-layer underwater magnetic induction communication, wherein the magnetic induction communication is a stable and ergodic random service process, comprises the following steps:

[0009] Step 1: Establish a circuit model of a magnetic induction communication system, including a transmitter having a transmitting coil and a receiver having a receiving coil;

[0010] Step 2: Calculate the probability density function of the mutual inductance based on the probability density function of the mutual inductance misalignment factor between the transmitting coil and the receiving coil;

[0011] Step 3: Based on the circuit model established in step 1, calculate the received power and transmit power ;

[0012] Step 4: Calculate the service quality index based on the probability density function of the mutual inductance obtained in step 2 and the received power calculated in step 3. The effective capacity of the magnetic induction communication system expression;

[0013] Step 5: Add actual constraints based on the transmit current and the transmit power obtained in step 3.

[0014] In step 6, based on the effective capacity expression obtained in step 4 and the actual constraints added in step 5, a mathematical optimization problem is established, and the optimization problem is solved using convex optimization theory to obtain a current distribution method for underwater magnetic induction communication with service quality guarantee.

[0015] In step 1, the transmitter consists of a current source connected in series , a transmitting coil , a resonant capacitor , an equivalent internal resistance ;

[0016] Among them, the current source The current value is , transmitting coil The inductance value is , resonant capacitor The capacitance value is , equivalent internal resistance The resistance value is ;

[0017] The receiver consists of a receiving coil connected in series , a resonant capacitor , an equivalent internal resistance , a load resistor ;

[0018] Among them, the receiving coil The inductance value is , resonant capacitor The capacitance value is , equivalent internal resistance The resistance value is , load resistance The resistance value is ;

[0019] The transmitting coil Coil radius Larger than the receiving coil Coil radius 10 times more, receiving coil Considered to be placed in the transmitting coil In the uniform magnetic field generated, magnetic induction communication is regarded as a random service process, which is stable and ergodic.

[0020] The operating frequency of the magnetic induction communication system is recorded as ; Transmitter current source The current and terminal voltage are respectively recorded as , ; The transmitter and receiver communicate through mutual inductance coupling and load resistance The voltage across the two ends is used as the receiving signal; the transmitting coil Inductance value With receiving coil Inductance value Satisfy the resonance condition: , ; Transmitting coil With receiving coil The mutual inductance between .

[0021] Step 2 specifically includes the following steps:

[0022] When the transmitting coil and receiving coil When parallel and aligned with each other, the transmitting coils With receiving coil The mutual inductance between , use Stokes' theorem to calculate the mutual inductance when they are parallel and aligned:

[0023] (1)

[0024] in, is the magnetic permeability, is the number of turns of the transmitting coil, is the number of turns of the receiving coil, is the radius of the transmitting coil, is the radius of the receiving coil, is the distance between the centers of the two coils;

[0025] The mutual inductance probability density function (PDF) of a practical configuration consisting of a single coil and a collinear coil array is derived based on the Stochastic Misalignment Model, where the orientations of the transmitting and receiving coils in the Stochastic Misalignment Model are uniformly distributed. The expected attenuation due to misalignment is then determined from the mutual inductance PDF, and the misalignment factor is defined. , misalignment factor , mutual induction and the mutual inductance when the two coils are parallel and aligned with each other The relationship between:

[0026] (2)

[0027] In the underwater magnetic induction communication system, the probability density function of the mutual inductance misalignment factor between the two coils is expressed as:

[0028] (3)

[0029] Finally, the probability density function of the mutual inductance misalignment factor is used Calculate the mutual inductance The probability density function of .

[0030] Step 3 specifically includes the following steps:

[0031] The symbol to be transmitted is represented as , ,in, After digital to analog conversion (DAC), the transmitter transmits the The current when the symbol is:

[0032] (4)

[0033] in, is the emission current, is the operating frequency;

[0034] Then, according to Kirchhoff's voltage law, we can get the transmitter's voltage at the time of transmission. The transmitted voltage , emission current and receiving current The relationship between them is expressed as:

[0035] (5)

[0036] (6)

[0037] in, is the equivalent resistance of the transmitter, is the equivalent resistance of the receiver, For the transmitting coil and receiving coil mutual induction between

[0038] According to formula (5) and formula (6), we can get The receiving current at the time of symbol and receiving voltage as follows:

[0039] (7)

[0040] (8)

[0041] in, represents independent and identically distributed (iid) Gaussian white noise in communication systems, with zero mean and variance ; will receive voltage After analog-to-digital conversion (ADC), the baseband signal is:

[0042] (9)

[0043] in, represents independent and identically distributed (iid) Gaussian white noise in communication systems, with zero mean and variance ; According to the baseband signal Get the receiving current and received power :

[0044] (10)

[0045] (11)

[0046] in, is the normalized equivalent resistance of the receiver's load resistor;

[0047] According to Kirchhoff's voltage law, the emission voltage is obtained and transmit power :

[0048] (12)

[0049] (13)

[0050] in, is the normalized equivalent resistance of the receiving end at the transmitting end.

[0051] Step 4 specifically includes the following steps:

[0052] For the random service process, the queue length Exceeding the threshold The probability of the threshold increases and decreases at an exponential rate, expressed as:

[0053] (14)

[0054] in, is the service quality index, which reflects the queue length exceeding the threshold The probability decay rate of

[0055] Based on the effective bandwidth theory, the definition of effective capacity is given dually: the maximum constant arrival rate that a given service process can support under the QoS requirements that meet specific statistical delay constraints. Its expression is:

[0056] (15)

[0057] in, Indicates the expected value of the signal-to-noise ratio (SNR) at the receiving end; thus, in the OSI seven-layer model, the data link layer uses the service quality index Control the achievable rate of the physical layer across layers; set the sequence represents the discrete, stationary and ergodic random service process of the magnetic induction communication system, and express forward The sum of the terms, let The Gartner-Elli limit exists and is convex and differentiable, then the effective capacity Defined as:

[0058] (16)

[0059] when sequence When is an uncorrelated sequence, the above formula is simplified to:

[0060] (17)

[0061] For the magnetic induction communication system, the receiver load resistor The signal-to-noise ratio at is expressed as:

[0062] (18)

[0063] in, is the power of the load resistor, is the noise power, is the emission current, For the transmitting coil and receiving coil The mutual intuition between , is the resistance of the load resistor, is the equivalent resistance of the receiver, For the transmitting coil and receiving coil mutual induction between

[0064] Assuming that both the transmitter and the receiver have appropriate encoding and decoding schemes so that the magnetic induction communication system can reach the channel capacity, the achievable rate is expressed as , then the effective capacity Expressed as:

[0065] (19)

[0066] in, , For the transmitting coil and receiving coil Mutual induction The probability density function of .

[0067] The actual constraints added in step 5 are:

[0068] Add a peak current constraint for the emission current:

[0069] (20)

[0070] in, is the emission current, is the peak current allowed by the transmitter, is the maximum achievable rate, For the transmitting coil and receiving coil The mutual intuition between , is the resistance of the load resistor, is the equivalent resistance of the receiver, For the transmitting coil and receiving coil mutual induction between

[0071] And add an average power constraint for the transmit power:

[0072] (twenty one)

[0073] in, is the average power constraint value.

[0074] Step 6 specifically includes the following steps:

[0075] make , then the objective function is expressed as:

[0076] (twenty two)

[0077] in, is the emission current, is the service quality index, , is the resistance of the load resistor, is the equivalent resistance of the receiver, For the transmitting coil and receiving coil The mutual intuition between Mutual Induction The probability density function of

[0078] Rewrite the objective function and take minimizing the rewritten objective function as the goal to obtain the optimization problem:

[0079] (twenty three)

[0080] in, is the maximum achievable rate, is the normalized equivalent resistance of the receiving end at the transmitting end, is the operating frequency;

[0081] The solution to the optimization problem is derived using the KKT condition, that is, the optimal current control method is:

[0082] (twenty four)

[0083] in, , , , Lagrange multiplier Obtained by numerical solution;

[0084] Under the optimal current control method, the effective capacity is expressed as:

[0085] (25)

[0086] Among them, the square of the current in formula (25) is and the square of the current Expressed as:

[0087] (26)

[0088] In particular, when When , the optimal current control method of the magnetic induction communication system converges to:

[0089] (27)

[0090] in, ;

[0091] The corresponding effective capacity is:

[0092] (28)

[0093] when hour, , , and the magnetic induction communication system is not affected by the peak rate limit, and the channel interruption probability is zero; the optimal current control method converges to:

[0094] (29)

[0095] The corresponding effective capacity is:

[0096] (30).

[0097] A current distribution device for cross-layer underwater magnetic induction communication, comprising:

[0098] Memory: used for storing a computer program for implementing a current distribution method for cross-layer underwater magnetic induction communication;

[0099] Processor: configured to implement a current distribution method for cross-layer underwater magnetic induction communication when executing the computer program.

[0100] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a current distribution method for cross-layer underwater magnetic induction communication.

[0101] Compared with the prior art, the present invention has the following beneficial effects:

[0102] First, the present invention establishes a circuit-level magnetic induction communication system, uses current as the optimization problem of the decision variable, and directly models the transmission power, reception power, transmission symbol and reception symbol from the circuit parameters, thereby reducing the hardware cost and volume, and making the present invention closer to the reality of physical layer transmission.

[0103] Second, since the present invention introduces a statistical service quality framework, it no longer uses general channel capacity as the optimization target, but uses effective capacity as the optimization target. The service quality index is used to measure the probability of queue overflow or delay overflow, and the system performance can be measured from the data link layer, better meeting the needs of delay-sensitive services.

[0104] Third, since the present invention obtains a convergent expression of the optimal current distribution strategy under extreme conditions from a complex optimal current distribution strategy, the current control is simpler and easier to control, and can achieve the optimal control effect, with stronger universality and application value.

[0105] In summary, the present invention provides a more reliable quality of service guarantee for the magnetic induction communication link. While meeting certain quality of service requirements, it can obtain the optimal current distribution method across layers through modeling through effective bandwidth theory, greatly improving the effectiveness and reliability of the magnetic induction communication system. BRIEF DESCRIPTION OF THE DRAWINGS

[0106] Figure 1 Flowchart of the present invention.

[0107] FIG2( a ) is a circuit diagram of a transmitting circuit of the present invention; FIG2( b ) is a circuit diagram of a receiving circuit of the present invention.

[0108] FIG3( a ) is a schematic diagram of a usage scenario of the present invention; FIG3( b ) is a schematic diagram of a statistical QoS framework for a link from a transmitting coil to a sensor.

[0109] Figure 4 This is a comparison chart of the current control strategies of the simulation experiments WFWR and WF of the present invention.

[0110] Figure 5 This is a comparison chart of the normalized effective capacity of different current adaptive distribution schemes in the simulation experiment of the present invention. DETAILED DESCRIPTION

[0111] The present invention will be described in detail below with reference to the accompanying drawings.

[0112] Reference Figure 1 , the implementation steps of the current distribution method for cross-layer underwater magnetic induction communication described in the present invention are further described in detail.

[0113] Step 1, as shown in FIG3(a), establish a circuit model of a magnetic induction communication system, including a transmitter with a transmitting coil arranged on a ship and a receiver with a receiving coil arranged in an underwater sensor;

[0114] As shown in Figure 2(a), the transmitter consists of a current source connected in series , a transmitting coil , a resonant capacitor , an equivalent internal resistance ; As shown in Figure 2(b), the receiver includes a receiving coil connected in series , a resonant capacitor , an equivalent internal resistance , a load resistor , where the current source The current value is , transmitting coil The inductance value is , resonant capacitor The capacitance value is , equivalent internal resistance The resistance value is ;Receiving coil The inductance value is , resonant capacitor The capacitance value is , equivalent internal resistance The resistance value is , load resistance The resistance value is ; Transmitting coil Coil radius Larger than the receiving coil Coil radius 10 times more, receiving coil Considered to be placed in the transmitting coil In the uniform magnetic field generated, magnetic induction communication is regarded as a random service process, which is stable and ergodic.

[0115] The operating frequency of the magnetic induction communication system is recorded as ; Transmitter current source The current and terminal voltage are respectively recorded as , ; The transmitter and receiver communicate through mutual inductance coupling and load resistance The voltage across the two ends is used as the receiving signal; the transmitting coil Inductance value With receiving coil Inductance value Satisfy the resonance condition: , ; Transmitting coil With receiving coil The mutual inductance between .

[0116] Step 2: Calculate the probability density function of the mutual inductance based on the probability density function of the mutual inductance misalignment factor between the transmitting coil and the receiving coil;

[0117] When the transmitting coil and receiving coil When parallel and aligned with each other, the transmitting coils With receiving coil The mutual inductance between , use Stokes' theorem to calculate the mutual inductance when they are parallel and aligned:

[0118] (1)

[0119] in, is the magnetic permeability, is the number of turns of the transmitting coil, is the number of turns of the receiving coil, is the radius of the transmitting coil, is the radius of the receiving coil, is the distance between the centers of the two coils;

[0120] The mutual inductance probability density function (PDF) for practical configurations consisting of single coils and collinear coil arrays is derived based on the Stochastic Misalignment Model (G. Dumphart and A.Wittneben, "Stochastic misalignment model for magneto-inductive SISO and MIMOlinks," 2016 IEEE 27th Annual International Symposium on Personal, Indoor,and Mobile Radio Communications (PIMRC), Valencia, Spain, 2016, pp. 1-6, doi:10.1109 / PIMRC.2016.7794767.). The orientations of the transmitting and receiving coils in the Stochastic Misalignment Model are uniformly distributed. The expected attenuation due to misalignment is then determined from the mutual inductance PDF, and the misalignment factor is defined. , misalignment factor , mutual induction and the mutual inductance when the two coils are parallel and aligned with each other The relationship between:

[0121] (2)

[0122] In underwater magnetic induction communication systems, the radius of the transmitting coil Much larger than the receiving coil radius , then the receiving coil is placed in the uniform magnetic field generated by the transmitting coil, and the probability density function of the mutual inductance misalignment factor between the two coils is expressed as:

[0123] (3)

[0124] Finally, the probability density function of the mutual inductance misalignment factor is used Calculate the mutual inductance The probability density function of .

[0125] Step 3: Based on the circuit model established in step 1, calculate the received power and transmit power ;

[0126] The symbol to be transmitted is represented as , ,in, After digital to analog conversion (DAC), since the source signal is a sine wave, the transmitter The current when the symbol is:

[0127] (4)

[0128] in, is the emission current, is the operating frequency;

[0129] Then, according to Kirchhoff's voltage law, we can get the transmitter's voltage at the time of transmission. The transmitted voltage , emission current and receiving current The relationship between them is expressed as:

[0130] (5)

[0131] (6)

[0132] in, is the equivalent resistance of the transmitter, is the equivalent resistance of the receiver, For the transmitting coil and receiving coil mutual induction between

[0133] According to formula (5) and formula (6), we can get The receiving current at the time of symbol and receiving voltage as follows:

[0134] (7)

[0135] (8)

[0136] in, represents independent and identically distributed (iid) Gaussian white noise in communication systems, with zero mean and variance ; will receive voltage After analog-to-digital conversion (ADC), the baseband signal is:

[0137] (9)

[0138] in, represents independent and identically distributed (iid) Gaussian white noise in communication systems, with zero mean and variance ; According to the baseband signal Get the receiving current and received power :

[0139] (10)

[0140] (11)

[0141] in, is the normalized equivalent resistance of the receiver's load resistor;

[0142] It should be noted that due to the mutual inductance between the transmitting and receiving circuits, the transmission power is not only determined by the parameters of the transmitting circuit, but also by the receiver due to mutual inductance. The equivalent resistance generated on the transmitter; according to Kirchhoff's voltage law, the transmitting voltage is obtained and transmit power :

[0143] (12)

[0144] (13)

[0145] in, is the normalized equivalent resistance of the receiving end at the transmitting end.

[0146] Step 4: Calculate the service quality index based on the probability density function of the mutual inductance obtained in step 2 and the received power calculated in step 3. The effective capacity of the magnetic induction communication system expression;

[0147] For the random service process, the queue length Exceeding the threshold The probability of the threshold increases and decreases at an exponential rate, expressed as:

[0148] (14)

[0149] in, is the service quality index, which reflects the queue length exceeding the threshold The probability decay rate can be used to measure data link layer indicators such as queue or delay overflow probability;

[0150] Based on the effective bandwidth theory, the definition of effective capacity is given dually: the maximum constant arrival rate that a given service process can support under the QoS requirements that meet specific statistical delay constraints. Its expression is:

[0151] (15)

[0152] in, Indicates the expected value of the signal-to-noise ratio (SNR) at the receiving end; as shown in Figure 3 (b), in the OSI seven-layer model, the data link layer uses the service quality index Control the achievable rate of the physical layer across layers; set the sequence represents the discrete, stationary and ergodic random service process of the magnetic induction communication system, and express forward The sum of the terms, let The Gartner-Elli limit exists and is convex and differentiable, then the effective capacity Defined as:

[0153] (16)

[0154] when sequence When is an uncorrelated sequence, the above formula is simplified to:

[0155] (17)

[0156] For the magnetic induction communication system, the receiver load resistor The signal-to-noise ratio at is expressed as:

[0157] (18)

[0158] in, is the power of the load resistor, is the noise power, is the emission current, For the transmitting coil and receiving coil The mutual intuition between , is the resistance of the load resistor, is the equivalent resistance of the receiver, For the transmitting coil and receiving coil mutual induction between

[0159] Assuming that both the transmitter and the receiver have appropriate encoding and decoding schemes so that the magnetic induction communication system can reach the channel capacity, the achievable rate is expressed as , then the effective capacity Expressed as:

[0160] (19)

[0161] in, , For the transmitting coil and receiving coil Mutual induction The probability density function of .

[0162] Step 5: Add actual constraints based on the transmit current and the transmit power obtained in step 3.

[0163] Due to the hardware limitation of the transmitter, add a peak current constraint for the transmit current:

[0164] (20)

[0165] in, is the emission current, is the peak current allowed by the transmitter, is the maximum achievable rate, For the transmitting coil and receiving coil The mutual intuition between , is the resistance of the load resistor, is the equivalent resistance of the receiver, For the transmitting coil and receiving coil mutual induction between

[0166] And add an average power constraint for the transmit power:

[0167] (twenty one)

[0168] in, is the average power constraint value.

[0169] Step 6: Based on the effective capacity expression obtained in step 4 and the actual constraints added in step 5, a mathematical optimization problem is established and solved using convex optimization theory to obtain a current distribution method for underwater magnetic induction communication with quality of service guarantee.

[0170] For convenience, , then the objective function is expressed as:

[0171] (twenty two)

[0172] in, is the emission current, is the service quality index, , is the resistance of the load resistor, is the equivalent resistance of the receiver, For the transmitting coil and receiving coil The mutual intuition between Mutual Induction The probability density function of

[0173] because yes A monotonically decreasing function of , so the objective function is rewritten to minimize the rewritten objective function, and the optimization problem is obtained:

[0174] (twenty three)

[0175] in, is the maximum achievable rate, is the normalized equivalent resistance of the receiving end at the transmitting end, is the operating frequency;

[0176] In this way, the optimization problem becomes the minimization of the rewritten objective function. Since this is a convex optimization problem, the solution of the optimization problem is derived using the KKT condition, that is, the optimal current control method is:

[0177] (twenty four)

[0178] in, , , , Lagrange multiplier Obtained by numerical solution;

[0179] Under the optimal current control method, the effective capacity is expressed as:

[0180] (25)

[0181] Among them, the square of the current in formula (25) is and the square of the current Expressed as:

[0182] (26)

[0183] In particular, when When , the magnetic induction communication system can tolerate arbitrarily large queuing delay, and the optimal current control method converges to:

[0184] (27)

[0185] in, ;

[0186] The corresponding effective capacity is:

[0187] (28)

[0188] when The magnetic induction communication system cannot tolerate any non-zero delay when ; in this case, , , and the magnetic induction communication system is not affected by the peak rate limit, and the channel interruption probability is zero; the optimal current control method converges to:

[0189] (29)

[0190] The corresponding effective capacity is:

[0191] (30).

[0192] A current distribution device for cross-layer underwater magnetic induction communication, comprising:

[0193] Memory: used for storing a computer program for implementing a current distribution method for cross-layer underwater magnetic induction communication;

[0194] Processor: A current distribution method for cross-layer underwater magnetic induction communication when executing the computer program.

[0195] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a current distribution method for cross-layer underwater magnetic induction communication.

[0196] Simulation experiment

[0197] Figure 4 Shows the comparison when arbitrarily long delays can be tolerated ( ), current control strategy of WFWR and WF. Set the following parameters: operating frequency , transmission distance , coil resistance , load resistance , coil radius , , the number of turns of the coil , the maximum normalized achievable rate , average transmit power , noise power .

[0198] Compared with the WF strategy, it can be observed that imposing current rate constraint introduces a current rate constraint threshold. When the peak rate constraint threshold is exceeded, the current is reduced to reduce energy consumption while maintaining a constant achievable rate. By comparing the cutoff thresholds of the two strategies, it is clear that the cutoff threshold of WFWR moves to the left, indicating that WFWR uses power more efficiently by reserving energy for use when the current is lower. This results in approximately The interruption probability is reduced, thereby improving the stability of information transmission.

[0199] Figure 5 The comparison of the effective capacity of different current adaptive distribution schemes is shown. When , the optimal current adaptive control strategy converges to the water injection strategy. When the statistical QoS requirement becomes more stringent, the normalized effective capacity of all current control schemes decreases. However, the current adaptive control scheme of the present invention always achieves the highest effective capacity.

Claims

1. A current distribution method for cross-layer underwater magnetic induction communication, wherein the magnetic induction communication is a stable and ergodic random service process, characterized in that: The following steps are involved: Step 1: Establish a circuit model of a magnetic induction communication system, including a transmitter having a transmitting coil and a receiver having a receiving coil; Step 2: Calculate the probability density function of the mutual inductance based on the probability density function of the mutual inductance misalignment factor between the transmitting coil and the receiving coil; Step 3: Based on the circuit model established in step 1, calculate the received power P L and the transmission power P tk ; Step 4: Calculate the effective capacity E of the magnetic induction communication system with the service quality index θ based on the probability density function of the mutual inductance obtained in step 2 and the received power calculated in step 3. C (θ) expression; Step 5: Add actual constraints based on the transmit current and the transmit power obtained in step 3. In step 6, based on the effective capacity expression obtained in step 4 and the actual constraints added in step 5, a mathematical optimization problem is established. The convex optimization theory is used to solve the optimization problem, and a current distribution method for underwater magnetic induction communication with quality of service is obtained. The specific steps are as follows: make Then the objective function is expressed as: Among them, I t (M) is the transmission current, θ is the service quality index, R L is the resistance of the load resistor, R r is the equivalent resistance of the receiver, M is the transmitting coil L t and receiving coil L r The mutual inductance between M (M) is the probability density function of mutual inductance M; Rewrite the objective function and take minimizing the rewritten objective function as the goal to obtain the optimization problem: Among them, R max is the maximum achievable rate, is the normalized equivalent resistance of the receiving end at the transmitting end, and f is the operating frequency; The solution to the optimization problem is derived using the KKT condition, that is, the optimal current control method is: in, The Lagrange multiplier λ0 is obtained by numerical solution; Under the optimal current control method, the effective capacity is expressed as: Wherein, the square of the current ξ1(M) and the square of the current ξ2(M) in equation (25) are expressed as: When θ→0, the optimal current control method of the magnetic induction communication system converges to: in, The corresponding effective capacity is: When θ→∞, M1→0, M2→∞, and the magnetic induction communication system is not affected by the peak rate limit, the channel interruption probability is zero; the optimal current control method converges to: The corresponding effective capacity is:

2. The current distribution method according to claim 1, characterized in that: In step 1, the transmitter includes a current source I connected in series t , a transmitting coil L t , a resonant capacitor C t , an equivalent internal resistance R t ; Among them, the current source I t The current value is I t , transmitting coil L t The inductance value is L t , resonant capacitor C t The capacitance value is C t , equivalent internal resistance R t The resistance value is R t ; The receiver includes a receiving coil L connected in series r , a resonant capacitor C r , an equivalent internal resistance R r , a load resistor R L ; Among them, the receiving coil L r The inductance value is L r , resonant capacitor C r The capacitance value is C r , equivalent internal resistance R r The resistance value is R r , load resistance R L The resistance value is R r ; The transmitting coil L t The coil radius a t Greater than the receiving coil L r The coil radius a r 10 times more, receiving coil L r Considered to be placed on the transmitting coil L t In the uniform magnetic field generated, magnetic induction communication is regarded as a random service process, which is stable and ergodic.

3. The current distribution method according to claim 1, characterized in that: In step 1, the operating frequency of the magnetic induction communication system is denoted as f; the transmitter current source I t The current and terminal voltage are respectively denoted as I t , U t ; The transmitter and receiver communicate through mutual inductance coupling and the load resistor R L The voltage at both ends is used as the receiving signal; the transmitting coil L t The inductance value L t With the receiving coil L r The inductance value L r Satisfy the resonance condition: Transmitting coil L t With the receiving coil L r The mutual inductance is denoted as M.

4. The current distribution method according to claim 1, characterized in that: Step 2 specifically includes the following steps: When the transmitting coil L t and receiving coil L r When parallel and aligned with each other, the transmitting coil L t With the receiving coil L r The mutual inductance between max , use Stokes' theorem to calculate the mutual inductance when they are parallel and aligned: Where μ is the magnetic permeability, N r is the number of turns of the transmitting coil, N r is the number of turns of the receiving coil, a t is the radius of the transmitting coil, a r is the radius of the receiving coil, and d is the distance between the centers of the two coils; The mutual inductance probability density function of a practical configuration consisting of a single coil and a collinear coil array is derived based on the random misalignment model, where the directions of the transmitting coil and the receiving coil of the random misalignment model are uniformly distributed. Then, the expected attenuation caused by the misalignment is determined using the mutual inductance probability density function, and the misalignment factor J, the mutual inductance M, and the mutual inductance M when the two coils are parallel and aligned with each other are defined. max The relationship between: M=M max ·J (2) In the underwater magnetic induction communication system, the probability density function of the mutual inductance misalignment factor between the two coils is expressed as: Finally, the probability density function of the mutual inductance misalignment factor f is used J (J) Calculate the probability density function f of mutual inductance M M (M).

5. The current distribution method according to claim 1, characterized in that: Step 3 specifically includes the following steps: The symbol to be transmitted is represented as X = [X1, X2, ..., X n ] T , where k = 1, 2, ..., n. After digital-to-analog conversion, the current of the transmitter when transmitting the kth symbol is: Among them, I t is the emission current, f is the operating frequency; Then, according to Kirchhoff's voltage law, the voltage U transmitted by the transmitter when transmitting the kth symbol is obtained tk , emission current I tk and receiving current I rk The relationship between them is expressed as: U tk =I tk R t -I rk jwM (5) I tk jwM=I rk (R L +R r ) (6) Among them, R t is the equivalent resistance of the transmitter, R r is the equivalent resistance of the receiver, M is the transmitting coil L t and receiving coil L r mutual induction between According to equations (5) and (6), the receiving current L when transmitting the kth symbol is derived as rk and receiving voltage U Lk as follows: Where n0 represents the independent and identically distributed Gaussian white noise in the communication system, with zero mean and variance Will receive voltage U Lk After analog-to-digital conversion, the baseband signal is: in, represents independent and identically distributed Gaussian white noise in the communication system, with zero mean and variance According to the baseband signal y k Get the receiving current I r and received power P L : in, is the normalized equivalent resistance of the receiver's load resistor; According to Kirchhoff's voltage law, the emission voltage U is obtained tk and the transmission power P tk : in, is the normalized equivalent resistance of the receiving end at the transmitting end.

6. The current distribution method according to claim 1, characterized in that: Step 4 specifically includes the following steps: For the random service process, the queue length Q exceeds the threshold Q th The probability of the threshold Q th increases and decreases at an exponential rate, expressed as: Where θ is the service quality index, which reflects the queue length exceeding the threshold Q th The probability decay rate of Based on the effective bandwidth theory, the definition of effective capacity is given dually: the maximum constant arrival rate that a given service process can support under the QoS requirements that meet specific statistical delay constraints. Its expression is: in, represents the expected value of the signal-to-noise ratio at the receiving end; thus, in the OSI seven-layer model, the data link layer controls the achievable rate of the physical layer across layers through the quality of service index θ; let the sequence {R[i], i = 1, 2, ...} represent the discrete, stationary and ergodic random service process of the magnetic induction communication system, and represents the sum of the first t terms of R[i]. Assume that the Gartner-Elli limit of S(t) exists and is convex and differentiable, then the effective capacity E C (θ) is defined as: When the sequence {R[i], i=1,2,…} is an uncorrelated sequence, the above formula is simplified to: For the magnetic induction communication system, the receiver load resistor R L The signal-to-noise ratio at is expressed as: Among them, P L is the power of the load resistor, is the noise power, I t is the transmitting current, M is the transmitting coil L t and receiving coil L r The mutual intuition between R L is the resistance of the load resistor, R r is the equivalent resistance of the receiver, M is the transmitting coil L t and receiving coil L r mutual induction between Assume that both the transmitter and the receiver have encoding and decoding schemes so that the magnetic induction communication system can reach the channel capacity, then the achievable rate is expressed as Then the effective capacity E C (θ) is expressed as: Where β = θ / ln2, p M (M) is the transmitting coil L t and receiving coil L r The probability density function of the mutual inductance M between them.

7. The current distribution method according to claim 1, characterized in that: The actual constraints added in step 5 are: Add a peak current constraint for the emission current: Among them, I t is the emission current, I max (M) is the peak current allowed by the transmitter, R max is the maximum achievable rate, M is the transmitting coil L t and receiving coil L r The mutual intuition between R L is the resistance of the load resistor, R r is the equivalent resistance of the receiver, M is the transmitting coil L t and receiving coil L r mutual induction between And add an average power constraint for the transmit power: Where P is the average power constraint value.

8. A current distribution device for cross-layer underwater magnetic induction communication, characterized in that: include: Memory: used for storing a computer program for implementing a current distribution method for cross-layer underwater magnetic induction communication according to any one of claims 1 to 7; Processor: configured to implement the current distribution method for cross-layer underwater magnetic induction communication as claimed in any one of claims 1 to 7 when executing the computer program.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the current distribution method for cross-layer underwater magnetic induction communication according to any one of claims 1 to 7 are implemented.

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