A clamping antenna assisted full-duplex wireless power supply communication system transmission method and device

Abstract

The application relates to a clamping antenna assisted full-duplex wireless power supply communication system transmission method and device, the method comprising: establishing a clamping antenna assisted full-duplex wireless power supply communication system model; through joint optimization of time allocation, power allocation and clamping antenna position deployment, a maximum optimization problem of system reachable total communication rate is constructed; the problem is divided into a perfect SIC scene and an imperfect SIC scene. For the perfect SIC scene, a low-complexity search-based algorithm is adopted to solve the optimization problem; for the imperfect SIC scene, a penalty-based alternating optimization algorithm is adopted to obtain the optimal solution of the original problem. The application studies the clamping antenna assisted full-duplex wireless power supply communication system, maximizes the system reachable total communication rate, and simulation results show that the algorithm is superior to a benchmark scheme, and the superiority of the performance of the algorithm is verified.

Description

Technical Field

[0001] This invention belongs to the field of communication technology, specifically relating to a transmission method and apparatus for a full-duplex wireless power supply communication system assisted by a clamping antenna. Background Technology

[0002] With the rapid popularization of IoT devices and the continuous evolution of sixth-generation wireless communication technology, Power over Wireless Communication Networks (WPCNs) have become a research hotspot of common interest to both academia and industry due to their unique ability to overcome the power limitations of IoT networks.

[0003] In the development of WPCN technology, traditional systems mostly adopt a half-duplex operating mode. In this mode, wireless power transfer (WET) and wireless information transfer (WIT) must be performed in a time-division multiplexing manner. This inherent characteristic makes it impossible for the system to overcome the fundamental limitation of spectrum efficiency, making it difficult to meet the communication efficiency requirements of the large-scale development of the Internet of Things. To overcome this dilemma, full-duplex WPCN technology has emerged. Compared with the half-duplex mode, full-duplex WPCN can simultaneously complete the transmission of power and information at the same frequency, theoretically doubling the spectrum efficiency. This successfully breaks through the spectrum theoretical bottleneck of the traditional half-duplex mode, laying the foundation for the large-scale application of WPCN.

[0004] However, when full-duplex WPCN is applied to large-scale multi-antenna systems, new technical challenges arise: the coupling between complex antennas can cause severe self-interference. This problem greatly restricts the full realization of the advantages of full-duplex mode and has become a key pain point that urgently needs to be solved.

[0005] To address the aforementioned self-interference problem, clamp-on antenna technology offers an effective solution. This technology achieves signal transmission through a dielectric waveguide and utilizes a freely positionable clamp-on antenna for signal radiation. This not only establishes stable line-of-sight connections and reduces free-space path loss but also enables reconfigurable antenna arrays. With these unique advantages, clamp-on antenna technology effectively reduces the direct interference path from the base station transmitter to the receiver, thereby fundamentally reducing the self-interference level of full-duplex WPCNs in large-scale multi-antenna systems and ensuring efficient and stable system operation.

[0006] This invention studies the transmission problem of a full-duplex wireless power supply communication system assisted by a clamped antenna. By jointly optimizing time allocation, power allocation, and the location deployment of the clamped antenna, an optimization problem is constructed to maximize the total achievable communication rate of the system. For perfect SIC scenarios, a low-complexity search-based algorithm is used to solve the optimization problem, while for imperfect SIC scenarios, a penalty-based alternating optimization algorithm is used to obtain the optimal solution to the original problem. Summary of the Invention

[0007] The purpose of this invention is to explore the performance improvement of wireless power supply communication systems by clamping antennas and to establish a model of a full-duplex wireless power supply communication system assisted by clamping antennas.

[0008] The objective of this invention is achieved as follows: a transmission method for a full-duplex wireless power-powered communication system assisted by a clamping antenna, comprising:

[0009] S1: Establish a model of a full-duplex wireless power supply and communication system assisted by a clamping antenna;

[0010] S2: By jointly optimizing time allocation, power allocation, and the location deployment of clamping antennas, we construct an optimization problem to maximize the total achievable communication rate of the system;

[0011] S3: Divide the problem into perfect SIC scenarios and imperfect SIC scenarios; for perfect SIC scenarios, use a low-complexity search-based algorithm to solve the optimization problem; for imperfect SIC scenarios, use a penalty-based alternating optimization algorithm to obtain the optimal solution to the original problem.

[0012] Step S1 specifically includes:

[0013] Establish a clamp-on antenna-assisted full-duplex wireless power-operated communication system. This system includes a HAP equipped with two waveguides, where a PA is deployed on each waveguide. Each user equipment has a single antenna; the HAP operates in full-duplex mode, while all user equipment uses a time-division half-duplex transmission protocol.

[0014] Step S2 specifically includes:

[0015] By planning the system objective function and jointly optimizing time allocation, power allocation, and the location deployment of clamping antennas, the optimization problem of maximizing the total achievable communication rate of the system is constructed as follows:

[0016] (1a)

[0017] (1b)

[0018] (1c)

[0019] (1d)

[0020] (1e)

[0021] in, Indicates the first The total communication rate that a user equipment can achieve in the uplink WIT phase; Represents the time allocation vector. Represents the power distribution vector. This represents the position vector of PA; Indicates the first The duration of uplink WIT for each user equipment, and the maximum transmit power of the HAP. , Indicates the first Power allocated by WET to each user equipment downlink Let (1a) represent the number of user equipment; (1b) and (1c) represent time allocation constraints; (1d) represent power allocation constraints; and (1e) represent PA location deployment constraints.

[0022] Step S3 specifically includes:

[0023] This invention first divides the original problem into perfect SIC scenarios and imperfect SIC scenarios. Given the non-convexity of the original problem, for the perfect SIC scenario, a low-complexity search-based algorithm is used to solve the optimization problem; for the imperfect SIC scenario, a penalty-based alternating optimization algorithm is used to obtain the optimal solution to the original problem.

[0024] A transmission device for a full-duplex wireless power-powered communication system assisted by a clamping antenna, comprising:

[0025] The model building module establishes a model of a full-duplex wireless power supply and communication system assisted by a clamping antenna.

[0026] The equation-building module constructs an optimization problem that maximizes the total achievable communication rate of the system by jointly optimizing time allocation, power allocation, and the location deployment of the clamping antenna.

[0027] The iterative solution module divides the problem into perfect SIC scenarios and imperfect SIC scenarios. For perfect SIC scenarios, a low-complexity search-based algorithm is used to solve the optimization problem. For imperfect SIC scenarios, a penalty-based alternating optimization algorithm is used to obtain the optimal solution to the original problem.

[0028] The model building module specifically includes:

[0029] Establish a clamp-on antenna-assisted full-duplex wireless power-operated communication system. This system includes a HAP equipped with two waveguides, where a PA is deployed on each waveguide. Each user equipment has a single antenna; the HAP operates in full-duplex mode, while all user equipment uses a time-division half-duplex transmission protocol.

[0030] The equation construction module specifically includes:

[0031] The equation-building module jointly optimizes time allocation, power allocation, and the location deployment of the clamping antennas to construct the optimization problem of maximizing the total achievable communication rate of the system:

[0032] (2a)

[0033] (2b)

[0034] (2c)

[0035] (2d)

[0036] (2e)

[0037] In a perfect SIC scenario The optimization problem then becomes:

[0038] (3a)

[0039] (3b)

[0040] Since question (3a) is about Therefore, the optimal solution to problem (3) must satisfy the following condition: The function is monotonically increasing. Therefore, problem (3) can be simplified to

[0041] (4a)

[0042] (4b)

[0043] Problem (4) is divided into two subproblems, for a given clamping antenna position. Time allocation The optimization problem is:

[0044] (5a)

[0045] (5b)

[0046] For any given time allocation Antenna clamping position The optimization problem is:

[0047] (6a)

[0048] (6b)

[0049] In imperfect SIC scenarios Introducing auxiliary variables The optimization problem then becomes:

[0050] (7a)

[0051] (7b)

[0052] (7c)

[0053] Adding (7c) as a penalty term to the objective function (7a) changes the optimization problem to:

[0054] (8a)

[0055] (8b)

[0056] Since problem (8) is still a non-convex problem, the alternating optimization algorithm is used as the inner iteration of the penalty algorithm.

[0057] For any given power allocation Antenna clamping position and auxiliary variables Time allocation The optimization problem is:

[0058] (9a)

[0059] (9b)

[0060] For any given time allocation Antenna clamping position and auxiliary variables Power distribution The optimization problem is:

[0061] (10a)

[0062] (10b)

[0063] For any given time allocation Power distribution and auxiliary variables Antenna clamping position The optimization problem is:

[0064] (11a)

[0065] (11b)

[0066] For any given time allocation Power distribution and the position of the clamping antenna Auxiliary variables The optimization problem is:

[0067] (12)

[0068] The k-th subproblem of optimization problem (12) is:

[0069] (13)

[0070] in, We use the SCA algorithm to apply the above equation at point... In the j-th iteration, a first-order Taylor expansion is performed, yielding its lower bound as:

[0071] (14)

[0072] Then the optimization problem (13) can be rewritten as:

[0073] (15)

[0074] This optimization problem is convex, and by making its first derivative equal to 0, we obtain... The optimal solution is:

[0075] (16)

[0076] The iterative solution module specifically includes:

[0077] In the iterative solution module, this invention first divides the original problem into a perfect SIC scenario and an imperfect SIC scenario. Given the non-convexity of the original problem, for the perfect SIC scenario, a low-complexity search-based algorithm is used to solve the optimization problem; for the imperfect SIC scenario, a penalty-based alternating optimization algorithm is used to obtain the optimal solution to the original problem. Attached Figure Description

[0078] Figure 1 This is a flowchart illustrating a transmission method for a full-duplex wireless power supply communication system assisted by a clamping antenna, provided by the present invention.

[0079] Figure 2 This is a system model diagram of a full-duplex wireless power supply and communication system assisted by a clamping antenna;

[0080] Figure 3 The convergence graph of the penalty-based alternating optimization algorithm is shown.

[0081] Figure 4The graph shows the relationship between the target value and the maximum transmit power of the HAP.

[0082] Figure 5 This graph shows the relationship between the target value and the number of user devices.

[0083] Figure 6 This diagram shows the relationship between the target value and the service area of ​​the user equipment along the x-axis.

[0084] Figure 7 This is a module structure diagram of a device for a full-duplex wireless power supply communication system transmission method assisted by a clamping antenna, provided by the present invention. Detailed Implementation

[0085] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0086] This invention provides a transmission method for a full-duplex wireless power-powered communication system assisted by a clamping antenna. It proposes a joint optimization problem involving time allocation, power allocation, and the placement of the clamping antenna to maximize the total achievable communication rate of the system. Figure 1 As shown, the method includes the following steps:

[0087] S1: Establish a model of a full-duplex wireless power supply and communication system assisted by a clamping antenna;

[0088] S2: By jointly optimizing time allocation, power allocation, and the location deployment of clamping antennas, we construct an optimization problem to maximize the total achievable communication rate of the system;

[0089] S3: Divide the problem into perfect SIC scenarios and imperfect SIC scenarios; for perfect SIC scenarios, use a low-complexity search-based algorithm to solve the optimization problem; for imperfect SIC scenarios, use a penalty-based alternating optimization algorithm to obtain the optimal solution to the original problem.

[0090] like Figure 2 As shown, the method described in this embodiment is applied to a model of a full-duplex wireless power supply and communication system assisted by a clamping antenna. A three-dimensional coordinate system is used for simulation deployment, where user equipment is randomly distributed around a coordinate system centered at the origin, with a length of... , width is Within a rectangular area. Since the clamping antenna has a large aperture, the channel between the clamping antenna and the user equipment can be modeled as a near-field channel. Therefore, the channels between the two clamping antennas and the k-th user equipment are respectively expressed as:

[0091] (17)

[0092] (18)

[0093] Wherein, the wavelength in the waveguide and the wavelength in free space are respectively determined by and express, The coordinates of the feed point are shown in Table 1. Other simulation parameters are shown in Table 1.

[0094] Table 1 System Simulation Parameters

[0095]

[0096] In this embodiment, step S1 is performed as follows:

[0097] Establish a clamp-on antenna-assisted full-duplex wireless power-operated communication system. This system includes a HAP equipped with two waveguides, where a PA is deployed on each waveguide. Each user equipment has a single antenna; the HAP operates in full-duplex mode, while all user equipment uses a time-division half-duplex transmission protocol.

[0098] According to the transmission protocol, each transmission time block is defined as follows: Each time block is divided into Each time slot , .in, For DL ​​WET only Available for DL ​​WET and UL WIT, within a time block, user In the time slot WIT is performed at the location, and at the rest WET is performed within each time slot.

[0099] In the downlink WET phase, assuming Let HAP represent a known pseudo-random signal that satisfies Then the first Within each time slot, the user The received signal is:

[0100] (19)

[0101] in, For H-AP in time slot Transmission power at that location, For the first The user equipment in the first Additive white Gaussian noise (AWGN) in the time slot. Throughout the entire transmission time block. Inside, user equipment The total energy collected is:

[0102] (20)

[0103] Among them, user equipment The energy conversion coefficient at the point is used This paper adopts a standardized unit transmission block, namely... Then the user equipment The average transmission power dedicated to the uplink WIT phase can be derived as follows:

[0104] (twenty one)

[0105] For the uplink WIT phase, HAP receives the first... The signal of each user equipment is:

[0106] (twenty two)

[0107] in Indicates the first The transmitted signals of each device during the WIT phase. This indicates the received AWGN. Indicates the effective loopback channel at the HAP, satisfying . This represents the self-interference introduced by HAP during downlink transmission. The quantization error caused by digital-to-analog conversion can be approximated as independent Gaussian white noise. ,in This can be deduced as:

[0108] (twenty three)

[0109] Subtracting the self-interference component from (22) yields a new expression for the signal received at the HAP:

[0110] (twenty four)

[0111] No. The communication rate that can be achieved by a user equipment is:

[0112] (25)

[0113] in, This represents the capacity gap between the actual modulation and coding scheme and the channel capacity.

[0114] The goal is to maximize the total achievable communication rate of the system through joint optimization of time allocation, power allocation, and the location deployment of the clamping antennas. The optimization problem is formulated as follows:

[0115] (26a)

[0116] (26b)

[0117] (26c)

[0118] (26d)

[0119] (26e)

[0120] In a perfect SIC scenario The optimization problem then becomes:

[0121] (27a)

[0122] (27b)

[0123] Since question (27a) is about Therefore, the optimal solution to problem (27) must satisfy the following condition: The function is monotonically increasing. Therefore, problem (27) can be simplified to

[0124] (28a)

[0125] (28b)

[0126] Problem (28) is divided into two subproblems, for a given clamping antenna position. Time allocation The optimization problem is:

[0127] (29a)

[0128] (29b)

[0129] Problem (29) is a convex problem, which can be solved using the interior point method.

[0130] For any given time allocation Antenna clamping position The optimization problem is:

[0131] (30a)

[0132] (30b)

[0133] For this subproblem, we use a search-based algorithm to traverse all potential candidate locations within a predefined spatial region.

[0134] In imperfect SIC scenarios Introducing auxiliary variables The optimization problem then becomes:

[0135] (31a)

[0136] (31b)

[0137] (31c)

[0138] Adding (31c) as a penalty term to the objective function (31a) changes the optimization problem to:

[0139] (32a)

[0140] (32b)

[0141] Since problem (32) is still a non-convex problem, the alternating optimization algorithm is used as the inner iteration of the penalty algorithm.

[0142] For any given power allocation Antenna clamping position and auxiliary variables Time allocation The optimization problem is:

[0143] (32a)

[0144] (32b)

[0145] Problem (32) is a convex problem, which can be solved using the interior point method.

[0146] For any given time allocation Antenna clamping position and auxiliary variables Power distribution The optimization problem is:

[0147] (33a)

[0148] (33b)

[0149] Problem (33) is a convex problem, which can be solved using the interior point method.

[0150] For any given time allocation Power distribution and auxiliary variables Antenna clamping position The optimization problem is:

[0151] (34a)

[0152] (34b)

[0153] For this subproblem, we use a search-based algorithm to traverse all potential candidate locations within a predefined spatial region.

[0154] For any given time allocation Power distribution and the position of the clamping antenna Auxiliary variables The optimization problem is:

[0155] (35)

[0156] The optimization problem (35) The sub-problem is:

[0157] (36)

[0158] in, We use the SCA algorithm to apply the above equation at point... , No. In this iteration, a first-order Taylor expansion is performed, yielding its lower bound as:

[0159] (37)

[0160] The optimization problem (37) can then be rewritten as:

[0161] (38)

[0162] This optimization problem is convex, and by making its first derivative equal to 0, we obtain... The optimal solution is:

[0163] (39)

[0164] For the outer iteration process, the first The penalty coefficient corresponding to the next iteration Updated in descending order, specifically as follows:

[0165] (40)

[0166] in, This represents the step size parameter. To quantitatively evaluate whether the algorithm violates the equality constraints in equation (31c) at each iteration, we introduce an index. Its definition is as follows:

[0167] (41)

[0168] If parameters If the value falls below a predefined threshold, the algorithm terminates.

[0169] As can be seen from the above technical solution, the present invention provides a transmission method for a full-duplex wireless power supply communication system assisted by a clamping antenna. By jointly optimizing time allocation, power allocation, and the location deployment of the clamping antenna, the total achievable communication rate of the system is maximized.

[0170] Figure 3 The convergence of the penalty-based alternation optimization algorithm is shown. It can be observed that when... At that time, its value decreased to the predefined precision after approximately 55 iterations. The results show that it is possible to finally satisfy the equality requirement (31c) in problem (31). It is noteworthy that in the initial iterations, There are slight fluctuations. This is due to the initial penalty parameter. When the value is large, the solution obtained by the penalty-based method does not satisfy the equality conditions described in equation (31c). However, when When it gradually decreases as the number of iterations increases, Forced to approach a predefined precision threshold This ensures that the penalty-based algorithm eventually converges.

[0171] Figure 4 The relationship between the target value and the maximum transmit power of the HAP is presented. When the maximum transmit power of the HAP is high, the system under perfect SiC can achieve a very high communication rate compared with other schemes. Furthermore, the system performance is superior to HD-WPCN in both perfect and imperfect SiC scenarios, indicating that SiC can be well suppressed. In the case of imperfect SiC, our proposed method outperforms fixed antenna and traditional antenna schemes, demonstrating the effectiveness of adjusting the clamping antenna position to reduce path loss and further improve the overall performance of WPCN.

[0172] Figure 5 The relationship between the target value and the number of user devices is given. The achievability and rate of all schemes increase with... The increase is due to the increase in [something]. Furthermore, the two proposed schemes [are relevant to all situations]. The values ​​are superior to those of the fixed-position antenna design. However, although the fixed antenna is not as good as the proposed design, its performance is still better than that of the conventional antenna. This is because the clamped antenna architecture can place the antenna closer to the user equipment, which significantly reduces the path loss between the antenna and the device. Furthermore, when... At that time, the FD-WPCN with an imperfect SIC clamp antenna has a lower sum rate than the HD-WPCN; while when Its performance is superior to HD-WPCN. This is because when the number of users is small, the SI in FD-WPCN is not completely offset.

[0173] Figure 6 The relationship between the target value and the user equipment's service area along the x-axis is given. The sum and rate of all schemes increase with... The gain decreases as the distance between users along the x-axis increases. This is mainly due to the reduced channel gain caused by the larger distance between users along the x-axis. However, the proposed system outperforms traditional antenna schemes, demonstrating the benefits of repositioning the antenna within a clamped antenna configuration.

[0174] Figure 7 This is a module structure diagram of a device for a full-duplex wireless power supply communication system transmission method assisted by a clamping antenna, provided by the present invention.

[0175] The model building module establishes a model of a full-duplex wireless power supply and communication system assisted by a clamping antenna.

[0176] The equation-building module constructs an optimization problem that maximizes the total achievable communication rate of the system by jointly optimizing time allocation, power allocation, and the location deployment of the clamping antenna.

[0177] The iterative solution module divides the problem into perfect SIC scenarios and imperfect SIC scenarios. For perfect SIC scenarios, a low-complexity search-based algorithm is used to solve the optimization problem. For imperfect SIC scenarios, a penalty-based alternating optimization algorithm is used to obtain the optimal solution to the original problem.

[0178] In this embodiment, the model building module specifically includes:

[0179] Establish a clamp-on antenna-assisted full-duplex wireless power-operated communication system. This system includes a HAP equipped with two waveguides, where a PA is deployed on each waveguide. Each user equipment has a single antenna; the HAP operates in full-duplex mode, while all user equipment uses a time-division half-duplex transmission protocol.

[0180] In this embodiment, the equation construction module specifically includes:

[0181] The equation-building module jointly optimizes time allocation, power allocation, and the location deployment of the clamping antennas to construct the optimization problem of maximizing the total achievable communication rate of the system:

[0182] (42a)

[0183] (42b)

[0184] (42c)

[0185] (42d)

[0186] (42e)

[0187] In problem (42), (42b) and (42c) are time allocation constraints, (42d) represents power allocation constraints, and (42e) represents PA location deployment constraints.

[0188] In this embodiment, the iterative solution module specifically includes:

[0189] In the iterative solution module, this invention first divides the original problem into a perfect SIC scenario and an imperfect SIC scenario. Given the non-convexity of the original problem, for the perfect SIC scenario, a low-complexity search-based algorithm is used to solve the optimization problem; for the imperfect SIC scenario, a penalty-based alternating optimization algorithm is used to obtain the optimal solution to the original problem.

Claims

1. A transmission method for a full-duplex wireless power supply communication system assisted by a clamping antenna, characterized in that, include: S1: Establish a model of a full-duplex wireless power supply and communication system assisted by a clamping antenna; S2: By jointly optimizing time allocation, power allocation, and the location deployment of clamping antennas, we construct an optimization problem to maximize the total achievable communication rate of the system; S3: Divide the problem into perfect SIC scenarios and imperfect SIC scenarios; For the perfect SIC scenario, a low-complexity search-based algorithm is used to solve the optimization problem; For imperfect SIC scenarios, a penalty-based alternating optimization algorithm is used to obtain the optimal solution to the original problem.

2. The transmission method of a full-duplex wireless power supply communication system assisted by a clamping antenna according to claim 1, characterized in that, Step S1 specifically includes: Establish a clamp-on antenna-assisted full-duplex wireless power-operated communication system. This system includes a HAP equipped with two waveguides, where a PA is deployed on each waveguide. Each user equipment has a single antenna; the HAP operates in full-duplex mode, while all user equipment uses a time-division half-duplex transmission protocol.

3. The transmission method of a full-duplex wireless power supply communication system assisted by a clamping antenna according to claim 1, characterized in that, Step S2 specifically includes: By planning the system objective function and jointly optimizing time allocation, power allocation, and the location deployment of clamping antennas, the optimization problem of maximizing the total achievable communication rate of the system is constructed as follows: (1a) (1b) (1c) (1d) (1e) in, Indicates the first The total communication rate that a user equipment can achieve in the uplink WIT phase; Represents the time allocation vector. Represents the power distribution vector. This represents the position vector of PA; Indicates the first The duration of uplink WIT for each user equipment, and the maximum transmit power of the HAP. , Indicates the first Power allocated by WET to each user equipment downlink Let (1a) represent the number of user equipment; (1b) and (1c) represent time allocation constraints; (1d) represent power allocation constraints; and (1e) represent PA location deployment constraints.

4. The transmission method of a full-duplex wireless power supply communication system assisted by a clamping antenna according to claim 1, characterized in that, Step S3 specifically includes: This invention first divides the original problem into perfect SIC scenarios and imperfect SIC scenarios. Given the non-convexity of the original problem, for the perfect SIC scenario, a low-complexity search-based algorithm is used to solve the optimization problem; for the imperfect SIC scenario, a penalty-based alternating optimization algorithm is used to obtain the optimal solution to the original problem.

5. A transmission device for a full-duplex wireless power-powered communication system assisted by a clamping antenna, characterized in that, include: The model building module establishes a model of a full-duplex wireless power supply and communication system assisted by a clamping antenna. The equation-building module constructs an optimization problem that maximizes the total achievable communication rate of the system by jointly optimizing time allocation, power allocation, and the location deployment of the clamping antenna. The iterative solution module divides the problem into perfect SIC scenarios and imperfect SIC scenarios; For the perfect SIC scenario, a low-complexity search-based algorithm is used to solve the optimization problem; For imperfect SIC scenarios, a penalty-based alternating optimization algorithm is used to obtain the optimal solution to the original problem.

6. The transmission device for a full-duplex wireless power supply communication system assisted by a clamping antenna as described in claim 5, characterized in that, The model building module specifically includes: Establish a clamp-on antenna-assisted full-duplex wireless power-operated communication system. This system includes a HAP equipped with two waveguides, where a PA is deployed on each waveguide. Each user equipment has a single antenna; the HAP operates in full-duplex mode, while all user equipment uses a time-division half-duplex transmission protocol.

7. The transmission device for a full-duplex wireless power supply communication system assisted by a clamping antenna as described in claim 5, characterized in that, The equation construction module specifically includes: The equation-building module jointly optimizes time allocation, power allocation, and the location deployment of the clamping antennas to construct the optimization problem of maximizing the total achievable communication rate of the system: (2a) (2b) (2c) (2d) (2e)。 8. A transmission device for a full-duplex wireless power supply communication system assisted by a clamping antenna, as described in claim 5, characterized in that, The iterative solution module specifically includes: In the iterative solution module, this invention first divides the original problem into a perfect SIC scenario and an imperfect SIC scenario. Given the non-convexity of the original problem, for the perfect SIC scenario, a low-complexity search-based algorithm is used to solve the optimization problem; for the imperfect SIC scenario, a penalty-based alternating optimization algorithm is used to obtain the optimal solution to the original problem.

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