Smart reflector assisted omni single antenna receiver interference cancellation method

Abstract

The present application belongs to the field of interference cancellation, and particularly relates to a kind of intelligent reflecting surface assisted omnidirectional single antenna receiver interference cancellation method.The scheme utilizes the reconstruction ability of intelligent reflecting surface to reflected signal, and makes the interference signal reaching the receiver coherent cancellation by optimizing reflection coefficient, which makes up the limitation that traditional antenna null method cannot be applied to omnidirectional single antenna receiver.For the case that reflected signal power is less than direct signal power, the optimal RIS reflection coefficient is derived to minimize the interference power;For the case that reflected signal is greater than direct signal power, an optimization method of reflection coefficient based on alternating iteration algorithm is designed, and the optimal RIS unit reflection coefficient in each iteration is derived to ensure the convergence of the algorithm and reduce the interference power to 0.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of interference cancellation, and particularly relates to a method for interference cancellation of an omnidirectional single-antenna receiver assisted by an intelligent reflecting surface. BACKGROUND

[0002] Reconfigurable Intelligent Surface (RIS) is a new type of two-dimensional material artificially synthesized. Unlike conventional materials in nature, RIS is often composed of a large number of sub-wavelength units that can dynamically adjust their electromagnetic parameters to achieve the adjustment of the amplitude, phase, and even polarization mode of the reflected or transmitted signal. RIS has been widely studied in the field of mobile communication in recent years due to its reconfigurable electromagnetic characteristics and the advantages of passivity and low cost. Without changing the existing wireless network infrastructure architecture, RIS can be flexibly arranged on walls, floors, ceilings, building surfaces, and even large vehicle surfaces to provide additional degrees of freedom from the perspective of wireless channels to improve communication quality.

[0003] In the wireless communication scenario, the interference of radio frequency signals is one of the key factors limiting the communication quality, especially in the field of modern military confrontation. Command communication, military intelligence, and weapon control increasingly rely on electronic equipment, especially radio equipment. In the presence of strong interference, it is necessary to study how to select appropriate technical means to eliminate or reduce enemy interference and ensure normal communication of equipment. Spatial processing is one of the emerging anti-jamming technologies, which aims to use antenna nulling technology to point the null of the receiving antenna pattern to the interference direction to improve the signal-to-interference ratio. However, the performance of the antenna nulling method is positively correlated with the number of antennas, making it difficult to apply to hardware-limited devices, especially single-receiving antenna devices. The emergence of RIS makes it possible to solve this problem: without changing the existing device hardware, the interference signal reaching the receiver is made to coherently cancel out by adjusting the reflection coefficient. Therefore, it is worth studying how to use the ability of RIS to control the reflected signal to weaken or even eliminate the interference signal of the omnidirectional single-antenna receiver. SUMMARY

[0004] In view of the problem that the single-antenna receiver cannot apply the traditional antenna nulling technology to eliminate interference, the application provides a method for interference cancellation of an omnidirectional single-antenna receiver assisted by an intelligent reflecting surface.

[0005] To better illustrate the application, the terms and system structure used in the technical solution of the application are introduced first.

[0006] AoA: Angle of Arrival, arrival angle.

[0007] RIS: Reconfigurable Intelligent Surface, which can dynamically change its electromagnetic properties to adjust the amplitude, phase, and even polarization of the reflected signal.

[0008] ULA: Uniform Linear Array, uniform linear array.

[0009] Figure 1 The RIS-assisted omnidirectional single-antenna receiver interference cancellation system schematic diagram of the application is shown:

[0010] In this system, it is assumed that the number of antennas of the interference source Tx and the receiver Rx is 1, and both use omnidirectional antennas; the number of RIS units is N, and it is assumed that a uniform linear array is used; and α1 and α2 represent the complex fading coefficients of the Tx-RIS and Rx-RIS two-channel sections, respectively, and the azimuth angles are and Therefore, the channel vectors of Tx-RIS and Rx-RIS can be represented as:

[0011]

[0012] and

[0013]

[0014] wherein, indicates the antenna array response vector of the RIS; for a uniform linear array with N elements, there is:

[0015]

[0016] In the formula, λ and △ represent the signal wavelength and the RIS unit spacing, respectively; therefore, the interference signal received by Rx can be represented as:

[0017] y = [α0+ g H diag(φ)q]s+w,

[0018] wherein, α0 represents the complex fading coefficient of the Tx-Rx channel; φ n indicates the phase shift of the nth RIS unit in {1, 2,..., N}; s ~ CN(0, P) is an interference signal with a power of P; w ~ CN(0, N0) is a receiver noise with a power of N0; thus, the interference received by the receiver can be reduced by solving the following optimization problem:

[0019]

[0020] The technical scheme adopted by the application is:

[0021] S1. Convert problem P1 into an unconstrained optimization problem. Specifically, the objective function of problem P1 can be expanded as follows:

[0022]

[0023] Therefore, minimizing E|y| 2 Equivalent to minimizing Let's define So P1 can be equivalent to:

[0024]

[0025] where Φ={φ1,φ2,…,φ N}, assuming that β and has been estimated in advance, and since the RIS position is fixed, It can be regarded as known, so the independent variable of the objective function in P3 is only Φ;

[0026] S2. Determine the size of |β|. If N|β|≤1, proceed to S3; if N|β|>1, proceed to S4.

[0027] S3. According to the triangle inequality, we can get:

[0028]

[0029] Among them, the equal conditions are:

[0030]

[0031] Here R represents the set of all real numbers. Therefore, according to the triangle inequality again, g(Φ) now has the following lower bound:

[0032] g(Φ)≥(1-N|β|) 2 ,

[0033] The conditions are:

[0034] ψ=-∠β+(2k+1)π,k∈Z,

[0035] Where Z represents the set of all integers, so φ n The optimal solution can be expressed as:

[0036]

[0037] Go to step S5;

[0038] S4, using the alternating iterative method, optimize φ1, φ2, ..., φ in turn N , specifically, when {φ mm≠n, m∈{1, 2, …, N} for φ n When optimization is performed, the following sub-problem of problem P3 can be expressed:

[0039]

[0040] First, the first and second order derivatives of g(Φ) with respect to φ n are solved, that is:

[0041]

[0042] and

[0043]

[0044] where A n is defined as

[0045]

[0046] The local optimal solution of problem P31 satisfies that the first order derivative is equal to 0 and the second order derivative is greater than or equal to 0, that is:

[0047]

[0048] and

[0049]

[0050] Therefore, the optimal solution of φ n has the following closed form:

[0051]

[0052] It is noted that g(Φ) is a periodic function with a period of 2π with respect to φ n , and therefore if the range of φ n is limited to [0, 2π), the local optimal solution of sub-problem P31 is the global optimal solution, thus ensuring the non-increasing property of each iteration, and therefore through continuous iteration, the local optimal solution can be converged;

[0053] S5, interference cancellation is realized according to the obtained optimal solution of φ n .

[0054] The present application has the following advantages:

[0055] The application provides an intelligent reflecting surface assisted omnidirectional single antenna receiver interference cancellation method. The scheme utilizes the reconstruction capability of the intelligent reflecting surface on the reflected signal, optimizes the reflection coefficient, and makes the interference signals reaching the receiver coherent and cancel each other out, thereby making up for the limitation that the traditional antenna nulling method cannot be applied to the omnidirectional single antenna receiver. For the case that the reflected signal power is less than the direct signal power, the optimal RIS reflection coefficient is derived to reduce the interference power to the minimum; for the case that the reflected signal power is greater than the direct signal power, an RIS reflection coefficient optimization method based on an alternating iteration algorithm is designed, and the optimal RIS unit reflection coefficient in each iteration is derived to ensure the convergence of the algorithm and reduce the interference power to 0. BRIEF DESCRIPTION OF DRAWINGS

[0056] Figure 1 The application provides an intelligent reflecting surface assisted omnidirectional single antenna receiver interference cancellation system schematic diagram.

[0057] Figure 2 The simulation results of low interference power with RIS unit number, wherein (a) is the simulation result of the minimum interference power with RIS unit number when the RIS unit number is less than the threshold value, (b) is the simulation result of the interference power with iteration number when the RIS unit number is equal to the threshold value: wherein the threshold value is defined as the first integer greater than or equal to 1 / |β|, which represents the minimum RIS unit number that can reduce the interference power to 0, and also represents the ratio of the direct signal strength to the reflected signal strength.

[0058] Figure 3 The simulation results of the interference power with iteration number when the RIS unit number is greater than the threshold value, wherein (a) and (b) are respectively the RIS unit number of 256 and 512. DETAILED DESCRIPTION

[0059] In the summary section, the technical solutions of the application have been described in detail, and the practicality of the application will be illustrated below in combination with the drawings and simulation examples.

[0060] Figures 2-3 The simulation conditions adopt a receiver located at (0, 0) and an interference source located at (2000m, 2000m), the interference power is 1w, the wavelength is 0.1m, the RIS is located at (0, 1m) or (0, 2m), and the RIS unit spacing is half the wavelength.

[0061] Figure 2The interference source is located at (2000m, 2000m), and the interference power P = 1w. 2(a) shows the lowest interference power varying with the number of RIS units when the number of RIS units is less than the threshold value; 2(b) shows the simulation results of the interference power varying with the iteration number when the number of RIS units is equal to the threshold value. As can be seen from the figure, the farther the RIS is from the receiver, the more units are needed for null interference, because the RIS has more serious road loss to the receiver, and the reflected signal strength is lower. In addition, by comparing 2(a) and 2(b), it can be found that the trend of the interference power varying with the iteration number when the number of RIS units is equal to the threshold value is very close to the trend of the lowest interference power varying with the number of RIS units when the number of RIS units is less than the threshold value. Therefore, it can be inferred that when the number of RIS units is greater than the threshold value, only threshold iterations are needed, and the algorithm can converge.

[0062] Figure 3 The RIS of the present application is located at (0, 1m), and (a) and (b) are the simulation results of the interference power varying with the iteration number when the number of RIS units is 256 and 512, respectively. As can be seen from the figure, whether the RIS has 256 or 512 units, as long as the iteration number reaches the threshold value 126, the interference power can be reduced to around 0. Therefore, it is also confirmed that the iteration number required for the algorithm to converge is the ratio of the direct signal strength to the reflected signal strength, and it is not necessary to perform subsequent iterations in practical applications.

[0063] It can be seen that the intelligent reflecting surface assisted omnidirectional single antenna receiver interference cancellation system proposed by the present application can effectively reduce the interference power, which makes up for the limitation that the traditional antenna nulling method is not suitable for single antenna receivers. When the number of RIS units is less than the ratio of the direct signal strength to the reflected signal strength, the present application gives a closed expression for the optimal solution of the RIS coefficient; when the number of RIS units is greater than the ratio of the direct signal strength to the reflected signal strength, the present application gives an iterative updating algorithm for the RIS coefficient, and when the iteration number reaches the ratio of the direct signal strength to the reflected signal strength, the interference power can be reduced to 0.

Claims

1. A method for eliminating interference from an omnidirectional single-antenna receiver assisted by a smart reflector. The interference elimination system includes an interference source Tx and a receiver Rx, both of which have 1 antenna. The number of units of the smart reflector RIS is N and it adopts a horizontal uniform linear array. The complex fading coefficients of the Tx-RIS and Rx-RIS channels are expressed as as well as , the azimuth angles are and , the channel vector is expressed as: and ,in The antenna array response vector of RIS is represented by: ， wherein with denote the signal wavelength and the RIS element spacing, respectively; the interference signal received by Rx is denoted as: ， wherein denotes a complex fading coefficient of the Tx-Rx channel, , denotes a phase offset of the RIS's th element, is a transmit jamming signal with power P, is a receiver noise with power Thus, the interference experienced by the receiver is reduced by formulating the following optimization problem: ； characterized in that The interference elimination method comprises the following steps: S1, converting the problem P1 into an unconstrained optimization problem, specifically, the objective function of the problem P1 can be expanded as: ， Thus, minimizing is equivalent to minimizing , define , , then P1 is equivalent to: ， wherein , set with has been estimated beforehand, while due to the RIS position being fixed, is considered known, so that the argument in the objective function P3 is only ; S2, judge the size, if , enter S3; if , enter S4; S3, according to the triangle inequality, we have: ， Wherein, the equal condition is: ， where R denotes the set of all real numbers, and again by the triangle inequality, At this point has the following lower bound: ， The equal condition is: ， where Z denotes the set of all integers, and thus The optimal solution of the problem is given by ； Enter step S5; S4, using an alternating iterative method, optimizing sequentially , in particular, when fixing optimizing for is expressed as the following sub-problem of problem P3: ， First, solve for with respect to the first and second derivatives of, i.e.: with respect to the first and second derivatives of, i.e.: ， ， wherein is defined as: ， Since the local optimal solution of the problem P31 satisfies that the first order derivative is equal to 0 and the second order derivative is greater than or equal to 0, that is: ， ， Thus The optimal solution of Problem 1 has the closed-form ， Because is a periodic function of with a period of , if the range of is limited to , then the local optimal solution of the sub-problem P31 is the global optimal solution, which guarantees the non-increasing property of each iteration, thus obtaining the local optimal solution through continuous iteration to convergence. S5. The optimal solution of the resulting implements interference cancellation.

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