Diversity reception method based on intelligent reflecting surface in vehicle-to-everything environment

Abstract

The application relates to a diversity receiving method based on an intelligent reflecting surface in a vehicle networking environment, which is performed according to the following steps: step 1: deploying an intelligent reflecting surface device on each vehicle in a vehicle networking system, and acquiring a channel between a transmitting end, a receiving end and the intelligent reflecting surface device according to the vehicle networking system; the transmitting end sends a pilot signal p(t) for channel estimation; step 2: the receiving end respectively estimates an equivalent channel coefficient h d of a direct path between the receiving end and the transmitting end and an equivalent channel coefficient h of a reflected path reflected by the intelligent reflecting surface deployed on the i-th vehicle; step 3: calculating the diversity degree of the receiving end signal according to the following algorithm; step 4: selecting the optimal K intelligent reflecting surfaces; step 5: configuring the i-th intelligent reflecting surface to a user, and the receiver can obtain corresponding diversity receiving gain by using a traditional symbol checking algorithm. The scheme can effectively make the robustness of vehicle networking communication after the introduction of RIS greatly improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of diversity reception in a vehicle Internet of Things environment, and in particular to a diversity reception method based on an intelligent reflective surface in a vehicle Internet of Things environment. BACKGROUND

[0002] The communication network capacity will increase by a thousand times in the next decade, and ubiquitous wireless connectivity will become a reality, but highly complex networks, high-cost hardware, and increasing energy consumption will become key problems facing future wireless communication. Among many candidate new technologies, intelligent super surfaces (RIS) stand out with their unique characteristics of low cost, low energy consumption, programmability, and easy deployment. RIS is an artificial electromagnetic surface structure with programmable electromagnetic properties, developed from metamaterial technology. Traditional metamaterials can achieve unique physical phenomena such as electromagnetic black holes and electromagnetic invisibility cloaks, but they are described by equivalent medium parameters, which are single-function and fixed analog metamaterials. In recent years, the rapidly developing RIS technology has the characteristics of real-time programmable electromagnetic properties. Real-time programmability is a revolutionary technological leap that allows the super surface to change its electromagnetic properties, enabling a variety of functions that traditional metamaterials cannot achieve. RIS is usually composed of a large number of carefully designed electromagnetic units arranged in a grid. By applying control signals to the adjustable elements on the electromagnetic units, the electromagnetic properties of these electromagnetic units can be dynamically controlled, and the electromagnetic field with controllable amplitude, phase, polarization, and frequency can be formed in a programmable way. This mechanism provides an interface between the electromagnetic world of RIS and the digital world of information science, which is extremely attractive for the development of future wireless networks.

[0003] The concept of vehicle Internet of Things is derived from the Internet of Things, that is, vehicle Internet of Things, which takes vehicles in motion as information sensing objects and uses new generation information communication technology to realize network connection between vehicles and X (i.e., vehicles, people, roads, and service platforms), improve the overall intelligent driving level of vehicles, provide users with safe, comfortable, intelligent, and efficient driving experience and traffic services, improve traffic efficiency, and enhance the intelligent level of social traffic services. Vehicle Internet of Things realizes full-range network connection through new generation information communication technology, including cloud platform, vehicles, roads, people, and vehicles, mainly realizes "three network integration", that is, the integration of in-vehicle network, inter-vehicle network, and vehicle mobile Internet. Vehicle Internet of Things uses sensing technology to sense the state information of vehicles, and realizes intelligent management of traffic, intelligent decision-making of traffic information services, and intelligent control of vehicles by means of wireless communication network and modern intelligent information processing technology.

[0004] With the maturity and application of vehicle-to-everything (V2X) technology, the real-time and reliability requirements for data transmission in the V2X environment have increased, which has placed higher demands on the robustness of communication in the V2X environment. Summary of the Invention

[0005] To address the aforementioned problems, this invention provides a diversity reception method based on intelligent reflective surfaces in a vehicle-to-everything (V2X) environment.

[0006] To achieve the above objectives, this invention provides a diversity reception method based on a smart reflective surface in a vehicle-to-everything (V2X) environment, characterized by the following steps:

[0007] Step 1: Deploy intelligent reflective surface devices on each vehicle in the vehicle-to-everything (V2X) system, and obtain the channel between the transmitter, receiver, and intelligent reflective surface devices according to the V2X system; the transmitter sends pilot signals for channel estimation. ;

[0008] Step 2: The receiver estimates the equivalent channel coefficients of the direct path at both the receiver and transmitter. And the equivalent channel coefficient reflected by the smart reflective surface deployed on the i-th vehicle. ;

[0009] Step 3: Calculate the diversity of the received signal. The calculation is performed according to the following algorithm:

[0010]

[0011] Where K is the maximum number of smart reflective surfaces matched by a single receiver configured in the system; k is the kth smart reflective surface device; This represents the channel power gain of the direct path; The channel power gain represents the reflection path of the smart reflective surface deployed on the i-th vehicle;

[0012] Step 4: Select the K optimal smart reflective surfaces and calculate using the following algorithm:

[0013] in, Let K represent the set of optimal smart reflective surfaces;

[0014] Indicates the diversity of the signal received. Obtain the value of the smart reflective surface that maximizes the equivalent channel gain;

[0015] Step 5: Configure the first A smart reflective surface is provided to the user, and the receiver can use a traditional symbol checking algorithm to obtain the corresponding diversity reception gain.

[0016] As preferred, the sending end in step 1 sends a pilot signal for channel estimation , the pilot signal is configured as a corresponding pseudo-random sequence, and the pseudo-random sequence includes at least one of an m sequence and a Zadoff-Chu sequence.

[0017] As preferred, the sending end in step 2 is configured as

[0018] wherein is the number of intelligent reflecting surface reflecting units deployed on the ith vehicle, is an equivalent channel coefficient vector from the intelligent reflecting surface deployed on the ith vehicle to the receiving end, and the size of the equivalent channel coefficient vector is , is an equivalent channel coefficient vector from the sending end to the intelligent reflecting surface deployed on the ith vehicle, and the size of the equivalent channel coefficient vector is , represents a vector transposition operation, represents a reflection coefficient configured on the nth reflecting unit on the intelligent reflecting surface deployed on the ith vehicle, is an amplitude of the reflection coefficient configured on the nth reflecting unit on the intelligent reflecting surface deployed on the ith vehicle, is a phase of the amplitude of the reflection coefficient configured on the nth reflecting unit on the intelligent reflecting surface deployed on the ith vehicle, and ; the channel estimation algorithm adopts a channel estimation algorithm based on a minimum mean square error.

[0019] As preferred, k in step 3 is the maximum number of intelligent reflecting surfaces matched by a single receiving end in the system, and k is the kth intelligent reflecting surface device, wherein , M is the maximum number of selectable intelligent reflecting surfaces in the system, represents a modulo operation.

[0020] The intelligent reflecting surface-based diversity reception method designed in the vehicle networking environment can improve the diversity degree of the receiving end in the vehicle networking system by using intelligent reflecting surfaces, select K optimal intelligent reflecting surfaces from M intelligent reflecting surfaces, effectively improve the diversity gain of information transmission in the vehicle networking system, and greatly improve the robustness of vehicle networking communication after the introduction of RIS. BRIEF DESCRIPTION OF DRAWINGS

[0021] Embodiment 1: a flowchart of an intelligent reflecting surface-based diversity reception method in a vehicle networking environment. DETAILED DESCRIPTION

[0022] The preferred embodiments of the present application will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are merely intended to illustrate and explain the present application, and are not intended to limit the present application.

[0023] Embodiment 1.

[0024] As shown in the following steps, the embodiment describes a diversity reception method based on intelligent reflecting surface in a vehicle networking environment: Figure 1

[0025] Step 1: Deploy intelligent reflecting surface devices on each vehicle in the vehicle networking system, and obtain the channel between the transmitting end, the receiving end and the intelligent reflecting surface device according to the vehicle networking system; the transmitting end sends pilot signals for channel estimation

[0026] Step 2: The receiving end estimates the direct path equivalent channel coefficients of the receiving end and the transmitting end respectively and the equivalent channel coefficients reflected by the intelligent reflecting surface deployed on the ith vehicle

[0027] Step 3: Calculate the diversity degree of the receiving end signal , according to the following algorithm:

[0028]

[0029] Where K is the maximum number of intelligent reflecting surfaces matched by a single receiving end configured by the system; k is the kth intelligent reflecting surface device; represents the channel power gain of the direct path; represents the channel power gain of the reflection path of the intelligent reflecting surface deployed on the ith vehicle;

[0030] Step 4: Select the optimal K intelligent reflecting surfaces, and calculate according to the following algorithm:

[0031]

[0032] Where, represents the set of optimal intelligent reflecting surfaces, a total of K;

[0033] represents the value of the intelligent reflecting surface with the maximum equivalent channel gain obtained from the diversity degree of the receiving end signal

[0034] Step 5: Configure the kth intelligent reflecting surface to the user, and the receiver can obtain the corresponding diversity reception gain by using the traditional symbol checking algorithm.

[0035] ​​​​​As preferred, the sending end in step 1 sends a pilot signal for channel estimation , the pilot signal is configured as a corresponding pseudo-random sequence, and the pseudo-random sequence includes at least one of an m sequence and a Zadoff-Chu sequence.

[0036] As preferred, the sending end in step 2 is configured as , wherein is the number of intelligent reflecting surface reflecting units deployed on the ith vehicle, is an equivalent channel coefficient vector from the sending end to the intelligent reflecting surface deployed on the ith vehicle, and the size of the equivalent channel coefficient vector is , is an equivalent channel coefficient vector from the sending end to the intelligent reflecting surface deployed on the ith vehicle, and the size of the equivalent channel coefficient vector is , represents a vector transposition operation, represents a reflection coefficient configured on the nth reflecting unit on the intelligent reflecting surface deployed on the ith vehicle, is the amplitude of the reflection coefficient configured on the nth reflecting unit on the intelligent reflecting surface deployed on the ith vehicle, is the phase of the amplitude of the reflection coefficient configured on the nth reflecting unit on the intelligent reflecting surface deployed on the ith vehicle, and ; the channel estimation algorithm adopts a channel estimation algorithm based on minimum mean square error.

[0037] As preferred, k in step 3 is the maximum number of intelligent reflecting surfaces matched by a single receiving end in the system, and k is the kth intelligent reflecting surface device, wherein , M is the maximum number of optional intelligent reflecting surfaces in the system, represents a modulo operation.

[0038] The intelligent reflecting surface-based diversity reception method designed in the present application improves the diversity degree of the vehicle receiving end in the vehicle networking system by using intelligent reflecting surfaces, selects K optimal intelligent reflecting surfaces from M intelligent reflecting surfaces, effectively improves the diversity gain of information transmission in the vehicle networking system, and greatly improves the robustness of vehicle networking communication after introducing RIS.

[0039] In the description of the present application, it should be noted that the terms "vertical", "upper", "lower", "horizontal" and the like indicate the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application.

[0040] In the description of the present application, it also needs to be explained that, unless explicitly specified and limited, the terms "set", "install", "connect", "connect" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium, or it can be connected inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0041] Finally, it should be pointed out that: the above only for the preferred embodiments of the present application, and not for limiting the present application, although the foregoing embodiments of the present application are described in detail, for those skilled in the art, the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for diversity reception based on intelligent reflecting surface in a vehicle-to-everything environment, characterized by The following steps are performed: Step 1: deploying an intelligent reflecting surface device on each vehicle in the vehicle networking system, and obtaining the channel between the transmitting end, receiving end and intelligent reflecting surface device according to the vehicle networking system; The transmitting end sends pilot signals for channel estimation ; Step 2: The receiving end estimates the equivalent channel coefficients of the receiving end and the transmitting end respectively and the equivalent channel coefficients reflected by the intelligent reflecting surface deployed on the ith vehicle ; Step 3: Calculate the diversity of the received signal in accordance with the following algorithm: wherein K is the maximum number of intelligent reflecting surfaces matched by a single receiving end configured by the system; k is the kth intelligent reflecting surface device; denotes the channel power gain of the direct path; denotes the channel power gain of the reflection path of the intelligent reflecting surface deployed on the ith vehicle; Step 4: Select the best K smart reflective surfaces and compute as follows: wherein, denotes the set of optimal smart reflecting surfaces, in total K; represents a degree of diversity from the received end signal the value of the intelligent reflecting surface that acquires the maximum equivalent channel gain; Step 5: configuring the first smart reflective surface to the user, the receiver can obtain the corresponding diversity reception gain by using the traditional symbol checking algorithm.

2. The intelligent reflecting surface-based diversity reception method in a V2X environment according to claim 1, characterized in that the pilot signal for channel estimation transmitted by the transmitting end in step 1 is configured as a corresponding pseudo-random sequence, and the pseudo-random sequence includes at least one of an m-sequence and a Zadoff-Chu sequence. ​​ 3. The method of claim 1, wherein, the equivalent channel coefficient described in step 2 is: wherein is the number of intelligent reflecting surface reflecting units deployed on the ith vehicle, is the equivalent channel coefficient vector from the intelligent reflecting surface deployed on the ith vehicle to the receiving end, whose size is , is the equivalent channel coefficient vector from the transmitting end to the intelligent reflecting surface deployed on the ith vehicle, whose size is , denotes vector transposition operation, denotes the reflection coefficient of the nth reflecting unit configuration on the intelligent reflecting surface deployed on the ith vehicle, is the amplitude of the reflection coefficient of the nth reflecting unit configuration on the intelligent reflecting surface deployed on the ith vehicle, is the phase of the amplitude of the reflection coefficient of the nth reflecting unit configuration on the intelligent reflecting surface deployed on the ith vehicle, and ; the channel estimation algorithm adopts a channel estimation algorithm based on minimum mean square error.

4. The method of claim 1, wherein, k described in step 3 is the maximum number of intelligent reflecting surfaces matched by a single receiving end of system configuration, k is the kth intelligent reflecting surface device, wherein M is the maximum number of selectable intelligent reflecting surfaces in the system, represents a modulo operation.

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