Communication system

Abstract

In the present invention, a communication system includes: a road-side unit (200) that, upon receipt from a vehicle (100) of request information that indicates a prediction request for communication quality, transmits prediction information, which is information that is used in prediction of the communication quality, and position information; a V2X application server (500) that provides a service to the vehicle; and a prediction device (700) that, upon receipt of the request information, the prediction information, and the position information of the road-side unit (200), predicts the communication quality of a communication path from the V2X application server (500) to the road-side unit (200), on the basis of the prediction information and the position information of the road-side unit (200).

Description

Technical Field

[0001] The present disclosure relates to a communication system.

Background Art

[0002] As V2X services, remote driving, autonomous driving, automatic parking, etc. are known. In order to realize V2X services, QoS (Quality of Service) is predicted. By notifying the prediction result to the vehicle, the vehicle can take actions such as stopping, decelerating, and steering operation of the vehicle before the QoS deteriorates. Note that the notification is also referred to as IQN (In-advance QoS Notification). Further, the action is also referred to as V2X adaptation.

[0003] For example, in Chapter 6.4.1 of Non-Patent Document 1, the sequence of IQN is described. A system for notifying IQN will be described with reference to FIG. 12. FIG. 12 shows a system in a 5G network. The system includes a vehicle 900, an OAM (Operation and Maintenance) 901, an NWDAF (Network Data Analytic Function) 902, a NEF (Network Exposure Function) 903, and a V2X Application Server 904. When the V2X Application Server 904 provides the prediction result of the QoS related to the V2X service to the vehicle 900, information such as the location information of the vehicle 900, the required QoS, and the QoS threshold is collected (step ST901). The V2X Application Server 904 transmits an IQN (In-advance QoS Notification) request (step ST902). The NWDAF 902 receives the IQN request via the NEF 903. Based on the collected information, the QoS is predicted (step ST903). The NWDAF 902 transmits the QoS Sustainability (prediction result) to the V2X Application Server 904 (step ST904). The V2X Application Server 904 transmits the QoS Sustainability to the vehicle 900 (step ST905). Thereby, V2X adaptation is performed (step ST906).

[0004] Also, for example, Chapter 5 of Non-Patent Document 2 describes the sequence of IQN. A system for notifying IQN will be described with reference to FIG. 13. FIG. 13 shows a system in a 5G network. The system includes a V2X Application Client 910, a VAE Client 911, an NWDAF / NEF 912, a VAE Server 913, and a V2X Application Server 914. The VAE Server 913 receives QoS Sustainability (step ST911). The VAE Server 913 transmits QoS Sustainability to the VAE Client 911 (step ST912). The VAE Client 911 performs signal processing to make QoS Sustainability processable within the vehicle (step ST913). The VAE Client 911 transmits QoS Sustainability to the V2X Application Client 910 (step ST914). Thereby, the V2X Application Client 910 can perform V2X adaptation (step ST915).

[0005] Also, for example, Chapter 4.9 of Non-Patent Document 3 proposes a Multi-access Edge Computing (MEC) platform. FIG. 14 shows that MEC Application #1 (IQN Analytics) for QoS prediction and MEC Application #2 (V2X App A) and MEC Application #3 (V2X App B) for V2X services are arranged on an MEC host.

Prior Art Documents

Non-Patent Documents

[0006]

Non-Patent Document 1

Non-Patent Document 2

Non-Patent Document 3

Summary of the Invention

Problems to be Solved by the Invention

[0007] By the way, a device having an NWDAF predicts QoS for an innumerable number of vehicles. Therefore, the load on the device increases.

[0008] An object of the present disclosure is to reduce the load on a device that predicts QoS.

Means for Solving the Problems

[0009] A communication system according to an aspect of the present disclosure is provided. The communication system includes a roadside device that transmits the request information, prediction information that is information used for predicting the communication quality, and location information when receiving request information indicating a prediction request for communication quality from a vehicle, a service providing device that provides a service to the vehicle, and a prediction device that predicts the communication quality of the communication path from the service providing device to the roadside device based on the prediction information and the location information of the roadside device when receiving the request information, the prediction information, and the location information of the roadside device.

Effects of the Invention

[0010] According to the present disclosure, the load on a device that predicts QoS can be reduced.

Brief Description of the Drawings

[0011]

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Best Mode for Carrying Out the Invention

[0012] Hereinafter, embodiments will be described with reference to the drawings. The following embodiments are merely examples, and various modifications are possible within the scope of the present disclosure.

[0013] Embodiment 1. FIG. 1 is a diagram showing the communication system of Embodiment 1. The communication system includes a roadside unit (RSU) 200, a V2X application server 500, and a prediction device 700. Further, the communication system may include a vehicle 100, a base station 300, a VAE server 400, and a NEF 600.

[0014] Vehicle 100 transmits an IQN request to roadside unit 200. The IQN request is also referred to as request information. The request information is information indicating a prediction request for communication quality. The communication quality is QoS.

[0015] When roadside unit 200 receives an IQN request from vehicle 100, it transmits the IQN request, information used for predicting QoS, and the location information of roadside unit 200. Note that the information used for predicting QoS is also referred to as prediction information. Also, the information used for predicting QoS may be information received from vehicle 100. The information used for predicting QoS may be information stored in roadside unit 200 or information stored in a device connectable to roadside unit 200. Further, for example, the location information of roadside unit 200 is information stored in roadside unit 200.

[0016] Base station 300 may be called a radio base station. Base station 300 transmits the IQN request, information used for predicting QoS, and the location information of roadside unit 200 to V2X application server 500.

[0017] V2X application server 500 is also referred to as a service providing device. V2X application server 500 provides services to vehicle 100. In the following description, the service is a V2X service. V2X application server 500 may be a physical server or a virtual server. When V2X application server 500 receives the IQN request, information used for predicting QoS, and the location information of roadside unit 200, it transmits the IQN request, information used for predicting QoS, and the location information of roadside unit 200 to prediction device 700 via NEF600. NEF600 may be implemented by one device. NEF600 may be included in prediction device 700.

[0018] The prediction device 700 has an NWDAF. The prediction device 700 receives an IQN request, information used for QoS prediction, and the location information of the roadside device 200. The prediction device 700 may receive information such as an IQN request from the roadside device 200 or the base station 300. The prediction device 700 predicts QoS based on the information used for QoS prediction and the location information of the roadside device 200. Specifically, the prediction device 700 predicts the QoS of the communication path from the V2X application server 500 to the roadside device 200. For example, the content of QoS is the error rate, delay, bit rate, etc. of the communication path. The prediction device 700 transmits QoS Sustainability, which is the QoS prediction result, to the vehicle 100 via the roadside device 200 or the like.

[0019] Hereinafter, the communication system will be described in detail. FIG. 2 is a diagram showing details of the vehicle according to Embodiment 1. The vehicle 100 has a V2X Application 110 and a wireless interface 120. The V2X Application 110 and the wireless interface 120 will be described later.

[0020] FIG. 3 is a diagram showing details of the roadside device according to Embodiment 1. The roadside device 200 has a wireless interface 210, an MEC V2X Application 220, an MEC VAE Client 230, and a wireless interface 240. The wireless interface 210, the MEC V2X Application 220, the MEC VAE Client 230, and the wireless interface 240 will be described later.

[0021] Next, the processes executed in the communication system will be described using a sequence diagram. FIG. 4 is a sequence diagram (Part 1) showing an example of the processes executed in the communication system according to Embodiment 1. In FIG. 4 and FIGS. 5 to 7 described later, the diagrams of the base station 300 and the NEF 600 are omitted. (Step ST101) The vehicle 100 that desires the V2X service registers for the V2X service with the V2X application server 500. (Step ST102) The V2X application server 500 provides the V2X service to the vehicle 100.

[0022] (Step ST103) The V2X Application 110 of the vehicle 100 transmits an IQN request and information used for QoS prediction to the nearest roadside unit 200 via the wireless interface 120. Note that, for example, the information used for QoS prediction includes the V2X service type related to the IQN, the requested QoS, the QoS prediction period, the QoS threshold at the time of notifying the IQN, the identification number of the vehicle 100 that transmitted the IQN request, and the like. Also, the QoS prediction period may be expressed as the prediction timing.

[0023] FIG. 5 is a sequence diagram (part 2) showing an example of the processing executed in the communication system of Embodiment 1. (Step ST111) The MEC V2X Application 220 of the roadside unit 200 transmits the IQN request, the information used for QoS prediction, and the location information of the roadside unit 200 to the V2X application server 500 via the base station 300.

[0024] (Step ST112) The V2X application server 500 transmits the IQN request, the information used for QoS prediction, and the location information of the roadside unit 200 to the prediction device 700 via the NEF 600.

[0025] FIG. 6 is a sequence diagram (part 3) showing an example of the processing executed in the communication system of Embodiment 1. (Step ST121) The prediction device 700 predicts the QoS of the communication path from the V2X application server 500 to the roadside unit 200 based on the information used for QoS prediction, the location information of the roadside unit 200, and the like. (Step ST122) The prediction device 700 transmits QoS Sustainability, which is the QoS prediction result, to the VAE server 400 via the NEF 600. (Step ST123) The VAE server 400 performs signal processing for aligning the APIs on QoS Sustainability. (Step ST124) The VAE server 400 transmits QoS Sustainability to the roadside device 200 via the base station 300.

[0026] Figure 7 is a sequence diagram (part 4) showing an example of the process executed in the communication system of Embodiment 1. (Step ST131) The MEC VAE Client 230 of the roadside device 200 executes signal processing to enable the MEC V2X Application 220 to process QoS Sustainability. (Step ST132) The MEC VAE Client 230 of the roadside device 200 transmits QoS Sustainability to the MEC V2X Application 220.

[0027] (Step ST133) The MEC V2X Application 220 of the roadside device 200 transmits QoS Sustainability to the vehicle 100 that has sent the IQN request via the wireless interface 210. (Step ST134) The V2X Application 110 of the vehicle 100 executes V2X adaptation according to the content of QoS Sustainability.

[0028] According to Embodiment 1, the prediction device 700 does not predict QoS for the IQN requests transmitted by an infinite number of vehicles. The prediction device 700 predicts QoS only for the IQN requests transmitted by the roadside device 200. Therefore, the communication system can reduce the load on the prediction device 700.

[0029] In addition, the roadside device 200 may receive a plurality of IQN requests from a plurality of vehicles. When a plurality of IQN requests are received, the following processing is performed in the communication system. First, the information used for QoS prediction includes prediction timing. The roadside device 200 transmits a plurality of IQN requests, information used for predicting a plurality of QoS corresponding to the plurality of IQN requests, and location information of the roadside device 200. When the prediction device 700 receives a plurality of IQN requests, information used for predicting a plurality of QoS, and location information of the roadside device 200, the prediction device 700 adds priorities to the plurality of IQN requests based on the plurality of prediction timings included in the information used for predicting a plurality of QoS and the current time. Specifically, the prediction device 700 adds priorities to the plurality of IQN requests in ascending order of proximity to the current time. The prediction device 700 predicts QoS based on the priorities. Thereby, the prediction device 700 can predict QoS in the order according to the prediction timing.

[0030] Embodiment 2. Next, Embodiment 2 will be described. In Embodiment 2, matters different from Embodiment 1 will be mainly described. And in Embodiment 2, the description of matters common to Embodiment 1 will be omitted. In Embodiment 1, the vehicle 100 receives QoS Sustainability via the roadside device 200. In Embodiment 2, the case where the vehicle 100 receives QoS Sustainability from the base station 300 will be described.

[0031] FIG. 8 is a diagram showing the communication system of Embodiment 2. FIG. 8 shows that the vehicle 100 receives QoS Sustainability from the base station 300.

[0032] Next, the vehicle 100 will be described in detail. FIG. 9 is a diagram showing the details of the vehicle in Embodiment 2. The vehicle 100 further includes a wireless interface 130 and a VAE Client 140. The wireless interface 130 receives QoS Sustainability from the base station 300. The wireless interface 130 transmits QoS Sustainability to the VAE Client 140. The VAE Client 140 performs signal processing for aligning the APIs on QoS Sustainability and transmits QoS Sustainability to the V2X Application 110. Thereby, the V2X Application 110 can execute V2X adaptation according to the content of QoS Sustainability.

[0033] Figure 10 is a sequence diagram (part 1) showing an example of the processing executed in the communication system of Embodiment 2. The processing in Figure 10 is different from the processing in Figure 6 in that step ST124a is executed. Therefore, in Figure 10, step ST124a is described. And the description of the processing other than step ST124a is omitted. Note that in Figure 10, the V2X application server 500 is omitted. (Step ST124a) The VAE server 400 transmits QoS Sustainability to the VAE Client 140 of the vehicle 100 via the base station 300.

[0034] Figure 11 is a sequence diagram (part 2) showing an example of the processing executed in the communication system of Embodiment 2. The processing in Figure 11 is different from the processing in Figure 7 in that step ST131a is executed. Therefore, in Figure 11, step ST131a is described. Note that step ST131a is executed after step ST124a. Also, in Figure 11, the V2X application server 500 is omitted. (Step ST131a) The VAE Client 140 of the vehicle 100 transmits QoS Sustainability to the V2X Application 110. (Step ST131b) The V2X Application 110 of the vehicle 100 executes V2X adaptation according to the content of QoS Sustainability.

[0035] Vehicle 100 may receive QoS Sustainability from prediction device 700. In other words, prediction device 700 may transmit QoS Sustainability to vehicle 100 without going through roadside device 200.

[0036] In this way, QoS Sustainability is received by vehicle 100 without going through roadside device 200. Therefore, in Embodiment 2, vehicle 100 can quickly receive QoS Sustainability.

[0037] The features in each of the embodiments described above can be combined with each other as appropriate.

Description of Reference Numerals

[0038] 100 Vehicle, 110 V2X Application, 120 Wireless Interface, 130 Wireless Interface, 140 VAE Client, 200 Roadside Device, 210 Wireless Interface, 220 MEC V2X Application, 230 MEC VAE Client, 240 Wireless Interface, 300 Base Station, 400 VAE Server, 500 V2X Application Server, 600 NEF, 700 Prediction Device, 900 Vehicle, 901 OAM, 902 NWDAF, 903 NEF, 904 V2X Application Server, 910 V2X Application Client, 911 VAE Client, 912 NWDAF / NEF, 913 VAE Server, 914 V2X Application Server.

Claims

1. A roadside device that transmits the request information, prediction information which is information used for predicting the communication quality, and location information when receiving request information indicating a prediction request for communication quality from a vehicle; A service providing device that provides a service to the vehicle; A prediction device that predicts the communication quality of a communication path from the service providing device to the roadside device based on the prediction information and the location information of the roadside device when receiving the request information, the prediction information, and the location information of the roadside device; A communication system comprising the same.

2. The prediction information includes a prediction timing; When the roadside device receives a plurality of pieces of the request information from a plurality of vehicles, the roadside device transmits the plurality of pieces of the request information, the plurality of pieces of the prediction information corresponding to the plurality of pieces of the request information, and the location information of the roadside device; When the prediction device receives the plurality of pieces of the request information, the plurality of pieces of the prediction information, and the location information of the roadside device, the prediction device adds priorities to the plurality of pieces of the request information based on a plurality of prediction timings included in the plurality of pieces of the prediction information and the current time, and predicts the communication quality based on the priorities. The communication system according to Claim 1.

3. The prediction result is received by the vehicle without passing through the roadside device. The communication system according to Claim 1.

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