Marine 5G network slice health assessment method and device and medium

Abstract

The invention discloses a marine 5G network slice health assessment method and device and a medium, and the method comprises the steps: collecting operation data in a marine 5G private network in real time through a network management interface disposed in a local machine room of a ship, inputting the operation data into a preset health assessment model, calculating an overall health degree value H, triggering a network parameter adjustment instruction if H is smaller than a preset value, and carrying out the adjustment of a network parameter. The adjustment instruction at least comprises one of the following: increasing the PRB downlink rate percentage; increasing the PRB uplink rate percentage; and increasing the maximum number of the RRC connected state users. The network operation state can be visually and conveniently presented through the overall health degree value, the network maintenance cost is reduced, and decision reference is provided for network maintenance, trend analysis, capacity expansion and contraction and the like.

Description

Technical Field

[0001] This invention belongs to the field of network health assessment technology, specifically relating to a method, device and medium for assessing the health of network slices in marine 5G. Background Technology

[0002] 5G network slicing is already commercially viable in the operator sector, and is being piloted and verified in the military field. Regarding 5G network health monitoring for operators, Chinese patent application CN115865736A, entitled "Method, Apparatus, Equipment, and Medium for 5G Network Health Monitoring," constructs a hierarchical monitoring model for 5G private network health, builds a basic index library for hierarchical monitoring, and implements hierarchical monitoring models for network health in different scenarios. This patent application constructs 49 index dimensions. Network maintenance still requires relatively specialized personnel to spend a considerable amount of time collecting, analyzing, and evaluating index data, resulting in high network maintenance costs. Compared to 5G networks in the operator sector, marine 5G networks in the military sector are smaller in scale, do not involve subdomain networks, and have reduced billing and roaming functions. Therefore, the aforementioned 5G network health monitoring methods for the operator sector are not applicable to network slice health monitoring for marine 5G in the military sector. Summary of the Invention

[0003] In view of this, the present invention provides a method, device, and medium for assessing the health of network slices in marine 5G. This assessment method collects preset key indicators and values ​​of network slices in real time, calculates a health score for the network based on a preset network health assessment model, and adjusts the network indicators according to preset parameters when network quality deteriorates or health is poor, until the health reaches an excellent level. It can present the real-time operating status of network slices, providing network maintenance personnel with digital visualization and decision-making support.

[0004] The network slicing health assessment method for marine 5G provided by this invention adopts the following technical solution:

[0005] A method for assessing the health of network slicing in marine 5G networks, comprising:

[0006] S1. Real-time collection of operational data in the ship's 5G private network via the network management interface deployed in the ship's local computer room. The operational data includes at least: registration success rate, session establishment success rate, handover success rate; uplink / downlink bit error rate, uplink / downlink data retransmission rate; number of alarms and alarm level.

[0007] S2. Input the above operational data into the preset health assessment model to calculate the overall health score H:

[0008] H = (Registration success rate × W1) + (Session establishment success rate × W2) + (Switch success rate × W3) + (1 - Downlink bit error rate) × W4 + (1 - Uplink bit error rate) × W5 + (1 - Downlink data retransmission rate) × W6 + (1 - Uplink data retransmission rate) × W7 + Critical alarm level value × W8 + Major alarm level value × W9 + Minor alarm level value × W10 + Warning alarm level value × W11;

[0009] Where W1 to W11 are preset weighting factors, and W1+W2+…+W11=100.

[0010] S3. If H is less than the preset value, a network parameter adjustment command is triggered. The adjustment command includes at least one of the following: increasing the PRB downlink rate percentage; increasing the PRB uplink rate percentage; increasing the maximum number of RRC connected users.

[0011] Furthermore, the alarm level value is determined based on the number of alarms.

[0012] Furthermore: if the number of alarms is less than 5, the alarm level value is 1;

[0013] If the number of alarms is 5 or less and the number of alarms is less than 10, the alarm level value is 0.9.

[0014] If the number of alarms is 10 or less and the total number of alarms is less than 20, the alarm level value is 0.7.

[0015] If the number of alarms is less than or equal to 20, the alarm level value is 0.6.

[0016] 30 ≤ number of alarms, alarm level value is 0.5.

[0017] Furthermore, 10≤W1≤15; 10≤W2≤15; 10≤W3≤15; 5≤W4≤10; 5≤W5≤10; 5≤W6≤10; 5≤W7≤10; 10≤W8≤35; 1≤W9≤10; 1≤W10≤5.

[0018] Furthermore, the network parameter adjustment mechanism is a closed-loop control mechanism. The adjusted network indicators will be re-substituted into the overall health calculation formula for real-time evaluation and dynamic optimization.

[0019] Beneficial effects:

[0020] 1. Based on existing marine 5G networks and terminals, this invention analyzes the main service indicators of the network, evaluates the weighting of the impact of each service indicator on the healthy operation of the network, and proposes a method for assessing and adjusting the overall health of the 5G network. The overall health value can intuitively and conveniently present the network's operating status, reduce network maintenance costs, and provide decision-making references for network maintenance, trend analysis, and capacity expansion / contraction.

[0021] 2. When the overall health is poor, this invention adjusts and optimizes the network indicator parameters, and the health value will also change accordingly. The health assessment model can provide near real-time and accurate feedback on the impact of the adjustment.

[0022] 3. When the health status declines due to reasons such as low registration success rate, low handover success rate, or high error rate, the present invention can ensure network health by increasing the PRB uplink / downlink rate (percentage) and increasing the maximum number of RRC connected users. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of a network slicing health assessment method for marine 5G provided by the present invention. Detailed Implementation

[0024] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0025] Example 1:

[0026] A method for assessing the health of network slicing in marine 5G networks, comprising:

[0027] S1. Real-time collection of operational data in the ship's 5G private network via the network management interface deployed in the ship's local computer room. The operational data includes at least: registration success rate, session establishment success rate, handover success rate; uplink / downlink bit error rate, uplink / downlink data retransmission rate; number of alarms and alarm level.

[0028] S2. Input the above operational data into the preset health assessment model to calculate the overall health score H:

[0029] H = (Registration success rate × W1) + (Session establishment success rate × W2) + (Switch success rate × W3) + (1 - Downlink bit error rate) × W4 + (1 - Uplink bit error rate) × W5 + (1 - Downlink data retransmission rate) × W6 + (1 - Uplink data retransmission rate) × W7 + Critical alarm level value × W8 + Major alarm level value × W9 + Minor alarm level value × W10 + Warning alarm level value × W11;

[0030] Where W1 to W11 are preset weighting factors, and W1+W2+…+W11=100.

[0031] S3. If H is less than the preset value, a network parameter adjustment command is triggered. The adjustment command includes at least one of the following: increasing the PRB downlink rate percentage; increasing the PRB uplink rate percentage; increasing the maximum number of RRC connected users.

[0032] Specifically, the alarm level value is determined based on the number of alarms. In this embodiment, if the number of alarms is less than 5, the alarm level value is 1; if 5 ≤ the number of alarms is less than 10, the alarm level value is 0.9; if 10 ≤ the number of alarms is less than 20, the alarm level value is 0.7; if 20 ≤ the number of alarms is less than 30, the alarm level value is 0.6; and if 30 ≤ the number of alarms is less than 30, the alarm level value is 0.5.

[0033] As an example, 10≤W1≤15; 10≤W2≤15; 10≤W3≤15; 5≤W4≤10; 5≤W5≤10; 5≤W6≤10; 5≤W7≤10; 10≤W8≤35; 1≤W9≤10; 1≤W10≤5.

[0034] Specifically, in this embodiment, the network parameter adjustment mechanism is a closed-loop control mechanism. The adjusted network indicators will be re-substituted into the overall health calculation formula for real-time evaluation and dynamic optimization.

[0035] As an example, the overall health score is divided into two levels: excellent and poor, with a health score of 80 as the dividing line. If, under stable and anomaly-free network conditions, the registration / session establishment / handover success rates are all 100%, the bit error rate and retransmission rate are both 0, and there are no alarms (alarm level value 1), then the overall health score can reach 100 points, resulting in an excellent score. This health assessment method is calculated from eight statistical dimensions of business indicators, with weighting factors being original network indicator factors, the values ​​of which can be obtained from the device network management side via an interface.

[0036] More specifically, the registration success rate is the AMF initial registration success rate. Registration success rate = Number of successful AMF initial registration requests / Number of initial AMF registration requests. The session establishment success rate is the SMF PDU session establishment success rate. Session establishment success rate = Number of successful SMF PDU session establishments / Number of SMF PDU session establishment requests. The handover success rate is the inter-station and intra-station handover success rate within the same frequency band. Handover success rate = (Number of successful inter-station handovers xn + Number of successful intra-station handovers Ng) / (Number of inter-station handover attempts xn + Number of intra-station handover attempts Ng). The uplink bit error rate refers to the uplink retransmission failure rate even after reaching the maximum retransmission count.

[0037] Uplink bit error rate = (Number of TBs that failed to retransmit after reaching the maximum number of retransmissions (Pi / 2BPSK) BPSK + Number of TBs that failed to retransmit after reaching the maximum number of retransmissions (QPSK) + Number of TBs that failed to retransmit after reaching the maximum number of retransmissions (16QAM) + Number of TBs that failed to retransmit after reaching the maximum number of retransmissions (64QAM) + Number of TBs that failed to retransmit after reaching the maximum number of retransmissions (256QAM)) / (Number of TBs retransmitted through the UL-SCH channel (Pi / 2BPSK) + Number of TBs retransmitted through the UL-SCH channel (QPSK)) SK)+DL-UL-SCH channel retransmission TB (16QAM)+UL-SCH channel retransmission TB (64QAM))+UL-SCH channel retransmission TB (256QAM)+UL-SCH channel initial transmission TB (Pi / 2BPSK)+UL-SCH channel initial transmission TB (QPSK)+UL-SCH channel initial transmission TB (16QAM)_1911816585+UL-SCH channel initial transmission TB (64QAM)+UL-SCH channel initial transmission TB (256QAM)).

[0038] Downlink bit error rate refers to the error rate when downlink retransmission fails even after reaching the maximum number of retransmissions. Downlink bit error rate = (Number of TBs that failed to retransmit after reaching the maximum number of retransmissions (QPSK) + Number of TBs that failed to retransmit after reaching the maximum number of retransmissions (16QAM) + Number of TBs that failed to retransmit after reaching the maximum number of retransmissions (64QAM) + Number of TBs that failed to retransmit after reaching the maximum number of retransmissions (256QAM)) / (DL-SCH channel retransmission TBs (QPSK) - 1911816684 + DL-SCH channel retransmission TBs (16QAM) + DL-SCH channel retransmission TBs (64QAM) + DL-SCH channel retransmission TBs (256QAM) + DL-SCH channel initial transmission TBs (QPSK) + DL-SCH channel initial transmission TBs (16QAM) + DL-SCH channel initial transmission TBs (64QAM) + DL-SCH channel initial transmission TBs (256QAM).

[0039] Uplink data retransmission rate refers to the UL-SCH channel retransmission rate. Uplink data retransmission rate = (UL-SCH channel retransmission TB (Pi / 2BPSK) + UL-SCH channel retransmission TB (QPSK) + DL-UL-SCH channel retransmission TB (16QAM) + UL-SCH channel retransmission TB (64QAM)) + UL-SCH channel retransmission TB (256QAM) + UL-SCH channel initial transmission TB (Pi / 2BPSK)) / (UL-SCH channel retransmission TB (Pi / 2BPSK) + UL-SCH channel retransmission TB) Number of retransmissions (QPSK) + DL-UL-SCH channel retransmissions (16QAM) + UL-SCH channel retransmissions (64QAM) + UL-SCH channel retransmissions (256QAM) + UL-SCH channel initial transmissions (Pi / 2BPSK) + UL-SCH channel initial transmissions (QPSK) + UL-SCH channel initial transmissions (16QAM) + UL-SCH channel initial transmissions (64QAM) + UL-SCH channel initial transmissions (256QAM).

[0040] Downlink data retransmission rate refers to the DL-SCH channel retransmission rate. Downlink data retransmission rate = (DL-SCH channel retransmission TB (QPSK) + DL-SCH channel retransmission TB (16QAM) + DL-SCH channel retransmission TB (64QAM) + DL-SCH channel retransmission TB (256QAM) / (DL-SCH channel retransmission TB (QPSK) + DL-SCH channel retransmission TB (16QAM) + DL-SCH channel retransmission TB (64QAM) + DL-SCH channel retransmission TB (256QAM)) + DL-SCH channel initial transmission TB (QPSK) + DL-SCH channel initial transmission TB (16QAM) + DL-SCH channel initial transmission TB (64QAM) + DL-SCH channel initial transmission TB (256QAM).

[0041] Alarm severity levels are categorized based on the total number of alarms across the network, with fewer alarms resulting in a higher severity level. For example: 1) Alarms < 5: Alarm severity level 1; 2) 5 <= Alarms < 10: Alarm severity level 0.9; 3) 10 <= Alarms < 20: Alarm severity level 0.7; 4) 20 <= Alarms < 30: Alarm severity level 0.6; 5) 30 <= Alarms: Alarm severity level 0.5. Alarm severity levels are also calculated based on alarm severity. For instance, if there are 4 severe alarms (less than 5), the severity severity level is 1; if there are 12 minor alarms (between 10 and 20), the minor alarm severity level is 0.7.

[0042] When the overall health is poor, it is necessary to adjust and optimize the network indicator parameters, and the health value will change accordingly. The health assessment model designed in this embodiment can accurately reflect the impact of the adjustments in near real-time. The adjustable network indicator parameters are as follows:

[0043] 1) PRB downlink rate (percentage);

[0044] 2) PRB uplink rate (percentage);

[0045] 3) Maximum number of RRC connected users.

[0046] When health deteriorates due to reasons such as low registration success rate, low handover success rate, or high error rate, network health can be ensured by increasing the PRB uplink / downlink rate (percentage) and increasing the maximum number of RRC connected users.

[0047] Example 2:

[0048] Based on the embodiments, a marine 5G network slice health assessment device is provided, comprising:

[0049] The data acquisition unit is used to collect registration success rate, session establishment success rate, handover success rate, bit error rate, retransmission rate and alarm information in real time.

[0050] The calculation unit is used to calculate the overall health score;

[0051] The judgment unit is used to determine whether the overall health score is below 80 points and trigger the adjustment mechanism.

[0052] The execution unit is used to adjust network parameters based on the judgment result.

[0053] Example 3:

[0054] Based on Embodiment 1, a computer-readable storage medium is provided, on which a computer program is stored, wherein the program, when executed by a processor, performs the steps of the network slice health assessment method for marine 5G described in Embodiment 1.

[0055] In summary, the above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for assessing the health of a marine 5G network slice, characterized in that, include: S1. Real-time collection of operational data in the ship's 5G private network via the network management interface deployed in the ship's local computer room. The operational data includes at least: registration success rate, session establishment success rate, handover success rate; uplink / downlink bit error rate, uplink / downlink data retransmission rate; number of alarms and alarm level. S2. Input the above operational data into the preset health assessment model to calculate the overall health score H: H = (Registration success rate × W1) + (Session establishment success rate × W2) + (Switch success rate × W3) + (1 - Downlink bit error rate) × W4 + (1 - Uplink bit error rate) × W5 + (1 - Downlink data retransmission rate) × W6 + (1 - Uplink data retransmission rate) × W7 + Critical alarm level value × W8 + Major alarm level value × W9 + Minor alarm level value × W10 + Warning alarm level value × W11; Where W1 to W11 are preset weighting factors, and W1+W2+…+W11=100. S3. If H is less than the preset value, a network parameter adjustment command is triggered. The adjustment command includes at least one of the following: increasing the PRB downlink rate percentage; increasing the PRB uplink rate percentage; increasing the maximum number of RRC connected users.

2. The method for assessing the health of a marine 5G network slice according to claim 1, characterized in that, The alarm level value is determined based on the number of alarms.

3. The method for assessing the health of a marine 5G network slice according to claim 2, characterized in that: The number of alarms is less than 5, and the alarm level value is 1. If the number of alarms is 5 or less and the number of alarms is less than 10, the alarm level value is 0.

9. If the number of alarms is between 10 and 20, the alarm level value is 0.

7. If the number of alarms is 20 or less and the number of alarms is less than 30, the alarm level value is 0.

6. 30 ≤ number of alarms, alarm level value is 0.

5.

4. A method for assessing the health of a marine 5G network slice according to any one of claims 1 to 3, characterized in that, 10≤W1≤15;10≤W2≤15;10≤W3≤15;5≤W4≤10;5≤W5≤10;5≤W6≤10;5≤W7≤10;10≤W8≤35;1≤W9≤10;1≤W10≤5。 5. A method for assessing the health of a marine 5G network slice according to any one of claims 1 to 3, characterized in that, The network parameter adjustment mechanism is a closed-loop control mechanism. The adjusted network indicators will be re-substituted into the overall health calculation formula for real-time evaluation and dynamic optimization.

6. A marine 5G network slice health assessment device, characterized in that, The network slice health assessment method for marine 5G according to any one of claims 1 to 5 includes: The data acquisition unit is used to collect registration success rate, session establishment success rate, handover success rate, bit error rate, retransmission rate and alarm information in real time. The calculation unit is used to calculate the overall health score; The judgment unit is used to determine whether the overall health score is below 80 points and trigger the adjustment mechanism. The execution unit is used to adjust network parameters based on the judgment result.

7. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the steps of the network slice health assessment method for marine 5G as described in any one of claims 1 to 5.

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