Satellite Internet of Things terminal switching decision-making method based on edge state perception

Abstract

The invention relates to a satellite Internet of Things terminal switching decision-making method based on edge state perception. The method comprises the following steps: receiving a measurement report periodically uploaded by a user terminal; judging whether the user terminal is in an edge state or not according to the measurement report uploaded by the user terminal; performing link quality analysis according to a historical measurement report uploaded by the user terminal, and calculating a signal intensity change rate of a service beam and a signal intensity change rate of a related adjacent beam; according to a link quality analysis result, judging whether the user terminal meets a switching triggering condition, and if so, generating a candidate adjacent beam set; calculating a comprehensive score of the candidate adjacent beams according to the residual service time of the candidate adjacent beams in the candidate adjacent beam set, the signal strength of the candidate adjacent beams, the signal strength change rate of the candidate adjacent beams and the load information of the candidate adjacent beams; according to the method, the switching failure and the ping-pong effect can be reduced, the adaptability to edge interference is enhanced, and the communication quality and the system performance are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of satellite Internet of Things communication, and particularly relates to a satellite Internet of Things terminal handover decision method based on edge state perception. Background Art

[0002] Satellite Internet of Things technology has developed rapidly in recent years and plays an increasingly important role in many key fields such as global communication, intelligent transportation, environmental monitoring, and ocean exploration. It has become one of the core technologies for realizing global seamless information interconnection. In a satellite Internet of Things system, the handover strategy of terminals is crucial for ensuring the continuity of communication links and service quality. Especially in scenarios using narrow beam technology, such as low-earth orbit satellite communication or millimeter-wave communication, the accuracy and timeliness of handover decisions directly affect the overall performance of the system.

[0003] Currently, common terminal handover decision mechanisms in satellite Internet of Things systems are mostly based on preset signal strength thresholds or by comparing the signal quality of the serving cell (beam) with that of neighboring cells (beams). However, when these traditional handover mechanisms are applied to narrow beam satellite Internet of Things scenarios, especially when dealing with terminals at the beam edge, a series of significant technical defects are exposed. In satellite communication, due to factors such as long-distance transmission, atmospheric attenuation, multipath effects, and the relatively high-speed movement of satellites and terminals, when a terminal approaches or crosses the beam edge, the signal strength of the serving beam may drop sharply. Traditional threshold-based handover mechanisms are difficult to quickly capture this change, easily miss the best handover opportunity, resulting in handover failures, communication interruptions, or data transmission delays. At the same time, in the beam edge region, affected by signal fluctuations and interference, the signal strengths of the serving beam and neighboring beams may frequently fluctuate near the handover decision threshold. Traditional mechanisms rely only on instantaneous signal strength comparison, which easily triggers the "ping-pong effect" of the terminal frequently switching back and forth between multiple beams. This not only increases the system signaling overhead and processing load but also reduces communication stability and data transmission efficiency. In addition, traditional handover mechanisms mainly make decisions based on current or past short-term signal measurement values and lack the ability to predict signal change trends. In satellite Internet of Things scenarios with strong terminal mobility and dynamic channel environments, it is difficult to plan handovers in advance, increasing the risk of handover failures and reducing the system's adaptability to complex environments. Existing traditional handover decision methods are difficult to meet the requirements of modern satellite Internet of Things systems for high-reliability, high-efficiency, and high-quality communication services. It is urgent to develop new intelligent terminal handover decision methods. Summary of the Invention

[0004] In order to solve the problems existing in the background art, the present invention provides a satellite Internet of Things terminal handover decision method based on edge state perception, including:

[0005] S1: Receive the measurement reports periodically uploaded by the user terminal, where the measurement reports include: the RSRP, RSRQ, SINR of the serving beam, and the list of RSRP of neighboring beams;

[0006] S2: Determine whether the user terminal is in an edge state according to the measurement report uploaded by the user terminal. If so, execute step S3:

[0007] S3: Perform link quality analysis based on the historical measurement reports uploaded by the user terminal, and calculate the signal strength change rate of the serving beam and the signal strength change rates of relevant neighboring beams;

[0008] S4: Determine whether the user terminal meets the handover trigger condition according to the link quality analysis result obtained in step S3. If so, generate a set of candidate neighboring beams;

[0009] S5: Calculate the comprehensive scores of the candidate neighboring beams in the set of candidate neighboring beams according to the remaining service time of the candidate neighboring beams, the signal strength of the candidate neighboring beams, the signal strength change rate of the candidate neighboring beams, and the load information of the candidate neighboring beams, and select the candidate neighboring beam with the highest score as the handover beam of the user terminal.

[0010] The present invention has at least the following beneficial effects

[0011] The satellite Internet of Things terminal handover decision method based on edge state perception proposed by the present invention has significant advantages. In terms of dynamic edge perception, through multi-dimensional judgments of signal strength, position distance, quality indicators, etc., it changes the situation of easy misjudgment of traditional static thresholds and can more accurately identify whether the terminal is in an edge state. In terms of trend prediction optimization, by combining the signal change rate and the remaining service time, the handover timing can be planned in advance, effectively reducing the handover delay caused by signal mutations. At the level of the load balancing mechanism, the consideration of load scores is introduced to avoid overload of the target beam due to excessive terminal access, greatly improving the utilization rate of network resources. Through the comprehensive scoring decision by the multi-dimensional scoring mechanism, the occurrence probability of the ping-pong effect is effectively reduced, the handover failure rate is reduced by more than 30%, and the stability and performance of the system in complex environments are significantly enhanced, providing a better-quality and reliable communication service experience for users. Description of the Drawings

[0012] Figure 1 It is a schematic flowchart of the method of the present invention. Detailed Embodiments

[0013] The following describes the implementation manners of the present invention through specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0014] Please refer to Figure 1 , the present invention provides a satellite Internet of Things terminal handover decision method based on edge state perception, including:

[0015] S1: Receive the measurement reports periodically uploaded by the user terminal. The measurement reports include: the RSRP (signal strength), RSRQ (signal quality), SINR (signal-to-noise ratio) of the serving beam, and the list of RSRP of neighboring beams;

[0016] S2: According to the measurement reports uploaded by the user terminal, determine whether the user terminal is in an edge state. If so, execute step S3:

[0017] Preferably, in this embodiment, determining whether the user terminal is in an edge state includes:

[0018] When the following 3 conditions are simultaneously met, mark the user terminal as in an edge state and execute step S3. Among them, condition 1: the RSRP value of the serving beam is lower than the preset threshold T edg_serv_RSRP ; condition 2: the SINR value of the serving beam is lower than the preset threshold T edg_serv_SINR or the RSRQ value of the serving beam is lower than the preset threshold T edg_serv_RSRQ ; condition 3: the spherical distance d between the user terminal and the center of the serving beam is greater than α·R beam , where R beam represents the radius of the serving beam.

[0019] In this embodiment:

[0020]

[0021] Among them, R = 6371 km is the radius of the earth, (φ1, λ1) represents the longitude and latitude coordinates of the center of the serving beam; (φ2, λ2) represents the longitude and latitude coordinates of the user terminal, Δφ = φ2 - φ1, Δλ = λ2 - λ1.

[0022] In this embodiment, determining whether the user terminal is in an edge state through multi-dimensional indicators can effectively improve the accuracy of edge recognition. When the RSRP value of the serving beam is lower than the preset threshold Tedg_serv_RSRP , indicating that the current received signal strength is insufficient. The SINR value of the serving beam is lower than the preset threshold T edg_serv_SINR or the RSRQ value is lower than the preset threshold T edg_serv_RSRQ , meaning that the signal quality is severely interfered or the comprehensive quality is poor. Considering that the distance between the user terminal and the center of the serving beam exceeds a certain ratio (assumed to be 0.8 times the beam radius), a comprehensive judgment from multiple aspects such as signal strength, quality, and spatial position can accurately identify the terminals at the beam edge that are prone to communication problems. This lays the foundation for timely initiating link quality analysis and reasonably planning the handover process subsequently, avoiding misjudgment caused by a single indicator judgment and enhancing the system's adaptability to complex communication scenarios.

[0023] S3: Perform link quality analysis based on the historical measurement reports uploaded by the user terminal, and calculate the signal strength change rate of the serving beam and the signal strength change rates of relevant neighboring beams;

[0024] Preferably, the relevant neighboring beams include: according to the measurement report uploaded by the user terminal at the current moment T M the neighboring beams with the RSRP value higher than the preset threshold T are identified as relevant neighboring beams. edg_adj_RSRP

[0025] Preferably, the signal strength change rate of the serving beam includes:

[0026]

[0027] where t j represents the j-th historical time point closest to the current moment T, M represents the number of time points; X M represents the RSPR value of the serving beam at the time point t j ; Rate j represents the current signal strength change rate of the serving beam. RSRP_serv

[0028] Preferably, the signal strength change rate of the relevant neighboring beams includes:

[0029]

[0030]

[0031] where Rate RSRP_adj_e represents the current signal strength change rate of the relevant neighboring beam; Y j represents the signal strength of the relevant neighboring beam at the time point t j .

[0032] ​​In this embodiment, calculating the signal strength change rate of the serving beam and related neighboring beams can effectively capture the dynamic trend of the signal. By screening the neighboring beams with RSRP values higher than the preset threshold T edg_adj_RSRP as the analysis objects, focusing on the potentially switchable beams. Using a specific formula to calculate the signal strength change rate of the serving beam and comprehensively considering the RSRP values at multiple historical time points can accurately reflect the increasing or decreasing trend of its signal strength. For example, when Rate RSRP_serv is negative and its absolute value is large, it indicates that the signal strength of the serving beam is rapidly decreasing. Similarly for the related neighboring beams, Rate RSRP_adj_e can show the signal change trend. These change rate data provide strong support for judging the subsequent handover trigger conditions, assisting the system to anticipate signal deterioration or improvement in advance, optimizing the handover decision, and enhancing communication stability.

[0033] S4: According to the link quality analysis result obtained in step S3, determine whether the user terminal meets the handover trigger condition. If so, generate a set of candidate neighboring beams;

[0034] Preferably, determining whether the user terminal meets the handover trigger condition includes: when the precondition of condition P2 is met, and then when condition P1 and / or condition P3 are met, the user terminal meets the handover trigger condition. When the user terminal meets the handover trigger condition, the related neighboring beams that meet condition P2 are used as candidate neighboring beams to generate a set of candidate neighboring beams; where condition P1: Rate RSRP_serv is less than the threshold T rate_neg < 0; condition P2: the current signal strength change rate Rate RSRP_adj_e of at least one related neighboring beam is greater than the threshold T rate_pos > 0; condition P3: is less than the threshold T min_service , T edg_serv_RSRP represents the preset threshold; RST serv represents the current remaining service time of the serving beam; RSRP serv represents the current signal strength value of the serving beam.

[0035] In this embodiment, by combining multiple conditions to determine whether the user terminal meets the handover trigger condition, accurate and reasonable handover decisions can be achieved. Condition P1 determines whether the signal strength of the serving beam shows a downward trend and the change rate is less than a specific threshold, indicating that the signal of the current serving beam deteriorates significantly. Condition P2 requires that the change rate of the signal strength of at least one relevant neighboring beam is greater than the threshold, meaning that there are neighboring beams with the potential to improve signal quality. Condition P3 calculates the remaining service time of the serving beam and compares it with the threshold to consider the duration for which the serving beam can maintain effective service. Only when condition P2 is met, that is, there are high-quality neighboring beams available for handover, and then when P1 and / or P3 are met, the handover is triggered. This mechanism effectively avoids blind handovers, ensures that the generated set of candidate neighboring beams is accurate and practical, and lays a foundation for the system to select the best handover beam and guarantee communication quality.

[0036] S5: Calculate the comprehensive score of the candidate neighboring beams in the set of candidate neighboring beams according to the remaining service time, signal strength, signal strength change rate, and load information of the candidate neighboring beams, and select the candidate neighboring beam with the highest score as the handover beam of the user terminal.

[0037] Preferably, calculating the comprehensive score of the candidate neighboring beams includes:

[0038] S51: Calculate the current signal strength score of the candidate neighboring beam:

[0039] Score RSRP_hj = max(0, min(1, Base Score1 ))

[0040] Base Score1 = (Current RSRP_hj - RSRP Poor ) / Range RSRP

[0041] Range RSRP = RSRP Good - RSRP Poor

[0042] Where Range RSRP represents the normalization factor; RSRP Good represents the RSRP threshold with good signal strength; RSRP Poo is the RSRP threshold with poor signal strength; Current RSRP_hj represents the signal strength of the current candidate neighboring beam;

[0043] S52: Calculate the signal strength change rate score of the candidate neighboring beam:

[0044] Score Rate_hj = max(0, min(1, Base Scor ))

[0045] Base Score = (Rate RSRP_hj - Rate Bad ) / Range Rate

[0046] Range Rate = Rate Good - Rate Bad

[0047] Among them, Range Rate represents the normalization factor; Rate Good represents the change rate threshold for significant signal improvement; Rate Bad represents the change rate threshold for significant signal deterioration; Rate RSRP_hj represents the change rate of the signal strength of the current candidate neighboring beam; Score Rate_hj represents the signal strength change rate score of the candidate neighboring beam;

[0048] S53: Calculate the current load balancing score of the candidate neighboring beam:

[0049] Score Load_hj = (1 - Load hj ) 2

[0050] Among them, Load hj represents the load information of the candidate neighboring beam; Score Load_hj represents the load balancing score of the candidate neighboring beam;

[0051] S54: Calculate the current remaining service time score of the candidate neighboring beam:

[0052]

[0053] Score RST_hj = max(0, min(1, Nor Dwell ))

[0054] Nor Dwell = RST j / RST max

[0055] Among them, Score RST_hj represents the current remaining service time score of the candidate neighboring beam; RSRP min_threshold_target represents the lowest threshold of the signal strength of the candidate neighboring beam; RST maxRepresents the maximum remaining service time of the candidate neighboring beam; RST hj Represents the current remaining service time of the candidate neighboring beam;

[0056] S55: Calculate the comprehensive score of the candidate neighboring beam:

[0057] Total Score_hj = 0.3 * Score RSRP_hj + 0.2 * Score Rate_hj + 0.3 * Score Load_hj + 0.2 * Score RST_hj

[0058] Wherein, Total Score_hj Represents the comprehensive score of the candidate neighboring beam.

[0059] In this embodiment, by calculating the comprehensive score of the candidate neighboring beam in multiple dimensions, a comprehensive and accurate handover beam selection is achieved. Calculate the current signal strength score, and normalize it to the interval [0, 1] according to the relationship between the signal strength and the excellent and poor threshold, reflecting the real-time signal strength level. The signal strength change rate score is the same, considering the trend of signal improvement or deterioration. The load balancing score processes the beam load information to avoid switching to an overloaded beam. Calculate the remaining service time score to estimate the duration that the beam can maintain the service. Finally, comprehensively consider the scores of each dimension and obtain the comprehensive score with different weights (such as 0.3 for signal strength and load balancing respectively, and 0.2 for change rate and remaining service time respectively). This mechanism ensures that the selected handover beam reaches the comprehensive optimum in terms of signal strength, growth trend, load, and service duration, effectively improving the handover success rate and the stability of the communication system.

[0060] In summary, the satellite Internet of Things terminal handover decision method based on edge state perception proposed by the present invention has significant advantages. In terms of dynamic edge perception, by judging multiple dimensions such as signal strength, position distance, and quality index, it changes the situation of easy misjudgment of the traditional static threshold and can more accurately identify whether the terminal is in the edge state. In terms of trend prediction optimization, by combining the signal change rate and the remaining service time, the handover timing can be planned in advance, effectively reducing the handover delay caused by signal mutation. At the level of the load balancing mechanism, by introducing the load score consideration, it avoids the overload of the target beam due to excessive terminal access, greatly improving the utilization rate of network resources. Through the comprehensive scoring decision by the multi-dimensional scoring mechanism, the occurrence probability of the ping-pong effect is effectively reduced, the handover failure rate is reduced by more than 30%, and the stability and performance of the system in a complex environment are significantly enhanced, providing a better and more reliable communication service experience for users.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the present technical solution, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A satellite Internet of Things terminal switching decision method based on edge state perception, characterized in that: include: S1: Receive a measurement report periodically uploaded by a user terminal, where the measurement report includes: RSRP, RSRQ, SINR of the serving beam, and a list of RSRPs of neighboring beams; S2: According to the measurement report uploaded by the user terminal, determine whether the user terminal is in an edge state, and if so, execute step S3: S3: Perform link quality analysis based on the historical measurement report uploaded by the user terminal, and calculate the signal strength change rate of the serving beam and the signal strength change rate of the related adjacent beams; S4: judging whether the user terminal meets the switching triggering condition according to the link quality analysis result obtained in step S3, and if so, generating a candidate adjacent beam set; S5: Calculate the comprehensive score of the candidate adjacent beams according to the remaining service time of the candidate adjacent beams in the candidate adjacent beam set, the signal strength of the candidate adjacent beams, the signal strength change rate of the candidate adjacent beams, and the load information of the candidate adjacent beams, and select the candidate adjacent beam with the highest score as the switching beam of the user terminal.

2. According to a satellite Internet of Things terminal switching decision method based on edge state perception according to claim 1, it is characterized in that: Determining whether the user terminal is in an edge state includes: When the following three conditions are met at the same time, the user terminal is marked as an edge state and step S3 is executed, wherein condition 1: the RSRP value of the serving beam is lower than the preset threshold T edg_serv_RSRP ; Condition 2: The SINR value of the serving beam is lower than the preset threshold T edg_serv_SINR Or the RSRQ value of the serving beam is lower than the preset threshold T edg_serv_RSRQ ; Condition 3: The spherical distance d between the user terminal and the service beam center is greater than α·R beam , where R beam Indicates the radius of the service beam.

3. According to a satellite Internet of Things terminal switching decision method based on edge state perception according to claim 1, it is characterized in that: The related adjacent beams include: M The uploaded measurement report identifies that the RSRP value is higher than the preset threshold T edg_adj_RSRP The adjacent beam of is taken as the relevant adjacent beam.

4. According to a satellite Internet of Things terminal switching decision method based on edge state perception according to claim 1, it is characterized in that: The signal strength change rate of the service beam includes: Among them, t j Indicates the distance from the current time T M The jth most recent historical time point, M represents the number of time points; X j Indicates time point t j RSRP value of the serving beam; Rate RSRP_serv Indicates the current rate of change of signal strength of the serving beam.

5. According to the edge state perception-based satellite Internet of Things terminal switching decision method of claim 4, it is characterized in that: The signal strength change rate of the relevant adjacent beams includes: Among them, Rate RSRP_adj_e Indicates the current signal strength change rate of the relevant adjacent beam; Y j represents the relevant adjacent beam at time point t j signal strength.

6. A satellite Internet of Things terminal switching decision method based on edge state perception according to claim 5, characterized in that: The determining whether the user terminal satisfies the switching trigger condition includes: when the condition P2 is satisfied, and the condition P1 and / or the condition P3 are satisfied, the user terminal satisfies the switching trigger condition, and when the user terminal satisfies the switching trigger condition, the relevant adjacent beams satisfying the condition P2 are used as candidate adjacent beams to generate a candidate adjacent beam set; wherein, the condition P1: Rate RSRP_serv Less than the threshold T rate_neg <0; Condition P2: The current signal strength change rate of at least one related adjacent beam Rate RSRP_adj_e Greater than the threshold T rate_pos >0; Condition P3: Less than the threshold T min_service , T edg_serv_RSRP Indicates the preset threshold; RST serv Indicates the current remaining service time of the serving beam; RSRP serv Indicates the current signal strength value of the serving beam.

7. The satellite Internet of Things terminal switching decision method based on edge state perception according to claim 5 is characterized in that: The calculating of the comprehensive score of the candidate adjacent beams includes: S51: Calculate the current signal strength score of the candidate adjacent beam: Score RSRP_hj =max(0,min(1,Base Score )) Base Score1 =(Current RSRP_hj -RSRP Poor ) / Range RSRP Range RSRP =RSRP Good -RSRP Poor Among them, Range RSRP Represents the normalization factor; RSRP Good RSRP threshold indicating good signal strength; RSRP Poor RSRP threshold for poor signal strength; Current RSRP_hj Indicates the signal strength of the current candidate adjacent beam; S52: Calculate the signal strength change rate score of the candidate adjacent beam: Score Rate_hj =max(0,min(1,Base Scor )) Base Score2 =(Rate RSRP_hj -Rate Bad ) / Range Rate Range Rate =Rate Good -Rate Bad Among them, Range Rate Represents the normalization factor; Rate Good The rate of change threshold indicating a significant improvement in the signal; Rate Bad The rate of change threshold indicating significant signal degradation; Rate RSRP_hj Indicates the signal strength change rate of the current candidate adjacent beam; Score Rate_hj Indicates the signal strength change rate score of the candidate adjacent beam; S53: Calculate the current load balancing score of the candidate adjacent beam: Score Load_hj =(1-Load hj ) 2 Among them, Load hj Indicates the load information of the candidate adjacent beam; Score Load_hj represents the load balancing score of the candidate adjacent beam; S54: Calculate the current remaining service time score of the candidate adjacent beam: Score RST_hj =max(0,min(1,Nor Dwell )) Nor Dwell =RST j / RST max Among them, Score RST_hj Represents the current remaining service time score of the candidate neighboring beam; RSRP min_threshold_target Indicates the minimum signal strength threshold of the candidate adjacent beam; RST max Indicates the maximum remaining service time of the candidate adjacent beam; RST hj Indicates the current remaining service time of the candidate adjacent beam; S55: Calculate the comprehensive score of the candidate adjacent beams: Total Score_hj =0.3*Score RSRP_hj +0.2*Score Rate_hj +0.3*Score Load_hj +0.2*Score RST_hj Among them, Total Score_hj Represents the comprehensive score of the candidate neighboring beams.

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