Perception-driven random access method and system for satellite-ground heterogeneous network

Abstract

The invention relates to a perception-driven random access method and system for a satellite-ground heterogeneous network, and the method comprises the steps: introducing active real-time perception in an initial stage of a user access process, and carrying out the shunting of users of which the channel quality is lower than a threshold value based on a dynamic decision threshold of real-time perception, therefore, the effective access load is controlled at a level which is lower than the nominal system load. Compared with the prior art, by actively sensing the channel state, users with poor channel conditions are effectively screened, and the beam search range is narrowed, so that the first access success rate and the system throughput are remarkably improved, the access delay is reduced, and the extra overhead is small.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a perception-driven random access method and system for heterogeneous satellite-ground networks (such as low Earth orbit satellite communication networks). Background Technology

[0002] In smart grids, emergency communications, and other scenarios, heterogeneous satellite-ground networks, especially low Earth orbit (LEO) satellite networks, play a crucial role. However, user equipment (UE) faces significant challenges in the initial access (IA) process when connecting to these networks. First, the high-speed movement of satellites and ground obstacles cause frequent and rapid signal congestion in the link between satellites and ground users. Second, long propagation delays make traditional multi-step handshake mechanisms inefficient. Furthermore, in emergency situations, the simultaneous access of a large number of users can trigger severe network congestion.

[0003] Existing random access (RA) mechanisms, such as the four-step random access channel (RACH) procedure defined in LTE and 5G NR, are primarily designed for terrestrial networks and are ill-suited to address the unique challenges of integrated space-ground networks. Current optimization schemes for non-terrestrial networks (NTNs) are mostly piecemeal improvements, such as using physical layer adaptation to compensate for latency or relying on external GNSS information for location-assisted beam management. However, these methods cannot detect instantaneous channel congestion. Furthermore, congestion control mechanisms like Access Class Limitation (ACB) are passive responses, intervening only after congestion occurs and failing to prevent invalid access attempts at the source.

[0004] A search revealed that Chinese Patent Publication No. CN103945558A discloses an adaptive channel access control method based on network load in wireless local area networks (WLANs). This method dynamically adjusts channel contention parameters by detecting the current network load, providing different channel access opportunities for services of different priorities to ensure users' QoS requirements. Simultaneously, it mitigates the unfairness in uplink and downlink throughput caused by differences in the number of APs and users by modifying the channel contention mechanism of access nodes (APs). However, this technology is applicable to WLANs but not to heterogeneous satellite-ground networks.

[0005] However, existing technologies lack a lightweight mechanism for heterogeneous satellite-ground networks that can proactively sense real-time channel conditions and use this information to intelligently guide access decisions and resource selection, thereby preventing invalid attempts and network congestion at the source of the access process.

[0006] Therefore, traditional random access mechanisms face three challenges in heterogeneous satellite-ground networks: signal congestion, high latency, and network congestion. These challenges together lead to low initial access success rates and poor system resource utilization efficiency. At the same time, existing technologies cannot actively avoid access attempts that are destined to fail due to poor channel conditions, nor can they effectively intervene before congestion occurs. As a result, valuable time and frequency resources are wasted on a large number of access collisions and retransmissions. The above are the technical problems that this invention aims to solve. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of the existing technology by providing a perception-driven random access method and system for heterogeneous satellite-ground networks. By introducing proactive sensing capabilities at the initial stage of the access process, the blind nature of access requests is fundamentally changed; and by ensuring from a mechanistic perspective, all competing users have a high probability of successful access, thereby effectively reducing the access load. Controlled at a level far below the nominal system load The level of [something] greatly alleviated the collision problem.

[0008] The objective of this invention can be achieved through the following technical solutions: According to one aspect of the present invention, a perception-driven random access method for heterogeneous satellite-ground networks is provided. This method introduces proactive real-time sensing at the initial stage of the user access process and, based on a dynamic decision threshold determined by real-time sensing, allows for access to systems with channel quality below a certain threshold. Users are diverted to avoid participating in the current Random Access Channel (RACH) contention, thereby reducing the effective access load. Controlled at a level below the nominal system load The level.

[0009] As a preferred technical solution, the method specifically includes the following steps: Step S1: Within a preset random access RA resource period, define an initial sensing micro-slot, the transmission priority of which is higher than that of the random access channel RACH. Step S2: The user equipment (UE) first sends a sensing signal to the network-side device through the sensing micro-time slot; Step S3: The network-side device receives and processes the sensing signal and obtains at least one piece of real-time status information about the user equipment (UE). Step S4: The network-side device generates an access policy based on the real-time status information and the current system load. The access policy includes at least a channel quality decision threshold and a candidate beam set. Step S5: The network-side device sends the access policy to the user equipment (UE). Step S6: The user equipment (UE) receives the access policy and compares its own channel quality with the channel quality decision threshold. Step S7: If and only if the channel quality of the user equipment UE meets the channel quality decision threshold, the user equipment UE initiates a subsequent RACH access request and selects a beam from the candidate beam set to send the access preamble.

[0010] As a preferred technical solution, the real-time status information in step S3 includes channel quality and / or user arrival direction; The network-side device evaluates the channel quality by analyzing the signal-to-noise ratio (SNR) or signal energy of the sensed signal, determines the user's direction of arrival by estimating the angle of arrival (AoA) of the sensed signal, and constructs the candidate beam set based on the angle of arrival.

[0011] As a preferred technical solution, the network-side device estimates an average user arrival rate in real time by counting the number of sensing signals received within the sensing micro-time slots. And based on this, the nominal system load is calculated. .

[0012] As a preferred technical solution, the network-side device dynamically adjusts the channel quality decision threshold. To achieve a balance between access opportunities and congestion control, when the nominal system load... When the threshold is increased, the channel quality decision threshold is raised to reduce the number of UEs initiating access requests, thereby reducing the effective access load. Keep it within the predetermined range; The channel quality decision threshold mentioned above The dynamic adjustment is based on a pre-calculated nominal system load. It is executed by mapping to a lookup table (LUT) that determines the decision threshold.

[0013] As a preferred technical solution, the access policy in step S4 further includes a backoff window W parameter, which the network-side device determines based on the total access delay budget. The fixed time occupied by sensing and beam alignment, and the channel quality decision threshold. Determined effective access load This allows for the dynamic determination of the backoff window parameters to meet the delay budget.

[0014] As a preferred technical solution, the access policy generation in step S4 specifically includes: solving the following constrained optimization problem to determine the channel quality decision threshold. Backoff window W and perceived resource ratio Beam selection strategy , in Let be the probability of successful initial access, which is the objective function for optimization. For effective load access, the channel quality decision threshold is... The function; T is the frame length; The length of the backoff slot; The size of the candidate beam set; This refers to the time for a single beam scan. The preset maximum allowed access latency; and These are the unit resource costs for sensing and control, respectively; Information entropy for beam selection strategies; This is the preset maximum allowed additional overhead.

[0015] According to another aspect of the present invention, a system is provided for the perception-driven random access method for a satellite-to-ground heterogeneous network, comprising at least one user equipment (UE) and a network-side device, the network-side device comprising: The communication unit is configured to receive sensing signals from the user equipment UE within a sensing micro-timeslot and to send access policies to the user equipment UE. A sensing unit is configured to process the sensing signal to acquire at least one piece of real-time status information about a user equipment (UE), the real-time status information including channel quality and / or user arrival direction; The decision unit is configured to generate the access policy based on the real-time status information and the current system load. The access policy includes at least a channel quality decision threshold and a candidate beam set. The communication unit receives the access preamble sent by the user equipment UE from the candidate beam set only during the subsequent random access channel (RACH) transmission process if the user equipment UE's own channel quality meets the channel quality decision threshold.

[0016] As a preferred technical solution, the decision unit estimates an average user arrival rate in real time by counting the number of sensing signals processed by the sensing unit within the sensing micro-time slot. And based on this, the nominal system load is calculated. ; The decision-making unit includes a storage module that stores a pre-computed lookup table (LUT). The decision-making unit utilizes this lookup table and, based on the nominal system load,... Determine the channel quality decision threshold To effectively access the load Keep it within the predetermined range; The decision-making unit is based on the total access delay budget. and the channel quality decision threshold Determined effective access load A backoff window parameter W is dynamically determined and included in the access policy.

[0017] As a preferred technical solution, the process by which the network-side device generates the access policy is performed by decoupling the decision variable set of the optimization problem into two subsets based on different time scales, specifically including: A semi-static configuration subset, whose parameters are configured based on long-term channel statistics and QoS requirements, includes at least the perceived resource allocation factor η and the size of the candidate beam set. ; The subset is dynamically adjusted, and its parameters are based on the real-time perceived system load. The dynamic adjustment subset includes at least the channel quality decision threshold τ and the backoff window parameter W, and is adjusted in accordance with the channel information. The dynamic determination of the backoff window parameter W specifically includes: a) Calculate the available delay budget for the RACH procedure of the random access channel. ,in The For the total access latency budget, the This is a fixed time occupied by sensing and beam alignment; b) Based on the available delay budget and effective access load ( ), calculate a maximum allowable backoff window The calculation method is as follows: c) Combine candidate backoff windows suggested by a pre-defined, load-related policy function. Finally, the backoff window parameter W was determined to be... .

[0018] Compared with the prior art, the present invention has the following advantages: 1) Proactive congestion control and load balancing: This invention uses perception-based access decisions to filter out access attempts with extremely low success rates at the source, thus effectively load balancing access. By keeping it within a controllable range, the probability of collisions is significantly reduced under high load conditions, avoiding the congestion and crash phenomenon commonly seen in traditional mechanisms. 2) Fast beam alignment: This invention reduces the beam search space from the entire space to a small candidate set by using the coarse position information obtained by sensing, which significantly reduces the time and signaling overhead required for beam scanning and alignment; 3) Improve access success rate and throughput: This invention can significantly improve the first access success rate of UE, especially under adverse conditions such as high load and poor channel conditions; since more users can access the system quickly and successfully, the waste of resources in invalid retransmissions is avoided, and the overall effective throughput of the system is also improved. 4) Low latency and low overhead: Although the present invention introduces sensing micro-slots, due to their short duration and ability to effectively reduce the number of retransmissions and beam alignment time in the subsequent RACH process, the total average access latency is kept at a low level, and the additional overhead of the entire mechanism is controlled within a very small range, achieving efficient resource utilization. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the SaRA system framework; Figure 2 This is a schematic diagram of the SaRA frame structure; Figure 3 A comparison chart of simulation results showing the relationship between initial connection success rate and system load; Figure 4 The simulation results show the relationship between the effective load and the nominal system load. Figure 5 A comparison graph showing the simulation results of the relationship between average access delay and system load; Figure 6 A breakdown diagram of access latency under different system loads; Figure 7 A comparison graph showing the simulation results of the relationship between system throughput and system load; Figure 8 A comparison chart of simulation results showing the relationship between initial access success rate and signal-to-noise ratio; Figure 9 A comparison chart of simulation results showing the relationship between initial access success rate and channel availability; Figure 10 A comparison chart of simulation results showing the relationship between the initial access success rate and the perceived missed detection rate; Figure 11 A comparison graph of simulation results showing the relationship between additional overhead and system load; Figure 12 This is a flowchart illustrating the specific process of the method of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0021] Example 1 This invention introduces effective access load. The concept of "effective access load" in RACH refers to the portion of user load that actually creates competitive pressure on limited RACH resources. In traditional mechanisms, the effective access load is approximately equal to the total nominal access load. In this invention, a dynamic decision threshold based on real-time perception is used to identify channels with channel quality below a certain threshold. Users are "distributed" to avoid participating in the current RACH channel contention. This mechanism ensures that users participating in the contention have a high probability of successful access, thereby distributing the effective access load. Controlled at a level far below the nominal load The level of [something] greatly alleviated the collision problem.

[0022] like Figure 1 As shown, a perception-driven random access method for heterogeneous satellite-ground networks specifically includes the following steps: Step S1: Within a preset random access RA resource period, define an initial sensing micro-slot, the transmission priority of which is higher than that of the random access channel RACH. Step S2: The user equipment (UE) first sends a sensing signal to the network-side device through the sensing micro-time slot; Step S3: The network-side device receives and processes the sensing signal and obtains at least one piece of real-time status information about the user equipment (UE). Step S4: The network-side device generates an access policy based on the real-time status information and the current system load. The access policy includes at least a channel quality decision threshold and a candidate beam set. Step S5: The network-side device sends the access policy to the user equipment (UE). Step S6: The user equipment (UE) receives the access policy and compares its own channel quality with the channel quality decision threshold. Step S7: If and only if the channel quality of the user equipment UE meets the channel quality decision threshold, the user equipment UE initiates a subsequent RACH access request and selects a beam from the candidate beam set to send the access preamble.

[0023] This invention effectively filters out users with poor channel conditions and narrows the beam search range by actively sensing the channel state, thereby significantly improving the first access success rate and system throughput, reducing access latency, and minimizing additional overhead.

[0024] Network-side devices assess channel quality by analyzing the signal-to-noise ratio (SNR) or signal energy of the sensed signals. The user's direction of arrival is determined by estimating the angle of arrival (AoA) of the sensed signals, and a candidate beamset is constructed based on this angle of arrival. An average user arrival rate is also estimated in real time by counting the number of sensed signals received within a sensing micro-timeslot. And based on this, the nominal system load is calculated. The network-side equipment dynamically adjusts the channel quality decision threshold. To achieve a balance between access opportunities and congestion control, when the nominal system load... When the threshold increases, the decision threshold is raised to reduce the number of UEs initiating access requests, thereby reducing the effective access load. Keep it within the predetermined range.

[0025] Channel quality decision threshold The dynamic adjustment is based on a pre-calculated nominal system load. The process is executed using a lookup table (LUT) mapped to a decision threshold. The access policy also includes a backoff window parameter W, based on the total access latency budget. The fixed time required for sensing and beam alignment, and the time determined by the decision threshold. Determined effective access load This allows for the dynamic determination of the backoff window parameters to meet the delay budget.

[0026] The channel quality decision threshold is determined by solving the following constrained optimization problem. Backoff window W and perceived resource ratio Beam selection strategy : in Let be the probability of successful initial access, which is the objective function for optimization. For effective load access, the channel quality decision threshold is... The function; T is the frame length; The length of the backoff slot; The size of the candidate beam set; This refers to the time for a single beam scan. The preset maximum allowed access latency; and These are the unit resource costs for sensing and control, respectively; Information entropy for beam selection strategies; This is the preset maximum allowed additional overhead.

[0027] This invention introduces a lightweight sensing micro-slot before the standard RACH procedure. During this micro-slot, the UE transmits a sparse sensing preamble. Network-side equipment (such as LEO satellites) can quickly obtain bypass information about the UE, such as channel quality and coarse direction of arrival, by receiving and analyzing this signal.

[0028] Based on this real-time acquired internal information, the network-side Radio Resource Manager (RRM) can dynamically generate an access policy. This policy mainly includes an access decision threshold. A candidate beam set And a backoff window parameter W. This decision threshold is used to proactively filter out users under severe channel conditions such as deep signal congestion, preventing them from initiating invalid access attempts, thus playing a role in proactive congestion control. Simultaneously, by using coarse direction-of-arrival information, the subsequent beam search range can be narrowed down to a small candidate set, greatly accelerating the beam alignment process. Only when the UE's own channel quality meets the decision threshold issued by the network is it allowed to select a beam from the specified candidate beam set to send the formal access preamble on subsequent RACH resources.

[0029] Example 2 This invention also constructs a perception-driven random access system for heterogeneous satellite-ground networks, comprising: The communication unit is configured to receive sensing signals from the user equipment UE within a sensing micro-timeslot and to send access policies to the user equipment UE. A sensing unit is configured to process the sensing signal to acquire at least one piece of real-time status information about a user equipment (UE), the real-time status information including channel quality and / or user arrival direction; The decision unit is configured to generate the access policy based on the real-time status information and the current system load. The access policy includes at least a channel quality decision threshold and a candidate beam set. The communication unit receives the access preamble sent by the user equipment UE from the candidate beam set only during the subsequent random access channel (RACH) transmission process if the user equipment UE's own channel quality meets the channel quality decision threshold.

[0030] The communication unit is further configured to receive the access preamble sent by the UE from the candidate beam set only on subsequent Random Access Channel (RACH) transmission opportunities if the UE's own channel quality meets the decision threshold. The decision unit is also configured to estimate an average user arrival rate in real time by counting the number of sensing signals processed by the sensing unit within the sensing micro-timeslot. And based on this, the nominal system load is calculated. The decision unit includes a storage module that stores a pre-computed lookup table (LUT). The decision unit uses this lookup table and, based on the nominal system load,... Determine the channel quality decision threshold To effectively access the load The delay is kept within a predetermined range. The decision-making unit also considers the total access latency budget. and by the decision threshold Determined effective access load A backoff window parameter W is dynamically determined and included in the access policy.

[0031] Example 3 System Model and Framework Reference Figure 1 This invention is implemented in a space-to-ground communication system consisting of LEO satellites and ground user equipment (UEs). The system includes UEs, LEO satellites as network-side equipment, and a Radio Resource Manager (RRM). In one embodiment of this invention, the RRM's functionality can be integrated onto the LEO satellite or located in a ground station. The network-side equipment can be internally divided into units that implement different functions, such as communication units, sensing units, and decision-making units. When a UE needs to access the network, the system executes the SaRA mechanism.

[0032] 1) The UE first transmits a sensing preamble in the sensing micro-slot.

[0033] 2) The communication unit of the LEO satellite receives the signal and hands it over to the sensing unit for processing, including channel sensing, direction of arrival estimation, and load estimation. The sensing results are then sent to the decision unit (RRM).

[0034] 3) The decision-making unit dynamically determines the access strategy based on the perceived information and system strategy, including the access threshold τ, the backoff window W, and the candidate beam set B.

[0035] 4) This access policy is fed back to the UE through downlink signaling of the communication unit.

[0036] 5) The UE determines whether its own channel quality meets the threshold τ. If it does, it is allowed to select a beam from the candidate beam set B to initiate an access request on subsequent RACH resources.

[0037] Frame structure reference Figure 2 The SaRA frame structure proposed in this invention is based on the 5G NR framework. Sensing micro-slots are located at the beginning of one or more subframes and consist of several OFDM symbols. Their total duration... It can be semi-statically adjusted according to network load to obtain channel information with minimal overhead. Where T is the frame length. This refers to the resource allocation factor for awareness. RACH corresponds to the PRACH transmission opportunity in 5G NR, allowing qualified UEs to initiate random access requests. Data is the resource used for uplink / downlink data transmission after a UE successfully accesses the network.

[0038] To more accurately describe the technical solution of this invention, the following mathematical model is introduced: 1) Arrival and Collision Model: It is assumed that within a frame, the total number of initial access requests from all UEs in the system follows an arrival rate of The system follows a Poisson distribution. It provides M RACH channels, each configured with K pseudo-random preamble sequences, therefore the total number of preamble resources is N = MK. The nominal system load... Defined as the ratio of average arriving requests to total preceding resources: Without a perception mechanism, the probability of a single access without collision is... Approximately .

[0039] 2) Perception and Decision Model: This invention introduces a decision threshold. Afterwards, not all Every user will initiate a RACH request. Only users who make decisions based on perception will do so. Assume the prior probability that the UE is in a good channel state is... The false negative rate (channel available but judged as unavailable) in the sensing process is: The false alarm rate (channel unavailable but judged as available) is: The average number of effective users in actual contention for the RACH channel. for: Corresponding payload for Therefore, after introducing a perception mechanism, the probability of no collision is increased to... .

[0040] 3) Latency Model: The total delay from when the UE generates an access intent to when the first data packet is successfully transmitted. It can be approximately decomposed into: in, It is the time spent perceiving; W is the average delay caused by collisions and backoff during the RACH process, and W is the size of the backoff window. The length of the backoff slot; In the size of The time required to perform beam scanning and alignment within the candidate beam set.

[0041] The core of this invention lies in constructing the resource allocation problem in random access as a constrained optimization problem, and solving it using a low-complexity suboptimal algorithm, thereby achieving dynamic and joint optimization of key parameters. The optimization objective is to maximize the probability of a user's first successful access. Its expression is: The objective function relates to system load, sensing accuracy, and link quality. Therefore, the following optimization problem can be constructed: Among them, constraint (C1) limits the average total access delay to no more than a preset threshold. (C2) limits the additional overhead from sensing and control signaling to no more than (C3) limits the false alarm rate of perception to no more than The rest are constraints on the range of parameter values.

[0042] The SaRA mechanism of this invention is a low-complexity, high-performance suboptimal solution algorithm for the aforementioned optimization problem. It decouples the complex joint optimization problem into configuration and adjustment based on different time scales, and its process can be decomposed into a three-step closed-loop process: Step 1: Real-time Information Acquisition During the sensing micro-slot at the beginning of each frame, the network side (satellite) processes the sensing preamble transmitted by the UE and obtains channel quality statistics. Roughly reach the angle Real-time system load Information such as...

[0043] Step 2: Dynamic optimization of access strategy After acquiring real-time information, the network-side decision unit (RRM) performs a lightweight optimization process to dynamically determine access parameters for the UEs. The decision-making unit bases its decisions on the real-time estimated nominal system load. (in To estimate the arrival rate (where N is the total number of leading resources), the optimal decision threshold is obtained by querying a pre-computed lookup table (LUT) in its internal storage module. This LUT can be generated through offline simulation or theoretical analysis, aiming to balance access success rate and system overhead. In determining the backoff window W, the decision unit first considers the total delay budget. Perception time of semi-static configuration Beam alignment time Calculate the maximum allowable delay budget for the RACH process. Then, based on that budget and according to Calculated effective load Calculate the maximum allowable backoff window. The final W will combine a load-related policy function and To determine and ensure that the total delay does not exceed the limit.

[0044] Step 3: Terminal-side access execution UE receives access policy from network Then, perform the following operations: 1) Measure its own instantaneous channel quality .

[0045] 2) With threshold Comparison. If If successful, proceed to the next step; otherwise, abandon this access attempt and wait for the next access opportunity.

[0046] 3. If the conditions are met, then select from the candidate beam set. Select a beam and transmit the access preamble on subsequent RACH resources. If a collision occurs, then... Retransmit after randomly selecting a backoff time slot within the range.

[0047] Example 4 To verify the beneficial effects of this invention, a simulation was conducted on a Monte Carlo event-driven simulation platform. In the simulation, the network-side device dynamically adjusted access parameters by solving a suboptimal algorithm for the aforementioned constrained optimization problem. The simulation parameters were set as follows: orbital altitude 550km, uplink carrier frequency 30GHz, system bandwidth 10MHz, UE transmit power 23dBm, average SNR range at cell edge 0-5dB, and total RACH preamble resources N=128. The maximum access delay budget was 150ms, and the maximum additional overhead budget was 8%.

[0048] Simulation results are as follows Figures 3 to 11 As shown, the SaRA method of the present invention is compared with three baseline schemes: 1) Traditional RACH: A baseline 4-step RACH without any sensing or active control.

[0049] 2) Location-Assisted Access: An idealized solution that assumes the UE can perfectly obtain beam information through external information (such as GNSS), but has no channel awareness capability.

[0050] 3) Fixed Frame - SaRA: A non-adaptive variant of SaRA, whose access parameters are fixed and do not dynamically adjust with load.

[0051] from Figure 3 As can be seen, the success rate of traditional RACH drops sharply with increasing system load. However, the adaptive SaRA method of this invention maintains a first-access success rate of nearly 80% even under extremely high load, far superior to all baseline solutions. The fundamental reason is as follows... Figure 4 As shown, SaRA effectively suppresses the effective load of competing resources to a level far below the nominal load through perception-based decision-making, thus avoiding a large number of collisions at the source.

[0052] from Figure 5 and Figure 6 It can be seen that the average access latency of traditional RACH increases exponentially with the increase of load, while the latency of SaRA remains at a low level and its latency composition is balanced, without any situation where the latency of a certain link surges due to collision.

[0053] from Figure 7 It can be seen that SaRA can achieve higher system peak throughput than traditional RACH, and will not crash due to congestion in high-load areas. Figure 8 and Figure 9 This indicates that SaRA exhibits the best performance and strongest robustness under different channel quality (SNR) and channel availability (non-blocking probability). Figure 10 The results show that even with some missed detections in the sensing module (i.e., misjudging available channels as unavailable), SaRA's performance is far superior to traditional methods, demonstrating the invention's tolerance for imperfect sensing accuracy. Figure 11 The results show that the additional overhead of SaRA is adaptively adjusted according to the load, but in all cases it is far below the preset 8% budget limit, demonstrating the high resource efficiency of the present invention.

[0054] In summary, this invention introduces a lightweight sensing micro-time slot and combines it with corresponding processing methods and system architecture to achieve proactive sensing of channel status and system load. Based on this, it dynamically optimizes access decision thresholds, backoff strategies, and candidate beam sets, thereby significantly improving the success rate and throughput of random access in the dynamic and challenging communication environment of heterogeneous satellite-ground networks, while effectively controlling access latency and system overhead.

[0055] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A perception-driven random access method for heterogeneous satellite-ground networks, characterized in that, This method introduces proactive real-time sensing at the initial stage of the user access process, and based on the dynamic decision threshold of real-time sensing, identifies channels with channel quality below a certain threshold. Users are diverted to avoid participating in the current Random Access Channel (RACH) contention, thereby reducing the effective access load. Controlled at a level below the nominal system load The level.

2. The sensing-driven random access method for heterogeneous satellite-ground networks according to claim 1, characterized in that, The method specifically includes the following steps: Step S1: Within a preset random access RA resource period, define an initial sensing micro-slot, the transmission priority of which is higher than that of the random access channel RACH. Step S2: The user equipment (UE) first sends a sensing signal to the network-side device through the sensing micro-time slot; Step S3: The network-side device receives and processes the sensing signal and obtains at least one piece of real-time status information about the user equipment (UE). Step S4: The network-side device generates an access policy based on the real-time status information and the current system load. The access policy includes at least a channel quality decision threshold and a candidate beam set. Step S5: The network-side device sends the access policy to the user equipment (UE). Step S6: The user equipment (UE) receives the access policy and compares its own channel quality with the channel quality decision threshold. Step S7: If and only if the channel quality of the user equipment UE meets the channel quality decision threshold, the user equipment UE initiates a subsequent RACH access request and selects a beam from the candidate beam set to send the access preamble.

3. The perception-driven random access method for heterogeneous satellite-ground networks according to claim 2, characterized in that, The real-time status information in step S3 includes channel quality and / or user arrival direction; The network-side device evaluates the channel quality by analyzing the signal-to-noise ratio (SNR) or signal energy of the sensed signal, determines the user's direction of arrival by estimating the angle of arrival (AoA) of the sensed signal, and constructs the candidate beam set based on the angle of arrival.

4. The sensing-driven random access method for heterogeneous satellite-ground networks according to claim 2, characterized in that, The network-side device estimates an average user reach rate in real time by counting the number of sensing signals received within the sensing micro-time slots. And based on this, the nominal system load is calculated. .

5. The perception-driven random access method for heterogeneous satellite-ground networks according to claim 4, characterized in that, The network-side device dynamically adjusts the channel quality decision threshold. To achieve a balance between access opportunities and congestion control, when the nominal system load... When the threshold is increased, the channel quality decision threshold is raised to reduce the number of UEs initiating access requests, thereby reducing the effective access load. Keep it within the predetermined range; The channel quality decision threshold mentioned above The dynamic adjustment is based on a pre-calculated nominal system load. It is executed by mapping to a lookup table (LUT) that determines the decision threshold.

6. The sensing-driven random access method for heterogeneous satellite-ground networks according to claim 2, characterized in that, The access policy in step S4 also includes a backoff window W parameter, which the network-side device uses based on the total access delay budget. The fixed time occupied by sensing and beam alignment, and the channel quality decision threshold. Determined effective access load This allows for the dynamic determination of the backoff window parameters to meet the delay budget.

7. The perception-driven random access method for heterogeneous satellite-ground networks according to claim 6, characterized in that, The access policy generation in step S4 specifically includes: solving the following constraint optimization problem to determine the channel quality decision threshold. Backoff window W and perceived resource ratio Beam selection strategy , in Let be the probability of successful initial access, which is the objective function for optimization. For effective load access, the channel quality decision threshold is... The function; T is the frame length; The length of the backoff slot; The size of the candidate beam set; This refers to the time for a single beam scan. The preset maximum allowed access latency; and These are the unit resource costs for sensing and control, respectively; Information entropy for beam selection strategies; This is the preset maximum allowed additional overhead.

8. A system for a sensing-driven random access method for a satellite-ground heterogeneous network as described in any one of claims 1-7, characterized in that, It includes at least one user equipment (UE) and one network-side device, wherein the network-side device includes: The communication unit is configured to receive sensing signals from the user equipment UE within a sensing micro-timeslot and to send access policies to the user equipment UE. A sensing unit is configured to process the sensing signal to acquire at least one piece of real-time status information about a user equipment (UE), the real-time status information including channel quality and / or user arrival direction; The decision unit is configured to generate the access policy based on the real-time status information and the current system load. The access policy includes at least a channel quality decision threshold and a candidate beam set. The communication unit receives the access preamble sent by the user equipment UE from the candidate beam set only during the subsequent random access channel (RACH) transmission process if the user equipment UE's own channel quality meets the channel quality decision threshold.

9. The system according to claim 8, characterized in that, The decision unit estimates an average user arrival rate in real time by counting the number of sensing signals processed by the sensing unit within the sensing micro-time slots. And based on this, the nominal system load is calculated. ; The decision-making unit includes a storage module that stores a pre-computed lookup table (LUT). The decision-making unit utilizes this lookup table and, based on the nominal system load,... Determine the channel quality decision threshold To effectively access the load Keep it within the predetermined range; The decision-making unit is based on the total access delay budget. and the channel quality decision threshold Determined effective access load A backoff window parameter W is dynamically determined and included in the access policy.

10. The system according to claim 8, characterized in that, The process by which the network-side device generates the access policy is performed by decoupling the decision variable set of the optimization problem into two subsets based on different time scales, specifically including: A semi-static configuration subset, whose parameters are configured based on long-term channel statistics and QoS requirements, includes at least the perceived resource allocation factor η and the size of the candidate beam set. ; The subset is dynamically adjusted, and its parameters are based on the real-time perceived system load. The dynamic adjustment subset includes at least the channel quality decision threshold τ and the backoff window parameter W, and is adjusted in accordance with the channel information. The dynamic determination of the backoff window parameter W specifically includes: a) Calculate the available delay budget for the RACH procedure of the random access channel. ,in The For the total access latency budget, the This is a fixed time occupied by sensing and beam alignment; b) Based on the available delay budget and effective access load ( ), calculate a maximum allowable backoff window The calculation method is as follows: c) Combine candidate backoff windows suggested by a pre-defined, load-related policy function. Finally, the backoff window parameter W was determined to be... 。

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