Satellite orbit parameter-based lead code adaptive selection method

Abstract

The invention relates to the technical field of satellite communication, in particular to a lead code adaptive selection method based on satellite orbit parameters, which comprises the following steps: acquiring satellite orbit information of each satellite in a non-ground network; performing normalization processing on the satellite orbit information of each satellite to obtain corresponding normalized orbit information; each user in the coverage range of each satellite beam calculates a grouping score value according to the normalized orbit information; all users in the coverage range of each satellite beam are divided into four user groups according to the grouping score values; different lead code pools are distributed to the four user groups in the coverage range of each satellite beam, and users in each user group compete for lead codes in the corresponding lead code pool; according to the invention, the collision probability is effectively reduced, and the access efficiency of the 5G NTN terminal is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of satellite communication technology, and in particular to a method for adaptively selecting a preamble code based on satellite orbit parameters. Background Art

[0002] Non-Terrestrial Network (NTN) relies on satellites or low-altitude platforms to move 5G base stations into the air and directly provide 5G connection services to the ground. It is an important supplement to ground cellular communication technology. In NTN networks, random access methods are an important means to achieve the connection between user equipment (UE) and the network. The current random access methods mainly include contention-based random access and non-contention-based random access. The contention-based random access method is prone to collision problems due to the random selection of common preambles by multiple user equipment (UE), resulting in access failure; while the non-contention-based random access can avoid collisions, but requires the allocation of exclusive preambles through signaling, which increases the network signaling overhead. Especially in the satellite communication scenario, due to the drastic changes in Doppler frequency shift and dynamic fluctuations in signal strength caused by the high-speed movement of satellites, traditional methods are difficult to take into account both access success rate and resource efficiency. Therefore, there is an urgent need for a random access scheme that can dynamically adapt to satellite orbit characteristics, reduce collisions and reduce signaling overhead. Summary of the invention

[0003] To solve the above problems, the present invention provides a method for adaptively selecting a preamble based on satellite orbit parameters, comprising the following steps:

[0004] S1. Obtaining satellite orbit information of each satellite in the non-terrestrial network; the satellite orbit information includes the satellite beam coverage, and the signal quality and Doppler shift of each user within the satellite beam coverage;

[0005] S2. Normalize the orbital information of each satellite to obtain the corresponding normalized orbital information;

[0006] S3. Each user calculates a group score value based on the normalized track information;

[0007] S4. All users within the coverage of each satellite beam are divided into four user groups according to the grouping score, including a first user group, a second user group, a third user group, and a fourth user group;

[0008] S5. Based on TS38.331 in 3GPP, different preamble code pools are allocated to the four user groups within the coverage of each satellite beam, and the users in each user group compete for the preamble code in the corresponding preamble code pool; among them, the first user group is allocated the first preamble code pool, the second user group is allocated the second preamble code pool, the third user group is allocated the third preamble code pool, and the fourth user group is allocated the fourth preamble code pool.

[0009] Further, obtaining the satellite orbit information of each satellite in the non-terrestrial network in step S1 includes: obtaining the satellite orbit information by using two-line orbital data or global navigation satellite system measurement.

[0010] Further, normalizing any satellite orbit information includes signal quality normalization, Doppler shift normalization, and beam coverage normalization, where:

[0011] The signal quality normalization is

[0012]

[0013] where f S (S ij ) represents the normalized signal quality of the jth user within the coverage of the ith satellite, S ij represents the signal quality of the jth user within the coverage of the ith satellite, S min represents the minimum signal quality,

[0014] S max represents the maximum signal quality;

[0015] The Doppler shift normalization is

[0016]

[0017] where f D (D ij ) represents the normalized Doppler shift of the jth user within the coverage of the ith satellite, D ij represents the Doppler shift of the jth user within the coverage of the ith satellite, D min represents the minimum Doppler shift, D max represents the maximum Doppler shift;

[0018] The beam coverage normalization is

[0019]

[0020] where f B (B i ) represents the normalized beam coverage of the ith satellite, N B represents the number of users under the current beam coverage of the ith satellite, N max represents the maximum user capacity.

[0021] Further, the calculation formula for the grouped score value is

[0022] G ij = ω1f S (S ij) + ω2f B (B ij ) + ω3f D (D i )

[0023]

[0024] ω1 = 1 - (ω2 + ω3)

[0025] Wherein, G ij represents the packet scoring value of the j-th user accessing the i-th satellite, and f S (S ij ) represents the normalized signal quality of the j-th user within the coverage of the i-th satellite, and f D (D ij ) represents the normalized Doppler shift of the j-th user within the coverage of the i-th satellite, and f B (B i ) represents the normalized beam coverage of the i-th satellite; ω1, ω2, ω3 represent weighting coefficients, α, β represent adjustment factors, S th represents the SNR threshold, and D th represents the Doppler shift threshold.

[0026] Furthermore, the adjustment factors α, β are optimized by the gradient descent method, and the values of the adjustment factors α, β are both within the range of 0.1 - 1.

[0027] Furthermore, for all users within the beam coverage of each satellite, users with a packet scoring value greater than or equal to 0.7 are classified into the first user group, users with a packet scoring value less than 0.7 and greater than or equal to 0.5 are classified into the second user group, users with a packet scoring value less than 0.5 and greater than or equal to 0.3 are classified into the third user group, and users with a packet scoring value less than 0.3 are classified into the fourth user group.

[0028] Furthermore, according to the preamble value specified in TS38.331 of 3GPP being 0 - 63, the preambles are divided into four different preamble pools; among them, the preamble values in the first preamble pool are 0 - 25, the preamble values in the second preamble pool are 26 - 41, the preamble values in the third preamble pool are 42 - 53, and the preamble values in the fourth preamble pool are 54 - 63.

[0029] Advantages of the present invention:

[0030] The present invention dynamically groups UEs by analyzing satellite orbit prediction data, comprehensively evaluates the signal strength, Doppler shift characteristics, and beam load status of terminal devices through multi-dimensional features, and establishes a differentiated preamble resource allocation mechanism. And independent preamble pools are allocated for different groups, thereby reducing collisions and optimizing the access efficiency. Description of the Drawings

[0031] Figure 1 This is the flow chart of the method of the present invention;

[0032] Figure 2 This is the scenario diagram of the present invention. Detailed implementation manners

[0033] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0034] The present invention proposes a preamble adaptive selection method based on satellite orbit parameters, as Figure 1 shown, including the following steps:

[0035] S1. Obtain the satellite orbit information of each satellite in the non-terrestrial network; the satellite orbit information includes the beam coverage range of the satellite, and the signal quality (SNR) and Doppler shift (Doppler) of each user within the beam coverage range of the satellite.

[0036] Specifically, step S1 of obtaining the satellite orbit information of each satellite in the non-terrestrial network includes: obtaining the satellite orbit information through measurement by Two-Line Element (TLE) or Global Navigation Satellite System (GNSS).

[0037] S2. Perform normalization processing on each satellite orbit information to obtain the corresponding normalized orbit information.

[0038] Specifically, performing normalization processing on any satellite orbit information includes signal quality normalization, Doppler shift normalization, and beam coverage range normalization, where:

[0039] By performing normalization processing on the signal quality, the influence of the signal strength is measured; the signal quality normalization is expressed as

[0040]

[0041] where f S (S ij ) represents the normalized signal quality of the jth user within the coverage range of the ith satellite, S ij represents the signal quality of the jth user within the coverage range of the ith satellite, S minrepresents the minimum value of the signal quality of all users within the coverage of the \(i\)-th satellite, \(S\) max represents the maximum value of the signal quality of all users within the coverage of the \(i\)-th satellite;

[0042] By normalizing the Doppler shift, the impact of the Doppler effect is measured; the normalized Doppler shift is expressed as

[0043]

[0044] where \(f\) D (\(D\) ij ) represents the normalized Doppler shift of the \(j\)-th user within the coverage of the \(i\)-th satellite, \(D\) ij represents the Doppler shift of the \(j\)-th user within the coverage of the \(i\)-th satellite, \(D\) min represents the minimum value of the Doppler shifts of all users within the coverage of the \(i\)-th satellite, \(D\) max represents the maximum value of the Doppler shifts of all users within the coverage of the \(i\)-th satellite; at high Doppler shifts, it will increase the difficulty for the UE to access, so the weight ratio of this parameter should be increased in the subsequent grouping process.

[0045] Normalizing the beam coverage range actually takes into account the impact of beam congestion, and the beam coverage range is normalized to

[0046]

[0047] where \(f\) B (\(B\) i ) represents the normalized beam coverage range of the \(i\)-th satellite, \(N\) B represents the number of users under the current beam coverage range of the \(i\)-th satellite, \(N\) max represents the maximum user capacity in the NTN network. If there are too many UEs in a beam, this value is higher, and the UE is more likely to be assigned to a special preamble pool to reduce the impact of congestion.

[0048] S3. Each user within the coverage of each satellite beam calculates a grouping score value according to the normalized orbit information.

[0049] Specifically, the calculation formula for the grouping score value is

[0050] \(G\) ij =\(\omega_1f\) S \((S\) ij )+\(\omega_2f\) B \((B\) ij )+\(\omega_3f\) D \((D\) i )

[0051] where \(G\) ijIt represents the packet scoring value of the j-th user within the coverage of the i-th satellite beam. ω1, ω2, and ω3 represent weighting factors, which are used to adjust the signal quality, Doppler shift, and the influence of the beam on the packet. Since the signal change rate and the degree of influence of Doppler shift are different for different orbits, the weighting factors ω1, ω2, and ω3 need to be adjusted accordingly. Under LEO orbit satellites, the Doppler shift changes drastically, and the weight of SNR should be reduced while the weight of the influence of Doppler shift should be increased; under MEO medium orbit satellites, the SNR and the influence of Doppler shift act together, and ω1, ω2, and ω3 should be balanced; under GEO geostationary orbit satellites, the signal quality is dominant, and ω1 should be increased while ω2 should be reduced. Therefore, the adjustment is made through the following formula:

[0052]

[0053] ω1 = 1 - (ω2 + ω3)

[0054] α and β represent adjustment factors, and the optimal values of these adjustment factors can be automatically found through some algorithms of machine learning. In the embodiments of the present invention, optimization is carried out in the way of gradient descent, and generally the values are between 0.1 and 1. According to the signal quality and Doppler shift of different orbits, regular summaries are made, and S th represents the SNR threshold, which is the average value of all signal qualities within the current satellite beam coverage; in the embodiments of the present invention, S th = -6 dB; D th represents the Doppler shift threshold, taking 5 kHz.

[0055] S4. All users within the coverage of each satellite beam are divided into 4 user groups according to the packet scoring value.

[0056] S5. Different preamble pools are allocated to the 4 user groups within the coverage of each satellite beam, and the users within each user group compete for preambles in the corresponding preamble pool. Specifically, after grouping the users and allocating the preamble pool, a contention-based random access method is adopted for each user group, where the contending preambles can only be selected from the allocated preamble pool.

[0057] Specifically, the UE is grouped according to the above calculation, and the UE is divided into four groups. According to the provisions of TS38.331 in 3GPP, the preamble values range from 0 to 63, and the preambles are divided into four different preamble pools. Combining with the UE grouping, UEs in different groups compete for preambles in their respective corresponding preamble pools. The specific grouping is shown in Table 1.

[0058] Table 1

[0059]

[0060] The specific division results are as follows Figure 2 As shown, each satellite divides all users within its beam coverage into 4 user groups.

[0061] The present invention analyzes the satellite signal strength, Doppler frequency shift, and beam congestion degree, dynamically adjusts the weight coefficient and divides the UE groups, and allocates independent preamble pools for different groups. This method effectively reduces the collision probability, adapts to different orbital characteristics such as LEO, MEO, and GEO, and significantly improves the access efficiency of 5G NTN terminals.

[0062] In the present invention, unless otherwise clearly defined and limited, terms such as "installation", "setting", "connection", "fixation", "rotation", etc. should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or integrated; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the internal communication of two components or the interaction relationship between two components. Unless otherwise clearly defined, for those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0063] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for adaptively selecting a preamble based on satellite orbit parameters, characterized in that: The following steps are involved: S1. Obtain satellite orbit information for each satellite in the non-terrestrial network; The satellite orbit information includes the satellite's beam coverage, and the signal quality and Doppler frequency shift of each user within the satellite's beam coverage; S2. Normalizing the orbital information of each satellite to obtain the corresponding normalized orbital information; S3. Each user calculates a group score value based on the normalized track information; S4. All users within the coverage of each satellite beam are divided into four user groups according to the grouping score, including a first user group, a second user group, a third user group, and a fourth user group; S5. Based on TS38.331 in 3GPP, different preamble code pools are allocated to the four user groups within the coverage of each satellite beam, and the users in each user group compete for the preamble code in the corresponding preamble code pool; among them, the first user group is allocated the first preamble code pool, the second user group is allocated the second preamble code pool, the third user group is allocated the third preamble code pool, and the fourth user group is allocated the fourth preamble code pool.

2. The method for adaptively selecting a preamble based on satellite orbit parameters according to claim 1, characterized in that: Step S1 of acquiring satellite orbit information of each satellite in the non-terrestrial network includes: acquiring satellite orbit information by using dual-line orbit data or global navigation satellite system measurement.

3. The method for adaptively selecting a preamble based on satellite orbit parameters according to claim 1, characterized in that: The normalization processing of any satellite orbit information includes signal quality normalization, Doppler frequency shift normalization and beam coverage normalization, where: The signal quality is normalized to Among them, f S (S ij ) represents the normalized signal quality of the jth user within the coverage of the i-th satellite, S ij represents the signal quality of the jth user within the coverage of the i-th satellite, S min Indicates the minimum signal quality, S max Indicates the maximum signal quality; The Doppler shift is normalized to Among them, f D (D ij ) represents the normalized Doppler shift of the jth user within the coverage of the ith satellite, D ij represents the Doppler shift of the jth user within the coverage area of ​​the i-th satellite, D min represents the minimum Doppler shift, D max represents the maximum Doppler shift; The beam coverage is normalized to Among them, f B (B i ) represents the normalized beam coverage of the ith satellite, N B represents the number of users under the current beam coverage of the i-th satellite, N max Indicates the maximum user capacity.

4. The method for adaptively selecting a preamble based on satellite orbit parameters according to claim 1, characterized in that: The calculation formula for the group score is: G ij =ω1f S (S ij )+ω2f B (B ij )+ω3f D (D i ) ω1=1-(ω2+ω3) Among them, G ij represents the group score of the jth user within the coverage of the i-th satellite beam, f S (S ij ) represents the normalized signal quality of the jth user within the coverage of the ith satellite, f D (D ij ) represents the normalized Doppler frequency shift of the jth user within the coverage area of ​​the ith satellite, f B (B i ) represents the normalized beam coverage of the ith satellite; ω1, ω2, ω3 represent weighting coefficients, α, β represent adjustment factors, S th represents the SNR threshold, D th Indicates the Doppler shift threshold.

5. The method for adaptively selecting a preamble based on satellite orbit parameters according to claim 4, characterized in that: The adjustment factors α and β are optimized by gradient descent, and the values ​​of the adjustment factors α and β are both between 0.1 and 1.

6. The method for adaptively selecting a preamble based on satellite orbit parameters according to claim 1, characterized in that: For all users within the coverage of each satellite beam, users with a grouping score greater than or equal to 0.7 are classified into the first user group, users with a grouping score less than 0.7 and greater than or equal to 0.5 are classified into the second user group, users with a grouping score less than 0.5 and greater than or equal to 0.3 are classified into the third user group, and users with a grouping score less than 0.3 are classified into the fourth user group.

7. The method for adaptively selecting a preamble based on satellite orbit parameters according to claim 1, characterized in that: According to TS38.331 in 3GPP, the preamble code value is 0-63, and the preamble code is divided into four different preamble code pools; among them, the preamble code value in the first preamble code pool is 0-25, the preamble code value in the second preamble code pool is 26-41, the preamble code value in the third preamble code pool is 42-53, and the preamble code value in the fourth preamble code pool is 54-63.

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