A non-orthogonal multiple access random access method based on grouping of service data packet sizes

Abstract

The application discloses a non-orthogonal multiple access random access method based on service data packet size grouping, wherein users are grouped according to the size of data packets to be transmitted by the users; wherein the users in the same group are allocated to the same time-frequency resource block, and each user randomly selects one of the resource blocks in subsequent operations to perform a random access process based on a non-orthogonal multiple access technology; the optimal resource block orthogonal grouping scheme is determined according to the user grouping result, so as to determine the number of corresponding time-frequency resource blocks in each user group; and the non-orthogonal multiple access random access process is performed according to the user grouping result and the resource allocation result. The above method has wide application range, does not limit specific NOMA technology, is suitable for the case that data packet sizes are continuously distributed, can effectively reduce the user collision probability of the random access process, and improves the access capacity.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a nonorthogonal multiple access random access method based on service data packet size grouping. Background Technology

[0002] With the continuous iteration of wireless communication technology and the intelligent development of various devices, the number of devices in existing communication networks has increased dramatically. In order to ensure efficient data transmission between devices and base stations, devices need to establish an initial connection with the base station through a random access process at the beginning of the communication link establishment. However, the traditional random access scheme based on Orthogonal Multiple Access (OMA) is limited by limited spectrum resources. In scenarios where the number of active devices increases significantly, the access success rate drops significantly. The large-scale data retransmission and loss caused by access failure becomes unacceptable. Therefore, it is particularly important to study new access technologies to adapt to the increase in the number of devices.

[0003] To address the aforementioned problems with orthogonal multiple access (OMA) random access schemes, recent work has proposed utilizing non-orthogonal multiple access (NOMA) techniques to execute the random access process. For example, mathematical analysis and simulation experiments have demonstrated that using power multiple access (POMA) can significantly increase the data throughput of the access network. However, this approach only considers POMA as a single non-orthogonal technique, neglecting the performance gains offered by other non-orthogonal multiple access techniques. Furthermore, POMA leads to an exponential increase in user transmitter power with the number of users, thus limiting the actual performance gain. Therefore, although existing technologies have attempted to combine NOMA with random access procedures, optimizing its use remains an unresolved issue with significant room for improvement. Summary of the Invention

[0004] The purpose of this invention is to provide a non-orthogonal multiple access (NOMA) random access method based on service data packet size grouping. This method has a wide range of applications, is not limited to specific NOMA technologies, and is suitable for situations where data packet sizes are continuously distributed. It uses only the statistical information of the size of the data packets to be transmitted by the user per unit time as the input of the scheme to jointly group users and resource blocks, which can effectively reduce the probability of user collisions in the random access process and improve access capacity.

[0005] The objective of this invention is achieved through the following technical solution:

[0006] A nonorthogonal multiple access random access method based on service data packet size grouping, the method comprising:

[0007] Step 1: Group users according to the statistical information of the size of data packets to be transmitted per unit time; users in the same group will be assigned to the same time-frequency resource block, and each user will randomly select one of these resource blocks in subsequent operations to perform a random access process based on non-orthogonal multiple access technology.

[0008] Step 2: Determine the optimal orthogonal grouping scheme for resource blocks based on the user grouping results, thereby determining the number of time-frequency resource blocks in each user group;

[0009] Step 3: Execute the non-orthogonal multiple access random access procedure based on the user grouping results in Step 1 and the resource allocation results in Step 2.

[0010] As can be seen from the technical solution provided by the present invention, the above method has a wide range of applications and is not limited to specific NOMA technology. It is suitable for situations where the data packet size is continuously distributed. It uses only the statistical information of the size of the data packets to be transmitted by the user per unit time as the input of the scheme to jointly group users and resource blocks, which can effectively reduce the probability of user collisions in the random access process and improve access capacity. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of the nonorthogonal multiple access random access method based on service data packet size grouping provided in an embodiment of the present invention;

[0013] Figure 2 This is a schematic diagram illustrating the relationship between data packet size and the maximum number of users that can be supported in the example given in this invention. Detailed Implementation

[0014] 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 embodiments of the present invention, and not all embodiments, and do not constitute a limitation 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 are within the protection scope of the present invention.

[0015] like Figure 1 The diagram shows a flowchart of a non-orthogonal multiple access random access method based on service data packet size grouping provided in an embodiment of the present invention. The method includes:

[0016] Step 1: Group users according to the statistical information of the size of data packets to be transmitted per unit time.

[0017] Users within the same group will be assigned to the same time-frequency resource block. In subsequent operations, each user will randomly select one of these resource blocks to perform a random access process based on non-orthogonal multiple access technology.

[0018] In this step, considering the service characteristics of large-scale random access scenarios, the signaling overhead in this process cannot be too large. Therefore, the grouping scheme based on user data packet size must not be too complex, while ensuring a low probability of access collisions. Therefore, the first criterion for user grouping designed in this invention is to group users with the same or similar data packet sizes as much as possible to simplify the grouping scheme and reduce signaling overhead.

[0019] Based on the mathematical analysis of the multi-user access channel capacity formula and the user access collision probability model, it can be seen that the successful access condition for users overlapping on a certain resource block is as follows (1):

[0020]

[0021] Where, Φ k φ represents the set of overlapping users on the k-th resource block; k Φ k Any subset of T; f d represents the coherence time per unit resource block, W represents the coherence bandwidth; i P represents the data packet size of the i-th user; i Ni represents the received signal power of the i-th user; N0 represents the noise power spectral density.

[0022] Formula (1) requires that for any subset of overlapping users on a resource block, the sum of their data packet sizes must be within the channel carrying capacity corresponding to the sum of their power; otherwise, the data is unsolvable. To facilitate the base station's statistics on user access and simplify model analysis, users estimate the channel based on the received base station broadcast signal and then adjust their own transmission power so that the receiving power of each user on the base station side is the same. Further analysis shows that under this design, the maximum number of users with the same data packet size that can overlap on a single resource block depends only on the data packet size when the signal-to-noise ratio remains unchanged. At the same time, since the calculation of the maximum number of users that can be carried requires rounding, a certain value of the maximum number of users that can be carried actually corresponds to a certain range of data packet sizes. That is, there is a certain equivalent interval for data packet sizes in this problem. The collision models of users within this interval are completely consistent, so they can be equivalently grouped into the same type of users. Therefore, the user grouping scheme designed in this application needs to calculate the mapping relationship between the maximum number of users that can be carried in a single resource block and the user data packet size based on the access collision discrimination condition, and divide the users within each data packet size equivalent interval into the same group.

[0023] The initial user grouping scheme based on the maximum number of users that can be supported in the above steps works well when the user data packets are large. However, when the data packets are small, the grouping intervals are too dense, resulting in a large number of groups and increasing signaling overhead. Therefore, based on the obtained initial user grouping results, narrow intervals are merged according to the expected signaling overhead, and adjacent groups of users with small data packets are merged into one group to obtain the final user grouping results. This achieves a trade-off between signaling overhead and actual access performance. The specific group merging method is as follows:

[0024] The maximum data packet size d that can be successfully accessed is calculated according to formula (1). max As an upper bound, the required signaling overhead O for a given single group group With maximum tolerable signaling overhead O max Calculate the maximum number of groups g max and minimum interval length l min Specifically:

[0025]

[0026] l min =d max / g max (3)

[0027] Then, starting from the first group of the user's initial grouping results, the loop continues. If the interval length of the current group is greater than or equal to the minimum interval length, the current group remains unchanged, and the next group is checked; otherwise, the current group is merged with the subsequent groups until the group interval length is greater than the minimum interval length.

[0028] Meanwhile, before switching to the next group, the minimum interval length is updated based on the range of packet sizes corresponding to the remaining unadjusted groups and the number of available groups.

[0029] Step 2: Determine the optimal orthogonal grouping scheme for resource blocks based on the user grouping results, thereby determining the number of time-frequency resource blocks in each user group;

[0030] In this step, to avoid interference between the random access processes of users in different groups, it is necessary to ensure that the time-frequency resources of each group do not overlap, that is, to orthogonally allocate the time-frequency resource blocks of each group. Specifically:

[0031] Assume the number of user groups is G, the number of available time-frequency resource blocks is K, and the number of users in the g-th group is N. g Initialize intermediate variables; calculate the maximum number of users that can be carried on a single resource block of each group according to the multi-user successful access judgment condition, i.e., formula (1), where the maximum number of users that can be carried on a single resource block of the g-th group is denoted as For groups formed by merging multiple combinations, take the minimum value of the maximum number of users that can be supported;

[0032] Then, the maximum number of successfully connected users is calculated when different resource blocks are allocated to each group. The time-frequency resource block allocation problem in this scenario is actually an integer programming problem used to determine the number of resource blocks k in each group. g Specifically:

[0033] The allocation of k to the g-th group is calculated using formula (4). g The expected number of users successfully connected when there are 1 resource block, V[g][k] g ]:

[0034]

[0035] Then, the intermediate state matrix U[g][k] is used to store the expected maximum number of successfully accessed users when allocating k resource blocks to the first g groups, and the intermediate state matrix U[g][k] is updated according to the following formula (5):

[0036] U[g][k]=max(U[g-1][k],U[g-1][kk g ]+V[g][k g ]),k g =(1,...,k) (5)

[0037] Then, based on the updated intermediate state matrix U[g][k] and the following formula (6), the optimal resource block allocation number for each group is calculated:

[0038]

[0039] Wherein, the optimal number of resource blocks in group g is denoted as k' represents the number of time-frequency resource blocks. Within the valid range, if the equation on the right-hand side of formula (6) is satisfied, then... This refers to the current value of k'; if the entire traversal has been completed without finding a k' that makes the equation true, then... =0;

[0040] U[g-1][k-k'] represents the expected maximum number of successfully connected users when allocating k-k' resource blocks to the first g-1 group.

[0041] Step 3: Execute the non-orthogonal multiple access random access procedure based on the user grouping results in Step 1 and the resource allocation results in Step 2.

[0042] In this step, in step 3, based on the obtained user grouping and time-frequency resource allocation results, each user in each group randomly selects any one of the time-frequency resource blocks allocated to the current group to perform a random access procedure.

[0043] Due to the randomness of resource block selection, users in the same group may select the same time-frequency resource block. In order to further reduce the probability of access collision, this application decodes the received signals on each resource block based on non-orthogonal multiple access technology. The discrimination condition for successful access of users overlapping on a certain resource block is shown in formula (1). If the inequality of formula (1) is satisfied, the overlapping users have successfully completed the random access process; otherwise, if the inequality of formula (1) is not satisfied, the data is unsolvable, the overlapping user access fails, and the corresponding error retransmission and backoff process needs to be performed in subsequent time frames.

[0044] It is worth noting that the contents not described in detail in the embodiments of the present invention belong to the prior art known to those skilled in the art.

[0045] The method described in the embodiments of the present invention will be explained in detail below with specific examples:

[0046] First, the base station needs to obtain statistical information on the size of data packets to be transmitted by users per unit time as input information for the present invention. Based on this information, users are grouped. According to the multi-user access channel capacity formula defined in formula (1), the mapping relationship between different data packet sizes and the maximum number of users that can be carried on a unit resource block is calculated. When the signal-to-noise ratio of the access signal received by the base station is 15dB, the product of the coherence time and coherence bandwidth of the unit resource block is T. f When W = 1000 Hz·s, such as Figure 2 The diagram shown illustrates the relationship between data packet size and the maximum number of users that can be supported, as illustrated in this invention. Figure 2The horizontal axis of each line corresponds to the data packet size of the same group of users (adjacent groups of users with small data packets need to be merged to obtain the final user grouping result). Users with the same maximum number of users are grouped into the same group, that is, users within the same data packet size range corresponding to the same maximum number of users are grouped into the same group to obtain the preliminary user grouping result.

[0047] from Figure 2 It can be seen that the initial grouping results show extremely dense grouping in areas where data packets are small, requiring significant signaling overhead and making it impractical. Therefore, it is necessary to merge some packets in the initial grouping results. The specific process is as follows:

[0048] 1. For a random access scenario with a received signal-to-noise ratio of 15dB, channel capacity calculations show that the maximum data packet size that can be carried per unit time-frequency resource block (1000Hz·s) is 5027 bits. Therefore, the actual range of user data packets that need to be grouped is (0, 5027). Assuming that the maximum acceptable signaling overhead for random access per time frame is 100 bits, and a single packet requires 17 bits of signaling (including an 11-bit rate packet threshold and a 6-bit resource block packet threshold), the maximum number of packets is... Therefore, the initial minimum data packet size range is (5027-0) / 5≈1005;

[0049] 2. Starting from the largest data packet size range, group and merge: Since the first group's interval length is 5027-3002=2025>1005, keep this group unchanged and update the minimum interval length to (3002-0) / 4≈751; Check the second group in order. Since the second group's interval length is 3002-2194=808>751, keep this group unchanged and update the minimum interval length to (2194-0) / 3≈731; Check the third group in order. Since the third group's interval length is 2194-1748=446<731, it needs to be merged with subsequent groups until the interval length is greater than or equal to the minimum interval length. That is, merge the third and fourth groups to get the interval (1462,2194] as the new third group, and update the minimum interval length to (1462-0) / 2=731.

[0050] 3. Repeat step 2 until the current number of groups equals the maximum number of groups, and the final user grouping result is (0,714],(714,1462],(1462,2194],(2194,3002],(3002,5027).

[0051] After user grouping is completed, the time-frequency resource blocks are then grouped using the optimal resource allocation scheme. The specific process is as follows:

[0052] 1. Initialize parameters and state matrix;

[0053] 2. Calculate the expected number of successfully connected users when allocating different numbers of resource blocks to each group of users according to formula (4), and further calculate the expected maximum number of successfully connected users when allocating k time-frequency resource blocks to the n groups, thereby updating the intermediate state matrix U[g][k].

[0054] 3. Perform path backtracking based on the calculated updated intermediate state matrix U[g][k], and then calculate the optimal resource block allocation number for each user group according to formula (6), thereby obtaining the optimal resource block grouping result.

[0055] Then, based on the user grouping results and resource allocation results, a non-orthogonal multiple access random access procedure is executed. This non-orthogonal multiple access random access procedure is a common feature already existing in the prior art.

[0056] In summary, the method described in this embodiment of the invention, compared to other existing non-orthogonal multiple access (NOMA) random access technologies, is not limited to a specific NOMA technology. Instead, it optimizes NOMA random access technologies through a multiple access channel capacity formula. Furthermore, compared to similar rate-based random access schemes in the background technology, this scheme decouples and designs specific user and resource block grouping strategies. For the user grouping problem, the method described in this embodiment proposes the concept of an equivalent interval based on mathematical analysis of the access collision model, solving the user grouping problem under continuously distributed data packet sizes. Based on this, a strategy for balancing signaling overhead and access performance is proposed. For the resource block grouping problem, this scheme also proposes the optimal resource grouping algorithm given user grouping conditions.

[0057] Therefore, the user and resource block decoupling grouping strategy proposed in this embodiment of the invention has a wide range of applications (it is not limited to specific NOMA technology and is applicable to cases with continuous distribution of data packet size), and can effectively reduce the probability of user collisions in the random access process and improve access capacity.

[0058] Furthermore, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware, and the corresponding program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0059] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included 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. The information disclosed in the background section is intended only to enhance the understanding of the overall background technology of the present invention and should not be construed as an admission or implication in any way that such information constitutes prior art known to those skilled in the art.

Claims

1. A non-orthogonal multiple access random access method based on service data packet size grouping, characterized in that, The method includes: Step 1: Group users according to the statistical information of the size of data packets to be transmitted per unit time; users in the same group will be assigned to the same time-frequency resource block, and each user will randomly select one of these resource blocks in subsequent operations to perform a random access process based on non-orthogonal multiple access technology. In step 1, the process of grouping users based on the statistical information of the size of data packets to be transmitted per unit time is as follows: Based on the mathematical analysis of the multi-user access channel capacity formula and the user access collision probability model, it can be seen that the successful access condition for users overlapping on a certain resource block is as follows (1): （1） in, This represents the set of overlapping users on the k-th resource block; express Any subset of; Indicates the coherence time per unit resource block; Indicates the coherent bandwidth; This represents the size of the data packet for the i-th user; This represents the received signal power of the i-th user; Indicates the noise power spectral density; Formula (1) requires that for any subset of overlapping users on a resource block, the sum of their data packet sizes must be within the channel carrying range corresponding to the sum of their power; otherwise, the data cannot be solved. The mapping relationship between the maximum number of users that a single resource block can carry and the size of the user data packet is calculated based on the access collision discrimination condition, and users within the equivalent range of each data packet size are divided into the same group. Based on the initial user grouping results, narrow intervals are merged according to the expected signaling overhead. Adjacent user groups with smaller data packets are combined into one group to obtain the final user grouping results. This achieves a trade-off between signaling overhead and actual access performance. The specific grouping method is as follows: The maximum data packet size that can be successfully accessed is calculated according to formula (1). As an upper bound, it represents the signaling overhead required for a given single group. With maximum tolerable signaling overhead Calculate the maximum number of groups and minimum interval length Specifically: （2） （3） Then, starting from the first group of the user's initial grouping results, the loop continues. If the interval length of the current group is greater than or equal to the minimum interval length, the current group remains unchanged, and the next group is checked; otherwise, the current group is merged with the subsequent groups until the interval length of the group is greater than the minimum interval length. Meanwhile, before switching to the next group, the minimum interval length is updated based on the range of data packet sizes corresponding to the remaining unadjusted groups and the number of available groups; Step 2: Determine the optimal orthogonal grouping scheme for resource blocks based on the user grouping results, thereby determining the number of time-frequency resource blocks in each user group; Step 3: Execute the non-orthogonal multiple access random access procedure based on the user grouping results in Step 1 and the resource allocation results in Step 2.

2. The non-orthogonal multiple access random access method based on service data packet size grouping according to claim 1, characterized in that, The process of step 2 is as follows: Assume the number of user groups is The number of available time-frequency resource blocks is The number of users in group g is Initialize intermediate variables; calculate the maximum number of users that can be carried on a single resource block of each group according to the multi-user successful access judgment condition, i.e., formula (1), where the maximum number of users that can be carried on a single resource block of the g-th group is denoted as For groups formed by merging multiple combinations, the minimum value of the maximum number of users that can be supported is taken; Then, the maximum number of successfully connected users is calculated when different resource blocks are allocated to each group. The time-frequency resource block allocation problem in this scenario is an integer programming problem used to determine the number of resource blocks in each group. Specifically: The allocation to group g is calculated using formula (4). Expected number of successfully connected users per resource block : （4） Then, the intermediate state matrix is ​​used. Store to before Group assignment The expected maximum number of successfully accessed users corresponds to each resource block, and the intermediate state matrix is ​​updated according to the following formula (5). : （5） Then based on the updated intermediate state matrix The optimal number of resource blocks allocated to each group is calculated using the following formula (6): （6） Wherein, the optimal number of resource blocks in group g is denoted as ; This indicates that the number of time-frequency resource blocks k is traversed within the valid range: if the equation on the right side of formula (6) is satisfied, then That is, the current Value; if the entire traversal has ended and the value is still not found. For the equation to hold true, then =0; This represents the expected maximum number of successfully connected users when allocating k-k' resource blocks to the first g-1 groups.

3. The non-orthogonal multiple access random access method based on service data packet size grouping according to claim 1, characterized in that, In step 3, based on the obtained user groups and time-frequency resource allocation results, each user in each group randomly selects any one of the time-frequency resource blocks allocated to the current group to perform a random access procedure. Among them, the received signals on each resource block are decoded based on non-orthogonal multiple access technology. The judgment condition for successful access of users overlapping on a certain resource block is shown in formula (1). If the inequality of formula (1) is satisfied, the overlapping users have successfully completed the random access process; otherwise, if the inequality of formula (1) is not satisfied, the data is unsolvable, the overlapping user access fails, and the corresponding error retransmission and backoff process needs to be performed in subsequent time frames.

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