Method and system for controlling access capacity of mMTC slice based on beam splitting and combining

Abstract

The application discloses a kind of based on beam split and combine's mMTC slice's access capacity management and system.The method comprises the following steps: receiving the random access signaling sent by mMTC device, obtain the idle random access opportunity RACH opportunities number of each beam in current decision period in mMTC slice;Through mMTC slice, estimate the random access state estimation value of each beam in prediction period based on the random access configuration information and the number of idle random access opportunities of each beam in current decision period;Beam split and combine configuration parameters are determined according to the random access state estimation value by mMTC slice;Beam split and combine target beams are obtained according to beam split and combine configuration parameters, and the beam parameters in mMTC slice are configured to control the total random access capacity of mMTC slice in prediction period;The problem that the random access capacity of existing 5G NR system mMTC slice cannot change with the change of input load is solved.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to an access capacity management method and system based on beamforming and combining mMTC slices. Background Technology

[0002] In 5G wireless networks, Massive Machine Type Communication (mMTC) is a typical application scenario. mMTC refers to the automatic transmission of information between machines with almost no human intervention, characterized by a very high number of terminals, sporadic activity, and very small data packet lengths per transmission. Each time an mMTC device becomes active, it can initiate a random access procedure to complete synchronization and uplink transmission with the base station, or directly use a scheduling-free random access procedure to complete uplink data transmission. To simultaneously serve a variety of mMTC devices with different service requirements (such as latency sensitivity, power consumption limitations, and reliability), network slicing technology can be used to deploy mMTC slices in the base station.

[0003] In existing 5G NR systems, the number of beams in the Physical Random Access Channel (PRACH) is fixed, and the preamble sets used within each beam are orthogonal to each other. However, the total number of preambles is very limited, resulting in a limited random access capacity for each beam within a mMTC slice that does not change with input load. When there are many active terminal devices within a beam, multiple devices may choose the same preamble for uplink access, causing preamble collisions. This prevents the base station from correctly detecting devices using the preamble, ultimately leading to access failure. Conversely, when there are few active terminal devices within a beam, the random access resources within the beam become redundant, consuming excessive overhead. Summary of the Invention

[0004] This invention provides a method and system for managing the access capacity of mMTC slices based on beam splitting and combining. It solves the problem that the random access capacity of mMTC slices in existing 5G NR systems cannot change with the random access load. By splitting or combining beams within the mMTC slice, the random access capacity of the mMTC slice is managed, making the random access capacity of the mMTC slice adapt to the random access load and optimizing the efficiency of the mMTC slice.

[0005] According to one aspect of the present invention, an access capacity management method for mMTC slices based on beamforming and splitting is provided, the method comprising:

[0006] Receive random access signaling sent by mMTC equipment and obtain the number of idle random access opportunities for each beam in the mMTC slice during the current decision period;

[0007] Based on the random access configuration information of each beam in the current decision period and the number of idle random access opportunities, the mMTC slice is used to estimate the random access state of each beam in the prediction period.

[0008] The beam splitting and combining configuration parameters are determined by the mMTC slice based on the random access state estimate.

[0009] The beam splitting and combining is performed according to the beam splitting and combining configuration parameters to obtain the target beam, and the beam parameters in the mMTC slice are configured to control the total random access capacity of the mMTC slice within the prediction period; the beam splitting and combining includes: beam splitting and / or beam combining.

[0010] According to another aspect of the present invention, an access capacity management system is provided, the system comprising:

[0011] The signaling receiving module is used to receive random access signaling sent by the mMTC device and obtain the number of idle random access opportunities for each beam in the mMTC slice during the current decision period.

[0012] The state estimation module is used to estimate the random access state of each beam in the prediction period based on the random access configuration information of each beam in the current decision period and the number of idle random access opportunities through the mMTC slice.

[0013] The parameter determination module is used to determine beam splitting and combining configuration parameters based on the random access state estimate using the mMTC slice;

[0014] The capacity control module is used to perform beam splitting and combining to obtain the target beam according to the beam splitting and combining configuration parameters, and to configure the beam parameters in the mMTC slice to control the total random access capacity of the mMTC slice within the prediction period; the beam splitting and combining includes: beam splitting and / or beam combining.

[0015] According to another aspect of the present invention, a base station is provided, which is deployed with mMTC slices, the base station comprising:

[0016] One or more processors;

[0017] A communication device for communicating with mMTC equipment;

[0018] Storage device for storing one or more programs.

[0019] When the one or more programs are executed by the one or more processors, the one or more processors implement the access capacity management method for mMTC slices based on beam combining and splitting as described in any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions, the computer instructions being configured to cause a processor to execute and implement the access capacity management method for mMTC slices based on beam combining and splitting as described in any embodiment of the present invention.

[0021] The technical solution of this invention involves receiving random access signaling from an mMTC device to obtain the number of idle random access opportunities for each beam within the mMTC slice during the current decision period; estimating the random access state estimate for each beam during the prediction period based on the random access configuration information and the number of idle random access opportunities for each beam during the current decision period using the mMTC slice; determining beam splitting and combining configuration parameters based on the estimated random access state using the mMTC slice; performing beam splitting and combining according to the beam splitting and combining configuration parameters to obtain the target beam; and configuring the beam parameters within the mMTC slice to control the total random access capacity of the mMTC slice during the prediction period; beam splitting and combining includes beam splitting and / or beam combining. By controlling beam splitting or merging based on the estimated random access load state of beams within the mMTC slice, beam splitting reduces the number of active devices within a single beam, lowers the MSG1 collision rate, improves the random access success rate, and increases the total random access capacity of the mMTC slice. Beam merging reduces the number of beams, bringing the total random access capacity of the mMTC slice down to a level compatible with the current random access load, thereby reducing system overhead.

[0022] This solves the problem that the random access capacity of mMTC slices in existing 5G NR systems cannot change with the input load, achieving the goal of controlling the random access capacity of mMTC slices and optimizing the benefits of mMTC slices.

[0023] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0025] Figure 1A This is a schematic diagram of a competition-based random access process;

[0026] Figure 1B This is a schematic diagram of a scheduling-free random access process;

[0027] Figure 1C This is a flowchart of an access capacity management method for mMTC slices based on beam splitting and combining provided in Embodiment 1 of the present invention;

[0028] Figure 1D This is a schematic diagram of the beam splitting and combining process within an mMTC slice;

[0029] Figure 2A This is a flowchart of a control method provided in Embodiment 2 of the present invention;

[0030] Figure 2B This is a schematic diagram of the preamble resource sharing relationship for odd and even beams;

[0031] Figure 2C It is a flowchart of a beam splitting / combining decision and parameter configuration process;

[0032] Figure 3 This is a flowchart of an access capacity management method for mMTC slices based on beam splitting provided in Embodiment 3 of the present invention;

[0033] Figure 4 This is a flowchart of an access capacity management method for mMTC slices based on beam combining, provided in Embodiment 4 of the present invention;

[0034] Figure 5 This is a schematic diagram of an access capacity management system provided in Embodiment 3 of the present invention;

[0035] Figure 6 This is a schematic diagram of the base station structure for implementing the mMTC slicing access capacity management method based on beam splitting and combining, as described in this embodiment of the invention. Detailed Implementation

[0036] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. 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.

[0037] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0038] When an mMTC device is active, it can initiate a random access procedure to complete synchronization with the base station and transmit uplink data. The random access procedure includes a contention-based random access procedure and a scheduling-free random access procedure.

[0039] Figure 1A This is a schematic diagram of a contention-based random access process. (For example...) Figure 1A As shown, in a conventional contention-based random access process, the mMTC device obtains the random access configuration information of the base station cell (such as the resource location of the physical random access channel and the preamble set) by receiving system information periodically broadcast by the base station. The mMTC device randomly selects a preamble from the available preamble set and transmits it uplink on the PRACH channel, i.e., it transmits MSG1. Due to the randomness of the preamble selection, different mMTC devices may choose the same preamble and transmit it uplink on the same PRACH resource, causing MSG1 collisions. Obviously, the probability of collisions increases with the number of devices simultaneously initiating access. After detecting MSG1, the base station generates MSG2, which includes a Random Access Response (RAR), and transmits it downlink via the Physical Downlink Shared Channel (PDSCH). MSG2 also contains Timing Advance (TA) and resource grant information for the Physical Uplink Shared Channel (PUSCH) used for MSG3 transmission. Upon successfully receiving MSG2, the mMTC device scrambles MSG3 using the Cell Temporary Identifier (TC-RNTI) allocated by MSG2 and completes uplink transmission of MSG3 based on the PUSCH resources scheduled by MSG2. MSG3 contains information such as the mMTC device identifier (UEID).

[0040] However, when a collision occurs with MSG1, multiple mMTC devices will send MSG3 on the same PUSCH resource. Interference between these devices will prevent the base station from correctly decoding these MSG3s, leading to access failure. If the base station can correctly decode MSG3, it will send MSG4 containing collision resolution information with the UEID. The mMTC device corresponding to the UEID will successfully complete the random access after correctly receiving MSG4.

[0041] In mMTC uplink services, mMTC devices are sporadically active. When inactive, they only receive downlink data from the base station and return to inactive status after a single transmission. Furthermore, mMTC data packets are short. Using a conventional contention-based random access method would increase signaling overhead. Therefore, Figure 1B This is a schematic diagram of a scheduling-free random access process. For example... Figure 1B As shown, mMTC devices often combine the preamble and data information into MSG1 and use a grant-free method for uplink transmission.

[0042] During random access, mMTC devices randomly select a preamble from the available preamble set and transmit it on the Random Access Channel (RACH) to complete uplink access. When multiple devices select the same preamble for uplink access, preamble collisions occur. These collisions typically prevent the base station from correctly detecting the terminal device using the preamble, leading to access failure. In mMTC scenarios, the number of devices is significantly increased, far exceeding the number of available preambles. This significantly increases the probability of collisions and drastically reduces the access success rate. Furthermore, in latency-sensitive mMTC applications, numerous collisions can cause access latency to fail to meet the latency requirements of such applications. On the other hand, mMTC devices are diverse, with different types of service needs.

[0043] Future wireless communication systems need to simultaneously serve a variety of mMTC devices with different service requirements (such as latency sensitivity, power consumption constraints, and reliability). Network slicing technology can dynamically adjust network configurations in real time according to changing device needs, ensuring that such adjustments do not affect other services such as eMMB. Using network slicing technology, network owners virtualize public physical network infrastructure into multiple different "sub-networks" (slices). Network service providers can then lease these network slices to provide customized services to mMTC and eMMB terminal devices, significantly improving network flexibility. These network service providers are called slice tenants. Network slicing technology provides reliable support for addressing the diverse device service needs in mMTC scenarios. In scenarios such as the Industrial Internet of Things (IIoT), network slicing technology has become a frequently used key technology for addressing the diverse service needs of different types of mMTC devices.

[0044] Existing 5G NR systems can use either a single wide-beam SSB to cover a cell or multiple narrow-beam SSBs to scan and cover a cell. In the multiple SSB scanning method, a cell can use R (R≤64) preambles and can use S (S=1 / 4 / 8 / 16 / 32 / 64) SSBs in a time-sharing manner to cover synchronization signals in different directions of the cell. SSBs can share or exclusively use random access opportunities (PRACH Occasions). If a random access opportunity is shared by S S SSBs, the number of preambles that each SSB can use on that random access opportunity (PO) is R / S. If a random access opportunity is exclusively used by a particular SSB, the number of preambles that SSB can use on that random access opportunity is R. When S≥4, the number of preambles available on the original PRACH channel decreases to 1 / S, which also leads to a decrease in random access capacity within the SSB beam. Therefore, S times the time-frequency resources need to be allocated to PRACH to maintain the same number of available preambles. In existing 5G NR systems, during SSB splitting, the number of PRACH beams remains unchanged, still using a single wide beam. Therefore, the method of multiple SSBs scanning to cover cells does not actually increase the random access capacity of mMTC slices. Furthermore, when the number of active terminal devices within a beam is small, the random access capacity of the mMTC slice does not decrease, leading to redundancy of the preamble within the beam and excessive overhead. Therefore, existing 5G NR systems suffer from the problem of limited random access capacity per beam within an mMTC slice that does not change with input load.

[0045] To address the aforementioned issues, this invention provides a method for managing the access capacity of mMTC slices based on beam splitting and combining. By splitting or combining beams within an mMTC slice, the random access capacity of the mMTC slice is managed, ensuring that the random access capacity of the mMTC slice is adapted to the random access load and optimizing the efficiency of the mMTC slice.

[0046] Example 1

[0047] Figure 1C This is a flowchart of an access capacity management method for mMTC slices based on beam splitting and combining provided in Embodiment 1 of the present invention. This embodiment is applicable to controlling the access capacity of mMTC slices of a base station. This method can be executed by an access capacity management system, which can be implemented in hardware and / or software. The access capacity management system can be configured in the base station where mMTC slices are deployed, or it can be independent of the base station. Figure 1C As shown, the method includes:

[0048] S110: Receive random access signaling sent by the mMTC device and obtain the number of idle random access opportunities for each beam within the mMTC slice during the current decision period.

[0049] In this context, mMTC equipment refers to equipment used in a Massive Machine Type Communication (mMTC) environment. Random access signaling can be understood as the information exchanged between the mMTC equipment and the base station during the random access process, primarily including MSG1-MSG4, such as preambles, Random Access Response (RAR), and contention resolution information. An mMTC slice is a slice deployed in the base station for a Massive Machine Type Communication environment. The current decision period can be understood as the period during which the mMTC slice's beam is making a decision. The current decision period can be set to multiple Random Access (RA) periods according to actual needs, generally an integer multiple of the System Information Broadcast (SIB) period; however, this embodiment of the invention does not impose such a limitation.

[0050] Random access opportunities can include both occupied and idle random access opportunities. The number of random access opportunities (RACH Opportunities) is the product of the number of random access times (PRACH Occasions) and the number of preambles. A random access time (PRACH Occasion, PO) can be understood as the time-frequency domain resource used to transmit preambles, which can include both time and frequency domain positions. It should be noted that the number of random access times is determined by the transmission scheme configuration adopted by the base station, and in the operation of this invention, the number of random access times is considered constant; however, by configuring preamble resources under different beams, the number of random access opportunities within a beam can be changed. The number of idle random access opportunities is determined by subtracting the number of occupied random access opportunities from the number of random access opportunities; the number of occupied random access opportunities changes with the access status of mMTC devices; it can be understood that the more mMTC devices access, the more occupied random access opportunities there are, and thus the fewer idle random access opportunities there are.

[0051] The base station in this embodiment of the invention can be a serving cell of a massive MIMO system. The base station is equipped with mMTC slices and a massive antenna array, which can generate a beam with strong directionality and concentrated energy.

[0052] Specifically, the base station periodically broadcasts system information (such as SSB or SIB1) so that mMTC devices can receive the PRACH random access configuration parameters (such as the available preamble set) for the corresponding beam. Within each random access cycle, each active mMTC device randomly selects a preamble from the preamble set to initiate random access signaling (such as MSG1). By detecting and receiving the random access signaling sent by the mMTC devices through directional beam probing, the base station can obtain the number of occupied and idle random access opportunities for each beam in the current decision cycle through preamble detection. The occupied random access opportunities include preamble information for successful access and preamble collision information.

[0053] For example, the base station performs collision detection in each Random Access (RA) cycle within the decision period to obtain the number of idle Random Access Opportunities (RACH) in each beam. B(t) represents the number of beams contained in the mMTC slice during the t-th decision period.

[0054] S120. Based on the random access configuration information of each beam in the current decision period and the number of idle random access opportunities, estimate the random access state of each beam in the prediction period using the mMTC slice.

[0055] The random access configuration information can be understood as the random access information determined by the base station configuration for the beams within the mMTC slice, which may include, for example, the number of random access opportunities and random access capacity. The random access state estimate can be understood as an estimate of the random access state information within the beam; the random access state information can be understood as the state information describing the random access of the beam in a prediction period, which may include, for example, the random access load estimate, random access load rate, and random access success rate. This prediction period can be understood as the period following the current decision period.

[0056] Specifically, within the current decision period, for each beam within the mMTC slice, the estimated random access load can be determined based on the number of random access opportunities and the number of idle random access opportunities for the beam; based on the estimated random access load and the random access configuration information of the current decision period, the estimated random access state for the prediction period is predicted, thus obtaining the estimated random access state of the beam within the prediction period.

[0057] S130. Determine the beam splitting and combining configuration parameters based on the random access state estimate using the mMTC slice.

[0058] Beam splitting and / or beam combining includes beam splitting and / or beam combining; beam splitting refers to splitting a beam into two or more beams; beam combining refers to combining two or more beams into one beam; the target beam is the beam obtained after beam splitting or beam combining. It can be understood that within each decision cycle, a decision can be made regarding whether a beam needs to be split or combined.

[0059] Beam splitting and combining configuration parameters can be understood as the configuration parameters corresponding to beam splitting and combining. For example, they may include the configuration information of the beam to be changed that needs to be split and combined, the configuration information of the target beam generated after beam splitting and combining, and the configuration information of the preamble resources after beam splitting and combining.

[0060] Specifically, the mMTC slices deployed on the base station make decisions based on the predicted random access state estimates of each beam to determine whether there are beams that need to be split or combined; if so, the beam splitting and combining configuration parameters are determined based on the random access state estimates.

[0061] Understandably, if the decision result is that there is no beam that needs to be beam splitting or combining, then the current beam configuration information will not be changed, and the set random access procedure will still be followed (e.g., Figure 1A The competition-based random access procedure shown or Figure 1B The competition-based random access procedure shown is used to access the MTC device.

[0062] S140. Perform beam splitting and combining according to the beam splitting and combining configuration parameters to obtain the target beam, and configure the beam parameters in the mMTC slice to control the total random access capacity of the mMTC slice within the prediction period.

[0063] The total random access capacity of an mMTC slice can be understood as the sum of the random access capacities of all beams within the mMTC slice. The target beam is the beam obtained through beam splitting and combining, which includes beam splitting and / or beam combining. Accordingly, the target beam includes the target split beam obtained after beam splitting and / or the target combined beam obtained after beam combining. Beam parameters refer to all parameters that need to be reconfigured after beam splitting and combining. This beam not only includes the parameters of the target beam but may also include other changed beam parameters.

[0064] Specifically, the base station performs beam splitting and combining on the beam to be changed according to the beam splitting and combining configuration parameters determined by the mMTC slice to obtain the target beam, and configures the beam parameters of each beam in the mMTC slice according to the beam splitting and combining configuration parameters. Since the number of beams in the mMTC slice and the preamble resource information in each beam are changed after beam splitting and combining, the random access capacity of the mMTC slice can be controlled.

[0065] like Figure 1D As shown, the MTC slice access capacity control method provided in this embodiment of the invention can split the original beam into multiple narrower beams through beam splitting, thereby reducing the number of active devices in a single beam, reducing the MSG1 collision rate, improving the random access success rate, and increasing the total random access capacity of the mMTC slice. By combining multiple beams into a single wide beam through beam combining, the number of beams is reduced, allowing the total random access capacity of the mMTC slice to be reduced to a level adapted to the current random access load, thus reducing system overhead; thereby solving the problem in existing 5G NR systems where the random access capacity of the mMTC slice cannot change with the input load.

[0066] It should be noted that during the beam splitting process of services such as MSG1, the beam used by the synchronization signal block SSB does not need to be split and can still use a wide beam for coverage, in order to simplify management and save operating costs. In addition, the access capacity management method of mMTC slice based on beam splitting and combining completes the decision-making and configuration process of beam splitting and combining entirely on the base station side. The terminal-side access program does not need to be modified, which can more flexibly adapt to the needs of mMTC services.

[0067] The technical solution of this invention receives random access signaling from an mMTC device to obtain the number of idle random access opportunities for each beam within the mMTC slice during the current decision period. Based on the random access configuration information and the number of idle random access opportunities for each beam during the current decision period, the mMTC slice estimates the random access state of each beam during the prediction period. Based on the estimated random access state, the mMTC slice determines beam splitting and combining configuration parameters. Beam splitting and combining are performed according to the beam splitting and combining configuration parameters to obtain the target beam, and beam parameters within the mMTC slice are configured to control the total random access capacity of the mMTC slice during the prediction period. By controlling beam splitting or combining within the mMTC slice, the random access capacity of the mMTC slice is managed, making the random access capacity of the mMTC slice adaptable to the random access load. This solves the problem in existing 5G NR systems where the random access capacity of mMTC slices cannot change with input load variations, thus optimizing the efficiency of mMTC slices.

[0068] Optionally, beam splitting and combining are performed according to the beam splitting and combining configuration parameters to obtain the target beam, and the beam parameters within the mMTC slice are configured as follows:

[0069] The mMTC slice generates a beam splitting / combining request containing the beam splitting / combining configuration parameters; wherein the beam splitting / combining request includes: a beam splitting request or a beam combining request;

[0070] Determine whether to respond to the beam splitting / combining request based on the global load status information within the base station;

[0071] If the beam splitting and combining request is responded to, the target beam is generated by beam splitting and combining based on the beam splitting and combining configuration parameters contained in the beam splitting and combining request.

[0072] The global load status information within a base station can be understood as the global load status information that the base station can obtain, including: all mMTC slices of the base station and the load status information contained within the beams of the mMTC slices. This embodiment of the invention does not limit the global load status information; it can be understood that any information sufficient to reflect the load status of the base station can be included. It is understood that the larger the total random access capacity, the higher the service quality provided by the base station. Specifically, since mMTC slices generally only obtain information such as the load of the beams within their own slice, and cannot obtain the global load status information of the base station, this is to avoid the beam splitting and combining determined by the mMTC slices affecting the service quality of the base station. After determining the beam splitting and combining configuration parameters, the mMTC slice generates a beam splitting and combining request containing these parameters. This request is sent to the base station, which then determines, based on its global load and the beam splitting and combining configuration parameters, whether to allow beam splitting and combining, i.e., whether to respond to the request. Provided that the base station's service quality still meets requirements after beam splitting and combining, the mMTC slice responds to the request, performs beam splitting and combining based on the configuration parameters included in the request to generate the target beam, and configures the beam parameters within the mMTC slice according to these parameters.

[0073] For example, the base station determines whether beam combining / splitting is allowed based on beam combining / splitting configuration parameters and global load information. This strategy can be formulated according to the base station's service quality requirements and usage scenarios, and this embodiment of the invention does not impose any restrictions on it. Furthermore, it is understood that if the base station does not allow beam combining / splitting, the current beam configuration information is not changed, and the set random access procedure (e.g., ...) is still followed. Figure 1A The competition-based random access procedure shown or Figure 1B The scheduled random access procedure shown is used to access the MTC device.

[0074] Example 2

[0075] Figure 2A This is a flowchart of an access capacity management method for mMTC slices based on beam combining and splitting provided in Embodiment 2 of the present invention. This embodiment further defines step S130 of the above embodiment. Figure 2A As shown, the method includes:

[0076] S210: Receive random access signaling sent by the mMTC device and obtain the number of idle random access opportunities for each beam within the mMTC slice during the current decision period.

[0077] S220. Based on the random access configuration information of each beam in the current decision period and the number of idle random access opportunities, estimate the random access state of each beam in the prediction period using the mMTC slice.

[0078] Optionally, the random access configuration information includes: the number of random access opportunities and the random access capacity; the random access status estimate includes: the random access success rate estimate and the random access load rate estimate.

[0079] Step S220 includes:

[0080] S221. For each beam within the mMTC slice, calculate the estimated random access load within the corresponding beam based on the number of random access opportunities for each random access period of the beam in the current decision period and the number of idle random access opportunities.

[0081] Specifically, the number of available preambles in an mMTC slice is N, and the number of available PRACH time-frequency resources within one RA cycle is N. RA That is, the number of random access pRACH occasions, and the number of preambles available for the b-th beam is N. (b) The number of random access opportunities (RACH) within the b-th beam in one RA cycle of the mMTC slice is Q. (b) =N (b) ×N RA Based on the number of random access opportunities (RACH) Q in each random access cycle. (b) And the number of idle random access opportunities (RACH Opportunities) Calculate the estimated random access load within the b-th beam of the mMTC slice.

[0082] S222. Based on the estimated random access load and the number of random access opportunities, estimate the estimated random access success rate for each random access period of the corresponding beam within the prediction period.

[0083] Specifically, based on the random access load estimate... and the number of random access opportunities Q (b) The estimated random access success rate for the b-th beam in each random access period within the prediction period is:

[0084] S223. Based on the random access capacity of the beam in the current decision period and the estimated random access load, estimate the estimated random access load rate of the beam in each random access period of the prediction period.

[0085] Specifically, based on the random access capacity of the b-th beam during the current decision-making period. and random access load estimates The estimated random access load rate of the beam in each random access period within the prediction period is:

[0086] It should be noted that, in the embodiments of the present invention, the random access capacity of the beam is variable, but the random access capacity of the beam remains constant within each decision cycle.

[0087] S230. Based on the random access state estimate, determine the beams to be changed that need to be beam splitting or combining using the mMTC slice.

[0088] The beam splitting and combining includes beam splitting or beam combining; thus, the beam to be changed includes: the beam to be split and the beam to be combined; the beam to be split is the beam that needs to be split; the beam to be combined is the beam that needs to be combined.

[0089] Specifically, for each beam contained in an mMTC slice, it is determined whether the beam is a beam to be split based on a first random access state estimate within the beam; the first random access state estimate can be a random access success rate estimate. It is then determined whether the beam is a beam to be combined based on a second random access state estimate; the second random access state estimate can be a random access load rate estimate.

[0090] For example, all beams that need to be split or beams that need to be combined can constitute a set B of beams to be changed. When B is not empty, beam splitting and combining need to be performed to further determine the beam splitting and combining configuration parameters corresponding to the beams to be changed.

[0091] S240. Determine the beam splitting and combining configuration parameters corresponding to the beam to be changed based on the random access state estimate using the mMTC slice.

[0092] Specifically, since the beams to be changed include beams to be split or beams to be merged, the mMTC slice needs to determine the beam splitting and merging configuration parameters for each beam to be changed based on the estimated random access state value corresponding to the beam and the type to which the beam to be changed belongs (i.e., beams to be split or beams to be merged).

[0093] It is understandable that the beam splitting and combining configuration parameters corresponding to the beam to be split are the beam splitting configuration parameters, and the beam splitting and combining configuration parameters corresponding to the beam to be combined are the beam combining configuration parameters.

[0094] Because beam splitting and beam combining are based on different principles, the configuration parameters for beam splitting and beam combining may not be exactly the same, but they should at least include: the sequence number of the beam to be split or combined, the sequence number of each beam after splitting or combining, the configuration parameters of the preamble resources in the mMTC slice, and the beam coverage angle of the target beam.

[0095] S250. Perform beam splitting and combining according to the beam splitting and combining configuration parameters to obtain the target beam, and configure the beam parameters in the mMTC slice to control the total random access capacity of the mMTC slice within the prediction period.

[0096] Specifically, the beam to be split is split into a target split beam according to the beam splitting configuration parameters, and the beam parameters in the mMTC slice are configured according to the beam splitting configuration parameters; the beam to be merged is merged into a target merged beam according to the beam merging configuration parameters, and the beam parameters in the mMTC slice are configured according to the beam merging configuration parameters.

[0097] The technical solution of this invention involves receiving random access signaling from an mMTC device to obtain the number of idle random access opportunities for each beam within the mMTC slice during the current decision period; estimating the estimated random access state of each beam during the prediction period based on the random access configuration information and the number of idle random access opportunities for each beam within the current decision period using the mMTC slice; identifying beams whose first random access state estimate is lower than a first threshold value in any random access period within the decision period as beam splitting beams; wherein the first random access state estimate is the estimated random access success rate within the corresponding beam; and the second random access state estimate is... Beams whose values ​​are below the second threshold in each random access period within the decision period are identified as beam-combining beams to be combined. The second random access state estimate is the estimated random access load rate within the corresponding beam. The beam splitting and combining configuration parameters corresponding to the beam to be changed are determined using the mMTC slice based on the random access state estimate. The beam splitting and combining configuration parameters are then used to obtain the target beam, and the beam parameters within the mMTC slice are configured to control the total random access capacity of the mMTC slice within the prediction period. This solves the problem in existing 5G NR systems where the random access capacity of mMTC slices cannot change with input load variations. It achieves beam splitting and combining control of the number of beams and configuration of preamble resources within the mMTC slice based on actual access load conditions, thereby achieving the goal of controlling the random access capacity of the mMTC slice and optimizing its efficiency.

[0098] Optionally, the beam splitting and combining configuration parameters include: beam splitting configuration parameters and beam combining configuration parameters;

[0099] The beam splitting configuration parameters include: the original beam number of the beam to be split, the total number of beams, and the preamble resource configuration parameters, as well as the beam splitting update number and beam coverage angle of each beam within the mMTC slice; the total number of beams is the number of all beams contained in the mMTC slice after beam splitting the beam to be split; all beams contained in the mMTC slice after beam splitting include the target split beam obtained by beam splitting the beam to be split;

[0100] The beam merging configuration parameters include: the original beam number of the beam to be merged, the original beam number of the beams participating in the merging, the beam merging update number of each beam in the mMTC slice, the beam coverage angle of the target merging beam, and the preamble resource configuration parameters.

[0101] The preamble resource configuration parameter is the proportion of preambles allocated to even-numbered beams within the mMTC slice, and the sum of the proportion of preambles allocated to even-numbered beams and the proportion of preambles allocated to odd-numbered beams is 1.

[0102] In this embodiment, the beam coverage angle can be understood as the angular range that a beam can cover. It can be understood that the beam coverage angles between any two beams do not overlap. Each beam is assigned a different beam number. When a beam splits or merges, the beam number within the MTC slice may change. The beams that change include, but are not limited to, target split beams and target merge beams. Beam splitting and merging may also cause changes in the beam numbers of other beams within the MTC slice.

[0103] The preamble resource configuration parameter is the proportion of preambles allocated to odd-numbered or even-numbered beams within an mMTC slice, and the sum of the proportions allocated to even-numbered beams and odd-numbered beams is 1. That is, if the preamble resource configuration parameter η is the proportion of preambles allocated to even-numbered beams, then the proportion of preambles allocated to odd-numbered beams is 1-η. Conversely, if the preamble resource configuration parameter η is the proportion of preambles allocated to odd-numbered beams, then the proportion of preambles allocated to even-numbered beams is 1-η.

[0104] Optionally, S250, configuring the beam parameters within the mMTC slice includes:

[0105] S251. Update the mapping table of mMTC device and channel angles according to the beam coverage angle included in the beam splitting and combining configuration parameters and the random access load estimate of the mMTC slice.

[0106] S252. Generate a first preamble multiplexing subset and a second preamble multiplexing subset according to the preamble resource configuration parameters included in the beam splitting and combining configuration parameters; wherein, the first preamble multiplexing subset includes preambles that can be used by beams with odd-numbered sequences, and the second preamble multiplexing subset includes preambles that can be used by beams with even-numbered sequences.

[0107] Specifically, the base station updates the mapping table between the device identifier (UEid) and the channel angle of the mMTC device based on the beam coverage angle included in the beam splitting and combining configuration parameters and the estimated random access load of the mMTC slice; for example, the channel angle range of a UE with UEid of 500 is 5-15 degrees.

[0108] The available set of preambles is P = [p1, p2, ..., p m ], and satisfy:

[0109]

[0110] Where i and j represent the sequence numbers of the preambles in the preamble set P.

[0111] like Figure 2B As shown, the preamble set of each beam is divided into two mutually orthogonal multiplexed subsets: a first preamble and a second preamble. Adjacent beams use mutually orthogonal PRACH resources. For example, beams numbered 1, 3, 5, etc., with odd numbers can share the PRACH resources of the first preamble multiplexed subset, while beams numbered 2, 4, 6, etc., with even numbers can share the PRACH resources of the second preamble multiplexed subset. The relationship between the first preamble multiplexed subset A and the second preamble multiplexed subset B used by odd-numbered and even-numbered beams and the available preamble set P is as follows:

[0112]

[0113] like Figure 2B As shown, the odd-numbered beams, such as the 1st, 3rd, and 5th beams, share the preamble contained in the first preamble multiplexing subset, while the even-numbered beams, such as the 2nd, 4th, and 6th beams, share the preamble contained in the second preamble multiplexing subset.

[0114] Optionally, after configuring the beam parameters within the mMTC slice, the method further includes:

[0115] The first preamble multiplexed subset used by odd-numbered beams within the mMTC slice is broadcast via the SIB1 beam, and the second preamble multiplexed subset used by even-numbered beams within the mMTC slice is broadcast.

[0116] Specifically, the SIB1 beam is used to beam the odd-numbered beams within the mMTC slice using a first preamble multiplexed subset, allowing mMTC devices within the odd-numbered beams to access the mMTC slice using the first preamble multiplexed subset. Similarly, the SIB1 beam is used to beam the even-numbered beams within the mMTC slice using a second preamble multiplexed subset, allowing mMTC devices within the even-numbered beams to access the mMTC slice using the second preamble multiplexed subset. This achieves the multiplexing of preamble resources within the mMTC slice.

[0117] When the next SIB1 cycle arrives, the base station broadcasts the first preamble multiplexed subset to the odd-numbered beams in the mMTC slice via the SIB1 beam, and broadcasts the second preamble multiplexed subset to the even-numbered beams in the mMTC slice, thus completing the beam splitting and combining in the current decision cycle.

[0118] It is important to note that before broadcasting the SIB1 message, the mMTC slice needs to continuously receive notifications of changes in beam coverage. Furthermore, during dynamic beam splitting / merging management, when the mMTC slice receives a beam change notification, the SIB1 message needs to repeat the steps described above for configuring the beam parameters within the mMTC slice. Additionally, regarding the decision-making cycle for the mMTC slice, since the beam splitting / merging configuration parameters within the mMTC slice need to be communicated to the mMTC device via system information (SIB1, etc.), in practical implementation, the decision-making cycle is preferably defined as an integer multiple of the base station system information (SIB1, etc.) broadcast cycle.

[0119] In a specific example, such as Figure 2CAs shown, during the t-th decision period, the mMTC slice performs preamble detection in each beam during each RA cycle to obtain the number of idle random access opportunities (RACH Opportunities) in each beam and updates the UEid / angle mapping table of successfully accessed devices. It calculates the estimated random access success rate and load rate for each beam in each RA cycle using the mMTC slice. It then performs beam splitting / merging decisions for each beam using the mMTC slice and calculates beam splitting / merging configuration parameters. The mMTC generates corresponding beam splitting / merging requests based on the beam splitting / merging configuration parameters and sends them to the base station management program. The base station management program determines whether to accept the request. If the request is accepted, the base station management program completes the change of beam configuration parameters. If the request is not accepted, the t-th decision period ends, and the mMTC device is accessed according to the set contention-based random access procedure or the scheduling-free random access procedure.

[0120] The beam splitting / merging decision process is as follows: First, determine if the random access success rate within the beam is lower than the QoS requirement. If yes, the mMTC slice determines that the beam needs to be split, and calculates the beam splitting configuration parameters. If no, further determine if the load rate within the beam is lower than the system threshold. If yes, the mMTC slice determines that the beam needs to be merged, and calculates the beam merging configuration parameters. If no, the beam configuration parameters remain unchanged, thus completing the beam splitting / merging decision process.

[0121] The mMTC slicing access capacity management method based on beam splitting and combining provided by this invention can be applied to contention-based random access procedures or scheduling-free random access procedures. In a contention-based random access procedure, after receiving SIB1, the terminal selects the preamble resource in the SIB1 message to initiate random access. The base station can identify whether the preamble belongs to subset A or B, thereby determining whether the beam has an odd or even sequence number. Then, through a mapping table, it can determine which beam the terminal device (i.e., the mMTC device) belongs to. After beam splitting is completed, the base station and the terminal can enter the conventional contention-based random access procedure in a low-collision-probability scenario. The terminal selects a preamble from the allocated preamble subset to initiate random access and sends MSG1. The base station receives MSG1 and, based on the preamble's affiliation, can identify the beam to which the terminal device belongs. The base station replies with MSG2 information using the identified beam. The terminal sends MSG3 using the uplink PUSCH resources allocated in the received MSG2 information. The base station receives MSG3 and replies with MSG4. The terminal's random access is successful. In the scheduling-free random access process, after receiving SIB1, the terminal selects the preamble resource in the SIB1 message to initiate random access. The base station can identify whether the preamble is odd or even, and then determine which beam the terminal device belongs to through a mapping table. After beam splitting is completed, the base station and the terminal can enter the conventional scheduling-free random access process under low collision probability scenarios. The terminal selects a preamble from the allocated preamble subset to initiate random access and sends MSG1, which carries the terminal's data information. The base station receives and decodes the data information in MSG1, and determines whether the beam is odd or even based on whether the preamble belongs to subset A or B. Then, it can identify the beam to which the terminal device belongs through a mapping table. The terminal device successfully accesses the system.

[0122] Example 3

[0123] Figure 3 This is a flowchart of an access capacity management method for mMTC slicing based on beam splitting and combining provided in Embodiment 3 of the present invention. This embodiment further defines the beam splitting process of the beam to be split in the above embodiments. Figure 3 As shown, the method includes:

[0124] S310: Receive random access signaling sent by the mMTC device and obtain the number of idle random access opportunities for each beam within the mMTC slice during the current decision period.

[0125] S320. Based on the random access configuration information of each beam in the current decision period and the number of idle random access opportunities, estimate the random access state of each beam in the prediction period using the mMTC slice.

[0126] S330. If the estimated random access success rate of a beam within the mMTC slice is lower than the success rate threshold in any random access period within the decision period, then the beam is determined to be a beam to be split.

[0127] The success rate threshold is the minimum random access success rate used to determine whether a beam is a beam to be split. It can be determined according to the service quality requirements of the base station, and this embodiment of the invention does not impose any restrictions on it.

[0128] Specifically, if the estimated random access success rate of the b-th beam within the mMTC slice is within any RA cycle of the current decision period... Among them, P nc If the threshold value is set to the success rate, then the b-th beam is determined to be the beam to be split.

[0129] S340. Determine the beam splitting configuration parameters corresponding to the beam to be split based on the random access state estimate using the mMTC slice.

[0130] Specifically, the beam splitting configuration parameters include: the original beam number of the beam to be split, the total number of beams, the preamble resource configuration parameters and beam coverage angle within the mMTC slice, and the beam splitting update sequence number of each beam.

[0131] Optionally, the S340 includes:

[0132] S341. For each beam to be split, determine the access load angle distribution function based on the estimated random access load rate and the mMTC device angle.

[0133] Specifically, for each beam to be split, the estimated access load of that beam b within the coverage area is calculated. And the mMTC device angle determination access load angle distribution function f(θ) contained in the mMTC device angle mapping table.

[0134] S342. Determine the total number of beams after beam splitting using the mMTC slice; wherein, the total number of beams is the number of all beams contained in the mMTC slice after beam splitting the beam to be split; all beams contained in the mMTC slice after beam splitting include the target split beam obtained by beam splitting the beam to be split.

[0135] Specifically, the conditions that the total number of beams must meet may include: after beam splitting, the random access capacity of each beam of the mMTC slice is higher than the estimated access load within that beam, and the beamwidth of each beam is greater than the minimum achievable beamwidth.

[0136] For example, the random access capacity of each beam can be determined based on the random access capacity of the mMTC slice and the number of beams within the mMTC slice. Assume that, under the condition of meeting the quality of service requirements, the minimum random access success rate for the device to meet the quality of service requirements within each RA cycle is P. nc Then the access capacity of this beam under the given quality of service requirements is: Where c b =1-1 / Q b The number of available preambles in an mMTC slice is N, and the number of available PRACH time-frequency resources within one RA cycle is N. RA The number of preambles available for the b-th beam is N. (b) =N×η b 1; among which, η b η is the ratio of the number of preambles that can be used for the b-th beam to the total number of preambles; if b is an even number, then η b =η; if b is an odd number, then η b = 1 - η; η represents the ratio of the number of preambles allocated to even-numbered beams to the total number of preambles. Therefore, the number of random access opportunities (RACH) in one RA cycle within the b-th beam of the mMTC slice is Q. (b) =N (b) ×N RA When n is much greater than 1, In(1-1 / n)≈-1 / n holds true, and the random access capacity within the mMTC slice is...

[0137]

[0138] Where, c = ln(P) nc B represents the total number of beams within the mMTC slice after beam splitting. odd This represents the number of odd-numbered beams. From the above formula, it can be seen that when the total number of beams B is even, the access capacity of the target split beam is independent of η.

[0139] S343. Based on the order of the beams in the mMTC slice after beam splitting, the beam splitting update number of each beam is re-determined.

[0140] Specifically, if the b-th beam is the beam to be split, and the decision is made to split it into two target split beams, then the index of the first target split beam is b, and the index of the second target split beam is b+1. The corresponding beam indices within the mMTC slice following the beam to be split are incremented by 1 sequentially; that is, the original indices of beams b+1, b+2, b+3… are updated to b+2, b+3, b+4… Preamble subsets are then allocated according to the updated beam indices after beam splitting.

[0141] S344. Determine the preamble resource configuration parameters within the mMTC slice based on the total number of beams and the beam number of each beam within the mMTC slice after beam splitting.

[0142] Specifically, assuming η represents the ratio of the number of preambles assigned to even-numbered beams to the total number of preambles; then, when the total number of beams B within the mMTC slice after beam splitting is odd, the number of beams with odd-numbered indices is B. odd = (B+1) / 2, then the preamble resource allocation parameter η = B for beams with even-numbered indices within the mMTC slice. odd -(KB) / cQ; Correspondingly, the preamble resource configuration parameter allocated to even-numbered beams is 1-η. When the total number of beams B in the mMTC slice after beam splitting is even, since the access capacity of the target split beam is independent of η, in actual use, for convenience, it can be set to a preset value, such as η=0.5, so that the random access capacity of each beam is the same, and the access load is evenly distributed to each beam according to the access load angle distribution function f(θ) to improve the fairness of beam-to-beam access and the global random access performance.

[0143] S345. For each target split beam, the beam coverage angle of the target split beam is determined according to the random access capacity of the target split beam and the access load angle distribution function, wherein the random access load in each target split beam is less than its respective random access capacity; the sum of the beam coverage angles of all the target split beams is the beam coverage angle of the beam to be split, and the coverage angle of each target split beam is less than the beam coverage angle of the beam to be split, and the coverage angles of each target split beam do not overlap.

[0144] Specifically, based on the access load angle distribution function f(θ) and the beam coverage angle θ of the target split beam... (b) And target split beam in random access capacity The integral relationship between them determines the beam coverage angle of the target split beam. Among them, the conditions to be satisfied include (1) the random access load in each target split beam is less than its respective random access capacity; wherein, the random access load in each target split beam can be the same or different. (2) the sum of the beam coverage angles of each target split beam is the beam coverage angle of the beam to be split, the coverage angle of each target split beam is less than the beam coverage angle of the beam to be split, and the coverage angles of each target split beam do not overlap.

[0145] S350. The beam to be split is split into target split beams according to the beam splitting configuration parameters, and the beam parameters in the mMTC slice are configured to control the total random access capacity of the mMTC slice in the prediction period.

[0146] The technical solution of this invention involves receiving random access signaling from an mMTC device to obtain the number of idle random access opportunities for each beam within the mMTC slice during the current decision period; estimating the random access state estimate for each beam during the prediction period based on the random access configuration information and the number of idle random access opportunities for each beam within the current decision period using the mMTC slice; if the estimated random access success rate of a beam within the mMTC slice during any random access period within the decision period is lower than a success rate threshold, then the beam is determined to be a beam to be split; the beam splitting configuration parameters corresponding to the beam to be split are determined based on the estimated random access state using the mMTC slice; the beam to be split is then performed according to the beam splitting configuration parameters to obtain the target split beam, and the beam parameters within the mMTC slice are configured to control the total random access capacity of the mMTC slice during the prediction period. When a large number of active mMTC devices within a beam leads to numerous preamble (MSG1) collisions during random access, beam splitting can divide the original beam into multiple narrower beams. This reduces the number of active devices within the beam, lowers the MSG1 collision rate, improves the random access success rate, and increases the random access capacity of the mMTC slice. Furthermore, the beams within the split mMTC slice can achieve spatial multiplexing of random access resources such as preambles. This allows the number of available preambles on the original PRACH channel to reach half of the preamble number without increasing time-frequency resources, which is K / 2 (≥2) times that of scanning SSB coverage, even when a beam is split into two target beams.

[0147] Optionally, step S342, determining the total number of beams after beam splitting using the mMTC slice, includes:

[0148] S3421. Based on the mMTC slice's random access capacity and random access load estimate, determine the minimum number of beams after beam splitting, ensuring that the random access capacity of each beam within the mMTC slice after beam splitting is greater than the estimated random access load of that beam.

[0149] Specifically, the estimated random access load within the beam is... The mMTC slice access capacity is K can Determine whether the following conditions are met regarding B. The smallest integer value B min This is the minimum number of beams after beam splitting.

[0150] S3422. Determine the maximum number of beams after beam splitting based on the total beamwidth and minimum achievable beamwidth of the mMTC slice.

[0151] Among them, the minimum achievable beamwidth is the minimum width that each beam can detect. After the mMTC slice is beam split, it is necessary to ensure that all beamwidths are greater than the minimum achievable beamwidth.

[0152] Specifically, the maximum number of beams is determined when the ratio of the total beamwidth to the number of beams in the mMTC slice is greater than or equal to the minimum achievable beamwidth. This maximum number of beams is the maximum number of beams after beam splitting.

[0153] S3423. Based on a preset strategy, determine the total number of beams after beam splitting from the range of values ​​from the minimum number of beams to the maximum number of beams.

[0154] The value range of the number of beams is [minimum number of beams, maximum number of beams].

[0155] Specifically, after determining the range of values ​​for the total number of beams, the total number of beams after beam splitting is selected from the range and used as one of the parameters for beam splitting.

[0156] For example, the strategy of selecting the total number of beams after beam splitting from the range of values ​​can be comprehensively judged based on information such as the signal quality of the base station, the global load, and the parameters of the beams. This embodiment of the invention does not impose any restrictions on this.

[0157] This step can determine the total number of beams after beam splitting based on information such as random access capacity, estimated random access load, and beamwidth within the mMTC slice.

[0158] Optionally, S344, determining the preamble resource configuration parameters within the mMTC slice based on the total number of beams and the beam number of each beam within the mMTC slice after beam splitting, including:

[0159] S3441. If the total number of beams is odd, then the preamble resource configuration parameter allocated to the even-numbered beams after beam splitting is η = B. odd -(KB) / cQ; where B odd Where K is the number of beams with odd-numbered indices, K is the estimated random access load of the mMTC slice, and B is the total number of beams in the mMTC slice after beam splitting; c = -ln(P nc ), P ncQ represents the minimum random access success rate required for an mMTC device to meet quality of service requirements within a random access period; Q is the number of random access opportunities for an mMTC slice within a random access period.

[0160] The random access load estimate can be understood as the estimated number of access loads within the beam.

[0161] Specifically, based on the relationship between random access capacity and the number of beams within an mMTC slice, if the total number of beams B is odd, then the preamble resource configuration parameter allocated to the even-numbered beams after beam splitting is η = B. odd -(KB) / cQ, the preamble resource configuration parameter assigned to the even-numbered beam after beam splitting is 1-η.

[0162] S3442. If the total number of beams is even, the preamble resource configuration parameter allocated to the even-numbered beams after beam splitting is a first preset value; wherein, the sum of the preamble resource configuration parameters allocated to the odd-numbered beams and the preamble resource configuration parameters allocated to the even-numbered beams is 1.

[0163] Specifically, based on the relationship between random access capacity and the number of beams within an mMTC slice, if the total number of beams B is even, the random access capacity within the mMTC slice is independent of the preamble resource configuration parameters. Therefore, in practical use, for convenience, it can be set to a preset value, such as η = 0.5, so that the random access capacity of each beam is the same, and the access load is evenly distributed to each beam according to the access load angle distribution function f(θ), thereby improving the fairness of beam-to-beam access and the overall random access performance. This step can determine the preamble resource configuration parameters after beam splitting based on the total number of beams after beam splitting and the beam number of each beam within the mMTC slice.

[0164] Example 4

[0165] Figure 4 This is a flowchart of an access capacity management method for mMTC slicing based on beam splitting and combining provided in Embodiment 4 of the present invention. This embodiment further defines the beam splitting process of the beam to be split in the above embodiments. Figure 4 As shown, the method includes:

[0166] S410: Receive random access signaling sent by the mMTC device and obtain the number of idle random access opportunities for each beam within the mMTC slice during the current decision period.

[0167] S420. Based on the random access configuration information of each beam in the current decision period and the number of idle random access opportunities, estimate the random access state of each beam in the prediction period using the mMTC slice.

[0168] S430. If the estimated random access load rate of a beam within the mMTC slice is lower than the load rate threshold in all random access periods within the decision period, then the beam is determined to be a beam to be combined that needs to be beam-combined.

[0169] The load rate threshold is the minimum random access load rate used to decide whether a beam is a beam to be merged. It can be determined according to the service quality requirements of the base station. This embodiment of the invention does not impose any restrictions on this.

[0170] Specifically, if the estimated random access success rate of the b-th beam within the mMTC slice across all RA cycles in the current decision period is... Where δ is the load factor threshold; then the b-th beam is determined to be the beam to be combined that needs to be beam-combined.

[0171] S440. Determine the beam merging configuration parameters corresponding to the beam to be merged based on the random access state estimate using the mMTC slice.

[0172] Specifically, the beam merging configuration parameters of the beams to be merged include: the original beam number of the beams to be merged, the original beam number of the beams participating in the merging, the beam merging update number of each beam, the beam coverage angle of the target beam to be merged, and the preamble resource configuration parameters within the mMTC slice.

[0173] Optionally, S440 includes:

[0174] S441. For each beam to be merged, based on the estimated total random access load of the beam to be merged and each adjacent beam, and the expected random access success rate after beam merging, determine the participating beams from the adjacent beams that will be merged with the beam to be merged.

[0175] Here, the participating beams can be understood as the beams that will be combined with the beam to be combined to obtain the target combined beam. The expected random access success rate can be understood as the predicted random access success rate after the beams to be combined and the participating beams are combined.

[0176] Specifically, for each beam to be merged, the total random access load estimate of the beam to be merged and each adjacent beam is calculated. Based on the total random access load estimate, it is determined whether the adjacent beams meet the conditions. Based on the expected random access success rate, the participating beams for beam merging with the beam to be merged are determined from the adjacent beams that meet the conditions.

[0177] S442. The set of the original beam coverage angle of the beam to be merged and the original beam coverage angle of the beams participating in the merging is determined as the beam coverage angle of the target merging beam.

[0178] Specifically, the beam coverage angle of the target beam merging is the set of the original beam coverage angle of the beam to be merged and the original beam coverage angle of the beams participating in the merging. For example, the original beam coverage angle of the beam to be merged is 10 degrees to 30 degrees, and the original beam coverage angle of the beams participating in the merging is 30 degrees to 50 degrees. Since the coverage angles of each beam do not overlap, the beam coverage angle of the target beam merging after beam merging is 10 degrees to 50 degrees.

[0179] S443. Based on the order of the beams in the mMTC slice after beam merging, the beam merging update number of each beam is re-determined.

[0180] Specifically, if the beam to be merged, b, is merged with the participating beam, b-1, the sequence number of the target merged beam is set to b-1, and the original sequence numbers of the beams in the mMTC slice, b, b+1, ..., B, are changed to b-1, b, ..., B-1; if the beam to be merged, b, is merged with the participating beam, b+1, the sequence number of the merged beam is set to b, and the original sequence numbers of the beams in the mMTC slice, b+2, b+3, ..., B, are changed to b+1, b+2, ..., B-1.

[0181] S444. Determine that the preamble resource configuration parameters in the mMTC slice after beam merging are the second preset value.

[0182] Specifically, the preamble resource configuration parameters within the mMTC slice after beam combining can be set according to requirements. Preferably, η = 0.5, and the number of preambles allocated to the first preamble multiplexing subset with odd-numbered sequences is the same as that allocated to the first preamble multiplexing subset with even-numbered sequences. This ensures that the quality of service requirements in other beams are still met after resource reallocation.

[0183] S450. According to the beam combining configuration parameters, the beam to be combined and the participating beams are beam combined to obtain the target combined beam, and the beam parameters in the mMTC slice are configured to control the total random access capacity of the mMTC slice in the prediction period.

[0184] The technical solution of this invention involves receiving random access signaling from an mMTC device to obtain the number of idle random access opportunities for each beam within the mMTC slice during the current decision period; estimating the random access state estimate for each beam during the prediction period based on the random access configuration information of each beam during the current decision period and the number of idle random access opportunities; if the estimated random access load rate of a beam within the mMTC slice during all random access periods within the decision period is lower than a load rate threshold, then the beam is determined to be a beam to be combined that requires beam combining; and the method is to use the mMTC slice to determine the random access state estimate based on the random access status. The state estimation value determines the beam combining configuration parameters corresponding to the beam to be combined; according to the beam combining configuration parameters, the beam to be combined and the participating beams are beam combined to obtain the target combined beam, and the beam parameters in the mMTC slice are configured to control the total random access capacity of the mMTC slice within the prediction period; when there are few active mMTC devices in the beam, resulting in the preamble in the beam being in a redundant state, beam combining combines the beams with few access mMTC devices into a wide beam, reducing the number of beams, reducing the total random access capacity of the mMTC slice to a level that is compatible with the current random access load, and reducing system overhead.

[0185] Optionally, S441, determining the participating beams for beam merging with the beam to be merged from the adjacent beams based on the estimated total random access load of the beam to be merged and each adjacent beam, and the expected random access success rate after beam merging, includes:

[0186] S4411. Determine the estimated total random access load of the beam to be merged with each adjacent beam.

[0187] Specifically, the random access load estimates of the beam to be merged and the adjacent beams are calculated separately. The random access load estimates of the beam to be merged and one adjacent beam are also calculated separately. It is understood that if there are more than one adjacent beam, the random access load estimates of the beam to be merged and one of the adjacent beams need to be calculated sequentially.

[0188] For example, if the beam to be merged is beam b, then the adjacent beams are beam b-1 and beam b+1. Determine the total random access load estimate of beam b and beam b-1, and the total random access load estimate of beam b and beam b+1.

[0189] S4412. If the estimated total random access load of the beam to be merged with only one of its adjacent beams is less than the random access capacity of the target merged beam, then the adjacent beam is determined as a participating beam in beam merging with the beam to be merged.

[0190] Specifically, beams participating in beam merging must meet the following two conditions: First, they must be adjacent beams to the beam to be merged; second, the estimated total random access load of the beams to be merged must be less than the random access capacity of the target merged beam. or Where Q′ represents the number of RACH Opportunities in the target combined beam obtained after merging beam b and beam b-1; Q″ represents the number of RACH Opportunities in the target combined beam obtained after merging beam b and beam b+1; when η=0.5, Q′=Q″. If the estimated total random access load of the beam to be merged with only one of its adjacent beams is less than the random access capacity of the target combined beam obtained after merging, that is, if only one adjacent beam meets the condition for participating in the beam merging, then that adjacent beam is determined to be the beam participating in the beam merging.

[0191] S4413. If the estimated total random access load of the beam to be merged and the two adjacent beams is less than the random access capacity of the target merged beam, then the beam with the highest expected random access success rate among the two adjacent beams is selected as the participating beam to be merged with the beam to be merged.

[0192] Specifically, if the estimated total random access load of the beam to be merged and its two adjacent beams is less than the random access capacity of the target merged beam, meaning that both adjacent beams of the beam to be merged meet the conditions for participating in the beam merging, then it is necessary to further calculate the expected random access success rate of the beam to be merged and each of its adjacent beams separately. and Where P′ is the expected random access success rate obtained by merging beam b and beam b-1; P″ is the expected random access success rate obtained by merging beam b and beam b+1. The beam with the largest expected random access success rate among two adjacent beams that meet the conditions is selected as the beam to be merged. That is, when P′ > P″, beam b and beam b-1 are merged; otherwise, beam b and beam b+1 are merged.

[0193] This step can estimate the total random access load of the beam to be merged and its adjacent beams, as well as the expected random access success rate after merging. From the adjacent beams of the beam to be merged, the beam with the highest total random access load estimate and the largest expected random access success rate is selected as the beam to participate in the merging process.

[0194] Example 5

[0195] Figure 5 This is a schematic diagram of an access capacity management system provided in Embodiment 5 of the present invention. Figure 5 As shown, the system includes: a signaling receiving module 510, a status estimation module 520, a parameter determination module 530, and a capacity control module 540;

[0196] Among them, the signaling receiving module 510 is used to receive random access signaling sent by the mMTC device and obtain the number of idle random access opportunities for each beam in the mMTC slice during the current decision period.

[0197] The state estimation module 520 is used to estimate the random access state estimate of each beam in the prediction period based on the random access configuration information of each beam in the current decision period and the number of idle random access opportunities through the mMTC slice.

[0198] The parameter determination module 530 is used to determine beam splitting and combining configuration parameters based on the random access state estimation value through the mMTC slice;

[0199] The capacity control module 540 is used to perform beam splitting and combining to obtain the target beam according to the beam splitting and combining configuration parameters, and to configure the beam parameters in the mMTC slice to control the total random access capacity of the mMTC slice within the prediction period; the beam splitting and combining includes: beam splitting and / or beam combining.

[0200] Optionally, the beam splitting and combining configuration parameters include: beam splitting configuration parameters and beam combining configuration parameters;

[0201] The beam splitting configuration parameters include: the original beam number of the beam to be split, the total number of beams, and the preamble resource configuration parameters, as well as the beam splitting update number and beam coverage angle of each beam within the mMTC slice; the total number of beams is the number of all beams contained in the mMTC slice after beam splitting the beam to be split; all beams contained in the mMTC slice after beam splitting include the sub-beams obtained by beam splitting the beam to be split.

[0202] The beam merging configuration parameters include: the original beam number of the beam to be merged, the original beam number of the beams participating in the merging, and the beam merging update number of each beam within the mMTC slice.

[0203] The beam coverage angle and preamble resource configuration parameters of the target beam merging beam;

[0204] The preamble resource configuration parameter is the proportion of preambles allocated to odd-numbered or even-numbered beams within the mMTC slice, and the sum of the proportion of preambles allocated to even-numbered beams and the proportion of preambles allocated to odd-numbered beams is 1.

[0205] Optionally, the capacity control module 540 includes:

[0206] The mapping table update unit is used to update the mapping table of mMTC device and channel angles based on the beam coverage angle included in the beam splitting and combining configuration parameters and the random access load estimate of the mMTC slice.

[0207] The preamble multiplexing unit is used to divide the preamble in the mMTC slice into a first preamble multiplexing subset and a second preamble multiplexing subset according to the preamble resource configuration parameters included in the beam splitting and combining configuration parameters; wherein, the preamble included in the first preamble subset is used for beam multiplexing of odd-numbered sequences, and the preamble included in the second preamble multiplexing subset is used for beam multiplexing of even-numbered sequences.

[0208] Optional, also includes:

[0209] The broadcast module is used to broadcast, after configuring the beam parameters within the mMTC slice, the first preamble multiplexed subset used by the odd-numbered beams within the mMTC slice via the SIB1 beam, and the second preamble multiplexed subset usable by the even-numbered beams within the mMTC slice.

[0210] Optionally, the random access configuration information includes: the number of random access opportunities and the random access capacity; correspondingly, the state estimation module 520 includes:

[0211] For each beam within an mMTC slice, the estimated random access load within the corresponding beam is calculated based on the number of random access opportunities for that beam in each random access period within the current decision period and the number of idle random access opportunities.

[0212] Based on the estimated random access load and the number of random access opportunities, estimate the random access success rate of the corresponding beam in each random access period within the prediction period;

[0213] Based on the random access capacity of the beam in the current decision period and the estimated random access load, estimate the estimated random access load rate of the beam in each random access period within the prediction period.

[0214] Optionally, the parameter determination module 530 includes:

[0215] The beam to be changed determination unit is used to determine the beam to be changed that needs to be split or combined based on the random access state estimate through the mMTC slice;

[0216] The configuration parameter determination unit is used to determine the beam splitting and combining configuration parameters corresponding to the beam to be changed based on the random access state estimation value through the mMTC slice.

[0217] Optionally, the random access state estimate includes: a random access success rate estimate and a random access load rate estimate; correspondingly, the beam determination unit to be changed includes:

[0218] If the estimated random access success rate of a beam within the mMTC slice is lower than the success rate threshold in any random access period within the decision period, then the beam is determined to be a beam to be split.

[0219] If the estimated random access load rate of a beam within the mMTC slice is lower than the load rate threshold in all random access periods within the decision period, then the beam is determined to be a beam to be combined that needs to be beam-combined.

[0220] Optionally, the configuration parameter determining unit includes:

[0221] An angle distribution determination subunit is used to determine the access load angle distribution function for each beam to be split, based on the estimated random access load rate and the mMTC device angle.

[0222] A beam splitting quantity determination subunit is used to determine the total number of beams after beam splitting using the mMTC slice;

[0223] The beam splitting sequence number determination subunit is used to re-determine the beam splitting update sequence number of each beam according to the order of each beam in the mMTC slice after beam splitting.

[0224] The preamble allocation subunit is used to determine the preamble resource configuration parameters in the mMTC slice based on the total number of beams and the beam number of each beam in the mMTC slice after beam splitting.

[0225] A splitting angle determination subunit is used to determine the beam coverage angle of each target splitting beam based on the random access capacity of the sub-beam and the access load angle distribution function; wherein the random access load in each target splitting beam is less than its respective random access capacity; the sum of the beam coverage angles of all the target splitting beams is the beam coverage angle of the beam to be split, and the coverage angle of each target splitting beam is less than the beam coverage angle of the beam to be split, and the coverage angles of each target splitting beam do not overlap.

[0226] Optionally, the division number determining subunit is specifically used for:

[0227] Based on the minimum random access capacity of the mMTC slice and the estimated random access load, the minimum number of beams after beam splitting is determined, so that the random access capacity in each beam of the mMTC slice after beam splitting is greater than the estimated random access load in that beam.

[0228] The maximum number of beams after beam splitting is determined by the ratio of the total beamwidth of the mMTC slice to the minimum achievable beamwidth.

[0229] The total number of beams after beam splitting is determined based on a preset strategy, within the range of values ​​from the minimum number of beams to the maximum number of beams.

[0230] Optionally, the first preamble allocation subunit is specifically used for:

[0231] If the total number of beams is odd, then the maximum value of the preamble resource configuration parameter allocated to the even-numbered beams after beam splitting is η = B. odd -(KB) / cQ; where B odd Where K is the number of beams with odd-numbered indices, K is the estimated random access load of the mMTC slice, and B is the total number of beams in the mMTC slice after beam splitting; c = -ln(P nc ), P nc Q represents the minimum random access success rate for an mMTC device to meet the quality of service requirements within a random access period; Q is the number of random access opportunities for an mMTC slice within a random access period.

[0232] If the total number of beams is even, the preamble resource configuration parameter allocated to the even-numbered beam after beam splitting is the first preset value.

[0233] The sum of the preamble resource configuration parameters allocated to odd-numbered beams and the preamble resource configuration parameters allocated to even-numbered beams is 1.

[0234] Optionally, the configuration parameter determining unit includes:

[0235] The beam merging determination subunit is used to determine, for each beam to be merged, the participating beams for beam merging with the beam to be merged from the adjacent beams, based on the estimated total random access load of the beam to be merged and each adjacent beam, and the expected random access success rate after beam merging.

[0236] The merging angle determination subunit is used to determine the set of the original beam coverage angle of the beam to be merged and the original beam coverage angle of the beams participating in the merging as the beam coverage angle of the target merging beam.

[0237] The merge sequence number determination subunit is used to re-determine the beam merge update sequence number of each beam according to the order of each beam in the mMTC slice after beam merging.

[0238] The merged preamble allocation subunit is used to determine the preamble resource configuration parameters within the mMTC slice after beam merging to a second preset value.

[0239] Optionally, the participating beamforming subunit is specifically used for:

[0240] Determine the estimated total random access load of the beam to be merged with each of its adjacent beams;

[0241] If the estimated total random access load of the beam to be merged with only one of its adjacent beams is less than the random access capacity of the target merged beam, then the adjacent beam is identified as a participating beam in the beam merging process with the beam to be merged.

[0242] If the estimated total random access load of the beam to be merged and its two adjacent beams is less than the random access capacity of the target merged beam, then the beam with the highest expected random access success rate among the two adjacent beams is selected as the participating beam to be merged with the beam to be merged.

[0243] Optionally, the capacity control module is specifically used for:

[0244] The mMTC slice generates a beam splitting / combining request containing the beam splitting / combining configuration parameters; wherein the beam splitting / combining request includes: a beam splitting request or a beam combining request;

[0245] Determine whether to respond to the beam splitting / combining request based on the global load status information within the base station;

[0246] If the beam splitting and combining request is responded to, the beam splitting and combining is performed based on the beam splitting and combining configuration parameters contained in the beam splitting and combining request to generate the target beam, and the beam parameters in the mMTC slice are configured.

[0247] The access capacity management system provided in this embodiment of the invention can execute the access capacity management method based on beam splitting and combining of mMTC slices provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0248] Example 6

[0249] Figure 6 This is a schematic diagram of the structure of a base station provided in Embodiment Six of the present invention, as shown below. Figure 6 As shown, the base station includes a processor 610, a memory 620, an input device 630, an output device 640, and a communication device 650; the number of processors 610 in the base station can be one or more. Figure 6 Taking a processor 610 as an example; the processor 610, memory 620, input device 630, output device 640, and communication device 650 in the base station can be connected via a bus or other means. Figure 6 Taking the example of a connection between China and Israel via a bus.

[0250] The memory 620, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the beam-splitting-based mMTC slice access capacity management method in this embodiment of the invention (e.g., the signaling receiving module 510, state estimation module 520, parameter determination module 530, and capacity control module 540 in the access capacity management system). The processor 610 executes various functional applications and data processing of the device / terminal / server by running the software programs, instructions, and modules stored in the memory 620, thereby realizing the aforementioned beam-splitting-based mMTC slice access capacity management method.

[0251] The memory 620 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a given function; the data storage area may store data created based on terminal usage. Furthermore, the memory 620 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory, or other non-volatile solid-state storage device. In some instances, the memory 620 may further include memory remotely located relative to the processor 610, which can be connected to the device / terminal / server via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0252] Input device 630 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the device / terminal / server. Output device 640 may include display devices such as a screen. Communication device 650 may include signal transceivers such as an antenna.

[0253] Example 7

[0254] Embodiment 7 of the present invention also provides a storage medium containing computer-executable instructions. When executed by a computer processor, the computer-executable instructions are used to execute an access capacity management method for mMTC slices based on beam splitting and combining. The method includes: receiving random access signaling sent by an mMTC device to obtain the number of idle random access opportunities for each beam in the current decision period; estimating the estimated random access state of each beam in the prediction period based on the random access configuration information of each beam in the current decision period and the number of idle random access opportunities through the mMTC slice; determining beam splitting and combining configuration parameters through the mMTC slice based on the estimated random access state; performing beam splitting and combining according to the beam splitting and combining configuration parameters to obtain a target beam, and configuring the beam parameters in the mMTC slice to control the total random access capacity of the mMTC slice in the prediction period.

[0255] Of course, the computer-executable instructions provided in the embodiments of the present invention are not limited to the method operations described above, but can also execute related operations in the access capacity management method based on beam combining and splitting mMTC slices provided in any embodiment of the present invention.

[0256] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0257] It is worth noting that in the above embodiments of the access capacity management system, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0258] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for managing access capacity of mMTC slice based on beam splitting and combining, characterized in that, The method includes: Receive random access signaling sent by mMTC equipment and obtain the number of idle random access opportunities for each beam in the mMTC slice during the current decision period; Based on the random access configuration information of each beam in the current decision period and the number of idle random access opportunities, the mMTC slice is used to estimate the random access state of each beam in the prediction period. The beam splitting and combining configuration parameters are determined by the mMTC slice based on the random access state estimate. The target beam is obtained by beam splitting and combining according to the beam splitting and combining configuration parameters, and the beam parameters in the mMTC slice are configured to control the total random access capacity of the mMTC slice within the prediction period; the beam splitting and combining includes: beam splitting and / or beam combining; the beam includes the Physical Random Access Channel (PRACH) beam; during the beam splitting process, the SSB beam is not split.

2. The method of claim 1, wherein, The beam splitting and combining configuration parameters include: beam splitting configuration parameters and beam combining configuration parameters; The beam splitting configuration parameters include: the original beam number of the beam to be split, the total number of beams and the preamble resource configuration parameters, as well as the beam splitting update number and beam coverage angle of each beam in the mMTC slice. The beam merging configuration parameters include: the original beam number of the beam to be merged, the original beam number of the beams participating in the merging, the beam merging update number of each beam in the mMTC slice, the beam coverage angle of the target beam to be merged, and the preamble resource configuration parameters. Wherein, the total number of beams is the number of all beams contained in the mMTC slice after beam splitting the beam to be split; the total number of beams contained in the mMTC slice after beam splitting includes the target beam obtained by beam splitting the beam to be split. The preamble resource configuration parameter is the proportion of preambles allocated to odd-numbered or even-numbered beams within the mMTC slice, and the sum of the proportion of preambles allocated to even-numbered beams and the proportion of preambles allocated to odd-numbered beams is 1.

3. The method of claim 2, wherein, The configuration of beam parameters within the mMTC slice includes: The mapping table of mMTC device and channel angles is updated based on the beam coverage angle included in the beam splitting and combining configuration parameters and the estimated random access load of the mMTC slice. According to the preamble resource configuration parameters included in the beam splitting and combining configuration parameters, the preamble in the mMTC slice is divided into a first preamble multiplexing subset and a second preamble multiplexing subset; wherein, the preamble included in the first preamble multiplexing subset is used for beam multiplexing of odd-numbered sequences, and the preamble included in the second preamble multiplexing subset is used for beam multiplexing of even-numbered sequences.

4. The method of claim 3, wherein, After configuring the beam parameters within the mMTC slice, the following is also included: The first preamble multiplexed subset used by odd-numbered beams within the mMTC slice is broadcast via the SIB1 beam, and the second preamble multiplexed subset used by even-numbered beams within the mMTC slice is broadcast.

5. The method of claim 1, wherein, The random access configuration information includes: the number of random access opportunities and the random access capacity; correspondingly, estimating the random access state estimate of each beam in the prediction period based on the random access configuration information of each beam in the current decision period and the number of idle random access opportunities through the mMTC slice includes: For each beam within an mMTC slice, the estimated random access load within the corresponding beam is calculated based on the number of random access opportunities for that beam in each random access period within the current decision period and the number of idle random access opportunities. Based on the estimated random access load and the number of random access opportunities, estimate the random access success rate of the corresponding beam in each random access period within the prediction period; Based on the random access capacity of the beam in the current decision period and the estimated random access load, estimate the estimated random access load rate of the beam in each random access period within the prediction period.

6. The method of claim 1, wherein, The step of determining beam splitting and combining configuration parameters based on the random access state estimate using the mMTC slice includes: The mMTC slice is used to determine the beams to be changed that need to be beam splitting or combining based on the random access state estimate. The beam splitting and combining configuration parameters corresponding to the beam to be changed are determined by the mMTC slice based on the random access state estimate.

7. The method of claim 6, wherein, The random access state estimate includes: a random access success rate estimate and a random access load rate estimate; correspondingly, based on the random access state estimate, the beams to be changed that require beam splitting and combining are determined, including: If the estimated random access success rate of a beam within the mMTC slice is lower than the success rate threshold in any random access period within the decision period, then the beam is determined to be a beam to be split. If the estimated random access load rate of a beam within the mMTC slice is lower than the load rate threshold in all random access periods within the decision period, then the beam is determined to be a beam to be combined that needs to be beam-combined.

8. The method of claim 7, wherein, The step of determining the beam splitting and combining configuration parameters corresponding to the beam to be changed based on the random access state estimate includes: For each beam to be split, the access load angle distribution function is determined based on the estimated random access load rate and the mMTC device angle. The total number of beams after beam splitting is determined by the mMTC slice; wherein, the total number of beams is the number of all beams contained in the mMTC slice after beam splitting the beam to be split; all beams contained in the mMTC slice after beam splitting include the target split beam obtained by beam splitting the beam to be split. The beam split update number of each beam is re-determined based on the order of each beam in the mMTC slice after beam splitting. The preamble resource configuration parameters within the mMTC slice are determined based on the total number of beams and the beam number of each beam within the mMTC slice after beam splitting. For each target split beam, the beam coverage angle of the target split beam is determined based on the random access capacity of the target split beam and the access load angle distribution function; wherein, the random access load in each target split beam is less than its respective random access capacity; the sum of the beam coverage angles of all the target split beams is the beam coverage angle of the beam to be split, and the coverage angle of each target split beam is less than the beam coverage angle of the beam to be split, and the coverage angles of each target split beam do not overlap.

9. The method of claim 8, wherein, Determining the total number of beams after beam splitting includes: Based on the minimum random access capacity and the estimated random access load of the mMTC slice, the minimum number of beams after beam splitting is determined, so that the random access capacity of each beam in the mMTC slice after beam splitting is greater than the estimated random access load of that beam. The maximum number of beams after beam splitting is determined by the ratio of the total beamwidth of the mMTC slice to the minimum achievable beamwidth. The total number of beams after beam splitting is determined based on a preset strategy, within the range of values ​​from the minimum number of beams to the maximum number of beams.

10. The method of claim 8, wherein, The step of determining the preamble resource configuration parameters within the mMTC slice based on the total number of beams and the beam number of each beam within the mMTC slice after beam splitting includes: If the total number of beams is odd, then the maximum value of the preamble resource configuration parameter allocated to the even-numbered beams after beam splitting is... ;in, The number of beams with odd-numbered indices. This is the estimated random access load for mMTC slices. The total number of beams within the mMTC slice after beam splitting; , The minimum random access success rate for an mMTC device to meet the quality of service requirements within a random access cycle; The number of random access opportunities for an mMTC slice within a random access period; If the total number of beams is even, the preamble resource configuration parameter allocated to the even-numbered beam after beam splitting is the first preset value. The sum of the preamble resource configuration parameters allocated to odd-numbered beams and the preamble resource configuration parameters allocated to even-numbered beams is 1.

11. The method of claim 7, wherein, The step of determining the beam splitting and combining configuration parameters corresponding to the beam to be changed based on the random access state estimate includes: For each beam to be merged, based on the estimated total random access load of the beam to be merged with each of the adjacent beams and the expected random access success rate after beam merging, the participating beams for beam merging with the beam to be merged are determined from the adjacent beams. The set of the original beam coverage angle of the beam to be merged and the original beam coverage angle of the beams participating in the merging is determined as the beam coverage angle of the target merging beam. The beam merging update number of each beam is re-determined based on the order of each beam in the mMTC slice after beam merging. The preamble resource configuration parameters within the mMTC slice after beam combining are determined to be the second preset value.

12. The method according to claim 11, characterized in that, The step of determining the participating beams for beam merging with the beam to be merged from the adjacent beams based on the estimated total random access load of the beam to be merged and each adjacent beam, and the expected random access success rate after beam merging, includes: Determine the estimated total random access load of the beam to be merged with each adjacent beam; If the estimated total random access load of the beam to be merged with only one of its adjacent beams is less than the random access capacity of the target merged beam, then the adjacent beam is identified as a participating beam in the beam merging process with the beam to be merged. If the estimated total random access load of the beam to be merged and its two adjacent beams is less than the random access capacity of the target merged beam, then the beam with the highest expected random access success rate among the two adjacent beams is selected as the participating beam to be merged with the beam to be merged.

13. The method of claim 1, wherein, The step of obtaining the target beam by beam splitting and combining according to the beam splitting and combining configuration parameters, and configuring the beam parameters within the mMTC slice, includes: The mMTC slice generates a beam splitting / combining request containing the beam splitting / combining configuration parameters; wherein the beam splitting / combining request includes: a beam splitting request or a beam combining request; Determine whether to respond to the beam splitting / combining request based on the global load status information within the base station; If the beam splitting and combining request is responded to, the beam splitting and combining is performed based on the beam splitting and combining configuration parameters contained in the beam splitting and combining request to generate the target beam, and the beam parameters in the mMTC slice are configured.

14. An access capacity management system, characterized by, The system includes: The signaling receiving module is used to receive random access signaling sent by the mMTC device and obtain the number of idle random access opportunities for each beam in the mMTC slice during the current decision period. The state estimation module is used to estimate the random access state of each beam in the prediction period based on the random access configuration information of each beam in the current decision period and the number of idle random access opportunities through the mMTC slice. The parameter determination module is used to determine beam splitting and combining configuration parameters based on the random access state estimate using the mMTC slice; The capacity control module is used to perform beam splitting and combining to obtain the target beam according to the beam splitting and combining configuration parameters, and to configure the beam parameters within the mMTC slice to control the total random access capacity of the mMTC slice within the prediction period; the beam splitting and combining includes: beam splitting and / or beam combining; the beam includes the Physical Random Access Channel (PRACH) beam; during the beam splitting process, the SSB beam is not split.

15. A base station, characterized by The base station is equipped with mMTC slicing and includes: One or more processors; A communication device for communicating with mMTC equipment; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the access capacity management method for mMTC slices based on beam combining and splitting as described in any one of claims 1-13.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the access capacity management method for mMTC slices based on beam combining and splitting as described in any one of claims 1-13.

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