Ultra-dense cell-less massive multiple-input multiple-output control plane initial synchronization method

Abstract

The application provides an initial synchronization method for an ultra-dense cell-free large-scale multiple-input multiple-output control plane, and relates to the technical field of networks. First, different transmission and reception points (TRPs) are assigned with transmission and reception point identifiers (TRP IDs) to replace traditional physical cell identifiers (PCIs). Second, based on the TRP IDs, a synchronization signal allocation problem of a cloud radio access network is converted into a TRP ID allocation problem with preset constraints. Third, the TRP ID allocation problem is converted into a minimum k-partition optimization problem, and the minimum k-partition optimization problem is solved to obtain an optimal TRP ID allocation scheme that satisfies the preset constraints. The application can effectively reduce the strong interference of a broadcast channel of an ultra-dense cell-free large-scale multiple-input multiple-output control plane and improve the initial synchronization access success rate.

Description

Technical Field

[0001] This invention relates to In the field of network technology, this invention relates in particular to an initial synchronization method for an ultra-dense, cell-free, large-scale multiple-input multiple-output control plane. Background Technology

[0002] With the development of mobile communication technology, it is projected that by 2029, the number of mobile subscribers will reach 9.3 billion, and global mobile data traffic is expected to triple to 450 exabytes per month. 5G is also expected to become the mainstream mobile access technology in the near future. As an upgrade to 5G, it is expected to provide network enhancement capabilities in the future, including Peak data rate, 10 per square kilometer 6 -10 8 To achieve ambitious goals such as high connection density per device and latency of 0.1-1ms, ultra-dense, cell-free, massively multi-input multiple-output (MIMO) technology has become a key enabling technology.

[0003] Ultra-dense, cellless, massive MIMO (Multiple-Input Multiple-Output) networks, also known as Cloud Radio Access Networks (CF-MM), consist of numerous Transport Points (TRPs) and users distributed over a large area. While the control plane is crucial for CF-MM, most research focuses on initial access and handover, neglecting the initial synchronization issue. To address this, existing technologies disclose synchronization signals conforming to Long Term Evolution (LTE) and New Radio (NR) standards. LTE, a core technology standard for fourth-generation mobile communication, was developed by the 3rd Generation Partnership Project (3GPP) to improve the speed and efficiency of 3G networks. NR, a radio access technology standard for fifth-generation mobile communication, is also led by 3GPP, supporting more flexible frame structures and higher frequency bands, and optimized for scenarios such as enhanced mobile broadband and ultra-reliable low-latency communication. However, regardless of whether LTE or NR synchronization signals are used, the broadcast channels of ultra-dense, cellless, massive MIMO networks suffer from strong interference, leading to a high initial synchronization failure rate. Summary of the Invention

[0004] To address the problem of high initial synchronization failure rates caused by strong interference in ultra-dense, cellless, large-scale MIMO broadcast channels, this invention proposes an initial synchronization method for the control plane of ultra-dense, cellless, large-scale MIMO broadcast channels. This method can effectively reduce strong interference in ultra-dense, cellless, large-scale MIMO broadcast channels and improve the success rate of initial synchronization access.

[0005] To achieve the above-mentioned technical effects, the technical solution of the present invention is as follows: A method for initial synchronization of a large-scale, cell-free, ultra-dense control plane includes the following steps: S1. Assign Transmission Receiver Point Identifiers (TRP IDs) to different Transmission Receiver Points (TRPs) to replace the traditional Physical Cell Identifier (PCI); S2. Based on the Transmission Receiver Point Identifier (TRP ID), the synchronization signal allocation problem of the cloud wireless access network is transformed into a Transmission Receiver Point Identifier (TRP ID) allocation problem with preset constraints. S3. The Transmission Point Receiving ID (TRP ID) allocation problem is transformed into a minimum k-partition optimization problem. The minimum k-partition optimization problem is solved to obtain the optimal TRP ID allocation scheme that satisfies the preset constraints.

[0006] Preferably, the cloud wireless access network includes a central processing unit and multiple Transmission Receiving Points (TRPs), wherein the number of TRPs is greater than the number of Transmission Receiving Point Identifiers (TRP IDs).

[0007] Preferably, the step of transforming the synchronization signal allocation problem of the cloud wireless access network into a Transmitter Point Receiving Identifier (TRP ID) allocation problem with preset constraints includes: S21. Map the Transmission Receiver Point Identifier (TRP ID) to the synchronization signal of the cloud wireless access network. The synchronization signal includes a primary synchronization signal (PSS) and a secondary synchronization signal. Encapsulate the synchronization signal and the physical broadcast channel in several consecutive symbols to obtain a synchronization signal block. S22. The calculation expression for the Transmission Receiver Point Identifier (TRP ID) is used by the user equipment (UE) to recover the time position of the synchronization signal block as follows:

[0008] in, This represents the value of the Transmission Receiver Point Identifier (TRP ID). This indicates the number of groups into which the Transmission Receiver Point (TRP) is divided. This indicates the first parameter within the transmit / receive point identifier group. This indicates the second parameter within the transmit / receive point identifier group.

[0009] Preferably, the first parameter The location of the demodulation reference signal of the physical broadcast channel is transmitted via the physical broadcast channel. It is determined by the Transmission Receiver Point Identifier (TRP ID).

[0010] Preferably, the preset constraints include: adjacent transmission receiving points (TRPs) must not use the same transmission receiving point identifier (TRP ID); two adjacent transmission receiving points (TRPs) that are the switching targets of the current transmission receiving point (TRP) must not use the same transmission receiving point identifier (TRP ID); and all transmission receiving points (TRPs) participating in joint transmission in the cooperative multi-point transmission mode must not have the same ID.

[0011] Preferably, the step of transforming the Transmitter Receiving Point Identifier (TRP ID) allocation problem into a minimum k-partition optimization problem includes: S31. Constructing a weighted graph for the cloud wireless access network ,in This represents the set of vertices that assign the transmit receive point identifier TRPID. To represent the relationship between Transmitter Points (TRPs), a weighted graph is defined. The first in The vertex is the first vertex in the cloud wireless access network. One Transmitter / Receiver Point (TRP); S32. Determine the location of the demodulation reference signal based on the Transmission / Receive Point Identifier (TRP ID). as follows:

[0012] in, This indicates the remainder calculation; S33. Set the position of the demodulation reference signal. Equivalent to determining the time position of the primary synchronization signal PSS or the secondary synchronization signal SSS, the Transmission Receiving Point Identifier (TRP ID) allocation problem is transformed into a minimum k-partition optimization problem as follows:

[0013] in, Represents the cost function, This indicates taking the minimum value. Represents a weighted graph edge weights, Represents a partition set. Represents the first in the partition set One partition, The first The first Transmitter Receiving Point (TRP) is assigned to the first... Binary variables of each partition, Indicates the location of a certain transmission and reception point Assigned to the Binary variables for each partition.

[0014] Preferably, solving the minimum k-partition optimization problem includes: S41. The minimum k partitioning optimization problem is equivalent to the maximum k cut problem; S42. Transform the maximum k-cut problem into a quadratic unconstrained binary optimization problem; S43. Solve the quadratic unconstrained binary optimization problem using a multi-operator heuristic algorithm and a parameterized local search method to obtain the optimal allocation scheme for the Transmitter Receiving Point Identifier (TRP ID).

[0015] Preferably, the mathematical expression for the maximum k-cut problem is as follows:

[0016] in, This indicates taking the maximum value.

[0017] Preferably, the mathematical expression of the quadratic unconstrained binary optimization problem is as follows:

[0018]

[0019]

[0020] in, P (.) indicates a penalty. Indicates the first The first Transmitter Receiving Point (TRP) is assigned to the first... Binary variables for each partition.

[0021] This invention also proposes an ultra-dense, cell-free, large-scale multiple-input multiple-output control plane initial synchronization system based on the aforementioned method, comprising: The Transmission Receive Point Identifier (TRP) allocation module is used to assign TRP IDs to different Transmission Receive Points (TRPs) to replace the traditional Physical Cell Identifier (PCI). The problem conversion module is used to convert the synchronization signal allocation problem of the cloud wireless access network into a TRP ID allocation problem that performs preset constraints, based on the Transmission Receiver Point Identifier (TRP ID). The solution module is used to transform the Transmission Point Receiving ID (TRP ID) allocation problem into a minimum k-partition optimization problem, solve the minimum k-partition optimization problem, and obtain the optimal TRP ID allocation scheme that satisfies the preset constraints.

[0022] Compared with the prior art, the beneficial effects of the technical solution of the present invention are: This invention proposes an initial synchronization method for the control plane of ultra-dense, cell-free, large-scale MIMO control. First, it assigns Transmission Point Identifiers (TRP IDs) to different Transmission Point Receiving Points (TRPs) to replace the traditional Physical Cell Identifier (PCI). The synchronization signal allocation problem in the cloud radio access network is transformed into a TRP ID allocation problem with preset constraints, achieving a new allocation of synchronization signals. Then, the TRP ID allocation problem is transformed into a k-partition optimization problem to obtain the optimal allocation scheme. This effectively solves the problem of high initial synchronization access failure rate due to strong interference in ultra-dense, cell-free, large-scale MIMO broadcast channels, significantly improving the success rate of initial synchronization access and optimizing system communication performance. Attached Figure Description

[0023] Figure 1 This is a schematic diagram illustrating the initial access process defined by 3GPP in this embodiment of the invention. Figure 2 This diagram illustrates the time and frequency mapping of the primary synchronization signal (PSS) / secondary synchronization signal (SSS) in the Long Term Evolution (LTE) proposed in this embodiment of the invention. Figure 3 This represents the time and frequency mapping diagram of the synchronization signal block in the NR proposed in this embodiment of the invention; Figure 4 This diagram illustrates the configuration of the synchronization signal block burst set in the New Radio (NR) interface proposed in this embodiment of the invention. Figure 5 This diagram illustrates the frequency location of the SSB in the new air interface proposed in this embodiment of the invention. Figure 6 This is a flowchart illustrating an initial synchronization method for a large-scale, cell-free, multi-input multi-output control plane proposed in an embodiment of the present invention. Figure 7 This diagram illustrates the TRP ID conflict principle proposed in this embodiment of the invention. Figure 8 This diagram illustrates the TRP ID obfuscation principle during the UE handover process proposed in this embodiment of the invention. Figure 9 This diagram illustrates the principle of cooperative TRP (Troubleshooting, Propagation, and Recognition) ambiguity cooperative multipoint transmission in the cloud wireless access network proposed in this embodiment of the invention. Figure 10 This diagram illustrates an initial synchronization system block diagram for an ultra-dense, cell-free, large-scale multiple-input multiple-output control plane proposed in this embodiment of the invention. Detailed Implementation

[0024] The accompanying drawings are for illustrative purposes only and should not be construed as limiting the scope of this patent. It is understandable to those skilled in the art that some well-known details may be omitted from the accompanying drawings; To facilitate understanding of this embodiment, the prior art information of this embodiment is first introduced as follows: Recently, CF-MM has attracted widespread attention from researchers. While not a completely new technology, it is based on the fusion of ultra-dense networks (UDN), distributed antenna systems (DAS), massive MIMO, and cooperative multipoint (CoMP), inheriting their advantages such as improved coverage, high spectral efficiency (SE), and enhanced energy efficiency (EE). Previous research has demonstrated the superiority of CF-MM in these aspects. For example, HQ Ngo et al. showed that CF-MM can increase single-user throughput by nearly five times in 95% of possible scenarios compared to small-cell schemes. Furthermore, research has found that CF-MM can more than double radiated energy efficiency while significantly improving single-user throughput. Considering user quality of service (QoS) requirements, CF-MM can improve energy efficiency by an order of magnitude compared to co-located massive MIMO.

[0025] Previous literature has primarily focused on the data plane of ultra-dense CF-MM networks, such as spectral efficiency, energy efficiency, and throughput. In contrast, research on the control plane, including initial access, synchronization, and calibration, has been somewhat insufficient. In fact, statistics from the past three years confirm this concern. According to the IEEE database, over 750 journal articles were published on CF-MM between 2023 and 2005, indicating significant research interest in the field. Based on the ratio of existing research on the data plane to the control plane, approximately 76% of papers focus on the data plane, while only 24% focus on the control plane, suggesting that data plane research dominates in this area. However, in the 3GPP standards, modern wireless networks, such as 4G and 5G / 5G-A, consist of both a data plane and a control plane. This architecture will be inherited by future 6G networks, and CF-MM is a promising technology for 6G; therefore, research on the CF-MM control plane is absolutely essential for next-generation wireless networks.

[0026] Although the control plane is crucial for Cloud Radio Access Networks (CF-MM), there is a lack of literature in this area. Most research focuses on initial access and handover. Chen et al. investigated uplink initial access and interference suppression in CF-MM by utilizing the clustering characteristics of User Equipment (UE). Recent literature in the Communications on Wireless explores previously neglected CF-MM handover characteristics. Specifically, the former aims to extend the traditional handover concept to the more complex Transmitter Receiver Point (TRP) and UE association scenarios in CF-MM, while the latter aims to control the number of handovers in user-centric CF-MM. None of these studies consider the initial synchronization problem in CF-MM.

[0027] Cloud Radio Access Network (CF-MM) was proposed to overcome the shortcomings of ultra-dense networks (UDNs), such as high handover rates and uneven coverage. CF-MM advocates an architecture similar to Distributed Antenna Systems (DAS) and Cooperative Multipoint Transmission (CoMP) to mitigate the inherent boundary effects of cellular-based wireless networks. Generally, CF-MM refers to a network consisting of a large number of Transport Receiver Points (TRPs) and users distributed over a large area. Wu Hanqiang et al. introduced a typical CF-MM, which consists of a central processing unit and a large number of distributed TRPs. All TRPs share the same cell. For each user, the TRP transmits coherent data to that user. This is similar to scenario 4 of CoMP, except that CF-MM has more distributed TRPs.

[0028] Similar to DAS and CoMP, all TRPs in CF-MM belong to the same physical cell, and its primary goal is to eliminate cell edges, thus providing more uniform coverage. In fact, these characteristics are based on the fact that all TRPs share the same cell identifier, namely the Physical Cell Identifier (PCI). When all TRPs in CF-MM share the same PCI, this poses a significant challenge to user network access, and the situation is even worse for ultra-dense CF-MM because TRPs are deployed densely and widely. To understand this problem, we first describe the function of the PCI in current wireless networks.

[0029] Whether in Long Term Evolution (LTE) or New Radio (NR), PCI is a crucial system parameter. In current wireless networks, the cell broadcasts the PCI to all UEs. Only after a UE receives this parameter can it access the network. standard, Closely related to the initial synchronization signals are the primary synchronization signal (PSS) and secondary synchronization signal (SSS). Based on the above analysis, TRPs in CF-MM share the same PCI; therefore, their PSS / SSS are also identical. As a result, all TRPs broadcasting the same synchronization signal causes strong interference in the broadcast channel. When the interference exceeds a threshold, the UE's synchronization success rate will drop to zero, and the UE will then be unable to access the network.

[0030] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0031] Example 1 To illustrate in more detail the proposed method for initial synchronization of the ultra-dense, cell-free, massive MIMO control plane in this embodiment, we first analyze the incompatibility challenges between NR / LTE initial synchronization and CF-MM. To understand the incompatibility between the LTE / NR standard and CF-MM, and why this issue warrants further investigation, we first briefly describe the overall picture of the initial access process. Then, we will delve deeper into the details of the LTE / NR initial synchronization process to explain this problem. This will help us identify the root cause of the problem and then provide a suitable solution.

[0032] According to 3GPP standards, a UE must perform certain steps before it can receive and transmit data. These steps include cell search / reselection, receiving system information, and random access. The complete process is called LTE / NR initial access, such as... Figure 1 As shown, a brief description is as follows: Cell search and selection: User equipment (UE) detects physical signals and channels to select a cell.

[0033] System Information Reception: User Equipment (UE) Configuration Channels and map them to The above is used to receive the Master Information Block (MIB).

[0034] Random access: User equipment (UE) establishes uplink synchronization and obtains a specific identifier for radio access communication.

[0035] The first step involves the User Equipment (UE) attempting to find an acceptable cell for any Public Land Mobile Network (PLMN) by searching all supported frequencies. This step includes a series of synchronization phases, also known as initial synchronization, through which the UE determines time and frequency parameters. These parameters are crucial for the UE to demodulate the downlink and transmit uplink signals in the correct timing.

[0036] In Long Term Evolution (LTE) or New Radio (NR), the initial synchronization signal is strictly associated with a physical cell, which is represented by the Physical Cell Identifier (PCI), defined as follows:

[0037] in These are the physical layer cell identifier group and the physical layer identifier within the physical layer cell identifier group. In fact... It is a sector ,for And New Radio (NR), The value is defined as follows:

[0038] As shown in equation (1), if we want to obtain the physical cell identifier (PCI) of a base station, we must obtain... and For Long Term Evolution (LTE) / New Radio (NR), these two parameters are closely related to the synchronization signals, namely the Primary Synchronization Signal (PSS) and the Secondary Synchronization Signal (SSS). Since the generation methods of the PSS and SSS differ between LTE and NR, we will explain them in detail separately.

[0039] For the Primary Synchronization Signal (PSS) and Secondary Synchronization Signal (SSS) in Long Term Evolution (LTE), the Primary Synchronization Signal (PSS) is defined as follows: The following sequence is generated from the frequency domain Zadoff-Chu (ZC) sequence:

[0040] in yes The root sequence index is given in Table I.

[0041] Table I: Root Sequence Index of Master Synchronization Signals

[0042] The 62-length secondary synchronization signal (SSS) is an interleaved concatenation of two 31-length M-sequences, referred to here as SSS1 and SSS2, which differ between subframe 0 and subframe 5.

[0043] (4) in superscript and It is based on the following rules from the Physical Cell Identifier (PCI) The first parameter was derived.

[0044]

[0045]

[0046]

[0047] In equations (3) and (4), and Defined as an M sequence The two different cyclic shifts are as follows:

[0048]

[0049] in ,here Defined as

[0050] Initial conditions are .

[0051] In Frequency Division Duplex (FDD) mode, the primary synchronization signal (PSS) is transmitted in the last symbol of time slots 0 and 10, while the secondary synchronization signal (SSS) is transmitted one symbol earlier.

[0052] In Time Division Duplex (TDD) mode, the PSS is transmitted in the third symbol of time slots 2 and 12, while the SSS is transmitted three symbols earlier. In the frequency domain, the base station maps the synchronization signal onto 63 subcarriers symmetrically arranged around the DC carrier, and punches holes in the middle elements, such as... Figure 2 As shown.

[0053] Based on the above description, initial synchronization helps the user equipment (UE) obtain basic orthogonal frequency division multiplexing (OFDM) system parameters, namely symbol and frame timing, carrier frequency and sampling clock, which are obtained by demodulating synchronization signals (i.e. PSS and SSS).

[0054] First, UE blindly demodulates PSS. At this point, we can obtain... However, we cannot determine the frame timing because the PSS is sent in both the first and second halves of a frame. Secondly, it can demodulate the SSS from a specific location, and then, based on the SSS sequence, determine the current subframe time, since the SSS sequences for subframe 0 and subframe 5 are different. This also helps us obtain... After demodulating PSS and SSS, we can calculate PCI according to equation (1).

[0055] For Cloud Radio Access Network (CF-MM) networks using similar LTE synchronization signals, due to Equations (2), (3), and (4), different Transmitter Receivers (TRPs) have the same PCI, resulting in identical PSS and SSS sequences. Furthermore, for LTE, these TRPs will transmit PSS and SSS on the same Radio Resource Block (RB), thus their synchronization signals will interfere with each other. Due to the large number of TRPs, this interference is stronger and more pronounced in CF-MM networks.

[0056] Conclusion: Since the TRPs in CF-MM have the same PCI, if the same synchronization process as LTE is used in CF-MM, then the synchronization signal interference between different TRPs will inevitably be very strong.

[0057] Similarly, for PSS and SSS in New Radio (NR), we will first briefly introduce the synchronization signal in NR, and then analyze the challenges of using it in cell-free massive multiple-input multiple-output (MIMO) systems. NR's PSS It is generated based on an M-sequence of length 127, which is defined as follows:

[0058]

[0059]

[0060] in The initial conditions are:

[0061] New Radio (NR) Secondary Synchronization Signal (SSS) Defined as:

[0062]

[0063]

[0064]

[0065]

[0066] in

[0067]

[0068] The initial conditions are:

[0069]

[0070] From equations (8) and (9), it can be seen that the master synchronization signal (PSS) sequence The sector ID is determined by the Physical Cell Identifier (PCI), while the Secondary Synchronization Signal (SSS) is determined by the PCI group number. and sector ID The decision is made jointly. Although the formula for New Radio (NR) is different from that for Long Term Evolution (LTE), PSS / SSS and PCI are mapped one-to-one, meaning that when the PCI of two cells is the same, the PSS / SSS sequence is also the same.

[0071] Although different Transmitter-Receiver Points (TRPs) use the same synchronization signal, they will not interfere with each other if they are transmitted in different time-frequency domains. The problem is that the time-frequency of the synchronization signal is highly dependent on the PCI, so different TRPs have no choice but to transmit PSS / SSS on the same time-frequency resource. We will describe this process in detail below.

[0072] To improve the efficiency of the User Equipment (UE) synchronization process, in the New Radio (NR) interface, the PSS / SSS and Physical Broadcast Channel (PBCH) are encapsulated in four consecutive symbols, called a Synchronization Signal Block (SSB), such as... Figure 3 As shown. In the frequency domain, the PSS and SSS are mapped to 127 consecutive subcarriers. For the SSS, there are 8 unused subcarriers below it and 9 unused subcarriers above it. In the time domain, the PSS and SSS are transmitted in the first and third symbols, respectively. The PBCH occupies two full Orthogonal Frequency Division Multiplexing (OFDM) symbols, namely the second and fourth symbols, spanning 240 subcarriers. In the third OFDM symbol, the SSS spans 48 subcarriers above and below it. The demodulation reference signal (DMRS) of the PBCH occupies 144 resource elements (REs), with the remainder used for the PBCH payload. The frequency position of the PBCH DMRS depends on the PCI, i.e., the DMRS Position via PCI Mod 4 is obtained.

[0073] Base station (BS) periodically Most broadcast A set of SSBs. Here It is related to frequency, and its value can be 4, 6, or 8. It can be 5, 10 (default), 20, 40, 80, and The transmission of SSBs within a Synchronization Signal Burst Set (SS Burst Set) is limited to one. Inside the window, such as Figure 4 As shown.

[0074] In summary, if different TRPs use the same synchronization signal and choose to send the maximum number of synchronization signals, synchronization signal conflicts will occur in the time domain.

[0075] Regarding the frequency domain, such as Figure 5 As shown, the frequency position of the SSB is determined by the parameter absolute frequency SSB, which represents the center frequency of the SSB block. According to reference

[22] , this parameter is used for the serving cell, which means that the parameter remains unchanged when the serving cell remains unchanged. For co-site multipoint (CF-MM), all TRPs belong to the same cell, that is, the same serving cell with a unique PCI. All TRPs have the same absolute frequency SSB, so different TRPs transmit their synchronization signals on the same frequency resources.

[0076] Conclusion: Similarly, if NR-like synchronization signals are used in CF-MM (Cooperative Full Spectrum Multiple Connections), then different TRPs (Transmitter Points to Receive) will use the same synchronization sequence in the same time-frequency domain, meaning that PSS (Primary Synchronization Signal) / SSS (Secondary Synchronization Signal) from different TRPs will interfere with each other.

[0077] Our goal is to design a novel synchronization scheme, specifically a method for initial synchronization of ultra-dense, cell-free, large-scale MIMO control planes. (See [link to relevant documentation]). Figure 6 This includes the following steps: S1. Assign Transmission Receiver Point Identifiers (TRP IDs) to different Transmission Receiver Points (TRPs) to replace the traditional Physical Cell Identifier (PCI); S2. Based on the Transmission Receiver Point Identifier (TRP ID), the synchronization signal allocation problem of the cloud wireless access network is transformed into a Transmission Receiver Point Identifier (TRP ID) allocation problem that executes preset constraints; the cloud wireless access network includes a central processing unit and multiple Transmission Receiver Points (TRPs), and the number of Transmission Receiver Points (TRPs) is greater than the number of Transmission Receiver Point Identifiers (TRP IDs). S3. The Transmission Point Receiving ID (TRP ID) allocation problem is transformed into a minimum k-partition optimization problem. The minimum k-partition optimization problem is solved to obtain the optimal TRP ID allocation scheme that satisfies the preset constraints.

[0078] This approach must ensure that CF-MM is compatible with the current NR standard, while also considering future compatibility. Evolution of Requirements. Based on the above analysis, if NR synchronization signals are to be used in CF-MM, a feasible method is to have different TRPs broadcast their respective PSS / SSS at different times, that is, one TRP broadcasts its PSS / SSS in each cycle. Send a PSS / SSS once. Because transmitting these signals has... With each degree of freedom, the challenge lies in determining the optimal time slot for each TRP within each cycle to minimize interference. Solving this problem requires considering the actual deployment scenario and ensuring that timing and allocation strategies effectively reduce interference while adapting to different network configurations.

[0079] exist In the network, Physical Cell Identifiers (PCIs) are assigned based on a predefined set provided by Operations and Maintenance (OAM). In practice, PCI allocation follows a specific scenario; once assigned, each cell broadcasts its synchronization signal using the assigned PCI. However, in the CF-MM architecture, there are no traditional cells, and the TRP ID serves an equivalent function to the PCI. Therefore, we recommend using the TRP ID instead of the PCI and assigning PSS / SSS to each TRP based on its TRP ID. It's important to note that this is not simply a replacement; the differences will soon become apparent.

[0080] A key question arises: how to transmit the TRP ID to the UE (User Equipment)? Given that the PCI is communicated to the UE via PSS / SSS, we transform the synchronization signal allocation problem of the cloud radio access network into a Transmission Point Identifier (TRP ID) allocation problem that executes preset constraints, including: S21. Map the Transmission Receiver Point Identifier (TRP ID) to the synchronization signal of the cloud wireless access network. The synchronization signal includes a primary synchronization signal (PSS) and a secondary synchronization signal. Encapsulate the synchronization signal and the physical broadcast channel in several consecutive symbols to obtain a synchronization signal block. S22. The calculation expression for the Transmission Receiver Point Identifier (TRP ID) is used by the user equipment (UE) to recover the time position of the synchronization signal block as follows: (11) in, This represents the value of the Transmission Receiver Point Identifier (TRP ID). This indicates the number of groups into which the Transmission Receiver Point (TRP) is divided. This indicates the first parameter within the transmit / receive point identifier group. This represents the second parameter within the transmit / receive point identifier group. For the first parameter... Second parameter We designed the following signaling to carry them: for It can be explicitly determined by the SSB time position (i.e., the SSB index). Therefore, if the UE decodes the SSB index, then this parameter is determined.

[0081] Another parameter It can be transmitted via the PBCH (Physical Broadcast Channel). For the current... The PBCH payload has an input bit sequence length of 32 and an output encoded bit sequence length of 864. The PBCH payload uses polar coding. According to the polar coding process, we can add up to 9 bits to the input bit sequence without extending the total output encoded bit sequence length; therefore, the encoded bit sequence is also 864. It can be equivalent to 512.

[0082] Due to the first parameter For transmission via the physical broadcast channel, we also recommend using the TRP ID instead of PCI in CF-MM to determine the location of the DMRS (demodulation reference signal) of the PBCH. ,Location The location of the DMRS is determined by the PCI, specifically PCI modulo 4. However, in CF-MM, all TRPs share the same PCI, making interference between different TRPs unavoidable. Therefore, we recommend using the TRP ID to determine the location of the DMRS. This is a suitable alternative to CF-MM. By utilizing the above approach, we can ensure that both PCI and TRP IDs can be transmitted to the UE in a compatible manner using traditional NR procedures.

[0083] Based on the above analysis, the number of TRP IDs (Transmitter Receiver Identifiers) is limited to approximately 4096, while the number of TRPs deployed in a Cloud Radio Access Network (CF-MM) is much greater. Therefore, it is inevitable that different TRPs will reuse the same TRP ID. In practice, we need to consider some pre-defined constraints.

[0084] The preset constraints include: adjacent Transmission Receiver Points (TRPs) must not use the same Transmission Receiver Point Identifier (TRP ID); two adjacent Transmission Receiver Points (TRPs) that are the switching targets of the current Transmission Receiver Point (TRP) must not use the same Transmission Receiver Identifier (TRP ID); and all Transmission Receiver Points (TRPs) participating in joint transmission in cooperative multipoint transmission mode must not have the same ID.

[0085] First, we should avoid adjacent TRPs using the same ID, as this can lead to TRP conflicts, such as... Figure 7As shown. When this happens, the User Equipment (UE) cannot access the network because it cannot distinguish from which access point its initial access began. Secondly, we should also avoid two adjacent handover target TRPs using the same ID or having... Figure 8 The same modulus value is shown. When this happens, the mobile UE will experience TRP handover problems simply because it cannot determine its handover target during the handover process, which will lead to TRP handover failure and dropped calls in the overlapping area. We realize that TRP conflicts and confusion are similar to the Physical Cell Identifier (PCI) allocation problem; however, TRP IDs and PCIs have different functions and constraints. Finally, we should consider the constraints of Cooperative Multipoint Transmission (CoMP) mode [6]. In CoMP mode, all TRPs participating in joint transmission should have different IDs; otherwise, the UE cannot distinguish between different measurement reports, such as Channel State Information (CSI) measurements. These TRPs are called CoMP sets. Figure 9 As shown, two TRPs participate in the joint transmission. However, for traditional CF-MM, all TRPs can participate in the cooperative transmission. However, in practice, due to the bandwidth limitation of the fronthaul link, it is very challenging to have all TRPs participate in the cooperative joint transmission. Therefore, we believe that the number of TRPs in a CoMP set is limited, such as 3 or 4.

[0086] In summary, the synchronization signal design for Cloud Radio Access Network (CF-MM) is transformed into a TRP ID allocation problem. Our goal for this problem is to minimize synchronization signal interference, and furthermore, to avoid demodulation reference signal (DMRS) collisions, TRP ID collisions, handover ambiguity, and CoMP ambiguity on the Physical Broadcast Channel (PBCH). Considering all these pre-existing constraints, we first establish a mathematical model and then design an efficient solution to allocate IDs to all TRPs in CF-MM.

[0087] We have designed a mathematical model for synchronization signals in Cloud Radio Access Network (CF-MM). The entire network consists of a central processing unit (CPU) and... It consists of 1 TRP, and the maximum number of usable TRP IDs is 1. We believe the number of TRPs is greater than the number of available IDs, i.e. It is worth noting that this aligns with actual deployment scenarios. In practice, a typical wireless network service area has approximately 10,000 base stations, and when the same area is served by CF-MM, the number of TRPs exceeds 10,000, which is far greater than the maximum number of available TRP IDs.

[0088] The process of transforming the Transmitter Receiving Point Identifier (TRP ID) allocation problem into a minimum k-partition optimization problem includes: S31. Constructing a weighted graph for the cloud wireless access network ,in This represents the set of vertices that assign the transmit receive point identifier TRPID. To represent the relationship between Transmitter Points (TRPs), a weighted graph is defined. The first in The vertex is the first vertex in the cloud wireless access network. One Transmitter / Receiver Point (TRP); In S31, the topology of the Cloud Radio Access Network (CF-MM) is modeled as a weighted graph, using... This indicates that the vertex set Represents the allocation of TRP IDs, edge sets This represents the relationship between TRPs. Since the total number of TRPs is... ,but Diagram Vertex in TRP in CF-MM Because we want to assign IDs to different TRPs based on (11), that is, the TRPs are divided into Groups. We use sets. Representing each group, therefore we have TRPs in different groups have different modulus values, so synchronization interference between them is negligible. However, for TRPs within the same group, the primary synchronization signal (PSS) / secondary synchronization signal (SSS) are the same for different TRPs because they have the same TRP ID, thus synchronization interference exists between these TRPs. To improve the synchronization success rate, we should minimize the synchronization interference between different TRPs; this is our design goal. Defined as a partition set, Defined as a Transmitter-Receiver Point (TRP) Transmitter-Receiver Point (TRP) Synchronization interference between them, which is also the diagram The edge weights. For each vertex and each partition Define binary variables If the Transmitter-Receiver Point (TRP) Assigned to partition If the value is 1, then the variable is 1; otherwise, it is 1. 0.

[0089] S32. Determine the location of the demodulation reference signal based on the Transmission / Receive Point Identifier (TRP ID). as follows: (12) in, This indicates the remainder calculation; when At that time, the demodulation reference signal (DMRS) position This is equivalent to determining the timing of the primary synchronization signal (PSS) / secondary synchronization signal (SSS). Therefore, the demodulation reference signal (DMRS) collision problem is equivalent to the synchronization interference problem. Thus, the transmit receiver point (TRP) ID allocation problem can be transformed into a minimum k-partition optimization problem as follows: (13a) in, This represents the cost function, used to represent the total interference between different groups. This indicates taking the minimum value. Represents a weighted graph edge weights, Represents a partition set. Represents the first in the partition set One partition, The first The first Transmitter Receiver (TRP) is assigned to the first... Binary variables of each partition, Indicates the location of a certain transmission and reception point Assigned to the Binary variables for each partition.

[0090] Solving the minimum k-partition optimization problem includes: S41. The minimum k partitioning optimization problem is equivalent to the maximum k cut problem; In S41, the physical meaning of the maximum k-cut problem is to maximize the interference between different Transmitter-Receiver Point (TRP) groups. Since the primary synchronization signal (PSS) / secondary synchronization signal (SSS) used in different TRP groups are orthogonal in the code domain, the interference is very low.

[0091] Since the maximum k-cut problem has a fast and efficient solution, we transform the problem into an equivalent maximum k-cut problem expressed using binary quadratic optimization (BQO). This maximum k-cut problem is then transformed into a quadratic unconstrained binary optimization problem, specifically including:

[0092]

[0093]

[0094]

[0095] (14d)

[0096] Where (14b), (14c), and (14d) are constraints for avoiding Transmission Receiver Point (TRP) ID conflicts, handover confusion, and coordination confusion, respectively. Represents a set of adjacent cells. Indicates the set of cells to be switched. This indicates a collaborative collection of multiple community points.

[0097] When the number of partitions is greater than 2 (i.e.) 2) It has been proven that the minimum k partitioning (MkP) problem and the maximum k-cut (Max-k-cut) problem are both problems in combinatorial optimization. Difficult problem. It is useful to transform problem (14) into an unconstrained problem. The equivalent penalty term corresponding to (14b) or (14c) is:

[0098] in Since it is a positive scalar, then problem (14) can be rewritten as follows:

[0099]

[0100] (16b)

[0101] Similarly, the equivalent penalty term corresponding to (16b) is

[0102] So problem (16) becomes:

[0103]

[0104]

[0105]

[0106] Constraint (18b) can be viewed as a linear equation, with the corresponding penalty term being:

[0107] Finally, problem (18) is equivalent to the following unconstrained form:

[0108]

[0109]

[0110] Now, the original problem (14) with constraints is transformed into a quadratic unconstrained binary optimization (QUBO) problem. Although readily available software (such as Gurobi or Matlab) can be used to solve the quadratic unconstrained binary optimization (QUBO) problem, we cannot easily use these commercial software to solve the problem (20) because the problem under consideration is very complex, with more than 10,000 vertices.

[0111] S43. Solve the quadratic unconstrained binary optimization problem using a multi-operator heuristic algorithm and a parameterized local search method to obtain the optimal allocation scheme for the Transmitter Receiving Point Identifier (TRP ID).

[0112] The algorithm proposed in S43 consists of two parts, as shown in Table II. The first part consists of the steps in Table II. The first part, based on the Multi-Objective Heuristic (MOH) algorithm, aims to find a better suboptimal solution. The second part, the final step (step 5 in Table II), is based on the Parametric Local Search Maximum k-Cut (PLS) algorithm. It can be viewed as a post-processing method to obtain a better solution. Its task is to find the maximum k-cut that modulates the solution. A better solution for partitioning vertices (actually) If such a partition exists, then the given partition is c-optimal; otherwise, c-optimal. In the following sections, we will see that the proposed method optimally solves the problem under consideration.

[0113] Table II presents the proposed algorithms for solving the TRP ID partitioning problem in CF-MM (Collaborative Fog Computing-Mobile Edge Computing).

[0114] In this embodiment, firstly, a Transmission Point Identifier (TRP ID) is assigned to different Transmission Point Receiving Points (TRPs) to replace the traditional Physical Cell Identifier (PCI). The synchronization signal allocation problem of the cloud radio access network is transformed into a TRP ID allocation problem with preset constraints, thus realizing a new allocation of synchronization signals. Then, the TRP ID allocation problem is transformed into a k-partition optimization problem to obtain the optimal allocation scheme. This effectively solves the problem of high initial synchronization access failure rate caused by strong interference in ultra-dense, cellless, large-scale MIMO broadcast channels, significantly improving the success rate of initial synchronization access and optimizing system communication performance.

[0115] Example 2 This embodiment simulates and verifies the ultra-dense, cell-free, large-scale MIMO control plane initial synchronization method described in the previous embodiment. In our simulation, we used the OpenCellID dataset. This dataset provides key information for each cell, such as longitude, latitude, cell ID, and Mobile Country Code (MCC). Specifically, in our simulation, we used LTE and NR cell data from a certain port region, with an MCC of 454. The maximum transmit power per Transmitter-Receiver Point (TRP) was set to 40 dBm. The total number of cells in the port region is approximately 10,000, and the minimum distance between cells is approximately 100 meters. We adopted a multi-slope path loss model.

[0116] In our simulation, each cell represents a transmit-receive point (TRP) in CF-MM. We compared the performance of the proposed method with that of the Quadratic Unconstrained Binary Optimization (QUBO) method and the tabu search method. As mentioned above, the proposed method... This study combines the methods with the Local Parametric Search (PLS) method. To evaluate these methods, we selected four representative cases representing different areas of a port. The area sizes of these cases range from small to large, including a street, an administrative district, an island, and finally, the entire city. Specifically, the smallest area is a street, served by approximately 200 transmit / receive points, while coverage of an administrative district requires approximately 1000 transmit / receive points. An island is served by approximately 2000 transmit / receive points, and the entire city, encompassing the four areas, is covered by 10,000 transmit / receive points.

[0117] The overall performance of different methods is shown in Table III. For cases with a small number of transmitters (TRPs), such as 200 or 1000, we can observe that if interference (i.e., duality) occurs... The value of is the most important metric, so the proposed method, MOH + PLS (Multi-Objective Heuristic Algorithm + Path Reconnection Algorithm), achieves the best results. Table III shows that tabu search takes less time to find a suitable solution; however, it also violates some constraints when the TRP number is 1000. As a compromise, MOH (Multi-Objective Heuristic Algorithm) is a good choice because its results are good enough and its time consumption is not too high. The PLS (Path Reconnection Algorithm) method can improve... Solution for a large number of TRPs. When the number of TRPs is large, the simulation time of the BUBO algorithm is very long, for example, more than a day. Therefore, when the number of TRPs is greater than 2000, it is not a suitable method to solve the problem under consideration. So detailed results on this method are not meaningful and we do not provide these results in this table.

[0118] Table III. Performance Comparison of Different Methods

[0119] Secondly, we present the convergence behavior of the proposed method and previous methods. As shown in Table IV, the convergence speed is faster when the number of vertices is small, and the proposed method can obtain the optimal solution because... The value is the same as that obtained by integer linear programming (ILP)

[31] . This verifies the optimality of the MOH solution in the case of low TRP.

[0120] Table IV. Performance Comparison of Different Methods When the Number of Temporary Reference Points (TRPs) is 200

[0121] Next, we demonstrate the performance of different methods when the number of TRPs (transmitter-receiver points) is large (e.g., 10,000), as shown in Table V. For a large number of TRPs, finding a solution to the integer linear programming (ILP) problem in a finite time is infeasible; therefore, we use an upper bound to verify the effectiveness of the proposed method. As shown in Table III, the optimal solutions obtained by MOH and MOH + PLS are 1330493 and 1337145, respectively. The difference between these values ​​and the upper bound (1350516) is approximately... This indicates The difference between the final solution and the optimal solution is less than 2%. For the sake of brevity, we have not shown the results for other cases.

[0122] Table V. Performance Comparison of Different Methods When the Number of TRPs (Transmitter Points) is 2000

[0123] In our final analysis, we compared the synchronization success rates of various methods. Table VI shows that the synchronization success rate is very low, below 30%, leading to poor initial access rates and a poor user experience. Therefore, it is clear that NR (New Radio) type synchronization signals are not suitable for CF-MM (Cellular Non-Mobile Multi-Input Multi-Output) networks without significant modifications. In the results of Tabu Search and MOH & PLS, the synchronization signal is based on the design proposed in Section 3. For scenarios involving 10,000 TRPs (Transmitter-Receiver Points), Table VI highlights that our proposed method outperforms the others, thus validating its effectiveness in enhancing initial synchronization in CF-MM networks.

[0124] Table VI Synchronization Rate of Different Methods When the Number of TRPs (Transmitter Points) is 10000

[0125] In this embodiment, we investigate the initial synchronization problem in the control plane of a CF-MM (Cellular Massive MIMO) network. Existing LTE and NR synchronization signals are not suitable for CF-MM deployments. To address this issue, we first propose a novel synchronization signal specifically designed for CF-MM. Then, we reformulate the synchronization problem as a TRP (Transmitter-Receiver Point) ID allocation problem. Finally, we solve this problem by integrating the MOH and PLS methods. Simulation results show that when the number of TRPs is small, the proposed method achieves near-optimal performance, with the solution deviating from the optimal value by less than [value missing]. In future work, we aim to improve the scalability of this method in scenarios with TRPs exceeding 10,000. Furthermore, we plan to leverage the proposed method and... Technological advancements are shaping the future. Develop an optimized synchronization program for the network.

[0126] Example 3 See Figure 10 This embodiment also proposes an ultra-dense, cell-free, large-scale multiple-input multiple-output control plane initial synchronization system based on the method described in the above embodiments, comprising: The Transmission Receive Point Identifier (TRP) allocation module is used to assign TRP IDs to different Transmission Receive Points (TRPs) to replace the traditional Physical Cell Identifier (PCI). The problem conversion module is used to convert the synchronization signal allocation problem of the cloud wireless access network into a TRP ID allocation problem that performs preset constraints, based on the Transmission Receiver Point Identifier (TRP ID). The solution module is used to transform the Transmission Point Receiving ID (TRP ID) allocation problem into a minimum k-partition optimization problem, solve the minimum k-partition optimization problem, and obtain the optimal TRP ID allocation scheme that satisfies the preset constraints.

[0127] In this embodiment, firstly, a Transmission Point Identifier (TRP ID) is assigned to different Transmission Point Receiving Points (TRPs) to replace the traditional Physical Cell Identifier (PCI). The synchronization signal allocation problem of the cloud radio access network is transformed into a TRP ID allocation problem with preset constraints, thus realizing a new allocation of synchronization signals. Then, the TRP ID allocation problem is transformed into a k-partition optimization problem to obtain the optimal allocation scheme. This effectively solves the problem of high initial synchronization access failure rate caused by strong interference in ultra-dense, cellless, large-scale MIMO broadcast channels, significantly improving the success rate of initial synchronization access and optimizing system communication performance.

[0128] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art can make other variations or modifications based on the above description. It is neither necessary nor possible to exhaustively describe all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A method for initial synchronization of a large-scale, cell-free, ultra-dense control plane, characterized in that: Includes the following steps: S1. Assign Transmission Receiver Point Identifiers (TRP IDs) to different Transmission Receiver Points (TRPs) to replace the traditional Physical Cell Identifier (PCI); S2. Based on the Transmission Receiver Point Identifier (TRP ID), the synchronization signal allocation problem of the cloud wireless access network is transformed into a Transmission Receiver Point Identifier (TRP ID) allocation problem with preset constraints. S3. The Transmission Point Receiving Point Identifier (TRP ID) allocation problem is transformed into a minimum k-partition optimization problem. The minimum k-partition optimization problem is solved to obtain the optimal allocation scheme of Transmission Point Receiving Point Identifier (TRP ID) that satisfies the preset constraints. The process of transforming the Transmitter Receiving Point Identifier (TRP ID) allocation problem into a minimum k-partition optimization problem includes: S31. Constructing a weighted graph for the cloud wireless access network ,in The set of vertices that represents the Transmitter Receiver Point Identifier (TRP ID) assigned to them. To represent the relationship between Transmitter Points (TRPs), a weighted graph is defined. The first in The vertex is the first vertex in the cloud wireless access network. One Transmitter / Receiver Point (TRP); S32. Determine the location of the demodulation reference signal based on the Transmission / Receive Point Identifier (TRP ID). as follows: in, This represents the value of the Transmission Receiver Point Identifier (TRP ID). This indicates the remainder calculation; S33. Set the position of the demodulation reference signal. Equivalent to determining the time position of the primary synchronization signal PSS or the secondary synchronization signal SSS, the Transmission Receiving Point Identifier (TRP ID) allocation problem is transformed into a minimum k-partition optimization problem as follows: in, Represents the cost function, This indicates taking the minimum value. Represents a weighted graph edge weights, Represents a partition set. Represents the first in the partition set One partition, The first The first Transmitter Receiver (TRP) is assigned to the first... Binary variables of each partition, Indicates the location of a certain transmission and reception point Assigned to the Binary variables for each partition; Solving the minimum k-partition optimization problem includes: S41. The minimum k partitioning optimization problem is equivalent to the maximum k cut problem; S42. Transform the maximum k-cut problem into a quadratic unconstrained binary optimization problem; S43. Solve the quadratic unconstrained binary optimization problem using a multi-operator heuristic algorithm and a parameterized local search method to obtain the optimal allocation scheme for the Transmission Receiving Point Identifier (TRP ID); The mathematical expression for the maximum k-cut problem is as follows: in, This indicates taking the maximum value.

2. The method for initial synchronization of ultra-dense, cell-free, large-scale multiple-input multiple-output control planes according to claim 1, characterized in that, The cloud wireless access network includes a central processing unit and multiple Transmission Receiver Points (TRPs), the number of which is greater than the number of Transmission Receiver Point Identifiers (TRP IDs).

3. The method for initial synchronization of ultra-dense, cell-free, large-scale multiple-input multiple-output control planes according to claim 1, characterized in that, The process of transforming the synchronization signal allocation problem of the cloud wireless access network into a Transmitter Point Receiving ID (TRP ID) allocation problem with preset constraints includes: S21. Map the Transmission Receiver Point Identifier (TRP ID) to the synchronization signal of the cloud wireless access network. The synchronization signal includes a primary synchronization signal (PSS) and a secondary synchronization signal. Encapsulate the synchronization signal and the physical broadcast channel in several consecutive symbols to obtain a synchronization signal block. S22. The calculation expression for the user equipment (UE) to recover the transmission receiver point identifier TRPID using the time position of the synchronization signal block is as follows: in, This represents the value of the Transmission Receiver Point Identifier (TRP ID). This indicates the number of groups into which the Transmission Receiver Point (TRP) is divided. This indicates the first parameter within the transmit / receive point identifier group. This indicates the second parameter within the transmit / receive point identifier group.

4. The method for initial synchronization of ultra-dense, cell-free, large-scale multiple-input multiple-output control planes according to claim 3, characterized in that, The first parameter The location of the demodulation reference signal of the physical broadcast channel is transmitted via the physical broadcast channel. It is determined by the Transmission Receiver Point Identifier (TRP ID).

5. The method for initial synchronization of a large-scale, cell-free, multi-input multi-output control plane according to claim 4, characterized in that, The preset constraints include: adjacent Transmission Receiver Points (TRPs) must not use the same Transmission Receiver Point Identifier (TRP ID); two adjacent Transmission Receiver Points (TRPs) that are the switching targets of the current Transmission Receiver Point (TRP) must not use the same Transmission Receiver Identifier (TRP ID); and all Transmission Receiver Points (TRPs) participating in joint transmission in cooperative multipoint transmission mode must not have the same ID.

6. The method for initial synchronization of ultra-dense, cell-free, large-scale multiple-input multiple-output control planes according to claim 5, characterized in that, The mathematical expression for the quadratic unconstrained binary optimization problem is as follows: in, P (.) indicates a penalty. Indicates the first The first Transmitter Receiving Point (TRP) is assigned to the first... Binary variables for each partition.

7. A super-dense, cell-free, large-scale multiple-input multiple-output control plane initial synchronization system based on the method described in any one of claims 1-6, characterized in that, include: The Transmission Receive Point Identifier (TRP) allocation module is used to assign TRP IDs to different Transmission Receive Points (TRPs) to replace the traditional Physical Cell Identifier (PCI). The problem conversion module is used to convert the synchronization signal allocation problem of the cloud wireless access network into a TRP ID allocation problem that performs preset constraints, based on the Transmission Receiver Point Identifier (TRP ID). The solution module is used to transform the Transmission Receiver Point Identifier (TRP ID) allocation problem into a minimum k-partition optimization problem, solve the minimum k-partition optimization problem, and obtain the optimal allocation scheme of the Transmission Receiver Point Identifier (TRPID) that satisfies the preset constraints.

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