Downlink device of 5G millimeter wave base station and communication method thereof

Abstract

The invention relates to the technical field of communication technology, in particular to a downlink device of a 5G millimeter wave base station and a communication method thereof, comprising the following steps: step 1, determining the same frequency interference degree among cells based on the subcarrier interference distribution condition, and generating a corresponding power distribution regulation strategy; step 2, adjusting the power of a millimeter wave base station transmitting signal according to the power distribution regulation and control strategy so as to reduce co-channel interference between cells; step 3, performing statistics on service requirements of user equipment, calculating resource block allocation proportions required for meeting different transmission delays, and dynamically adjusting power by monitoring subcarrier interference to reduce co-channel interference between cells; resource blocks are accurately scheduled according to user service requirements, and transmission delay is balanced. Meanwhile, by means of adaptive learning, exception handling and user experience management technologies, the overall performance of the base station is cooperatively improved, the communication efficiency and reliability of the 5G network are guaranteed, and the user experience is optimized.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a downlink device of a 5G millimeter wave base station and a communication method thereof. Background Art

[0002] The downlink communication method of 5G millimeter wave base stations mainly involves improving the communication efficiency and reliability of 5G networks by optimizing key technologies such as power allocation, resource block scheduling, and interference coordination.

[0003] In practical applications, this method faces two key problems:

[0004] One is the problem of co-channel interference between cells. Since adjacent cells may use the same frequency band, it is necessary to dynamically adjust the power allocation strategy based on the subcarrier interference distribution to effectively reduce the impact of interference on communication quality.

[0005] The second issue is the imbalance in downlink transmission latency. In multi-user scenarios, different types of user devices have different service requirements, such as real-time voice services or low-latency data services. Therefore, how to flexibly adjust the allocation ratio of resource blocks based on these specific needs to ensure the latency requirements of each service type has become a major challenge.

[0006] Solving these problems is crucial to improving the overall performance of millimeter wave base stations. Summary of the Invention

[0007] In order to solve the problems raised by the above background technology, the present application provides a downlink device of a 5G millimeter wave base station and a communication method thereof.

[0008] The present application provides a downlink device and communication method of a 5G millimeter wave base station, which adopts the following technical solution: A downlink communication method of a 5G millimeter wave base station, comprising:

[0009] Step 1: Determine the degree of co-channel interference between cells based on the subcarrier interference distribution and generate a corresponding power allocation control strategy;

[0010] Step 2: adjusting the power of the millimeter wave base station transmit signal according to the power allocation control strategy to reduce the co-channel interference between cells;

[0011] Step 3: Count the service demands of user equipment and calculate the resource block allocation ratio required to meet different transmission delays;

[0012] Step 4: Perform resource scheduling on the user equipment according to the resource block allocation ratio to balance the downlink transmission delay.

[0013] According to one embodiment, determining the degree of co-channel interference between cells based on the subcarrier interference distribution further includes:

[0014] By measuring the received power on each subcarrier, a subcarrier interference intensity distribution map SIF is generated;

[0015] According to the formula Calculate the interference index IFI, where IFI represents the integrated interference index, SIF[i] is the interference intensity on the i-th subcarrier, Wf[i] is the i-th subcarrier weight factor, and N is the total number of subcarriers;

[0016] When IFI exceeds the preset threshold IF TH When , it is determined that there is significant co-channel interference between the cells;

[0017] Adjust the power regulation factor based on the above judgment results where K pf and P0 are the proportional coefficient and reference power respectively.

[0018] According to one embodiment, determining the degree of co-channel interference between cells based on the subcarrier interference distribution further includes:

[0019] Estimating the Signal-to-Interference Ratio of User Equipment at the Cell Boundary Using Historical Data and stored in a database;

[0020] Select the target signal-to-interference ratio range based on statistical analysis [T MIN ,T MAX ] and update the weight factor table WWF;

[0021] Based on the formula Dynamically adjust the weighting factor, where α is the sensitivity parameter;

[0022] The IFI is recalculated based on the new weight factor, and the power allocation strategy is optimized to reduce co-channel interference between cells.

[0023] According to one embodiment, determining the degree of co-channel interference between cells based on the subcarrier interference distribution further includes:

[0024] Define a spatial direction vector d vec (i) indicates the main coverage direction of base station i;

[0025] Calculate the cross-correlation between adjacent base stations using interference alignment technology

[0026] Set threshold C TH Used to determine whether there is overlapping coverage between base stations. Then execute the subsequent resource scheduling steps: Based on the formula Calculate the power allocation adjustment coefficient of adjacent cells ε is used to prevent division by zero errors.

[0027] According to one embodiment, determining the degree of co-channel interference between cells based on the subcarrier interference distribution further includes:

[0028] Record real-time business type ratio Combined with the historical average interference level to generate a reference table

[0029] When a certain type of business B is detected k When the highest demand priority is achieved, the special adjustment mode SA is activated;

[0030] According to the formula Adjust the power allocation coefficient, where η is used to adjust the impact of the balance priority, P total is the total available power;

[0031] If the delay still does not meet the standard after SA is started, the maximum allowable transmit power upper limit of non-priority services is recursively reduced to the lower limit range L bound .

[0032] According to one embodiment, a method for more fine-tuning resource block allocation is also included:

[0033] Extract the traffic prediction curve uploaded by the user device

[0034] Apply linear interpolation to each traffic change point to predict future bandwidth pressure

[0035] Introducing load balancing adjustments Measuring local overload risk;

[0036] When β LB >β Threshold When the redundant RB share is increased, the formula Implementation specific extension, φ is the elasticity factor.

[0037] According to one embodiment, the fine-tuning of resource block allocation includes the following operations:

[0038] Monitor the relationship between the task execution period C and the required number of resource blocks NR in the user queue Q;

[0039] For tasks with high delay sensitivity, T high , define the time window Wtime =C avg ×ψ allows for fast processing to complete the check, where C avg is the periodic mean, ψ is the amplification constant;

[0040] According to the fairness index Comprehensively evaluate the weight distribution of all tasks, where λ and ρ are exponents for controlling nonlinearity;

[0041] Redistribute limited RBs based on FE to maximize T high Process the priority until the satisfaction level S≥S target .

[0042] According to one embodiment, a dynamic feedback resource adjustment mechanism is further proposed:

[0043] In the case of n consecutive resource scheduling failures, re-evaluate the overall business demand matrix D in the system matrix =[D ik ];

[0044] Calculate the new resource block reallocation ratio To compensate for the transmission delay t gap The impact of t gap It refers to the difference between the expected delay and the actual delay, ζ regulates the exponential effect, and δ is the bias compensation term;

[0045] Substitute the results into the existing allocation model to rebuild RB new ;

[0046] At the same time, a portion of the reserved resources R svd , so that the minimum service capability requirements can be maintained in extreme situations.

[0047] According to one embodiment, an adaptive learning module is added to assist in power and resource allocation decisions:

[0048] Obtain multi-round scheduling feedback data and construct a loss function Using the gradient descent algorithm Find the optimal parameter setting combination, where P init Represents the initial parameter configuration set for the initial table. LearningRate controls the convergence speed and prevents oscillation problems.

[0049] After verifying the global optimal solution, it is deployed in a real-time system environment for online adjustment, verification and testing;

[0050] Through cyclic correction, the target state balance scheme that is consistent with theoretical derivation and actual performance is finally achieved;

[0051] Add abnormal event handling process as a supplementary guarantee: If monitoring shows that any base station has a sudden failure F event , then the backup mechanism is triggered and the backup signal channel is activated

[0052] Based on the probability evaluation formula Determine the conditions necessary to return to normalcy;

[0053] If the maximum number of attempts is exceeded or the failure state lasts for more than T max , then an alarm signal Alert is issued Sig Wait for manual confirmation or higher-level intervention to resolve the problem until stable operation is fully restored;

[0054] Enhanced robustness and user experience perception management logic design: Targeting key customer groups CG p Set special attention label Flag Priority ; Once Flag Priority Trigger, enter the deep protection state DP status And start the emergency optimization process EO proc ;

[0055] By dynamically weighing the key factors formula The adjustment involves the service level assurance (SLA) parameters, where ω represents the adjustment weight.

[0056] Always keep the core customer experience free from external interference and fluctuation, thereby achieving the goal of end-to-end service quality consistency.

[0057] A downlink device for a 5G millimeter wave base station, comprising:

[0058] The interference assessment module is used to determine the degree of co-channel interference between cells based on the subcarrier interference distribution and generate corresponding power allocation control strategies;

[0059] A power adjustment module, connected to the interference assessment module, configured to adjust the power of the millimeter wave base station transmit signal according to the power allocation control strategy to reduce the co-channel interference between cells;

[0060] The demand statistics module is used to count the service demands of user equipment and calculate the resource block allocation ratio required to meet different transmission delays;

[0061] The resource scheduling module is connected to the demand statistics module and is used to schedule resources for user equipment according to the resource block allocation ratio to balance downlink transmission delay.

[0062] In summary, this application includes at least one of the following beneficial technical effects:

[0063] The disclosed embodiments optimize power allocation, resource block scheduling and interference coordination technology, monitor subcarrier interference power spectrum density, and combine multiple factors to accurately calculate interference indicators and adjust power control factors. Compared with traditional fixed power settings, they can intelligently adapt to the environment and can specifically reduce base station transmission power in adjacent cell A, B, and C scenarios, reduce data transmission errors and dropped calls, improve signal stability and coverage quality, and reduce inter-cell interference by [X]%. At the same time, they comprehensively consider the service needs of user equipment, accurately calculate the resource block allocation ratio and reasonably schedule it, such as allocating different ratios of resource blocks to high-definition video and ordinary text services, to maximize resource utilization, reduce the average network transmission delay by [X]%, ensure the delay requirements of various services, and improve user experience. In addition, the adaptive learning module optimizes power and resource allocation, the abnormal event handling process ensures the continuous operation of the network, the user experience perception management logic protects important customer groups, and multiple technologies work together to enhance the overall performance of the base station, provide high-quality 5G communication services, and promote the application and development of 5G technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 The present invention is a flowchart of a downlink communication method for a 5G millimeter wave base station. DETAILED DESCRIPTION

[0065] Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings.

[0066] Throughout this specification, reference to the terms "certain embodiments," "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0067] The present application discloses a downlink device and communication method for a 5G millimeter wave base station. Referring to the accompanying drawings, the invention describes various steps and implementation methods of a downlink communication method for a 5G millimeter wave base station. The method includes the following key steps, which solve the problems of co-channel interference between cells and unbalanced downlink transmission delay.

[0068] A downlink communication method for a 5G millimeter wave base station, comprising:

[0069] Step 1: Determine the degree of co-channel interference between cells based on the subcarrier interference distribution and generate a corresponding power allocation control strategy;

[0070] Step 2: adjusting the power of the millimeter wave base station transmit signal according to the power allocation control strategy to reduce the co-channel interference between cells;

[0071] Step 3: Count the service demands of user equipment and calculate the resource block allocation ratio required to meet different transmission delays;

[0072] Step 4: Perform resource scheduling on the user equipment according to the resource block allocation ratio to balance the downlink transmission delay.

[0073] Determining the degree of co-channel interference between cells based on the subcarrier interference distribution further includes:

[0074] By measuring the received power on each subcarrier, a subcarrier interference intensity distribution map SIF is generated;

[0075] According to the formula Calculate the interference index IFI, where IFI represents the integrated interference index, SIF[i] is the interference intensity on the i-th subcarrier, Wf[i] is the i-th subcarrier weight factor, and N is the total number of subcarriers;

[0076] When IFI exceeds the preset threshold When , it is determined that there is significant co-channel interference between the cells;

[0077] Based on the above judgment results, the power regulation factor PF is adjusted to (IFI-IF TH )×K pf +P0, where K pf and P0 are the proportional coefficient and reference power respectively;

[0078] The specific method for determining the degree of co-channel interference based on subcarrier interference distribution includes generating a subcarrier interference intensity distribution map, calculating interference indicators, determining the interference situation, and adjusting the power control factor.

[0079] Taking a 5G millimeter wave base station cell with 1000 subcarriers as an example, by measuring the received power on each subcarrier, the subcarrier is decomposed into frequency domain units for analysis, and a subcarrier interference intensity distribution map SIF is generated. The subcarrier weight factor Wf[i] is set according to the importance of the subcarrier, such as subcarriers closer to the center frequency have a higher weight. According to the formula Calculate the interference index IFI. If the preset threshold IFT TH =50, the calculated IFI is 60, which exceeds the threshold, and it is determined that there is significant co-channel interference in the cell. At this time, according to the formula PF=(IFI-IFT TH )×K pf +P0 adjusts the power regulation factor PF, assuming Kpf =0.5, P0=10, then PF=(60-50)×0.5+10=15, which is used to adjust the base station transmission power and reduce interference.

[0080] Determining the degree of co-channel interference between cells based on the subcarrier interference distribution further includes:

[0081] Estimating the Signal-to-Interference Ratio of User Equipment at the Cell Boundary Using Historical Data and stored in a database;

[0082] Select the target signal-to-interference ratio range based on statistical analysis [T MIN ,T MAX ] and update the weight factor table WWF;

[0083] Based on the formula Dynamically adjust the weighting factor, where α is the sensitivity parameter;

[0084] Recalculate the IFI based on the new weight factor and use it to optimize the power allocation strategy to mitigate co-channel interference between cells;

[0085] The weight factors are further dynamically adjusted based on historical data, target signal-to-interference ratio range, etc. to optimize the power allocation strategy.

[0086] For example, in a 5G millimeter wave base station cell, the signal-to-interference ratio of user equipment at the cell edge was estimated based on historical data in the past week. Stored in the database. After statistical analysis, select the target signal-to-interference ratio range [30, 40] and update the weight factor table WWF. Assume that the cell edge user equipment signal-to-interference ratio corresponding to a certain subcarrier is Sensitivity parameter α = 0.8, maximum weight According to the formula Dynamically adjust the weighting factor. Recalculate the IFI based on the new weighting factor to optimize the power allocation strategy. If the IFI decreases after calculation, it means that the adjustment is effective and can further reduce co-channel interference between cells.

[0087] Determining the degree of co-channel interference between cells based on the subcarrier interference distribution further includes:

[0088] Define a spatial direction vector d vec (i) indicates the main coverage direction of base station i;

[0089] Calculate the cross-correlation between adjacent base stations using interference alignment technology

[0090] Set threshold C THUsed to determine whether there is overlapping coverage between base stations. Then execute the subsequent resource scheduling steps: Based on the formula Calculate the power allocation adjustment coefficient of adjacent cells ε is used to prevent division by zero errors;

[0091] The spatial direction vector and interference alignment technology determines the power allocation adjustment coefficient by calculating the cross-correlation between base stations and setting thresholds to deal with the interference problem in the overlapping coverage area of ​​base stations. Assume that there are two adjacent 5G millimeter wave base stations X and Y, and define the spatial direction vector d vec (X) and d vec (Y) represents the direction of their main coverage. The cross correlation between the two base stations is calculated by interference alignment technology. Setting thresholds because This indicates that there is overlapping coverage between the two base stations. Based on the formula Calculate the power allocation adjustment coefficient of adjacent cells The power allocation of base station Y is adjusted according to the coefficient to reduce interference in the overlapping area.

[0092] Determining the degree of co-channel interference between cells based on the subcarrier interference distribution further includes:

[0093] Record real-time business type ratio Combined with the historical average interference level to generate the reference table RI ref [TP];

[0094] When a certain type of business B is detected k When the highest demand priority is achieved, the special adjustment mode SA is activated;

[0095] According to the formula Adjust the power allocation coefficient, where η is used to adjust the impact of the balance priority, P total is the total available power;

[0096] If the delay still does not meet the standard after SA is started, the maximum allowable transmit power upper limit of non-priority services is recursively reduced to the lower limit range L bound ;

[0097] Combined with the real-time service type ratio and historical interference level, a special adjustment mode is activated for high-priority services to adjust the power allocation coefficient and handle situations where the delay does not meet the standard. For example, voice services account for 30%, HD video services account for 50%, and ordinary data services account for 2096. Combined with the historical average interference level, a reference table is generated. When it is detected that the high-definition video service has the highest demand priority, the special adjustment mode SA is started. total =100, according to the formula Adjust the power allocation coefficient to allocate more power to high-definition video services. If the delay still does not meet the standard after SA is started, recursively reduce the upper limit of the maximum allowable transmission power of ordinary data services to the lower limit range L bound For example, the power limit of ordinary data services is reduced from 20 to 15 to ensure the latency requirements of high-definition video services.

[0098] It also includes methods for more fine-grained control of resource block allocation:

[0099] Extract the traffic prediction curve uploaded by the user device

[0100] Apply linear interpolation to each traffic change point to predict future bandwidth pressure

[0101] Introducing load balancing adjustments Measuring local overload risk;

[0102] when When the redundant RB share is increased, the formula

[0103] Implementation specific extension, φ is the elasticity factor;

[0104] A more refined method of regulating resource block allocation can achieve reasonable expansion of resource blocks through operations such as traffic prediction, bandwidth pressure calculation, and load balancing adjustment.

[0105] Extract the traffic prediction curve uploaded by user equipment within the millimeter wave base station cell

[0106] Predict traffic changes in the future. Apply linear interpolation to each traffic change point to predict future bandwidth pressure BW. pred (i) If bandwidth pressure BW is predicted for a certain period of time pred (current) = 80 Mbps, bandwidth threshold BW threshold =60Mbps, introducing load balancing set up because Increase the redundant RR share. Assume that the minimum resource min resource=10, bandwidth requirement of a user The total weight factor ∑WeightFactor=5, elasticity factor φ=1.2, through the formula

[0107] ×1.2=12: A specific extension is implemented to add 12 resource blocks for the user.

[0108] The fine-tuning of resource block allocation includes the following operations:

[0109] Monitor the relationship between the task execution period C and the required number of resource blocks NR in the user queue Q;

[0110] For tasks with high delay sensitivity, T high , define the time window W time =C avg ×ψ allows for fast processing to complete the check, where C avg is the periodic mean, ψ is the amplification constant;

[0111] According to the fairness index Comprehensively evaluate the weight distribution of all tasks, where λ and ρ are exponents for controlling nonlinearity;

[0112] Redistribute limited RBs based on FE to maximize T high Process the priority until the satisfaction level S≥S target ;

[0113] The specific operations for fine-tuning resource block allocation include monitoring the relationship between tasks and resources, defining time windows, calculating fairness indices, and reallocating resources based on fairness indices. In a user queue Q of a 5G millimeter wave base station cell, the relationship between the monitoring task execution period C and the number of required resource blocks NR is monitored. For tasks T with high delay sensitivity, high , such as online gaming business, the cycle mean C avg =100ms, amplification constant ψ=1.5, define the time window W time =100×1.5=150ms, allowing the task to complete the check quickly. Assume that there are three tasks in the queue, and the queue lengths are Queue[1]=5, Queue[2]=3, Queue[3]=2, and the control nonlinearity exponents λ=1.2, ρ=0.8. According to the fairness index Comprehensively evaluate the weight distribution of all tasks. Redistribute limited RBs based on FE, giving priority to the resource needs of online gaming services until their processing priority reaches a satisfactory level S≥S target , such as reducing the game screen delay to an acceptable range.

[0114] A dynamic feedback resource adjustment mechanism is further proposed:

[0115] In the case of n consecutive resource scheduling failures, re-evaluate the overall business demand matrix D in the system matrix =[D ik ];

[0116] Calculate the new resource block reallocation ratio To compensate for the transmission delay t gap The impact of t gap It refers to the difference between the expected delay and the actual delay, ζ regulates the exponential effect, and δ is the bias compensation term;

[0117] Substitute the results into the existing allocation model to rebuild RB new ;

[0118] At the same time, a portion of the reserved resources R svd , so as to maintain minimum service capability requirements in extreme situations;

[0119] The dynamic feedback resource adjustment mechanism re-evaluates the business demand matrix, calculates the resource block reallocation ratio, rebuilds the resource block allocation model and retains the reserved resources when resource scheduling fails. In a 5G millimeter wave base station system, after three consecutive resource scheduling failures, the overall business demand matrix D in the system is re-evaluated. matrix =[D ik ], assuming that the maximum demand D max =50, a business requirement D ik =20, transmission delay t gap =20ms ro , adjustment index ζ=0.1, bias compensation term δ=5, calculate the new resource block reallocation ratio Substitute the results into the existing allocation model and rebuild At the same time, the reserved resource R svd =10, ensuring that in extreme situations, such as when a large number of users suddenly access the network, the minimum service capacity requirements can still be maintained to guarantee the basic communication needs of some users.

[0120] Add an adaptive learning module to assist in power and resource allocation decisions:

[0121] Obtain multi-round scheduling feedback data and construct a loss function

[0122] Using the gradient descent algorithm Find the optimal parameter setting combination, where P initRepresents the initial parameter configuration set of the initial table. LearningRate controls the convergence speed and prevents oscillation problems.

[0123] After verifying the global optimal solution, it is deployed in a real-time system environment for online adjustment, verification and testing;

[0124] Through cyclic correction, the target state balance scheme that is consistent with theoretical derivation and actual performance is finally achieved;

[0125] During the operation of a 5G millimeter wave base station, multiple rounds of scheduling feedback data, such as power parameters, resource block configuration, and corresponding communication quality indicators, are obtained to construct a loss function. (Power param ,RB config ). Assume that the initial parameter configuration set P init = [20, 30] (representing the initial power and the initial number of resource blocks respectively), learning rate LearningRate = 0.1, using the gradient descent algorithm Find the optimal parameter setting combination. After multiple iterative calculations and verification of the global optimal solution, deploy it in a real-time system environment for online adjustment and verification testing, continuously optimizing power and resource allocation. For example, adjusting the power to 25 and the number of resource blocks to 35 optimizes communication quality, ultimately achieving a state balance target solution that is consistent with theoretical derivation and actual performance.

[0126] Add abnormal event handling process as a supplementary guarantee: If monitoring shows that any base station has a sudden failure F event , then the backup mechanism is triggered and the backup signal channel is activated

[0127] Based on the probability evaluation formula Determine the conditions necessary to return to normalcy;

[0128] If the maximum number of attempts is exceeded or the failure state lasts for more than T max , an alarm signal is issued Wait for manual confirmation or higher-level intervention to resolve the problem until stable operation is fully restored;

[0129] If a sudden fault is detected on a 5G millimeter wave base station, event , immediately trigger the backup mechanism and activate the backup signal channel Assume that the power required by the faulty base station is P required =30, remaining available power P remaining =20, backup channel ratio ratio =0.6, redundancy threshold Adjustment coefficient μ=0.8,ξ=0.7,limit

[0130]

[0131] Determine the conditions required for recovery. If the maximum number of attempts (such as 5) is exceeded or the failure state lasts for more than T max =10min, an alarm signal is issued Wait for manual confirmation or higher-level intervention to resolve the problem until the base station is fully restored to a stable operating state

[0132] Enhance robustness and user experience perception management logic design: Targeting key customer groups Set special attention label Flag Priority ; Once Flag Priority Trigger and enter deep protection state And start the emergency optimization process

[0133] By dynamically weighing the key factors formula The adjustment involves the service level assurance (SLA) parameters, where ω represents the adjustment weight.

[0134] Always keep the core customer experience free from external interference and fluctuation, thus achieving the goal of end-to-end service quality consistency;

[0135] Targeting key customer groups For example, VIP corporate customers can set a special attention tag F l ag Priority When the client group has a large amount of data transmission demand, trigger Enter deep protection state And start the emergency optimization process Assuming that the maximum resource max_resource=100, the current resource Current_resource=60, and the importance adjustment ratio ω=1.2, through the dynamic weighing key factor formula Adjustments involve service level assurance (SLA) parameters, prioritizing the data transmission quality of VIP corporate customers and ensuring their experience is always free from external interference and fluctuations, thereby achieving the end-to-end service quality consistency target commitment, such as ensuring smooth corporate video conferencing.

[0136] A downlink device for a 5G millimeter wave base station, comprising:

[0137] The interference assessment module is used to determine the degree of co-channel interference between cells based on the subcarrier interference distribution and generate corresponding power allocation control strategies;

[0138] A power adjustment module, connected to the interference assessment module, configured to adjust the power of the millimeter wave base station transmit signal according to the power allocation control strategy to reduce the co-channel interference between cells;

[0139] The demand statistics module is used to count the service demands of user equipment and calculate the resource block allocation ratio required to meet different transmission delays;

[0140] The resource scheduling module is connected to the demand statistics module and is used to schedule resources for user equipment according to the resource block allocation ratio to balance downlink transmission delay.

[0141] First, based on the subcarrier interference distribution, the degree of co-channel interference between cells is determined and a power allocation control strategy is generated. This step is achieved by the millimeter wave base station monitoring the interference power spectral density from adjacent cells on different subcarriers. Specifically, each subcarrier is decomposed into smaller frequency domain units for separate analysis to identify frequency ranges with high interference. An interference distribution map is constructed based on the collected data, and the actual interference level caused by different neighboring cells in the current network environment is estimated using the channel model. Subsequently, the optimal power adjustment scheme is calculated based on the established mathematical model to reduce mutual interference within the co-channel area. This process requires full consideration of factors such as antenna directivity and signal propagation loss. For example, in one embodiment, assuming three adjacent small areas, A, B, and C, all use the same frequency band resources for service coverage, the interference caused by cell A on cells B and C at specific frequencies, with varying strengths, can be precisely analyzed to develop targeted measures to reduce or avoid this interference, thereby deriving the optimal output intensity setting for transmitter A.

[0142] Then, according to the generated power allocation and control strategy, the actual power output of the millimeter-wave base station's transmitted signal is adjusted, effectively mitigating cross-cell interference caused by co-frequency band usage. This means converting the conclusions from the first step into action commands and sending them to the hardware, dynamically controlling its transmitted energy value and its rate of change in real time. To ensure smooth and lossless switching, a smooth gradient algorithm can be introduced to make the change more gentle and natural, avoiding sudden disturbances that could adversely affect other operating devices. Furthermore, protection mechanisms must be implemented to limit abnormal conditions from exceeding the permitted range and compromising the stability of the overall system.

[0143] At the same time, the various service request characteristics of each user device connected to the current system are analyzed, and the differences in their respective performance requirements are comprehensively assessed. This allows for the precise resource allocation ratio recommendations required to meet various latency expectations. Key to this step is a detailed and quantitative record of each terminal's workload, considering everything from the volume of received packet traffic to the processing time span. These factors are then weighted and ranked within a comprehensive evaluation system, ultimately resulting in a specific plan that clearly indicates the bandwidth allocation for each task. In a specific example, if some clients require video streaming while others only require periodic simple text updates, the former clearly require significantly more bandwidth than the latter. Therefore, a larger proportion of RB resources may be allocated to the former to ensure consistent and stable display quality, while the latter may only require minimal support.

[0144] Based on the resource block allocation ratios obtained previously, the actual scheduling and deployment details for all incoming users are replanned, striving to balance the interests of all parties as fairly as possible and achieve the optimal global transmission delay balance. Throughout this process, continuous operational feedback must be monitored to verify that the established plan is meeting expectations. Flexible responses to unexpected situations can be made, with timely parameter adjustments and reorganization of the process to continue moving toward the desired final outcome until satisfactory standards are achieved and the entire operation cycle is concluded. Overall, such measures can significantly improve the overall network efficiency, allowing users to enjoy higher-quality, more responsive service experiences and experience the convenience and beauty brought by technological advancement every day.

[0145] The present invention provides a downlink communication method for a 5G millimeter wave base station, comprising: analyzing the subcarrier interference distribution between cells, evaluating the degree of co-channel interference between cells, and then generating an accurate power allocation control strategy to optimize the power of the millimeter wave base station's transmitted signal, thereby alleviating the co-channel interference between cells. At the same time, the method further combines the service demand characteristics of the user device, calculates the required data rate and delay requirements, and calculates the resource block allocation ratio required to meet different transmission delays based on this. Resource scheduling is completed based on this ratio, ultimately achieving the effect of balancing the downlink transmission delay.

[0146] To address the technical challenge of adjusting power allocation strategies based on subcarrier interference distribution to address inter-cell co-channel interference, this method comprehensively monitors the interference intensity distribution on each subcarrier to determine the specific interference level and impact range. Based on this information, a power allocation strategy tailored to the current environment is dynamically generated, effectively reducing signal interference between adjacent cells. Compared to traditional fixed power settings, this method more intelligently adapts to actual environmental changes, minimizing data transmission quality issues or dropped calls caused by co-channel interference.

[0147] To address the technical issue of how to regulate resource block allocation ratios based on user device service requirements to address the issue of unbalanced downlink transmission delays, this invention employs a detailed service statistics method to accurately grasp the actual traffic requirements and priority characteristics of each user device. After calculating the resource allocation requirements corresponding to different transmission delays, this invention uses a reasonable resource block ratio for scheduling to prevent low-priority users from occupying resources for extended periods, thereby degrading the transmission performance of other users. This ensures maximum resource utilization across the entire network and effectively controls the deviation of overall downlink transmission delays.

[0148] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A downlink communication method for a 5G millimeter wave base station, characterized in that: include: Step 1: Determine the degree of co-channel interference between cells based on the subcarrier interference distribution and generate a corresponding power allocation control strategy; Step 2: adjusting the power of the millimeter wave base station transmit signal according to the power allocation control strategy to reduce the co-channel interference between cells; Step 3: Count the service demands of user equipment and calculate the resource block allocation ratio required to meet different transmission delays; Step 4: Perform resource scheduling on the user equipment according to the resource block allocation ratio to balance the downlink transmission delay.

2. A 5G millimeter wave base station downlink communication method according to claim 1, characterized in that: Determining the degree of co-channel interference between cells based on the subcarrier interference distribution further includes: By measuring the received power on each subcarrier, a subcarrier interference intensity distribution map SIF is generated; According to the formula Calculate the interference index IFI, where IFI represents the integrated interference index, SIF[i] is the interference intensity on the i-th subcarrier, Wf[i] is the i-th subcarrier weight factor, and N is the total number of subcarriers; When IFI exceeds the preset threshold When , it is determined that there is significant co-channel interference between the cells; Based on the above judgment results, the power regulation factor PF is adjusted to (IFI-IF TH )×K pf +P0, where K pf and P0 are the proportional coefficient and reference power respectively.

3. A 5G millimeter wave base station downlink communication method according to claim 2, characterized in that: Determining the degree of co-channel interference between cells based on the subcarrier interference distribution further includes: Estimating the Signal-to-Interference Ratio of User Equipment at the Cell Boundary Using Historical Data and stored in a database; Select the target signal-to-interference ratio range based on statistical analysis [T MIN ,T MAX ] and update the weight factor table WWF; Based on the formula Dynamically adjust the weighting factor, where α is the sensitivity parameter; The IFI is recalculated based on the new weight factor, and the power allocation strategy is optimized to reduce co-channel interference between cells.

4. A 5G millimeter wave base station downlink communication method according to claim 3, characterized in that: Determining the degree of co-channel interference between cells based on the subcarrier interference distribution further includes: Define a spatial direction vector d vec (i) indicates the main coverage direction of base station i; Calculate the cross-correlation between adjacent base stations using interference alignment technology Set threshold C TH Used to determine whether there is overlapping coverage between base stations. Then execute the subsequent resource scheduling steps: Based on the formula Calculate the power allocation adjustment coefficient of adjacent cells ε is used to prevent division by zero errors.

5. A downlink communication method for a 5G millimeter wave base station according to claim 4, characterized in that: Determining the degree of co-channel interference between cells based on the subcarrier interference distribution further includes: Record real-time business type ratio Combined with the historical average interference level to generate a reference table When a certain type of business B is detected k When the highest demand priority is achieved, the special adjustment mode SA is activated; According to the formula Adjust the power allocation coefficient, where η is used to adjust the impact of the balance priority, P total is the total available power; If the delay still does not meet the standard after SA is started, the maximum allowable transmit power upper limit of non-priority services is recursively reduced to the lower limit range L bound .

6. A 5G millimeter wave base station downlink communication method according to claim 5, characterized in that: It also includes methods for more fine-grained control of resource block allocation: Extract the traffic prediction curve uploaded by the user device Apply linear interpolation to each traffic change point to predict future bandwidth pressure Introducing load balancing adjustments Measuring local overload risk; When β LB >β Threshold When the redundant RB share is increased, the formula Implementation specific extension, φ is the elasticity factor.

7. A 5G millimeter wave base station downlink communication method according to claim 6, characterized in that: The fine-tuning of resource block allocation includes the following operations: Monitor the relationship between the task execution period C and the required number of resource blocks NR in the user queue Q; For tasks with high delay sensitivity, T high , define the time window W time =C avg ×ψ allows for fast processing to complete the check, where C avg is the periodic mean, ψ is the amplification constant; According to the fairness index Comprehensively evaluate the weight distribution of all tasks, where λ and ρ are exponents for controlling nonlinearity; Redistribute limited RBs based on FE to maximize T high Process the priority until the satisfaction level S≥S target .

8. A 5G millimeter wave base station downlink communication method according to claim 7, characterized in that: A dynamic feedback resource adjustment mechanism is further proposed: In the event of n consecutive resource scheduling failures, re-evaluate the overall business demand matrix D within the system matrix =[D ik ]; Calculate the new resource block reallocation ratio To compensate for the transmission delay t gap The impact of t gap It refers to the difference between the expected delay and the actual delay, ζ regulates the exponential effect, and δ is the bias compensation term; Substitute the results into the existing allocation model to rebuild RB new ; At the same time, a portion of the reserved resources R svd , so that the minimum service capability requirements can be maintained in extreme situations.

9. A downlink communication method for a 5G millimeter wave base station according to claim 8, characterized in that: Add an adaptive learning module to assist in power and resource allocation decisions: Obtain multi-round scheduling feedback data and construct a loss function Using the gradient descent algorithm Find the optimal parameter setting combination, where P init Represents the initial parameter configuration set of the initial table. LearningRate controls the convergence speed and prevents oscillation problems. After verifying the global optimal solution, it is deployed in a real-time system environment for online adjustment, verification and testing; Through cyclic correction, the target state balance scheme that is consistent with theoretical derivation and actual performance is finally achieved; Add abnormal event handling process as a supplementary guarantee: If monitoring shows that any base station has a sudden failure F event , then the backup mechanism is triggered and the backup signal channel is activated Based on the probability evaluation formula: Determine the conditions necessary to return to normalcy; If the maximum number of attempts is exceeded or the failure state lasts for more than T max , an alarm signal is issued Wait for manual confirmation or higher-level intervention to resolve the problem until stable operation is fully restored; Enhance robustness and user experience perception management logic design: Targeting key customer groups Set special attention label Flag Priority ;Flag Priority Trigger and enter deep protection state And start the emergency optimization process By dynamically weighing the key factors formula The adjustments involve service level assurance (SLA) parameters, where ω represents the weight of the adjustment to protect the core customer experience from external interference and fluctuations.

10. A downlink device for a 5G millimeter wave base station, characterized in that: The system is executed by the downlink communication method of a 5G millimeter wave base station according to claim 9, and the system includes: The interference assessment module is used to determine the degree of co-channel interference between cells based on the subcarrier interference distribution and generate corresponding power allocation control strategies; A power adjustment module, connected to the interference assessment module, configured to adjust the power of the millimeter wave base station transmit signal according to the power allocation control strategy to reduce the co-channel interference between cells; The demand statistics module is used to count the service demands of user equipment and calculate the resource block allocation ratio required to meet different transmission delays; The resource scheduling module is connected to the demand statistics module and is used to schedule resources for user equipment according to the resource block allocation ratio to balance downlink transmission delay.

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