Cell state self-adaptive adjustment method and device, equipment and storage medium

Abstract

The application provides a cell state self-adaptive adjustment method, device, equipment and storage medium, and relates to the technical field of communication. The method comprises the following steps: obtaining current service data of a cell, and determining a current service load level of the cell according to the service data; the service load level is divided into multiple levels, and each service load level corresponds to at least one working mode; from the working mode corresponding to the current service load level of the cell, a working mode meeting a preset QoS constraint condition and having a lowest current estimated energy consumption is selected as a current optimal working mode of the cell and is put into operation; in each subsequent scheduling period, whether the cell state needs to be switched is judged according to a preset switching condition; in response to the need to switch the cell state, the working mode of the cell is changed step by step according to a cell state switching direction and is put into operation; and in response to the fact that the cell state does not need to be switched, the current working mode of the cell is kept. The application can realize timely and effective energy-saving control under the premise of guaranteeing the service quality.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a cell state adaptive adjustment method, a cell state adaptive adjustment device, a computer device, and a computer-readable storage medium. Background Technology

[0002] With the widespread deployment of mobile communication networks, the number of base stations has increased dramatically. While communication capabilities have been greatly enhanced, the corresponding energy consumption problem has become increasingly serious, posing a significant challenge to operators. Statistics show that base stations in mobile communication systems account for approximately 60% to 80% of the total network energy consumption, with radio frequency links, power amplifiers, baseband processing units (BBUs), and air conditioning systems being the main energy-consuming components. Especially during off-peak hours (such as late at night), if base stations operate at full power, it leads to substantial energy waste.

[0003] Currently, base station energy-saving technologies mainly include static energy-saving schemes and dynamic energy-saving schemes. Although they have achieved energy-saving effects to a certain extent, there are still problems such as response lag and impact on service quality. Summary of the Invention

[0004] This invention was developed to at least partially address the technical problems of existing base station energy-saving technologies, such as response lag and impact on service quality.

[0005] According to one aspect of the present invention, a cell state adaptive adjustment method is provided, comprising: Obtain current service data of the cell and determine the current service load level of the cell based on the service data; wherein, the service load level is divided into multiple levels, each service load level corresponds to at least one working mode, and the higher the service load level, the higher the power consumption of the corresponding working mode. From the working modes corresponding to the current service load level of the cell, select the working mode that meets the preset QoS constraints and has the lowest current estimated energy consumption as the current optimal working mode of the cell and put it into operation. In each subsequent scheduling cycle, it is determined whether the cell state needs to be switched based on the preset switching conditions; if the cell state needs to be switched, the cell working mode is changed step by step according to the cell state switching direction and put into operation; if the cell state does not need to be switched, the current cell working mode is maintained.

[0006] Optionally, obtaining the current service data of the cell and determining the current service load level of the cell based on the service data includes: Get the current service throughput of the cell; Obtain the average service throughput of the cell during the same historical period, where the historical period refers to the historical time period corresponding to the current moment; The current service load level of the cell is determined based on the current service throughput of the cell and the average service throughput of the cell during the same period in history.

[0007] Optionally, determining the current service load level of the cell based on the current service throughput of the cell and the historical average service throughput of the cells during the same period includes: If T(t) ≥ 1.2 × T his If L(t) is a high load level, then L(t) is determined to be a high load level. If 0.5×T his (t) <T(t)<1.2×T his If L(t) is a medium load level, then L(t) is determined to be a medium load level. If T(t)≤0.5×T his If L(t) is a low load level, then L(t) is determined to be a low load level. Where T(t) is the cell traffic throughput at time t, and t is the current time; T his (t) represents the average cell traffic throughput over the historical time period corresponding to time t, and T his (t)>0; L(t) is the service load level of the cell at time t.

[0008] Optionally, each service load level corresponds to at least one working mode, specifically: If the current service load level of the community is high load level, the corresponding working mode is full working mode; If the current service load level of the cell is medium load level, the corresponding working modes include secondary carrier shutdown mode and power saving mode, and the power consumption of secondary carrier shutdown mode is higher than that of power saving mode. If the current service load level of the cell is low load level, the corresponding working modes include cell DRX mode, air interface silent mode, deep sleep mode and complete shutdown mode, and the power consumption of cell DRX mode, air interface silent mode, deep sleep mode and complete shutdown mode decreases in that order.

[0009] Optionally, selecting the working mode that meets preset QoS constraints and has the lowest estimated energy consumption from the working modes corresponding to the current service load level of the cell, and putting it into operation as the current optimal cell working mode, includes: In response to the current high load level of the service in the cell, the full working mode is directly selected as the optimal working mode for the cell and put into operation. In response to the current service load level of the cell being medium load level, the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption is selected from the secondary carrier shutdown mode and energy-saving power mode as the current optimal cell working mode and put into operation. In response to the current low load level of the cell, if the load level is predicted to rise to the medium load level within a preset time window in the future, the working mode that meets the preset QoS constraints and has the lowest current estimated energy consumption is selected from the secondary carrier shutdown mode and the energy-saving power mode as the current optimal cell working mode and put into operation. In response to the current low-load level of the cell's service load, if the predicted service load level will remain at a low-load level within a preset time window, it is determined whether the neighboring cells of this cell meet the preset neighboring cell coordination conditions. If the neighboring cell coordination conditions are met, the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption among the air interface silent mode, deep sleep mode, and complete shutdown mode is selected as the current optimal cell working mode and put into operation. If the air interface silent mode, deep sleep mode, and complete shutdown mode do not meet the preset QoS constraints, the cell DRX mode is directly selected as the current optimal cell working mode and put into operation. If the neighboring cell coordination conditions are not met, it is further determined whether the cell meets the preset admission conditions. If the admission conditions are met, the air interface silent mode is directly selected as the current optimal cell working mode and put into operation. If the admission conditions are not met, the cell DRX mode is directly selected as the current optimal cell working mode and put into operation.

[0010] Optionally, the neighbor cell coordination conditions are divided into first neighbor cell coordination conditions and second neighbor cell coordination conditions. The air interface silent mode and deep sleep mode correspond to the first neighbor cell coordination conditions, and the complete shutdown mode corresponds to the second neighbor cell coordination conditions. The determination of whether the neighboring cells of this cell meet the preset neighboring cell cooperation conditions includes: Calculate the collaborative carrying capacity factor of all neighboring cells to this cell, and select neighboring cells whose collaborative carrying capacity factor exceeds a preset threshold. Then, accumulate the service capacity of the selected neighboring cells. If the accumulated service capacity can cover the current service capacity of this cell, it is determined that the neighboring cells of this cell meet the first neighboring cell collaboration condition; if the accumulated service capacity cannot cover the current service capacity of this cell, it is determined that the neighboring cells of this cell do not meet the first neighboring cell collaboration condition. Calculate the collaborative carrying capacity factor of all neighboring cells to this cell, and screen out neighboring cells whose collaborative carrying capacity factor exceeds a preset threshold. Then, accumulate the service capacity of the screened neighboring cells. If the accumulated service capacity can reach the preset redundancy ratio of the current service capacity of this cell, it is determined that the neighboring cells of this cell meet the second neighboring cell collaboration condition; if the accumulated service capacity cannot reach the preset redundancy ratio of the current service capacity of this cell, it is determined that the neighboring cells of this cell do not meet the second neighboring cell collaboration condition. The admission criteria include: the fast wake-up monitoring mechanism has been activated, and the confidence level of predicting that the load will remain at a low load level within a preset time window is higher than a preset confidence threshold.

[0011] Optionally, the formula for calculating the collaborative carrying capacity factor is as follows:

[0012] in, The collaborative carrying capacity factor of neighboring cell j to cell i; Let be the overlap coverage capability factor of neighboring cell j to cell i, and The value range is from 0 to 1, which is used to indicate the degree of overlap between the coverage area of ​​neighboring cell j and the coverage area of ​​this cell i; The load of the current neighboring cell j; This represents the distance between the geographic center of cell i and the neighboring cell j, or the channel propagation distance. This is the distance attenuation coefficient.

[0013] Optionally, the method further includes: If none of the working modes corresponding to the current service load level of the cell meet the preset QoS constraints, the working mode corresponding to the next higher load level is selected as the optimal working mode for the cell, which meets the preset QoS constraints and has the lowest estimated energy consumption. If the working mode corresponding to the next higher load level does not meet the preset QoS constraints, then continue to float to the working mode corresponding to the next higher load level and select the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption as the current optimal cell working mode. This process continues until the working mode corresponding to the highest load level is selected and the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption is selected as the current optimal cell working mode. If none of the operating modes corresponding to the highest load level meet the preset QoS constraints, the operating mode with the highest power consumption will be taken as the current optimal cell operating mode, and load balancing will be triggered or an overload alarm will be sent to the network management system.

[0014] Optionally, the operating mode corresponding to the current service load level of the cell is selected as a candidate operating mode, and the current energy consumption of the cell under each candidate operating mode is calculated using the following formula:

[0015] in, For time t, the cell is in candidate working mode The energy consumption is shown below, where t is the current time. For the community in the candidate work mode The corresponding static power consumption; This represents the current PRB usage rate in the community. For the community in the candidate work mode Maximum permissible transmit power; For the efficiency of the community power amplifier; Let be the cooling energy consumption function, representing the ambient temperature of the community cooling system at time t. and candidate job modes The energy required to maintain stable operation of the equipment.

[0016] Optionally, the formula for calculating the cooling energy consumption function is as follows:

[0017] in, This is a function of cooling energy consumption; Let t be the ambient temperature. In candidate working mode The minimum temperature threshold for starting the cooling system in the next residential area; In candidate working mode The maximum allowable power of the cooling system in the lower residential area; This is the temperature regulation coefficient for the community's cooling system.

[0018] Optionally, the QoS constraint is:

[0019] in, The working mode corresponding to the current service load level of the community The following service quality indicators; This is a preset acceptable range for service quality, and it corresponds to the type of service quality indicator.

[0020] Optionally, the step of determining whether a cell state needs to be switched based on preset switching conditions; responding to the need to switch the cell state, progressively changing the cell operating mode according to the cell state switching direction and putting it into operation; responding to the need not to switch the cell state, maintaining the current cell operating mode, includes: Determine whether the cell meets the first handover condition or the second handover condition; wherein, the first handover condition includes the predicted load of the cell in the future preset time window being lower than a preset low load threshold, and if the working mode corresponding to the current state of the cell after sinking one level needs to consider the preset neighbor cell coordination condition, then the neighbor cells of the cell meet the neighbor cell coordination condition; the second handover condition includes the predicted load of the cell in the future preset time window being higher than a preset high load threshold, and the high load threshold being greater than the low load threshold, or the current access failure rate of the cell being greater than a preset failure rate threshold, and the current call drop rate of the cell being greater than a preset call drop rate threshold; If the cell meets the first handover condition, the cell's current state will be downgraded by one level, so that it can switch from the current working mode to the next level of working mode with lower power consumption and put it into operation, until the working mode with the lowest power consumption is reached. If the cell meets the second handover condition, the cell's current state will be raised one level, switching it from the current working mode to the next higher level working mode with higher power consumption and putting it into operation, until the working mode with the highest power consumption is reached. If the cell does not meet either the first handover condition or the second handover condition, then the cell's current working mode will be maintained.

[0021] Optionally, the method further includes: If the cell meets the first handover condition or the second handover condition, determine whether the cell meets the preset anti-jump mechanism; wherein, the anti-jump mechanism includes the duration of the current state of the cell being greater than the minimum dwell time threshold under the current working mode of the cell, and the number of cell working mode switching times per unit time not exceeding the preset upper limit of the number of switching times. If the cell meets the aforementioned anti-jump mechanism, the cell working mode will be changed step by step according to the cell state switching direction and put into operation; If the current cell does not meet the anti-jump mechanism, then the current cell operating mode will be maintained.

[0022] According to another aspect of the present invention, a cell state adaptive adjustment device is provided, comprising: The service load level determination module is configured to acquire the current service data of the cell and determine the current service load level of the cell based on the service data; wherein, the service load level is divided into multiple levels, each service load level corresponds to at least one working mode, and the higher the service load level, the higher the power consumption of the corresponding working mode. The optimal working mode selection module is configured to select the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption from the working modes corresponding to the current service load level of the cell, and put it into operation as the current optimal cell working mode. The cell state switching module is configured to determine whether a cell state needs to be switched based on preset switching conditions in each subsequent scheduling cycle; in response to the need to switch the cell state, it changes the cell working mode step by step according to the cell state switching direction and puts it into operation; in response to the need not to switch the cell state, it maintains the current cell working mode.

[0023] According to another aspect of the present invention, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes the aforementioned cell state adaptive adjustment method.

[0024] According to another aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor performs the aforementioned cell state adaptive adjustment method.

[0025] The technical solution provided by this invention may include the following beneficial effects: The cell state adaptive adjustment method and apparatus provided by this invention establishes a positive correspondence between different service load levels and cell operating modes with different power consumption, ensuring that the selection of operating modes always matches actual service needs. This avoids energy waste caused by running high-power operating modes under low load. The method uses QoS constraints as a hard screening condition and the lowest estimated energy consumption as the optimization goal to select operating modes, ensuring that the selected energy-saving mode does not sacrifice user experience. At the same time, through continuous monitoring and handover condition judgment in subsequent scheduling cycles, the method can dynamically optimize the operating mode according to the time changes of service load, effectively shortening the response delay between load changes and operating mode adjustments, avoiding response lag problems, and thus achieving timely and effective energy-saving control while ensuring service quality.

[0026] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims and drawings. Attached Figure Description

[0027] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the technical solutions of the present invention, and do not constitute a limitation on the technical solutions of the present invention.

[0028] Figure 1 A flowchart illustrating a cell state adaptive adjustment method provided in an embodiment of the present invention; Figure 2A flowchart illustrating another cell state adaptive adjustment method provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of the cell state adaptive adjustment device provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the specific implementation methods of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific implementation methods described herein are for illustration and explanation only and are not intended to limit the present invention.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a set order or sequence; furthermore, in the absence of conflict, the embodiments and features in the embodiments of this invention can be arbitrarily combined with each other. In the following description, the use of suffixes such as "module," "component," or "unit" to represent elements is only for the convenience of the description of this invention and has no inherent meaning. Therefore, "module," "component," or "unit" can be used interchangeably.

[0031] Among related technologies, base station energy-saving technologies mainly include: Static energy-saving solutions save energy during the base station deployment or initial configuration phase by reducing radio frequency transmission power, reducing the number of carriers, and shutting down some equipment modules. The dynamic energy-saving scheme automatically adjusts the base station's operating status based on real-time service load, including shutting down some carriers when there is less service, and retaining only the main carrier to carry signaling and a small amount of data.

[0032] However, the above-mentioned base station energy-saving technologies have the following drawbacks: Delayed Response: Both static and dynamic energy-saving solutions suffer from varying degrees of response lag. Static energy-saving solutions cannot detect fluctuations in user service load in real time and often implement shutdown or power reduction strategies based on preset time periods, lacking flexibility. While dynamic energy-saving solutions can detect current service load, they lack the ability to predict future service trends, and still face the risk of response lag.

[0033] Energy saving and service quality conflict: Static energy saving schemes and dynamic energy saving schemes will both cause access failures or a decline in user experience if there is a sudden increase in business after the community is shut down or the power is reduced.

[0034] Lack of network coordination: Both static and dynamic energy-saving schemes lack coordination strategies between different communities, which can easily lead to uneven load or service blind spots.

[0035] To address the aforementioned problems, this invention provides a cell state adaptive adjustment scheme that can dynamically adjust the cell state according to changes in service load, achieving energy-saving control of "on-demand operation, load awareness, and rapid recovery," reducing cell energy consumption, and improving the overall network energy efficiency. A detailed description is provided below through specific embodiments.

[0036] Figure 1 This is a flowchart illustrating a cell state adaptive adjustment method provided in an embodiment of the present invention. Figure 1 As shown, the method includes the following steps S101 to S103, which are repeatedly executed in each scheduling cycle.

[0037] S101. Obtain the current service data of the cell, and determine the current service load level of the cell based on the service data.

[0038] The service load level is divided into multiple levels, and each service load level corresponds to at least one working mode. The higher the service load level, the higher the power consumption of the corresponding working mode.

[0039] S102. From the working modes corresponding to the current service load level of the cell, select the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption as the current optimal cell working mode and put it into operation.

[0040] S103. In each subsequent scheduling cycle, determine whether it is necessary to switch the cell state based on the preset switching conditions; if it is necessary to switch the cell state, change the cell working mode step by step according to the cell state switching direction and put it into operation; if it is not necessary to switch the cell state, maintain the current cell working mode.

[0041] In this embodiment, a positive correlation is established between different service load levels and cell operating modes with different power consumption. This ensures that the selection of the operating mode always matches the actual service needs, avoiding energy waste caused by running a high-power operating mode under low load. The operating mode selection is based on QoS (Quality of Service) constraints as a hard screening condition and the optimization goal of minimizing estimated energy consumption. This ensures that the selected energy-saving mode does not sacrifice user experience. At the same time, through continuous monitoring and switching condition judgment in subsequent scheduling cycles, the operating mode can be dynamically optimized according to the time changes of service load. This effectively shortens the response delay between load changes and operating mode adjustments, avoiding response lag problems. Thus, timely and effective energy-saving control is achieved while ensuring service quality.

[0042] In one specific embodiment, step S101 includes the following steps S1011 to S1013.

[0043] S1011. Obtain the current service throughput of the cell; S1012. Obtain the average service throughput of the cell during the same historical period, wherein the same historical period is the historical time period corresponding to the current moment; S1013. Determine the current service load level of the cell based on the current service throughput of the cell and the average service throughput of the cell in the same historical period.

[0044] In this embodiment, the load level is determined by comparing the current throughput with the historical average for the same period. Since the historical average reflects the baseline level of normal business volume in the same period, using it as a reference can eliminate the interference caused by the inherent differences in business volume in different periods on the load determination, making the load level determination result more reasonable.

[0045] In one specific embodiment, step S1013 specifically includes: If T(t) ≥ 1.2 × T his If L(t) is a high load level, then L(t) is determined to be a high load level. If 0.5×T his (t) <T(t)<1.2×T his If L(t) is a medium load level, then L(t) is determined to be a medium load level. If T(t)≤0.5×T his If L(t) is the load level, then L(t) is determined to be a low load level.

[0046] Where T(t) is the cell traffic throughput at time t, and t is the current time; T his (t) represents the average cell traffic throughput over the historical time period corresponding to time t, and T his (t)>0; L(t) is the service load level of the cell at time t.

[0047] In this embodiment, by dividing the load status into multiple continuous intervals with no overlap between them, it is ensured that the load status at any given time corresponds to a unique and definite load level, avoiding the uncertainty of the load level caused by the fuzzy classification boundary, and providing a clear basis for the selection of subsequent working modes.

[0048] In one specific implementation, each service load level corresponds to at least one working mode, specifically: If the current service load level of the community is high load level, the corresponding working mode is full working mode; If the current service load level of the cell is medium load level, the corresponding working modes include secondary carrier shutdown mode and power saving mode, and the power consumption of secondary carrier shutdown mode is higher than that of power saving mode. If the current service load level of the cell is low load level, the corresponding working modes include cell DRX mode, air interface silent mode, deep sleep mode and complete shutdown mode, and the power consumption of cell DRX mode, air interface silent mode, deep sleep mode and complete shutdown mode decreases in that order.

[0049] The modes are as follows: Full Operating Mode (M1): All carriers, BBU (Building Baseband Unit), and RF (Radio Frequency) units are enabled, transmitting at full power to provide 100% capacity, with the highest power consumption. Secondary Carrier Shutdown Mode (M2): All or some secondary carriers are disabled, while the primary carrier, BBU, and RF units remain operational, preserving full coverage but reducing peak capacity. Energy-Saving Power Mode (M3): Transmit power is reduced, all functional units (such as BBU and RF units) remain online, and no carriers are disabled, but coverage is reduced in exchange for lower power consumption. Cell DRX (Discontinuous Reception) Mode (M4): RF units periodically sleep and wake up, reducing average power consumption by intermittently shutting down RF units, while still serving low-speed services. Air Interface Silent Mode (M5): RF units are completely powered down, the BBU retains core network connectivity, and there is no signal transmission on the air interface, supporting millisecond-level fast wake-up. Deep Sleep Mode (M6): BBU and RF units are completely asleep, with only the monitoring module receiving power; recovery time is longer. Complete shutdown mode (M7): After the services of this cell are transferred to the neighboring cell, the entire station is powered off, relying on the neighboring cell to carry the services.

[0050] In this embodiment, a complete "load level - operating mode" mapping table is formed by corresponding high, medium, and low load levels to different power consumption levels of operating mode sets, and arranging the operating modes within each set in descending order of power consumption. This mapping table covers seven progressive levels from full operation to complete shutdown, ensuring that the system has a clear range of operating modes to choose from under any load condition. Once the load level is determined, the set of operating modes is also determined, narrowing the search space for subsequent energy consumption comparisons.

[0051] In one specific embodiment, step S102 specifically includes the following steps S1021 to S1024.

[0052] S1021. In response to the current service load level of the cell being high load level, the full working mode is directly selected as the optimal working mode for the cell and put into operation; S1022. In response to the current service load level of the cell being medium load level, select the working mode that meets the preset QoS constraints and has the lowest current estimated energy consumption from the secondary carrier shutdown mode and energy saving power mode, and put it into operation as the current optimal cell working mode. S1023. In response to the current service load level of the cell being low, if it is predicted that the service load level will rise to medium load level within a preset time window in the future, the working mode that meets the preset QoS constraints and has the lowest current estimated energy consumption is selected from the secondary carrier shutdown mode and the energy-saving power mode as the current optimal cell working mode and put into operation. S1024. In response to the current service load level of the cell being low, if the predicted service load level will remain at a low load level within a preset time window, then determine whether the neighboring cells of this cell meet the preset neighboring cell coordination conditions. If the neighboring cell coordination conditions are met, then select the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption from the air interface silent mode, deep sleep mode, and complete shutdown mode as the current optimal cell working mode and put it into operation. If the air interface silent mode, deep sleep mode, and complete shutdown mode do not meet the preset QoS constraints, then directly select the cell DRX mode as the current optimal cell working mode and put it into operation. If the neighboring cell coordination conditions are not met, then further determine whether this cell meets the preset admission conditions. If the admission conditions are met, then directly select the air interface silent mode as the current optimal cell working mode and put it into operation. If the admission conditions are not met, then directly select the cell DRX mode as the current optimal cell working mode and put it into operation.

[0053] This embodiment provides specific selection rules for the optimal operating mode under different load levels. Specifically, for high load levels, the full operating mode is directly selected to avoid unnecessary computational overhead; for medium load levels, the optimal mode is selected after a comprehensive comparison of energy consumption and QoS between the secondary carrier shutdown mode and the energy-saving power mode; for low load levels, branching processing is performed based on the load prediction results. When the predicted load is expected to rebound, the secondary carrier shutdown mode or the energy-saving power mode is still selected to avoid premature entry into the deep energy-saving mode, which would lead to insufficient service capacity when services rebound; when the predicted load is expected to remain at a low load level, the neighbor cell cooperation conditions and admission conditions are evaluated first, and the system enters the air interface silent mode, deep sleep mode, or complete shutdown mode only if the corresponding conditions are met. If none of these conditions are met, the system reverts to the cell DRX mode. Through the above branching design, clear judgment criteria and corresponding processing actions are set at each decision node, covering all possible situations from high load to low load, from predicted rebound to predicted low load, and from meeting cooperation conditions to meeting or not meeting admission conditions. This avoids judgment blind spots and ensures that the operating mode selection has a definite and reasonable output result under various conditions.

[0054] In one specific implementation, the neighbor cell coordination conditions are divided into first neighbor cell coordination conditions and second neighbor cell coordination conditions. The air interface silent mode and deep sleep mode correspond to the first neighbor cell coordination conditions, and the complete shutdown mode corresponds to the second neighbor cell coordination conditions.

[0055] The determination of whether the neighboring cells of this cell meet the preset neighboring cell cooperation conditions includes: Calculate the collaborative carrying capacity factor of all neighboring cells to this cell, and select neighboring cells whose collaborative carrying capacity factor exceeds a preset threshold. Then, accumulate the service capacity of the selected neighboring cells. If the accumulated service capacity can cover the current service capacity of this cell, it is determined that the neighboring cells of this cell meet the first neighboring cell collaboration condition; if the accumulated service capacity cannot cover the current service capacity of this cell, it is determined that the neighboring cells of this cell do not meet the first neighboring cell collaboration condition. Calculate the collaborative carrying capacity factor of all neighboring cells to this cell, and select neighboring cells whose collaborative carrying capacity factor exceeds a preset threshold. Then, accumulate the service capacity of the selected neighboring cells. If the accumulated service capacity can reach the preset redundancy ratio of the current service capacity of this cell, it is determined that the neighboring cells of this cell meet the second neighboring cell collaboration condition; if the accumulated service capacity cannot reach the preset redundancy ratio of the current service capacity of this cell, it is determined that the neighboring cells of this cell do not meet the second neighboring cell collaboration condition.

[0056] In this embodiment, by dividing the neighbor cell collaboration conditions into first and second levels, and making M5 and M6 correspond to the first neighbor cell collaboration condition (cumulative value covers the current business volume) and M7 correspond to the second neighbor cell collaboration condition (cumulative value reaches the preset redundancy ratio), the energy-saving mode of different depths corresponds to the neighbor cell collaboration requirements of different strictnesses, thereby expanding the scope of application of the energy-saving mode as much as possible while ensuring service continuity.

[0057] In one specific implementation, the admission criteria include: the fast wake-up monitoring mechanism has been activated, and the confidence level that the load will remain at a low load level within a preset time window is higher than a preset confidence threshold.

[0058] In this embodiment, by setting admission conditions (fast wake-up monitoring mechanism is activated + prediction confidence is higher than the threshold), an alternative entry path is provided for M5 mode when neighbor cell collaboration is insufficient. This allows the system to enter M5 mode to save energy when the neighbor cell load is high and cannot take on services.

[0059] In one specific embodiment, the formula for calculating the collaborative carrying capacity factor is as follows:

[0060] in, The collaborative carrying capacity factor of neighboring cell j to cell i; Let be the overlap coverage capability factor of neighboring cell j to cell i, and The value range is from 0 to 1, which is used to indicate the degree of overlap between the coverage area of ​​neighboring cell j and the coverage area of ​​cell i. The load of the current neighboring cell j; This represents the distance between the geographic center of cell i and the neighboring cell j, or the channel propagation distance. This is the distance attenuation coefficient.

[0061] In this embodiment, the cooperative capability of neighboring cells to this cell is quantified as an overlapping coverage capability factor. Neighboring cell load and distance decay factor Among them, the overlap coverage capability factor reflects the physical basis that neighboring cells can spatially compensate for the current cell, the neighboring cell load reflects the remaining resources currently available in the neighboring cell, and the distance attenuation factor reflects the wireless propagation law that the cooperative effect decreases with increasing distance. By calculating the cooperative carrying capacity factor through these three factors, the cooperative capability of neighboring cells can be quantified into a comparable value, which can be used to subsequently determine whether neighboring cells are qualified to undertake the services of the current cell, so that the entry judgment of deep energy saving mode has a verifiable quantitative basis.

[0062] In one specific embodiment, step S102 further includes the following steps S1025 to S1027.

[0063] S1025. If none of the working modes corresponding to the current service load level of the cell meet the preset QoS constraints, the working mode corresponding to the next higher load level is selected as the optimal working mode of the cell that meets the preset QoS constraints and has the lowest estimated energy consumption. S1026. If the working mode corresponding to the next higher load level does not meet the preset QoS constraints, then continue to float to the working mode corresponding to the next higher load level and select the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption as the current optimal cell working mode. This process continues until the working mode corresponding to the highest load level is selected and the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption is selected as the current optimal cell working mode. S1027. If none of the operating modes corresponding to the highest load level meet the preset QoS constraints, the operating mode with the highest power consumption will be taken as the current optimal cell operating mode, and load balancing will be triggered or an overload alarm will be sent to the network management system.

[0064] In this embodiment, a tiered escalation mechanism is implemented. When all operating modes corresponding to the current load level fail to meet QoS constraints, the search scope is progressively expanded to the set of operating modes corresponding to a higher load level until a working mode that meets QoS requirements and has the lowest energy consumption is found. This tiered escalation mechanism ensures that when no suitable operating mode is available due to overly strict QoS constraints at low load levels, the system can proactively improve service capabilities instead of continuously maintaining a state that does not meet QoS requirements. If escalation to the highest load level (i.e., full operating mode) still fails to meet QoS constraints, the system is determined to be in an overload state, triggering load balancing or an alarm, providing a clear handling path for extreme cases.

[0065] In one specific implementation, the operating mode corresponding to the current service load level of the cell is taken as a candidate operating mode, and the current energy consumption of the cell under each candidate operating mode is calculated using the following formula:

[0066] in, For time t, the cell is in candidate working mode The energy consumption is shown below, where t is the current time. For the community in the candidate work mode The corresponding static power consumption; The current PRB (Physical Resource Block) utilization rate of the cell; For the community in the candidate work mode Maximum permissible transmit power; For the efficiency of the community power amplifier; Let be the cooling energy consumption function, representing the ambient temperature of the community cooling system at time t. and candidate job modes The energy required to maintain stable operation of the equipment.

[0067] In this embodiment, the total energy consumption of a cell under a certain operating mode is divided into three components: static power consumption, transmission power consumption, and cooling power consumption. Mathematical relationships are established between these components and the operating mode, PRB utilization rate, and ambient temperature. Static power consumption varies with the operating mode, reflecting the difference in the minimum energy consumption required to maintain operation under different modes. Transmission power consumption incorporates PRB utilization rate, maximum transmission power, and power amplifier efficiency in its calculation, reflecting the changes in actual transmission energy consumption with resource occupancy rate and the upper limit of transmission power for each mode. Cooling power consumption incorporates ambient temperature as an influencing factor, making energy consumption estimation under high-temperature conditions more accurate.

[0068] In one specific embodiment, the formula for calculating the cooling energy consumption function is as follows:

[0069] in, This is a function of cooling energy consumption; Let t be the ambient temperature. In candidate working mode The minimum temperature threshold for starting the cooling system in the next residential area; In candidate working mode The maximum allowable power of the cooling system in the lower residential area; This is the temperature regulation coefficient for the community's cooling system.

[0070] In this embodiment, a piecewise calculation formula for cooling energy consumption clarifies the quantitative relationship between cooling energy consumption and ambient temperature: when the ambient temperature is below or equal to the start-up threshold, the cooling system does not work and energy consumption is zero; when the ambient temperature exceeds the start-up threshold, cooling energy consumption increases linearly with temperature, with the maximum cooling power as the upper limit. This formula simultaneously considers three factors: ambient temperature, the start-up threshold of the cooling system corresponding to the operating mode, and the maximum cooling power. Furthermore, it clearly separates the zero energy consumption before start-up from the linear growth region after start-up through a piecewise function, consistent with the operating characteristics of the cooling system in actual equipment. Since the start-up threshold varies with the operating mode—for example, it is higher in low-power mode and the cooling system is less likely to start, while it is lower in high-power mode and the cooling system intervenes earlier—this aligns with the physical law of differences in heat generation between different modes.

[0071] In one specific implementation, the QoS constraint is:

[0072] in, The working mode corresponding to the current service load level of the community The following service quality indicators; This is a preset acceptable range for service quality, and it corresponds to the type of service quality indicator.

[0073] In this embodiment, by expressing QoS constraints as service quality indicators falling within a preset acceptable range, the constraints can be uniformly applied to different types of QoS indicators. For indicators such as access failure rate and call drop rate, where lower values ​​are better, the acceptable range is expressed as an upper limit constraint; for indicators such as throughput, where higher values ​​are better, the acceptable range is expressed as a lower limit constraint.

[0074] In one specific embodiment, step S103 specifically includes the following steps S1031 to S1034.

[0075] S1031. In each subsequent scheduling cycle, determine whether the cell meets the first handover condition or the second handover condition.

[0076] The first handover condition includes that the predicted load of the cell in the future preset time window is lower than a preset low load threshold, and if the working mode corresponding to the current state of the cell after sinking one level needs to consider the preset neighbor cell coordination condition, then the neighbor cells of the cell meet the neighbor cell coordination condition. The second handover condition includes that the predicted load of the cell in the future preset time window is higher than a preset high load threshold, and the high load threshold is greater than the low load threshold, or the current access failure rate of the cell is greater than a preset failure rate threshold, and the current call drop rate of the cell is greater than a preset call drop rate threshold.

[0077] S1032. If the cell meets the first handover condition, the cell's current state is downgraded by one level, so that it is switched from the current working mode to the next level of working mode with lower power consumption and put into operation, until the working mode with the lowest power consumption is reached.

[0078] S1033. If the cell meets the second handover condition, the current state of the cell is raised one level, so that it is switched from the current working mode to the next higher level working mode with higher power consumption and put into operation, until the working mode with the highest power consumption is reached.

[0079] S1034. If the cell does not meet either the first handover condition or the second handover condition, then the cell's current working mode shall be maintained.

[0080] In this embodiment, by setting the state sinking condition as a combination of predicted load being below a low threshold and neighbor cell coordination conditions being met, the sinking decision considers both future load trends and service continuity assurance, avoiding blind sinking due to temporarily low predicted load that could lead to subsequent neighbor cells being unable to take over. Setting the state floating condition as an OR logic combination of predicted load being above a high threshold and QoS anomaly triggering allows the system to proactively avoid service congestion through prediction (proactive floating) and also to urgently recover when QoS has deteriorated (responsive floating), with the two mechanisms complementing each other. Simultaneously, the setting of a high threshold being greater than a low threshold creates a hysteresis interval between the two triggering conditions, preventing frequent handovers when predicted load fluctuates between the high and low thresholds.

[0081] In one specific embodiment, step S103 further includes the following steps S1035 to S1037.

[0082] S1035. If the cell meets the first handover condition or the second handover condition, determine whether the cell meets the preset anti-flipping mechanism.

[0083] The anti-jump mechanism includes a current state duration longer than the minimum dwell time threshold under the current working mode of the cell, and a preset number of cell working mode switching times per unit time not exceeding a preset upper limit of switching times.

[0084] S1036. If the cell meets the aforementioned anti-jump mechanism, the cell working mode will be changed step by step according to the cell state switching direction and put into operation.

[0085] S1037. If the current cell does not meet the anti-jump mechanism, then the current cell operating mode shall be maintained.

[0086] In this embodiment, two anti-jump rules—a minimum dwell time constraint and an upper limit on the number of switches per unit time—jointly limit the rhythm of state switching from both time and frequency dimensions. The minimum dwell time constraint ensures that the system has sufficient stabilization time after each switch, avoiding back-and-forth switching caused by short-term load fluctuations; the upper limit on the number of switches ensures that the total number of switches within any unit time is controllable, avoiding frequent oscillations caused by the superposition of multiple reasonable switches in long-term operation. The two rules apply to the minimum interval of a single switch and the upper limit of the total number of cumulative switches, respectively, complementing each other and jointly maintaining the long-term stability of the system state and the reliability of equipment operation.

[0087] The cell state adaptive adjustment method provided in this invention establishes a positive correlation between service load levels and power consumption in the working mode, ensuring that the selection of the working mode always matches actual service needs. This avoids energy waste caused by running a high-power mode under low load. Based on this, the initial mode selection uses service quality constraints as a hard screening condition and the lowest estimated energy consumption as the optimization objective, ensuring that the selected working mode achieves energy saving without degrading user experience. Furthermore, through continuous monitoring and switching condition judgment in subsequent scheduling cycles, the system can adjust the working mode in a timely manner according to changes in service load, effectively shortening the response delay from load change to mode adjustment. This provides a deep energy-saving mode for low-load scenarios. The system further introduces a collaborative carrying capacity factor based on three factors: overlapping coverage capability, neighboring cell load, and propagation distance. It also introduces an admission condition based on a rapid wake-up monitoring mechanism and prediction confidence level. This provides a verifiable quantitative basis for entering the deep energy-saving mode. When multiple candidate modes fail to meet service quality constraints, a step-by-step floating mechanism ensures service availability and triggers load balancing or alarms in case of extreme overload, providing a clear handling path for abnormal situations. At the same time, by constraining the minimum dwell time during state switching and setting an upper limit on the number of switching times per unit time, it avoids the adverse effects of frequent mode oscillations on network stability and equipment lifespan. Thus, it achieves timely, stable, and effective energy-saving control while ensuring service quality.

[0088] Figure 2 This is a flowchart illustrating another cell state adaptive adjustment method provided in an embodiment of the present invention. Figure 2 As shown, the method includes the following steps S201 to S205.

[0089] S201. Business load perception and classification.

[0090] Dynamically acquire current service data of the community, including: Current service throughput of the cell, T(t) (in Mbps); The number of physical resource blocks currently active in the cell, PRB(t); Average service throughput of the community during the same historical period (T) his (t) (unit: Mbps).

[0091] Then, based on the current service throughput T(t) of the cell, the current service load level of the cell is classified (high, medium, low): If T(t) ≥ 1.2 × T his If L(t) = L(t), then L(t) represents a high load level. If 0.5×T his (t) <T(t)<1.2×T his If L(t) is a medium load level, then L(t) represents the medium load level. If T(t)≤0.5×T his If L(t) is a low load level, then L(t) is a low load level.

[0092] Where T(t) is the current service throughput of the cell; T his (t) represents the average cell service throughput over the historical time period corresponding to the current time t, and T his (t)>0; L(t) is the current service load level of the cell.

[0093] S202. Energy consumption estimation model construction.

[0094] This step is to estimate the cell power consumption under different scheduling strategies, so as to provide data for the subsequent selection of the optimal scheduling strategy (operating mode).

[0095] Get the current working mode M of the cell i (e.g., full power, partial carrier shutdown, deep sleep, etc.), current service load level of the cell L(t), current ambient temperature Temp(t).

[0096] The formula is constructed to estimate the cell's current operating mode M. i Total energy consumption :

[0097] The parameters are defined as follows: : The community in working mode The corresponding static power consumption is the minimum power consumption required to maintain operation even without transmitting signals, including the total energy consumption of continuously operating units such as the cell main control board, transmission module, clock, and monitoring.

[0098] Current PRB usage rate in the community.

[0099]

[0100] Where PRB(t) is the number of currently active physical resource blocks; PRB max This represents the total number of PRBs available for data transmission under the current cell bandwidth (the specific value depends on the bandwidth size, such as 100 PRBs for 20MHz).

[0101] : The community in working mode The maximum permissible transmit power is measured in watts (W), for example, 43 dBm ≈ 20 W. The maximum transmit power limit may vary depending on the operating mode; for example, the maximum permissible transmit power decreases when the carrier is turned off.

[0102] Cell power amplifier efficiency refers to the efficiency with which a power amplifier in a cell converts electrical energy into radio frequency signal energy. It reflects how much of the input power is effectively used for signal transmission, while the rest is wasted as heat. It is usually around 10% to 20%.

[0103] Ccooling(): Cooling energy consumption function. The higher the ambient temperature, the higher the cooling energy consumption. Cooling energy consumption refers to the energy consumption of cooling systems such as air conditioners or fans in community equipment under the current ambient temperature and operating mode M. i The energy required to maintain stable operation of equipment is usually strongly correlated with ambient temperature.

[0104] The formula for calculating the cooling energy consumption function is as follows:

[0105] The parameters are defined as follows: Temp(t): Current ambient temperature (which can be measured by a local temperature sensor).

[0106] Temp threshold (M i ): In working mode M i Below this, the minimum temperature threshold for starting the community's cooling system (e.g., 28°C) is set; cooling is not required below this temperature. Furthermore, different operating modes M... i The minimum temperature thresholds differ.

[0107] Cooling max (Mi ): In working mode M i Below, the maximum allowable power of the community's cooling system (e.g., an air conditioner with a power of 1000 W). Different operating modes M i The maximum allowable power varies depending on the specific operating mode and must be determined based on the actual heat generation and heat dissipation requirements of the equipment, and calibrated by actual measurement of the equipment.

[0108] η c The temperature regulation coefficient of the community cooling system represents the additional power required by the community cooling system (in W / °C) for every 1°C increase in ambient temperature. It needs to be measured and calibrated.

[0109] Among them, when the ambient temperature Temp(t) is lower than or equal to the minimum temperature threshold Temp for starting the cooling system threshold (M i When the ambient temperature (Temp) exceeds the minimum temperature threshold (Temp) for activating the cooling system, the cooling system is not activated and the cooling energy consumption is 0. threshold (M i When the temperature is at that point, the cooling energy consumption increases linearly with temperature, and then increases with the cooling rate. max (M i () is the upper limit.

[0110] After estimating the energy consumption for each working mode, the system can select the working mode with the lowest energy consumption without affecting service quality.

[0111] This step outputs: estimated energy consumption for each operating mode. .

[0112] S203. Adaptive scheduling of cell operating status.

[0113] The purpose of this step is to dynamically select the optimal cell operating mode (such as full on / partial hibernation / deep hibernation) based on the current business load level, estimated energy consumption under each operating mode, and ambient temperature, without compromising service quality, in order to achieve energy saving.

[0114] The working modes include: M = {M1, M2, ..., M} n}

[0115] The specific descriptions of each working mode are shown in Table 1 below.

[0116] Table 1

[0117] The following decision calculation will be performed, and the final output will be: which working mode to select for running the cell.

[0118] First, construct the objective function. It is used to identify the lowest energy consumption mode among all operating modes.

[0119]

[0120] At the same time, the following QoS constraints must be met:

[0121] in, Indicates working mode Service quality indicators such as: user access failure rate, user disconnection rate, throughput requirements, maximum allowed user waiting time, etc. This refers to the acceptable range of service quality, and different types of service quality indicators correspond to different acceptable ranges of service quality.

[0122] The purpose of employing the above QoS constraints is to ensure that user experience or service continuity are not sacrificed for energy conservation. QoS constraints can also be abstracted into a single comprehensive indicator or multiple boundary conditions.

[0123] For example, if disabling the secondary carrier in a certain operating mode would affect the data rate, then it cannot be enabled when there are many users or when data services are busy; if a certain operating mode causes the user access failure rate to be higher than 10%, it must also be excluded.

[0124] The specific decision-making logic is described below: If the current service load level L(t) of the cell is high load level: Only full working mode (M1) can be selected; Else if the current service load level L(t) of the cell is medium load level: You can choose between secondary carrier shutdown mode (M2) or power saving mode (M3). Else if the current service load level L(t) of the cell is low load level: If it is predicted that the load will rise to a medium load level within a preset window (e.g., 10 minutes), you can choose the secondary carrier shutdown mode (M2) or the power saving mode (M3). If the load level is predicted to remain low within a preset window (e.g., 10 minutes), it is determined whether the neighboring cells of this cell meet the neighboring cell coordination conditions (see subsequent step S204). If the neighboring cell coordination conditions are met, the air interface silent mode (M5), deep sleep mode (M6), or complete shutdown mode (M7) can be selected. If the neighboring cell coordination conditions are not met, it is further determined whether the admission conditions are met (see subsequent step S204). If the admission conditions are met, the air interface silent mode (M5) can be selected. If the admission conditions are not met, it is floated to the cell DRX mode (M4).

[0125] Based on the above decision-making logic, the candidate working modes corresponding to the current service load level of the community can be determined.

[0126] For each candidate working mode M i : Calculate its energy consumption ; Determine whether it meets the QoS constraints; Select the working mode that meets the QoS constraints and has the lowest estimated energy consumption from the candidate working modes.

[0127] It should be noted that when the current service load level L(t) of the community is high load level, only the full working mode (M1) can be selected, and its estimated energy consumption... It is not used as a basis for selecting the working mode, but only for recording. Moreover, even if the full working mode (M1) cannot meet its QoS constraints, it cannot be downgraded for energy saving. It must be forced to stay in M1 mode and trigger the load balancing / alarm mechanism.

[0128] When the current service load level L(t) of the cell is medium or low, the working mode that meets the QoS constraints and has the lowest estimated energy consumption can be selected from the corresponding candidate working mode set. Further, if the working mode with the lowest estimated energy consumption in the candidate working mode set corresponding to the current service load level of the cell does not meet the QoS constraints, this working mode is removed from the candidate working mode set, and a new working mode with the lowest energy consumption and meeting the QoS constraints is selected from the remaining candidate working modes in the set. If all working modes in the candidate working mode set do not meet the QoS constraints, it is determined that there is no available energy-saving working mode for the current service load level of the cell, and it is necessary to forcibly float up to the candidate working mode set corresponding to the next higher load level for a new working mode selection (for example, if M4 / M5 modes are unqualified at low load, then it is upgraded to M2 / M3 modes corresponding to medium load for reselection). If the QoS constraints still cannot be met even after floating up to M1 mode, load balancing is triggered or an overload alarm is issued to the network management system.

[0129] The purpose of this step is to identify the optimal operating mode. The service load level L(t) participates in the decision-making process by influencing parameters such as throughput and access latency in the QoS constraints. That is, the higher the load level, the more severe the QoS degradation in low-power mode, and the easier it is to eliminate the affected mode. The ambient temperature Temp(t) affects the cooling energy consumption C under different operating modes. cooling This changes the energy consumption estimates for each operating mode, indirectly influencing the selection of the optimal operating mode. Ultimately, the current workload level, estimated energy consumption, and ambient temperature all work together on the objective function to ensure that the selected operating mode achieves the lowest energy consumption while meeting the service quality threshold.

[0130] S204. Neighboring cell coordinated adjustment.

[0131] Neighbor cell coordination adjustment strategy is a strategy that must be considered to address the impact on network connectivity, coverage and load caused by working modes such as "air interface silence", "deep hibernation" or "complete shutdown" (M5, M6 or M7). The purpose is to ensure that the overall network availability and user experience are not negatively affected by energy-saving operations in local cells.

[0132] The reason for neighbor cell coordinated adjustment is that in mild energy-saving modes (such as secondary carrier shutdown mode M2, energy-saving power mode M3, cell DRX mode M4, etc.), the impact on coverage is small, and users can still access the network normally, generally without the need for coordination. However, in deep energy-saving modes (such as air interface silent mode M5, deep hibernation mode M6, complete shutdown mode M7, etc.), because the cell stops radio broadcasting or is completely powered off, users cannot register, initiate service access, or complete handover, which will cause "coverage holes" or "handover failures." It is necessary to assess the carrying capacity of neighbor cells in advance. Therefore, neighbor cell coordinated scheduling is to solve the network risks brought about by deep energy-saving modes, not to say that all operating modes need coordination.

[0133] The effects of the neighboring cell collaborative adjustment strategy are shown in Table 2 below: Table 2

[0134] Here is a specific example: Suppose there are three macro cells, such as cell A, cell B, and cell C. At night, cell A decides to enter deep sleep mode (because there is almost no service in the coverage area). If cell A is shut down directly, existing users in cell A will lose service and be forced to switch to neighboring cells. If cells B and C have not adjusted their parameters in advance, they will not be able to support all new users in time, resulting in some users experiencing access failures or dropped calls. However, if cell B activates its secondary carrier in advance, cell C increases its transmit power, and adjusts its core network handover parameters, then cell A's sleep process is safe and controllable, and will not lead to a decline in network service quality.

[0135] To quantify neighbor cell collaboration capabilities, this step introduces a neighbor cell collaboration carrying capacity factor, which measures the extent to which neighbor cell j can assist cell i in carrying its services.

[0136] The formula for calculating the neighboring cell collaborative carrying capacity factor is as follows:

[0137] The parameters in the above formula are explained in Table 3 below: Table 3

[0138] in, The value ranges from 0 to 1. The closer it is to 1, the higher the degree of overlap. It can be obtained by statistical analysis of coverage simulation, drive test data or MR measurement reports reported by UE.

[0139] Coverage simulation method: Calculates the proportion of overlapping coverage area to the coverage area of ​​the current cell based on the coverage radius and inter-cell spacing of each cell. Specifically, it calculates the proportion of overlapping coverage area to the coverage area of ​​the current cell based on the coverage radius and inter-cell spacing of two cells.

[0140]

[0141] in, Let i be the overlapping area of ​​the coverage areas of cell i and cell j. Let i be the total coverage area of ​​cell i.

[0142] MR measurement statistics: This method involves statistically analyzing the ratio of a UE's ability to simultaneously receive signals from two cells at the same location. Specifically, in a real network, this can be obtained through statistics from the MR data reported by the UE.

[0143]

[0144] in, This represents the total number of sampling points within the effective coverage area of ​​cell i (e.g., RSRP ≥ -120dBm). This refers to the number of sampling points in the total sampling points that are located at the same geographical location (such as having the same latitude and longitude, or being within the same grid) and can simultaneously receive signals from cell i and cell j (both of which have an RSRP greater than or equal to -120dBm).

[0145] When the air interface silent mode (M5) is the working mode that meets the preset QoS constraints and has the lowest current energy consumption among the working modes corresponding to the current service load level of the cell, the neighboring cell cooperative carrying capacity factor w of all neighboring cells j to cell i will be calculated. ij If there exist several neighboring cells j that satisfy the neighboring cell collaborative carrying capacity factor w ij When the threshold is exceeded (e.g., 0.7), the system presses w. ij The available service capacity (w) of these neighboring areas j is accumulated sequentially from high to low. ij(×remaining available capacity of neighboring cell j), until the accumulated value of the service capacity is sufficient to cover the current service capacity of cell i (i.e., neighboring cell coordination condition). If the accumulation is successful, the neighboring cell coordination condition is met, indicating that the current service of this cell can be taken over by neighboring cells, and this cell can enter the air interface silent mode (M5). If the accumulation fails, it means that the neighbor cell coordination conditions are not met, indicating that the current services of this cell cannot be taken over by neighbor cell coordination. Since the RF unit retains the core network connection and has a short wake-up delay (hundreds of milliseconds) even though it is powered off in M5 mode, the system can still enter M5 mode, but the following two admission conditions must be met simultaneously: ① The fast wake-up monitoring mechanism has been activated, that is, after the RF unit is powered off, the baseband processing unit maintains the ability to listen for core network paging messages and uplink random access preambles. When a paging message, user random access request, or service volume recovery trend is detected for this cell, the RF unit is automatically triggered to power on and resume service; ② The confidence level of predicting that the load will remain at a low load level within the preset window is higher than the preset confidence threshold (e.g., 80%). If the accumulation fails and the two admission conditions cannot be met at the same time, this cell should not enter the air interface silent mode (M5) and should float up to the cell DRX mode (M4).

[0146] When the deep sleep mode (M6) is the working mode that meets the preset QoS constraints and has the lowest current energy consumption among the current service load levels of the cell, the neighbor cell cooperative carrying capacity factor w of all neighbor cells j to cell i will be calculated. ij If there exist several neighboring regions j that satisfy the neighboring region collaborative carrying capacity factor w ij When the threshold is exceeded (e.g., 0.7), the system presses w. ij The available service capacity (w) of these neighboring areas j is accumulated sequentially from high to low. ij (×Remaining available capacity of neighboring cell j), until the accumulated value of the service capacity is sufficient to cover the current service capacity of cell i (i.e., neighboring cell coordination condition). If the accumulation is successful, the neighboring cell coordination condition is met, indicating that the current service of this cell can be taken over by neighboring cell coordination, and this cell can enter deep dormancy mode (M6); if the accumulation is unsuccessful, the neighboring cell coordination condition is not met, indicating that the current service of this cell cannot be taken over by neighboring cell coordination, and this cell cannot enter deep dormancy mode (M6), but instead is evaluated according to the two admission conditions of the aforementioned M5 mode. If both admission conditions can be met at the same time, it will float up to the air interface silent mode (M5); if both admission conditions cannot be met at the same time, it will continue to float up to the cell DRX mode (M4).

[0147] When the complete shutdown mode (M7) is the working mode that meets the preset QoS constraints and has the lowest current energy consumption among the current service load levels of the cell, the neighboring cell cooperative carrying capacity factor w of all neighboring cells j to cell i will be calculated. ij If there exist several neighboring regions j that satisfy the neighboring region collaborative carrying capacity factor wij When the threshold is exceeded (e.g., 0.7), the system presses w. ij The available service capacity (w) of these neighboring areas j is accumulated sequentially from high to low. ij The cumulative capacity of neighboring cell j is calculated until it is sufficient to cover the current service volume of cell i and reaches the preset redundancy ratio of the current service volume of cell i, such as 1.2 times (i.e., the neighboring cell coordination condition). If the accumulation is successful, the neighboring cell coordination condition is met, indicating that the current service of this cell can be taken over by the neighboring cell. At the same time, the core network needs to complete the handover parameter adjustment to ensure that users can seamlessly hand over to the target neighboring cell after a complete shutdown. Then, this cell can enter the complete shutdown mode (M7). If the accumulation is unsuccessful, the neighboring cell coordination condition is not met, indicating that the current service of this cell cannot be taken over by the neighboring cell. Then, this cell cannot enter the shutdown mode (M7) and instead evaluates according to the two admission conditions of the aforementioned M5 mode. If both admission conditions can be met at the same time, it will float up to the air interface silent mode (M5). If both admission conditions cannot be met at the same time, it will continue to float up to the cell DRX mode (M4).

[0148] In this step, the neighbor cell coordination mechanism is based on the neighbor cell carrying capacity factor w. ij The judgment is based on whether neighboring areas have sufficient business carrying capacity when the community plans to enter the deep energy-saving mode (M5, M6, M7).

[0149] S205. Cell status switching and recovery.

[0150] In multi-mode energy consumption optimization in residential communities, the system selects a certain energy-saving operating mode (such as power reduction, deep sleep, etc.) based on the estimated load. However, communication networks are dynamic, and service load fluctuates over time, such as a sudden increase in users or a surge in data traffic, while the cell is still in a low-power or sleep state. Therefore, the purpose of this step is to intelligently adjust the cell state (sinking down, saving energy, and waking up) based on the real-time changes in the cell's service load in each scheduling cycle, without affecting network service quality. In particular, it is necessary to be able to quickly respond to sudden increases in service and avoid a decline in user experience. Therefore, it is necessary to implement an intelligent, responsive, jitter-resistant, QoS-aware state switching and recovery control system for multi-state cell energy-saving strategies.

[0151] This step periodically collects the core parameters shown in Table 4 below as input: Table 4

[0152] Determine whether "cell status decline" or "cell status rise" is allowed based on a set of joint conditions.

[0153] A. The cell status is downgraded (switching to a lower energy consumption state).

[0154] Triggering conditions (all must be met): 1) < λ low This indicates that the predicted load is low, where λ low A low load threshold (e.g., PRB occupancy rate <20%) is used to determine whether the service load will be low enough to support cell state downsizing in the future. 2) If the current working mode of the community after sinking to level 1 is M5, M6, or M7, then the neighbor cell coordination condition must be met (i.e., the neighbor cell's capacity to take over is sufficient); if it is another working mode, then the neighbor cell's capacity to take over does not need to be considered.

[0155] Whether the neighboring cell collaboration conditions are met is determined by referring to the neighboring cell collaboration carrying capacity factor cumulative evaluation method in step S204.

[0156] If both of the above conditions are met, the cell state changes from M. i →M i+1 Among them, predicting a future time window based on historical load data ( The load change trend within the region is analyzed, and the prediction results are used as a reference for state adjustment.

[0157] Cell B status has been restored (returned to high-performance state).

[0158] Triggering conditions (any one of them must be met): 1) > λ high This indicates a surge in business, where λ high A high load threshold (e.g., PRB utilization > 60%) is used to determine whether the business load is about to surge in the future, and λ low <λ high ; 2) QoS anomaly driver: R fail (t)>R th Or R drop (t)>D th , where R th It is the access failure rate threshold (e.g., 2%), D th It is the call drop rate threshold (e.g., 1%).

[0159] If either of the above two conditions is met, the cell state changes from M. i →M i-1 (At most, it can be restored to M1).

[0160] In this step, the energy-saving solution includes multiple energy-saving operating states and state switching logic. The state switching is based on the predicted service load, the duration of the current state, the neighbor cell coordination capability, and QoS indicators.

[0161] Furthermore, to prevent frequent transitions, the following mechanism is designed: 1) Hysteresis time control: T idle >T min (M i This indicates that the current state lasts long enough, where T min (M i ) represents the current working mode M i The minimum dwell time threshold, i.e., how long one must remain in this working mode before being allowed to switch working modes again, and the scheduling period is less than T. min (M i ).

[0162] It should be noted that, under any circumstances, if the current working mode's duration does not exceed the corresponding minimum dwell time threshold T, the cell will remain operational. min (M i If the specified condition is met, then switching working modes is not allowed.

[0163] 2) Frequency limiting during state transition: Number of working mode switching times per unit time ≤ f max To ensure state stability and prevent "oscillations" during switching, f is the system's preset upper limit for the number of working mode switching times per unit time, such as no more than 3 times per hour.

[0164] In this step, a state hysteresis time control threshold and a maximum switching frequency control threshold are set to suppress frequent state changes.

[0165] The cell state adaptive adjustment method provided in this embodiment of the invention has the following special design and beneficial effects: 1) Multi-mode energy-saving state model design: The cell is divided into multiple working modes (such as full working, secondary carrier off, energy saving power, cell DRX, air interface silent, deep sleep, complete shutdown, etc.), and each working mode has a clear power consumption model and service load level division; 2) Load forecast-based state switching decision mechanism: Predict future business load and use the load forecast results to make state switching decisions, improve foresight and avoid switching lag; 3) Neighboring cell collaboration capability assessment mechanism: Calculate the collaborative carrying capacity factor between this cell and its neighboring cells, and only allow this cell to sink its status when the neighboring cells have sufficient carrying capacity, so as to avoid service blind spots; 4) QoS constraint mechanism: Introduce QoS indicators such as access failure rate and call drop rate as one of the conditions for state floating (recovery) to ensure that critical user experience is not affected during energy saving; 5) State switching hysteresis and frequency control mechanism: To avoid frequent oscillations, the state hysteresis time and switching frequency upper limit are set to ensure the stable and orderly operation of the energy-saving strategy.

[0166] The cell state adaptive adjustment method reduces energy consumption to the greatest extent without affecting service quality by sensing service load in real time and performing hierarchical power control, hibernation of some functional modules, and dynamic shutdown / wake-up operations on the cell.

[0167] Figure 3 This is a schematic diagram of the cell state adaptive adjustment device provided in an embodiment of the present invention. Figure 3 As shown, the device includes: a service load level determination module 301, an optimal working mode selection module 302, and a cell state switching module 303.

[0168] The service load level determination module 301 is configured to acquire the current service data of the cell and determine the current service load level of the cell based on the service data; wherein the service load level is divided into multiple levels, each service load level corresponds to at least one working mode, and the higher the service load level, the higher the power consumption of the corresponding working mode. The optimal working mode selection module 302 is configured to select the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption from the working modes corresponding to the current service load level of the cell, and put it into operation as the current optimal cell working mode. The cell state switching module 303 is configured to determine whether a cell state needs to be switched based on preset switching conditions in each subsequent scheduling cycle; in response to the need to switch the cell state, it changes the cell working mode step by step according to the cell state switching direction and puts it into operation; in response to the need not to switch the cell state, it maintains the current cell working mode.

[0169] In one specific implementation, the service load level determination module 301 includes a first acquisition unit, a second acquisition unit, and a determination unit.

[0170] The first acquisition unit is configured to acquire the current service throughput of the cell; the second acquisition unit is configured to acquire the average service throughput of the cell in the same historical period, wherein the historical period is the historical time period corresponding to the current moment; and the determination unit is configured to determine the current service load level of the cell based on the current service throughput of the cell and the average service throughput of the cell in the same historical period.

[0171] In one specific implementation, the determining unit is specifically configured as follows: If T(t) ≥ 1.2 × T his If L(t) is a high load level, then L(t) is determined to be a high load level. If 0.5×T his(t) <T(t)<1.2×T his If L(t) is a medium load level, then L(t) is determined to be a medium load level. If T(t)≤0.5×T his If L(t) is a low load level, then L(t) is determined to be a low load level. Where T(t) is the cell traffic throughput at time t, and t is the current time; T his (t) represents the average cell traffic throughput over the historical time period corresponding to time t, and T his (t)>0; L(t) is the service load level of the cell at time t.

[0172] In one specific implementation, each service load level corresponds to at least one working mode, specifically: If the current service load level of the community is high load level, the corresponding working mode is full working mode; If the current service load level of the cell is medium load level, the corresponding working modes include secondary carrier shutdown mode and power saving mode, and the power consumption of secondary carrier shutdown mode is higher than that of power saving mode. If the current service load level of the cell is low load level, the corresponding working modes include cell DRX mode, air interface silent mode, deep sleep mode and complete shutdown mode, and the power consumption of cell DRX mode, air interface silent mode, deep sleep mode and complete shutdown mode decreases in that order.

[0173] In one specific implementation, the optimal working mode selection module 302 includes a first selection unit, a second selection unit, a third selection unit, and a fourth selection unit.

[0174] The first selection unit is configured to respond to the current service load level of the cell being high load level, and directly select the full working mode as the current optimal cell working mode and put it into operation. The second selection unit is configured to select, in response to the current service load level of the cell being medium load level, the working mode that meets the preset QoS constraints and has the lowest current estimated energy consumption from the secondary carrier shutdown mode and energy-saving power mode, and put it into operation as the current optimal cell working mode. The third selection unit is configured to, in response to the current service load level of the cell being low, if the service load level is predicted to rise to medium load level within a preset time window in the future, select the working mode that meets the preset QoS constraints and has the lowest current estimated energy consumption from the secondary carrier shutdown mode and energy-saving power mode, and put it into operation as the current optimal cell working mode. The fourth selection unit is configured to respond to a low-load level of the current service load of the cell. If the predicted service load level will remain at a low load level within a preset time window, it will determine whether the neighboring cells of this cell meet the preset neighboring cell coordination conditions. If the neighboring cell coordination conditions are met, it will select the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption from the air interface silent mode, deep sleep mode, and complete shutdown mode as the current optimal cell working mode and put it into operation. If the air interface silent mode, deep sleep mode, and complete shutdown mode do not meet the preset QoS constraints, it will directly select the cell DRX mode as the current optimal cell working mode and put it into operation. If the neighboring cell coordination conditions are not met, it will further determine whether the cell meets the preset admission conditions. If the admission conditions are met, it will directly select the air interface silent mode as the current optimal cell working mode and put it into operation. If the admission conditions are not met, it will directly select the cell DRX mode as the current optimal cell working mode and put it into operation.

[0175] In one specific implementation, the neighbor cell coordination conditions are divided into first neighbor cell coordination conditions and second neighbor cell coordination conditions. The air interface silent mode and deep sleep mode correspond to the first neighbor cell coordination conditions, and the complete shutdown mode corresponds to the second neighbor cell coordination conditions.

[0176] The fourth selection unit determines whether the neighboring cells of this cell meet the preset neighboring cell coordination conditions, specifically: Calculate the collaborative carrying capacity factor of all neighboring cells to this cell, and select neighboring cells whose collaborative carrying capacity factor exceeds a preset threshold. Then, accumulate the service capacity of the selected neighboring cells. If the accumulated service capacity can cover the current service capacity of this cell, it is determined that the neighboring cells of this cell meet the first neighboring cell collaboration condition; if the accumulated service capacity cannot cover the current service capacity of this cell, it is determined that the neighboring cells of this cell do not meet the first neighboring cell collaboration condition. Calculate the collaborative carrying capacity factor of all neighboring cells to this cell, and screen out neighboring cells whose collaborative carrying capacity factor exceeds a preset threshold. Then, accumulate the service capacity of the screened neighboring cells. If the accumulated service capacity can reach the preset redundancy ratio of the current service capacity of this cell, it is determined that the neighboring cells of this cell meet the second neighboring cell collaboration condition; if the accumulated service capacity cannot reach the preset redundancy ratio of the current service capacity of this cell, it is determined that the neighboring cells of this cell do not meet the second neighboring cell collaboration condition. The admission criteria include: the fast wake-up monitoring mechanism has been activated, and the confidence level of predicting that the load will remain at a low load level within a preset time window is higher than a preset confidence threshold.

[0177] In one specific embodiment, the formula for calculating the collaborative carrying capacity factor is as follows:

[0178] in, The collaborative carrying capacity factor of neighboring cell j to cell i; Let be the overlap coverage capability factor of neighboring cell j to cell i, and The value range is from 0 to 1, which is used to indicate the degree of overlap between the coverage area of ​​neighboring cell j and the coverage area of ​​cell i. The load of the current neighboring cell j; This represents the distance between the geographic center of cell i and the neighboring cell j, or the channel propagation distance. This is the distance attenuation coefficient.

[0179] In one specific implementation, the optimal working mode selection module 302 further includes a fifth selection unit, a sixth selection unit, and a seventh selection unit.

[0180] The fifth selection unit is configured to select the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption from the working modes corresponding to the next higher load level when none of the working modes corresponding to the current service load level of the cell meet the preset QoS constraints. This working mode is then selected as the current optimal working mode for the cell. The sixth selection unit is set to select the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption when floating up to the next higher load level. This process continues until the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption is selected when floating up to the highest load level. This process continues until the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption is selected as the current optimal cell working mode. The seventh selection unit is set to take the working mode with the highest power consumption as the current optimal cell working mode if none of the working modes corresponding to the highest load level meet the preset QoS constraints, and to trigger load balancing or send an overload alarm to the network management system.

[0181] In one specific implementation, the operating mode corresponding to the current service load level of the cell is taken as a candidate operating mode, and the current energy consumption of the cell under each candidate operating mode is calculated using the following formula:

[0182] in, For time t, the cell is in candidate working mode The energy consumption is shown below, where t is the current time. For the community in the candidate work mode The corresponding static power consumption; This represents the current PRB usage rate in the community. For the community in the candidate work mode Maximum permissible transmit power; For the efficiency of the community power amplifier; Let be the cooling energy consumption function, representing the ambient temperature of the community cooling system at time t. and candidate job modes The energy required to maintain stable operation of the equipment.

[0183] In one specific embodiment, the formula for calculating the cooling energy consumption function is as follows:

[0184] in, This is a function of cooling energy consumption; Let t be the ambient temperature. In candidate working mode The minimum temperature threshold for starting the cooling system in the next residential area; In candidate working mode The maximum allowable power of the cooling system in the lower residential area; This is the temperature regulation coefficient for the community's cooling system.

[0185] In one specific implementation, the QoS constraint is:

[0186] in, The working mode corresponding to the current service load level of the community The following service quality indicators; This is a preset acceptable range for service quality, and it corresponds to the type of service quality indicator.

[0187] In one specific implementation, the cell state switching module 303 includes a first judgment unit and a switching unit.

[0188] The first judgment unit is configured to determine whether the cell meets a first handover condition or a second handover condition. The first handover condition includes that the predicted load of the cell within a preset future time window is lower than a preset low load threshold, and that if the cell's current state requires consideration of preset neighbor cell coordination conditions after a one-level sink, then the neighbor cells of the cell meet the neighbor cell coordination conditions. The second handover condition includes that the predicted load of the cell within a preset future time window is higher than a preset high load threshold, and that the high load threshold is greater than the low load threshold, or that the cell's current access failure rate is greater than a preset failure rate threshold, and the cell's current call drop rate is greater than a preset call drop rate threshold.

[0189] The handover unit is configured such that if the cell meets the first handover condition, the current state of the cell is shifted down one level, switching it from the current operating mode to the next lower level operating mode with lower power consumption and putting it into operation, until the operating mode with the lowest power consumption is reached; if the cell meets the second handover condition, the current state of the cell is shifted up one level, switching it from the current operating mode to the next higher level operating mode with higher power consumption and putting it into operation, until the operating mode with the highest power consumption is reached; if the cell does not meet either the first handover condition or the second handover condition, the current operating mode of the cell is maintained.

[0190] In one specific implementation, the cell state switching module 303 further includes a second judgment unit.

[0191] The second judgment unit is configured to determine whether the cell meets a preset anti-jump mechanism if the cell meets either the first handover condition or the second handover condition. The anti-jump mechanism includes a current state duration exceeding a minimum dwell time threshold under the current cell operating mode, and a preset upper limit on the number of cell operating mode handovers per unit time.

[0192] The switching unit is also configured to, if the cell meets the anti-jump mechanism, change the cell working mode step by step according to the cell state switching direction and put it into operation; if the cell does not meet the anti-jump mechanism, maintain the current cell working mode.

[0193] The cell state adaptive adjustment device provided in this invention establishes a positive correlation between service load levels and power consumption in the operating mode, ensuring that the selection of the operating mode always matches actual service needs. This avoids energy waste caused by running a high-power mode under low load. Based on this, it uses service quality constraints as a hard screening condition and the lowest estimated energy consumption as the optimization goal for initial mode selection, ensuring that the selected operating mode achieves energy saving without reducing user experience. Simultaneously, through continuous monitoring and switching condition judgment in subsequent scheduling cycles, the system can adjust the operating mode in a timely manner according to changes in service load over time, effectively shortening the response delay from load change to mode adjustment. This provides a deep energy-saving mode for low-load scenarios. The system further introduces a collaborative carrying capacity factor based on three factors: overlapping coverage capability, neighboring cell load, and propagation distance. It also introduces an admission condition based on a rapid wake-up monitoring mechanism and prediction confidence level. This provides a verifiable quantitative basis for entering the deep energy-saving mode. When multiple candidate modes fail to meet service quality constraints, a step-by-step floating mechanism ensures service availability and triggers load balancing or alarms in case of extreme overload, providing a clear handling path for abnormal situations. At the same time, by constraining the minimum dwell time during state switching and setting an upper limit on the number of switching times per unit time, it avoids the adverse effects of frequent mode oscillations on network stability and equipment lifespan. Thus, it achieves timely, stable, and effective energy-saving control while ensuring service quality.

[0194] Based on the same technical concept, embodiments of the present invention also provide a computer device, such as... Figure 4 As shown, the computer device includes a memory 401 and a processor 402. The memory 401 stores a computer program. When the processor 402 runs the computer program stored in the memory 401, the processor 402 executes the aforementioned cell state adaptive adjustment method.

[0195] Based on the same technical concept, this embodiment of the invention also provides a computer-readable storage medium storing a computer program thereon, wherein when the computer program is executed by a processor, the processor executes the aforementioned cell state adaptive adjustment method.

[0196] In summary, the cell state adaptive adjustment method, apparatus, computer equipment, and storage medium provided in this invention can predict sudden surges in services in advance, improving the foresight and accuracy of state switching; a multi-state switching model is established, and by rationally designing energy-saving levels and state hysteresis mechanisms, the problem of frequent switching is effectively suppressed, improving system stability and equipment reliability; by constructing a neighbor cell collaborative weight factor mechanism, cross-base station collaborative adjustment is achieved, improving energy efficiency while ensuring service continuity; by introducing a QoS mechanism, user experience-related indicators are used as one of the triggering conditions for state improvement, ensuring communication quality while achieving base station energy saving.

[0197] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0198] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A cell state adaptive adjustment method, characterized in that, include: Obtain current service data of the cell and determine the current service load level of the cell based on the service data; wherein, the service load level is divided into multiple levels, each service load level corresponds to at least one working mode, and the higher the service load level, the higher the power consumption of the corresponding working mode. From the working modes corresponding to the current service load level of the cell, select the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption as the current optimal working mode of the cell and put it into operation. In each subsequent scheduling cycle, it is determined whether the cell status needs to be switched based on the preset handover conditions; In response to the need to switch cell status, the cell working mode is changed step by step according to the direction of cell status switching and put into operation; in response to the need not to switch cell status, the current cell working mode is maintained.

2. The cell state adaptive adjustment method according to claim 1, characterized in that, The step of obtaining the current service data of the cell and determining the current service load level of the cell based on the service data includes: Get the current service throughput of the cell; Obtain the average service throughput of the cell during the same historical period, where the historical period refers to the historical time period corresponding to the current moment; The current service load level of the cell is determined based on the current service throughput of the cell and the average service throughput of the cell during the same period in history.

3. The cell state adaptive adjustment method according to claim 2, characterized in that, The step of determining the current service load level of a cell based on its current service throughput and the historical average service throughput of cells during the same period includes: If T(t) ≥ 1.2 × T his If L(t) is a high load level, then L(t) is determined to be a high load level. If 0.5×T his (t) <T(t)<1.2×T his If L(t) is a medium load level, then L(t) is determined to be a medium load level. If T(t)≤0.5×T his If L(t) is a low load level, then L(t) is determined to be a low load level. Where T(t) is the cell traffic throughput at time t, and t is the current time; T his (t) represents the average cell traffic throughput over the historical time period corresponding to time t, and T his (t)>0; L(t) is the service load level of the cell at time t.

4. The cell state adaptive adjustment method according to claim 3, characterized in that, Each service load level corresponds to at least one working mode, specifically: If the current service load level of the community is high load level, the corresponding working mode is full working mode; If the current service load level of the cell is medium load level, the corresponding working modes include secondary carrier shutdown mode and power saving mode, and the power consumption of secondary carrier shutdown mode is higher than that of power saving mode. If the current service load level of the cell is low load level, the corresponding working modes include cell DRX mode, air interface silent mode, deep sleep mode and complete shutdown mode, and the power consumption of cell DRX mode, air interface silent mode, deep sleep mode and complete shutdown mode decreases in that order.

5. The cell state adaptive adjustment method according to claim 4, characterized in that, The step of selecting the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption from the working modes corresponding to the current service load level of the cell, and putting it into operation as the current optimal cell working mode, includes: In response to the current high load level of the service in the cell, the full working mode is directly selected as the optimal working mode for the cell and put into operation. In response to the current service load level of the cell being medium load level, the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption is selected from the secondary carrier shutdown mode and energy-saving power mode as the current optimal cell working mode and put into operation. In response to the current low load level of the cell, if the load level is predicted to rise to the medium load level within a preset time window in the future, the working mode that meets the preset QoS constraints and has the lowest current estimated energy consumption is selected from the secondary carrier shutdown mode and the energy-saving power mode as the current optimal cell working mode and put into operation. In response to the current low-load level of the cell's service load, if the predicted service load level will remain at a low-load level within a preset time window, it is determined whether the neighboring cells of this cell meet the preset neighboring cell coordination conditions. If the neighboring cell coordination conditions are met, the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption among the air interface silent mode, deep sleep mode, and complete shutdown mode is selected as the current optimal cell working mode and put into operation. If the air interface silent mode, deep sleep mode, and complete shutdown mode do not meet the preset QoS constraints, the cell DRX mode is directly selected as the current optimal cell working mode and put into operation. If the neighboring cell coordination conditions are not met, it is further determined whether the cell meets the preset admission conditions. If the admission conditions are met, the air interface silent mode is directly selected as the current optimal cell working mode and put into operation. If the admission conditions are not met, the cell DRX mode is directly selected as the current optimal cell working mode and put into operation.

6. The cell state adaptive adjustment method according to claim 5, characterized in that, The neighbor cell coordination conditions are divided into first neighbor cell coordination conditions and second neighbor cell coordination conditions. The air interface silent mode and deep sleep mode correspond to the first neighbor cell coordination conditions, and the complete shutdown mode corresponds to the second neighbor cell coordination conditions. The determination of whether the neighboring cells of this cell meet the preset neighboring cell cooperation conditions includes: Calculate the collaborative carrying capacity factor of all neighboring cells to this cell, and select neighboring cells whose collaborative carrying capacity factor exceeds a preset threshold. Then, accumulate the service capacity of the selected neighboring cells. If the accumulated service capacity can cover the current service capacity of this cell, it is determined that the neighboring cells of this cell meet the first neighboring cell collaboration condition; if the accumulated service capacity cannot cover the current service capacity of this cell, it is determined that the neighboring cells of this cell do not meet the first neighboring cell collaboration condition. Calculate the collaborative carrying capacity factor of all neighboring cells to this cell, and screen out neighboring cells whose collaborative carrying capacity factor exceeds a preset threshold. Then, accumulate the service capacity of the screened neighboring cells. If the accumulated service capacity can reach the preset redundancy ratio of the current service capacity of this cell, it is determined that the neighboring cells of this cell meet the second neighboring cell collaboration condition; if the accumulated service capacity cannot reach the preset redundancy ratio of the current service capacity of this cell, it is determined that the neighboring cells of this cell do not meet the second neighboring cell collaboration condition. The admission criteria include: the fast wake-up monitoring mechanism has been activated, and the confidence level of predicting that the load will remain at a low load level within a preset time window is higher than a preset confidence threshold.

7. The cell state adaptive adjustment method according to claim 6, characterized in that, The formula for calculating the collaborative carrying capacity factor is as follows: in, The collaborative carrying capacity factor of neighboring cell j to cell i; Let be the overlap coverage capability factor of neighboring cell j to cell i, and The value range is from 0 to 1, which is used to indicate the degree of overlap between the coverage area of ​​neighboring cell j and the coverage area of ​​this cell i; The load of the current neighboring cell j; This represents the distance between the geographic center of cell i and the neighboring cell j, or the channel propagation distance. This is the distance attenuation coefficient.

8. The cell state adaptive adjustment method according to claim 1, characterized in that, Also includes: If none of the working modes corresponding to the current service load level of the cell meet the preset QoS constraints, the working mode corresponding to the next higher load level is selected as the optimal working mode for the cell, which meets the preset QoS constraints and has the lowest estimated energy consumption. If the working mode corresponding to the next higher load level does not meet the preset QoS constraints, then continue to float to the working mode corresponding to the next higher load level and select the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption as the current optimal cell working mode. This process continues until the working mode corresponding to the highest load level is selected and the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption is selected as the current optimal cell working mode. If none of the operating modes corresponding to the highest load level meet the preset QoS constraints, the operating mode with the highest power consumption will be taken as the current optimal cell operating mode, and load balancing will be triggered or an overload alarm will be sent to the network management system.

9. The cell state adaptive adjustment method according to claim 1, characterized in that, The current operating mode corresponding to the current service load level of the cell is taken as the candidate operating mode. The current energy consumption of the cell under each candidate operating mode is calculated using the following formula: in, For time t, the cell is in candidate working mode The energy consumption is shown below, where t is the current time. For the community in the candidate work mode The corresponding static power consumption; This represents the current PRB usage rate in the community. For the community in the candidate work mode Maximum permissible transmit power; For the efficiency of the community power amplifier; Let be the cooling energy consumption function, representing the ambient temperature of the community cooling system at time t. and candidate job modes The energy required to maintain stable operation of the equipment.

10. The cell state adaptive adjustment method according to claim 9, characterized in that, The formula for calculating the cooling energy consumption function is as follows: in, This is a function of cooling energy consumption; Let t be the ambient temperature. In candidate working mode The minimum temperature threshold for starting the cooling system in the next residential area; In candidate working mode The maximum allowable power of the cooling system in the lower residential area; This is the temperature regulation coefficient for the community's cooling system.

11. The cell state adaptive adjustment method according to claim 1, characterized in that, The QoS constraints are as follows: in, The working mode corresponding to the current service load level of the community The following service quality indicators; This is a preset acceptable range for service quality, and it corresponds to the type of service quality indicator.

12. The cell state adaptive adjustment method according to claim 1, characterized in that, The system determines whether a cell state needs to be switched based on preset switching conditions; in response to the need to switch cell states, it changes the cell working mode step by step according to the cell state switching direction and puts the cell into operation. In response to the need to switch cell states, the current cell operating mode is maintained, including: Determine whether the cell meets the first handover condition or the second handover condition; wherein, the first handover condition includes the predicted load of the cell in the future preset time window being lower than a preset low load threshold, and if the working mode corresponding to the current state of the cell after sinking one level needs to consider the preset neighbor cell coordination condition, then the neighbor cells of the cell meet the neighbor cell coordination condition; the second handover condition includes the predicted load of the cell in the future preset time window being higher than a preset high load threshold, and the high load threshold being greater than the low load threshold, or the current access failure rate of the cell being greater than a preset failure rate threshold, and the current call drop rate of the cell being greater than a preset call drop rate threshold; If the cell meets the first handover condition, the cell's current state will be downgraded by one level, so that it can switch from the current working mode to the next level of working mode with lower power consumption and put it into operation, until the working mode with the lowest power consumption is reached. If the cell meets the second handover condition, the cell's current state will be raised one level, switching it from the current working mode to the next higher level working mode with higher power consumption and putting it into operation, until the working mode with the highest power consumption is reached. If the cell does not meet either the first handover condition or the second handover condition, then the cell's current working mode will be maintained.

13. The cell state adaptive adjustment method according to claim 12, characterized in that, Also includes: If the cell meets the first handover condition or the second handover condition, determine whether the cell meets the preset anti-jump mechanism; wherein, the anti-jump mechanism includes the duration of the current state of the cell being greater than the minimum dwell time threshold under the current working mode of the cell, and the number of cell working mode switching times per unit time not exceeding the preset upper limit of the number of switching times. If the cell meets the aforementioned anti-jump mechanism, the cell working mode will be changed step by step according to the cell state switching direction and put into operation; If the current cell does not meet the anti-jump mechanism, then the current cell operating mode will be maintained.

14. A cell state adaptive adjustment device, characterized in that, include: The service load level determination module is configured to acquire the current service data of the cell and determine the current service load level of the cell based on the service data; wherein, the service load level is divided into multiple levels, each service load level corresponds to at least one working mode, and the higher the service load level, the higher the power consumption of the corresponding working mode. The optimal working mode selection module is configured to select the working mode that meets the preset QoS constraints and has the lowest estimated energy consumption from the working modes corresponding to the current service load level of the cell, and put it into operation as the current optimal cell working mode. The cell state handover module is configured to determine whether a cell state handover is necessary based on preset handover conditions in each subsequent scheduling cycle. In response to the need to switch cell status, the cell working mode is changed step by step according to the direction of cell status switching and put into operation; in response to the need not to switch cell status, the current cell working mode is maintained.

15. A computer device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes the cell state adaptive adjustment method according to any one of claims 1 to 13.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, the processor performs the cell state adaptive adjustment method according to any one of claims 1 to 13.

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