Processing capacity in a wireless communications network

Abstract

A method performed by a control unit for adapting processing capacity in processing units arranged to serve wireless devices in a wireless communications network is provided. The method comprise obtaining time slot transmission pattern position or scheduling decision for at least one upcoming time slot. Also, the method comprise adapting processing capacity in the processing units at the time of the at least one upcoming time slot based on the required level of data processing at the time of the at least one upcoming time slot indicated by the obtained time slot transmission pattern position or scheduling decision for the at least one upcoming time slot. A control unit is also provided, as well as, computer programs and carriers.

Description

[0001] PROCESSING CAPACITY IN A WIRELESS COMMUNICATIONS NETWORK

[0002] TECHNICAL FIELD

[0003] Embodiments herein relate to processing capacity in a wireless communications network. In particular, embodiments herein relate to a control unit and method therein for adapting processing capacity in processing units arranged to serve wireless devices in a wireless communications network. Further, the embodiments herein also relate to a computer program and a carrier.

[0004] BACKGROUND

[0005] In today’s wireless communications networks a number of different technologies are used, such as, 6G / New Radio (NR), Long Term Evolution (LTE), LTE-Advanced, Wideband Code Division Multiple Access (WCDMA), Global System for Mobile communications / Enhanced Data rate for GSM Evolution (GSM / EDGE), Worldwide Interoperability for Microwave Access (WiMax), or Ultra Mobile Broadband (UMB), just to mention a few possible technologies for wireless communication. A wireless communications network commonly comprises Radio Base Stations, RUs, providing radio coverage over at least one respective geographical area forming a cell. This is commonly referred to as a Radio Access Network (RAN). The RAN is in turn connected to the core network in the wireless communications network via a so-called backhaul network. Wireless devices, also referred to as User Equipments (UEs), mobile stations, and / or wireless terminals, are served in the cells by the respective radio base station and are communicating with respective radio base station in the RAN over an air / radio interface. Commonly, the wireless devices transmit data over the air / radio interface to the radio base stations in uplink (UL) transmissions and the radio base stations transmit data over the air / radio interface to the wireless devices in downlink (DL) transmissions.

[0006] A substantial part of the operating expenses for an operator of a wireless communication network as described above is energy cost. Thus, there is a constant need to reduce the energy consumption in wireless communication networks. In view thereof, it has been noted that the processing resources in a wireless communication networks are normally dimensioned to be able to handle a peak traffic load, even though the traffic load is actually often very low in live wireless communication networks. This means that even if the current traffic load is low or even idle, the power consumption of the processing resources in the wireless communication network may still be substantial. However, for such processing resources in a wireless communication network, such as, e.g. a baseband application being executed on a Baseband Processing Unit (BPU), there are different energy saving techniques for unused processing resources that may be employed to save power in the wireless communication network. One example of such as energy saving technique is normally referred to as scale in / out ar\d is illustrated in Fig. 1. Here, the processing resources, e.g. processing hardware instance A, are scaled by instantiating more or fewer processing hardware instances B with the aim of utilizing as few processing hardware instances as possible, and thus save energy by powering down the unused processing hardware instances. This energy saving technique however reacts quite slowly when the average traffic load is changing. Another example of an energy saving technique is normally referred to scale up / down and is illustrated in Fig. 2. In this case, the processing resources, e.g. processing hardware instance A, are scaled by using more or less processing resources A’ within each hardware instance. This may, for example, be performed by scaling a clock frequency and voltage of a processing resource, which also may be referred to as Dynamic Voltage and Frequency Scaling, DVFS. Another example is to utilize less processing core units within a hardware instance and put unused processing core units in a low power state. These scale up / down energy saving techniques have a significantly shorter re-activation time in the hardware as compared to scale in / out techniques mentioned above.

[0007] However, the question still remains regarding when / how to scale the processing resources in a wireless communications network in order to be able to take full advantage of possible power reduction, while at the same time not compromise the regular operation of the wireless communication network. One way of reducing the energy consumption in a wireless communication network may be to, for example, scale the processing resources in a wireless communication networks based on a prediction of the average load in the wireless communication network.

[0008] Fig. 3 shows an example of how an average traffic load in a wireless communication network may vary over time, e.g. for a week from Monday to Sunday. In this case, however, one problem is that even during a low average load in the wireless communications network, e.g. during non-busy hours, there may still be some wireless devices that burst full throughput for a short periods of time. Thus, a power saving solution that is based on average traffic load predictions may negatively impact the user experience in those wireless devices (e.g. by reducing peak throughput) during those nonbusy hours. Also, extra margins of the enabled processing resources to handle short peaks are needed, which will limit the amount of possible energy savings. Hence, there is a need for improved power saving solutions for wireless communications networks.

[0009] SUMMARY

[0010] It is an object of the present disclosure to mitigate, alleviate or eliminate one or more of the above-identified deficiencies and disadvantages and provide an improved power saving solution for wireless communications networks.

[0011] According to a first aspect of embodiments herein, the object is achieved by a method performed by a control unit for adapting processing capacity in processing units arranged to serve wireless devices in a wireless communications network. The method comprises obtaining time slot transmission pattern position or scheduling decision for at least one upcoming time slot. The method also comprises adapting processing capacity in the processing units at the time of the at least one upcoming time slot based on the required level of data processing at the time of the at least one upcoming time slot indicated by the obtained time slot transmission pattern position or scheduling decision for the at least one upcoming time slot.

[0012] According to a second aspect of embodiments herein, the object is achieved by a control unit for adapting processing capacity in processing units arranged to serve wireless devices in a wireless communications network. The control unit is configured to obtain time slot transmission pattern position or scheduling decision for at least one upcoming time slot. The control unit is also configured to adapt processing capacity in the processing units at the time of the at least one upcoming time slot based on the required level of data processing at the time of the at least one upcoming time slot indicated by the obtained time slot transmission pattern position or scheduling decision for the at least one upcoming time slot.

[0013] According to a third aspect of the embodiments herein, a computer program is also provided configured to perform the method described above. Further, according to a fourth aspect of the embodiments herein, carriers are also provided configured to carry the computer program configured for performing the method described above.

[0014] By obtaining the time slot transmission pattern position for at least one upcoming time slot, the control unit may, when scaling processing resources of processing units in the wireless communications network, utilize the fact that some time-slots in certain transmission patterns have been observed to not require a high level of processing capacity during high traffic loads, and that some time-slots in certain transmission patterns have been observed to require a high level of processing capacity during low traffic loads. Alternatively, in case the hardware of the processing units in the wireless communications network is capable of supporting slot-based scaling, the control unit may, by obtaining a scheduling decision for at least one upcoming time slot, scale the processing resources of the processing units based on the information in the scheduling decision. This enables the control unit to adapt, dynamically or semi-dynamically on a slot or slot group level, the overall processing capacity in the wireless communications network and thus increase the energy efficiency in the wireless communications network by reducing the power consumption. Hence, an improved power saving solution for wireless communications networks is provided.

[0015] BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Features and advantages of the embodiments will become readily apparent to those skilled in the art by the following detailed description of exemplary embodiments thereof with reference to the accompanying drawings, wherein:

[0017] Fig. 1 are schematic illustration of scale in / out,

[0018] Fig. 2 are schematic illustration of scale up / down,

[0019] Fig. 3 illustrates average traffic load cause by wireless devices over a time period,

[0020] Fig. 4 illustrates a wireless communications network comprising a control unit according to some embodiments,

[0021] Fig. 5 illustrates an example of an average data traffic load and a power saving tuning solution according to prior art,

[0022] Fig. 6 illustrates the example of an average data traffic load as shown in Fig. 4 on a slot-level,

[0023] Fig. 7 illustrates another example of a real data traffic load versus an average data traffic load,

[0024] Fig. 8 illustrates an example of estimated data processing timing per time slot for a 4+1 TDD pattern,

[0025] Fig. 9 illustrates processing load measurements per time slot of processing units in a wireless communications network for a 4+1 TDD pattern, Fig. 10 illustrates an example of estimated data processing timing per time slot for a 8+2 TDD pattern,

[0026] Fig. 11 illustrates processing load measurements per time slot of processing units in a wireless communications network for a 8+2 TDD pattern,

[0027] Fig. 12 illustrates simulated data of required processing capacity per time slot for 4+1 and 8+2 TDD patterns,

[0028] Fig. 13 is a flowchart depicting embodiments of a method,

[0029] Fig. 14 illustrates semi-dynamic scaling using time slot-groups for a 4+1 TDD pattern according to some embodiments,

[0030] Fig. 15 illustrates dynamic scaling on a time slot-level according to some embodiments,

[0031] Fig. 16 is a block diagram depicting embodiments of a network entity.

[0032] DETAILED DESCRIPTION

[0033] The figures are schematic and simplified for clarity, and they merely show details which are essential to the understanding of the embodiments presented herein, while other details have been left out. Throughout, the same reference numerals are used for identical or corresponding parts or steps.

[0034] Fig. 4 illustrates a wireless communications system 100 comprising a control unit 101 according to some embodiments described in more detail in the following. The wireless communications system 100 comprises a plurality of processing units or Plls, 102-105, serving a plurality of network nodes, such as, e.g. Radio Units, RUs 106-109, and wireless devices 111-112 in a Radio Access Network, RAN, via a switched fronthaul network 110. Here, it should be noted that the number of PUs and the number of RUs in wireless communications system 100 may be different.

[0035] The Processing Units, PUs 102-105, perform baseband processing at the physical layer, also referred to as Layer 1 (L1) or L1 Phy processing, using a number of processing core units. The Processing Units, PUs 102-105, is connected to the switched fronthaul network 110 and is thus able to transmit and receive data to and from the wireless devices 111 , 112. The Processing Units, PUs 102-105, receives data and information on how the data should be processed from the control unit 101. The Processing Units, PUs 102-105, may be embodied in the form of microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), complex programmable logic devices (CPLDs), etc. As is understood, the Processing Units, PUs 102-105, may be separate chips or implemented as a multi-chip module (MCM).

[0036] The control unit 101 perform data processing at the data link layer, also referred to as Layer 2 (L2) processing. Here, the control unit 101 is configured to control Medium Access Control, MAC, scheduling, as well as, user plane processing, such as, e.g. Medium Access Control User-Plane, MAC UP, processing, Radio Link Control, RLC, processing, and potentially also higher layer processing. Also, the control unit 101 is responsible for scaling decisions for the L1 capacity in the Processing Units, PUs 102- 105, based on the aggregated processing need for all wireless devices 111-112 served by the processing units 102-105. The control unit 101 is configured to control how much L1 capacity in the Processing Units, PUs 102-105, that may be used by the MAC scheduler function. At low traffic loads, the wireless devices 111-112 from many cells are handled using less L1 capacity. As described above, unused capacity may results in lower energy consumption, either by powering down unused processing core units or hardware instances in the Processing Units, PUs 102-105, or by reducing the operating voltage and frequency for the L1 ASICs of the processing units 102-105.

[0037] Here, it should be noted that the control unit 101 and the Processing Units, PUs 102-105, may also be implemented in an Open-Radio Area Network, O-RAN or ORAN. Here, according to one example, the functionality of the control unit 101 may be implemented and operated at the baseband level, e.g. Central / Distributed Unit, CU / DU. In an ORAN implementation, the physical layer processing may be split in two parts wherein the lower layers are part of the radio level, i.e. part of the functionality of the Processing Units, PUs 102-105, may be implemented and operated partly at the same level as the Radio Units, RUs 106-109, and the upper layers are part of the DU, i.e. part of the functionality of the Processing Units, PUs 102-105, may be implemented and operated partly at the same level as the control unit 101. Here, the switched fronthaul network may also be a fronthaul Lower Layer Split, LLS, network or interface, and be either internal or external. Optionally, the functionality of the control unit 101 may also be implemented in one or more network nodes in the wireless communications network 100 using appropriate cloud or virtualization technologies.

[0038] As part of the developing of the embodiments described herein, it has been realized that conventionally the PUs 102-105 serving the RUs 106-109 and the wireless device 111-112 are selected to have a sufficient capacity for performing the baseband processing during a peak traffic load scenario for the wireless device 111-112. However, during a high average traffic load in the wireless communications network 100, e.g. during busy hours, it has been detect and realized that not all time slots are used at 100% capacity. Fig. 5 shows an example of an average traffic load 501 and how a power saving solution 502 that is based on the average traffic load according to the prior art as described above may behave, while Fig. 6 shows an example of how the actual traffic load may appear on a slot-level for the same average traffic load 501 as shown in Fig. 5. This illustrates that a power saving tuning solution that is based on average traffic load predictions may miss the opportunity to save power during short periods of low load, e.g. time slots 601 , which means that no power is saved when the average traffic load is high. Further, such a power saving tuning solution may also restrict the peak load time slots, e.g. time slot 602, which will have a negative impact on the performance in the wireless communications network 100. It should also be noted that the real data traffic on a slotlevel is normally very bursty as shown in Fig. 7, wherein an example of a real data traffic load per time slot 701 for 500 time-slots is shown versus the average load 702 over the same 500 time slots.

[0039] This issue is addressed by the embodiments herein by capturing the variation in required hardware processing resources on a time slot level and / or time slot group level, and then use this information in order to reduce energy consumption in the wireless communications network during short periods of low load. To perform said capture, some embodiments may use the current time slot transmission pattern position for at least one upcoming time slot. This may be referred to as semi-dynamic scaling, since it may operate on several time slots and uses the nature of the current time slot transmission pattern, e.g. a Time Division Duplex, TDD, pattern. Here, it has been realized that it is possible to determine whether a time slot is processing heavy or not based on the current TDD pattern. Thus, for the time slots that have very low amount of data to process, it is possible to reduce energy used by hardware resources, even in busy hours to save energy. For example, Fig. 8 shows an example of estimated data processing timing per time slot for a 4+1 TDD pattern, also referred to as TDDpattern2. It should be noted that the start and stop of processing time slot data for each of the time slots are here just exemplary and may be longer or shorter. In the example of Fig. 9, the data processing for the UL time slot 801 starts sometime after the UL air interface time slot U. The data processing for each of the DL time slots 802-804, has to be finished before each respective DL air interface time slot D1-D3 starts. Due to this nature of processing timing according to this 4+1 TDD pattern, it may be seen that the third DL air interface time slot D3 is a time slot with a low processing load, as indicated by the dashed area in Fig. 8. Fig 9 shows processing load measurements per time slot of Processing Units, PUs 102-105, in a wireless communications network 100 for a 4+1 TDD pattern during a busy hour time of a high loaded site. This confirms that the third DL air interface time slot D3 is a time slot with a low processing load as estimated above with reference to Fig. 8. Similarly, Fig. 10 shows an example of estimated data processing timing per time slot for a 8+2 TDD pattern, also referred to as TDDpatternl. Here, it may be seen that, due to the nature of processing timing according to this 8+2 TDD pattern, the seventh DL air interface time slot D7 together with the special time slot S are time slots with a low processing load, as indicated by the dashed area in Fig. 10. Fig 11 shows processing load measurements per time slot of Processing Units, PUs 102-105, in a wireless communications network 100 for a 8+2 TDD pattern during a busy hour time of a high loaded site. This confirms that the seventh DL air interface time slot D7 together with the special time slot S are time slots with a low processing load as estimated above with reference to Fig. 10. Additionally, Fig. 12 shows simulated data of required processing capacity per time slot for 4+1 (shown in the upper part of Fig. 12) and 8+2 TDD patterns (shown in the lower part of Fig. 12). This simulated data further supports of the fact that, even with full processing capacity load, there will be predictable time slots with low processing loads (indicated by the dashed areas in Fig. 12) due to the nature of the data processing timing of the current time slot transmission pattern, e.g. one or more TDD patterns.

[0040] Optionally, some embodiments may use the scheduling decision for at least one upcoming time slot. This may be referred to as dynamic scaling, since it operates on a single time slot basis. In this case, for each upcoming time slot, the scheduling decision for that time slot is used to only activate the hardware resources required in that particular time slot. Here, unused hardware processing cores may be powered down, or L1 processing may be scaled down using DVFS, for the upcoming time slot in order to save energy. In some embodiments, the semi-dynamic and dynamic scaling referred to above may also be combined. Here, it should also be noted that for some generations of certain hardware, the scaling may be performed fast enough to support dynamic time slot-based scaling, while in other generations of certain hardware the scaling is slightly slower but may yet still support semi-dynamic scaling during a couple of time slots.

[0041] Hence, the embodiments described herein advantageously increases the energy efficiency on time slot level, or time slot group level, by adjusting the processing capability of the available hardware resources in the wireless communications network based on scheduling decisions, transmission patterns and measured traffic load.

[0042] Examples of embodiments of a method performed by a control unit 101 for adapting processing capacity in Processing Units, PUs 102-105, arranged to serve wireless devices 111, 112 in a wireless communications network 100, will now be described with reference to the flowchart depicted in Fig. 13. Fig. 13 is an illustrated example of actions or operations which may be taken by the control unit 101 in the in a wireless communications network 100 shown in Fig. 4. The method may comprise the following actions.

[0043] Action 1301

[0044] The control unit 101 obtains time slot transmission pattern position or scheduling decision for at least one upcoming time slot. This means that the control unit 101 is able to be informed about one or more time slot transmission patterns currently being used in the wireless communications network 100, such as, e.g. a TDD 4+1 or TDD 8+2 transmission pattern. It also means the control unit 101 is able to be informed about a scheduling decision that has been made for an upcoming time slot. It should be noted that this information is normally readily available in a wireless communications network 100.

[0045] Action 1302

[0046] After obtaining the time slot transmission pattern position or scheduling decision in Action 1201, the control unit 101 adapts the processing capacity in the Processing Units, PUs 102-105, at the time of the at least one upcoming time slot based on a required level of data processing at the time of the at least one upcoming time slot indicated by the obtained time slot transmission pattern position or scheduling decision for the at least one upcoming time slot. This means, for example, that the control 101 is able to, when scaling processing resources of Processing Units, PUs 102-105, in the wireless communications network 100, utilize the fact that some time-slots in certain transmission patterns have been observed to not require a high level of processing capacity during high loads, and that some time-slots in certain transmission patterns have been observed to require a high level of processing capacity during low loads, as previously described herein. Hence, the control unit 101 is able to adapt the processing capacity in the wireless communications network 100 for a time slot or for a time slot group, i.e. two or more time slots, and thus increase the energy efficiency in the wireless communications network 100 by reducing the power consumption of the hardware in the processing units 102-105.

[0047] For example, in case the hardware in the Processing Units, PUs 102-105, in the wireless communications network 100 is capable of supporting slot-based scaling (i.e. when the activation / deactivation of the hardware in the Processing Units, PUs 102-105, may be done fast enough), the control unit 101 may be able to scale the processing resources of the Processing Units, PUs 102-105, for a time slot based on the information in the scheduling decision for that time slot in the wireless communications network 100. Hence, in this case, the control unit 101 is able to “dynamically” on a time slot level adapt the processing capacity in the wireless communications network 100 and thus increase the energy efficiency in the wireless communications network 100 by reducing the power consumption of the hardware in the processing units 102-105. The term “dynamically” here is intended to mean that the adaptation of processing capacity may be determined and adapted from one time slot to the next, i.e. individually for each upcoming time slot.

[0048] In some embodiments, the control unit 101 may decrease or increase processing capacity in the Processing Units, PUs 102-105, at the time of the at least one upcoming time slot in case the indicated required level of data processing at the time of the at least one upcoming time slot is lower or higher than for at least one time slot preceding the at least one upcoming time slot, respectively. This means that the control unit 101 may adapt the processing capacity in the Processing Units, PUs 102-105, for a certain time slot or time slot group based on a relative load comparison with other time slots or time slot groups occurring prior to the certain time slot or time slot group. For example, as shown in Fig. 8, the processing capacity in the Processing Units, PUs 102-105, may be decreased for the upcoming time slot D3 as compared to any of the preceding UL time slot U and / or any of DL time slots D1-D2 wherein a higher processing capacity in the Processing Units, PUs 102-105, is likely needed as shown in Fig. 9. Similarly, the processing capacity in the Processing Units, PUs 102-105, may be increased for the upcoming special time slot S, UL time slot U and / or any of DL time slots D1-D2 in Fig. 8 as compared to the preceding time slot D3 wherein a lower processing capacity in the Processing Units, PUs 102-105, is likely needed as shown in Fig. 9. According to another example, as shown in Fig. 10, the processing capacity in the Processing Units, PUs 102- 105, may be decreased for the time slot D7 and special time slot S as compared to any of the preceding UL time slots U1-U2 and / or any of DL time slots D1-D6 wherein a higher processing capacity in the Processing Units, PUs 102-105, is likely needed as shown in Fig. 11. Similarly, the processing capacity in the Processing Units, PUs 102-105, may be increased for the upcoming UL time slots U1-LI2 and / or any of the upcoming DL time slots D1-D6 in Fig. 10 as compared to the preceding time slots D7 and special time slot S wherein a lower processing capacity in the Processing Units, PUs 102-105, is likely needed as shown in Fig. 11.

[0049] In this case, according to some embodiments, the control unit 101 may decrease or increase the processing capacity in the Processing Units, PUs 102-105, by powering down or up one or more processing resources in the one or more processing units 102- 105, and / or by decreasing or increasing one or more operating voltages and / or clock frequencies of one or more processing resources in the processing units 102-105, respectively. This means that the control unit 101 may adapt the processing capacity in the Processing Units, PUs 102-105, for a certain time slot or time slot group according to the scale in / out and / or scale up / down energy saving techniques described in the background section above. However, for slot-based or “dynamic” scaling, only the scale up / down energy saving technique may be performed fast enough, e.g. powering down / up unused processing cores or scaling down / up Layerl (L1) processing using DVFS.

[0050] In some embodiments, the control unit 101 may determine an amount of processing capacity in the Processing Units, PUs 102-105, to be adapted based on a determined latency in the processing of the data by the Processing Units, PUs 102-105, and / or on a determined traffic load of the served wireless devices 111, 112. This means that the control unit 101 may adapt the processing capacity in the Processing Units, PUs 102-105, for a certain time slot or time slot group taking the impact of the processing latency for the baseband application into consideration, which is a notable side-effect when scaling up / down hardware resources. This is because scaling down too much processing capacity in the Processing Units, PUs 102-105, might cause the baseband application to miss its deadline for sending its result to the radio application, which in turn may result in that nothing gets transmitted to the wireless devices 111 , 112 in a wireless communications network 100.

[0051] In some embodiments, the at least one upcoming time slot is part of at least one group of determined re-occurring time slots. This means that the control unit 101 is able to “semi-dynamically” on a time slot or time slot group level adapt the processing capacity in the wireless communications network 100, and thus increase the energy efficiency in the wireless communications network 100 by reducing the power consumption of the hardware in the processing units 102-105. The term “semi-dynamically” here is intended to mean that the adaptation of processing capacity may be determined and then repeated in the same manner for a particular time slot or time slot group, i.e. two or more time slots, for a number of cycles or repetitions of a particular time slot transmission pattern. For example, the increase / decrease of the processing capacity in the Processing Units, PUs 102-105, described in Figs. 8-11 may be repeated for each iteration of the respective time slot transmission pattern. This may be advantageous in case of having hardware in the Processing Units, PUs 102-105, in the wireless communications network 100 that is not capable of supporting slot-based scaling or “dynamic” scaling, e.g. when having other generations of hardware that is not fast enough. Here, in some embodiments, each group of the at least one group of determined re-occurring time slots is associated with one of at least two different sets of determined processing capacity in the processing units 102-105. This means, for example, that the control unit 101 may group its time slots into different groups of time slots based on the current time slot transmission pattern or TDD pattern. However, the current baseband application hardware in the Processing Units, PUs 102- 105, and the current software or computer program deployment thereon may also be considered here.

[0052] Each group of time slots may be associated with a certain required processing capacity level, e.g. low, medium and high processing time slots. For example, as shown in Fig. 14, the time slots in a TDD 4+1 pattern has been grouped into three time slot groups, i.e. time slot groups 1-3. Here, each time slot group 1-3 may be associated with a default power mode, e.g. low, medium or high. The power mode for each time slot group 1-3 may however change over time, for example, based on current traffic load and latency. In Fig. 14, for example, for each time slot group 1-3, situation A shows a default power modes during average loads, situation B shows power modes during low traffic loads, and situation C shows power modes during high traffic loads. Here, the current traffic load and latency may, for example, be the average baseband hardware load and average latency, the amount of scheduled traffic load and latency on a time slot level, or daily / hourly based traffic load. In other words, the scaling of the processing resources of the Processing Units, PUs 102-105, may be performed by switching power mode within each time slot group 1-3 depending on current traffic load and latency. Here, it should also be noted that each power mode may further be associated with a corresponding setting or type of scaling of the processing resources of the Processing Units, PUs 102-105, in the wireless communications network 100.

[0053] This advantageously allows power saving to be performed at time slot group level, which is much more fine granular compared to normal power saving techniques for baseband applications. Here, it should be noted that the number of groups or power modes that is used may depend on the capability of the baseband application hardware in the processing units 102-105.

[0054] It should also be noted that most commonly the same time slot transmission pattern or TDD pattern are used for all cells served by the processing units 102-105. However, the embodiments described herein may also be used if multiple time slot transmission patterns or TDD patterns is supported within the same baseband application. In this case, the time slot groups may be created based on a combined pattern created when combining the multiple time slot transmission patterns or TDD patterns.

[0055] Optionally, the control unit 101 may determine an amount of processing capacity in the Processing Units, PUs 102-105, to be adapted based on a number of processing resources in the processing units 102-105, wherein the number of processing resources in the Processing Units, PUs 102-105, is estimated based on the number of allocated resource blocks, the number of layers, and the number of scheduled served wireless devices 111 , 112 for the at least one upcoming time slot. This means, for example, that the control unit 101 is able to, when the hardware in the Processing Units, PUs 102-105, in the wireless communications network 100 is capable of supporting slot-based or “dynamic” scaling, determine the required processing resources of the Processing Units, PUs 102-105, for each time slot based on its scheduling decision. For example, the control unit 101 may employ a cost function that estimates the number of required processing core units, or processing cores, based on the number of allocated resource blocks, RU, layers and scheduled users, SEs, as indicated by the scheduling decision. In this case, according to some embodiments, the number of processing resources in the Processing Units, PUs 102-105, is estimated using linear regression. According to one example, the cost function may use linear regression as described below in Eq. 1 :

[0056] Nmb Cores needed = ( / cl * Nmb SE + / c2 * Nmb RB + / c3 * Nmb Layers) (Eq. 1)

[0057] Fig. 14 shows an example of a typical DL use-case which illustrates slot-based or “dynamic” scaling on a time slot-level according to some embodiments. Here, a MAC scheduler is started three (3) time slots ahead of the radio air interface timing (as indicated by the antenna). This means that a scheduling decision is sent for L2 processing on the data link layer, i.e. Radio Link Control, RLC, MAC multiplexing, and subsequently for L1 processing on the physical layer, two (2) time slots ahead of the radio air interface timing. In parallel to the L2 processing on the data link layer, the control unit 101 may determine the number of L1 processing core units (i.e. processing resources of the processing units 102-105) needed for the subsequent L1 processing. The control unit 101 may then compare this to the number of L1 processing core units needed for the L1 processing in a preceding time slot. If the number of L1 processing core units needed for the subsequent L1 processing is increased compared to the preceding time slot, the control unit 101 may activate further L1 processing core units before the subsequent L1 processing is started (i.e. the transport blocks are sent from L2 to L1). Here, it should be noted that if the number of L1 processing core units needed for the subsequent L1 processing is decreased compared to the preceding time slot, the control unit 101 may de-activate L1 processing core units first after the processing of previous time slot is completed. Processed Over-The-Air, OTA, data is then ready to be transmitted in accordance with the radio air interface timing for the upcoming time slot D.

[0058] Here, it should be noted that, in UL direction, the scheduling decision is normally processed four (4) time slots ahead of the radio air interface timing, that is, the MAC scheduling decision is available four (4) time slots before wireless device’s transmission over the radio air interface. This means that, for the UL case, the timing for activation / deactivation of L1 processing core units are further relaxed as compared to DL direction exemplified above. In some embodiments, the one or more processing resources in the one or more Processing Units, PUs 102-105, is a processing core unit within a hardware instance.

[0059] To perform the method actions in a control unit 101 for adapting processing capacity in Processing Units, PUs 102-105, arranged to serve wireless devices 111 , 112 in a wireless communications network 100, the control unit 101 may comprise the following arrangement depicted in Fig. 16. Fig. 16 shows a schematic block diagram of embodiments of a control unit 101. The control unit 101 may comprise processing circuitry 1610 and a memory 1620. The processing circuitry 1610 may also comprise a Input / Output, I / O, module (not shown) for receiving and transmitting information in the wireless communications network 100. It should also be noted that some or all of the functionality described in the embodiments above as being performed by the control unit 101 may be provided by the processing circuitry 1610 executing instructions stored on a computer-readable medium, such as, e.g. the memory 1620 shown in Fig. 16. Alternative embodiments of the control unit 101 may comprise additional components, such as, for example, an obtaining module 1611, and an adjusting module 1612, each responsible for providing its respective functionality necessary to support the embodiments described herein.

[0060] The control unit 101 or processing circuitry 1610 is configured to, or may comprise the obtaining module 1611 configured to, obtain time slot transmission pattern position or scheduling decision for at least one upcoming time slot. Also, the control unit 101 or processing circuitry 1610 is configured to, or may comprise the adapting module 1612 configured to, adapt processing capacity in the Processing Units, PUs 102-105, at the time of the at least one upcoming time slot based on the required level of data processing at the time of the at least one upcoming time slot indicated by the obtained time slot transmission pattern position or scheduling decision for the at least one upcoming time slot.

[0061] In some embodiments, the control unit 101 or processing circuitry 1610 may be configured to, or may comprise the adapting module 1612 configured to, decrease or increase processing capacity in the Processing Units, PUs 102-105, at the time of the at least one upcoming time slot in case the indicated required level of data processing at the time of the at least one upcoming time slot is lower or higher than for at least one preceding time slot, respectively. In this case, according to some embodiments, the control unit 101 or processing circuitry 1610 may be configured to, or may comprise the adapting module 1612 configured to, power down or up one or more processing resources in the one or more processing units 102-105, and / or decrease or increase one or more operating voltages and / or clock frequencies of one or more processing resources in the processing units 102-105.

[0062] In some embodiments, the control unit 101 or processing circuitry 1610 may be configured to, or may comprise the adapting module 1612 configured to, determine an amount of processing capacity in the Processing Units, PUs 102-105, to be adapted based on a determined latency in the processing of the data by the Processing Units, PUs 102-105, and / or on a determined traffic load of the served wireless devices 111 , 112.

[0063] According to some embodiments, the at least one upcoming time slot is part of at least one group of determined re-occurring time slots. Here, in some embodiments, each group of the at least one group of determined re-occurring time slots is associated with one of at least two different sets of determined processing capacity in the processing units 102-105.

[0064] In some embodiments, the control unit 101 or processing circuitry 1610 may be configured to, or may comprise the adapting module 1612 configured to, determine an amount of processing capacity in the Processing Units, PUs 102-105, to be adapted based on a number of processing resources in the processing units 102-105, wherein the number of processing resources in the Processing Units, PUs 102-105, is estimated based on the number of allocated resource blocks, the number of layers, and the number of scheduled served wireless devices 111 , 112 for the at least one upcoming time slot. Here, in some embodiments, the number of processing resources in the Processing Units, PUs 102-105, is estimated using linear regression. Furthermore, in some embodiments, the one or more processing resources in the one or more Processing Units, PUs 102-105, is a processing core unit within a hardware instance.

[0065] Furthermore, the embodiments for adapting processing capacity in Processing Units, PUs 102-105, arranged to serve wireless devices 111 , 112 in a wireless communications network 100 described above may be implemented through one or more processors, such as the processing circuitry 1610 in the control unit 101 depicted in Fig. 16, together with computer program code for performing the functions and actions of the embodiments herein. The program code mentioned above may also be provided as a computer program product, for instance in the form of a data carrier carrying computer program code or code means for performing the embodiments herein when being loaded into the processing circuitry 1610 in the control unit 101. The computer program code may e.g. be provided as pure program code in the control unit 101 or on a server and downloaded to the control unit 101. Thus, it should be noted that the modules of the control unit 101 may in some embodiments be implemented as computer programs stored in memory, e.g. in the memory modules 1620 in Fig. 16, for execution by processors or processing modules, e.g. the processing circuitry 1610 of Fig. 16.

[0066] Those skilled in the art will also appreciate that the processing circuitry 1610 and the memory 1620 described above may refer to a combination of analog and digital circuits, and / or one or more processors configured with software and / or firmware, e.g. stored in a memory, that when executed by the one or more processors such as the processing circuitry 1620 perform as described above. One or more of these processors, as well as the other digital hardware, may be included in a single application-specific integrated circuit (ASIC), or several processors and various digital hardware may be distributed among several separate components, whether individually packaged or assembled into a system-on-a-chip (SoC).

[0067] The description of the example embodiments provided herein have been presented for purposes of illustration. The description is not intended to be exhaustive or to limit example embodiments to the precise form disclosed, and modifications and variations are possible in light of the above teachings or may be acquired from practice of various alternatives to the provided embodiments. The examples discussed herein were chosen and described in order to explain the principles and the nature of various example embodiments and its practical application to enable one skilled in the art to utilize the example embodiments in various manners and with various modifications as are suited to the particular use contemplated. The features of the embodiments described herein may be combined in all possible combinations of methods, apparatus, modules, systems, and computer program products. It should be appreciated that the example embodiments presented herein may be practiced in any combination with each other.

[0068] It should be noted that the word “comprising” does not necessarily exclude the presence of other elements or steps than those listed and the words “a” or “an” preceding an element do not exclude the presence of a plurality of such elements. It should further be noted that any reference signs do not limit the scope of the claims, that the example embodiments may be implemented at least in part by means of both hardware and software, and that several “means”, “units” or “devices” may be represented by the same item of hardware.

[0069] It should also be noted that the various example embodiments described herein are described in the general context of method steps or processes, which may be implemented in one aspect by a computer program product, embodied in a computer- readable medium, including computer-executable instructions, such as program code, executed by computers in networked environments. A computer-readable medium may include removable and non-removable storage devices including, but not limited to, Read Only Memory (ROM), Random Access Memory (RAM), compact discs (CDs), digital versatile discs (DVD), etc. Generally, program modules may include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Computer-executable instructions, associated data structures, and program modules represent examples of program code for executing steps of the methods disclosed herein. The particular sequence of such executable instructions or associated data structures represents examples of corresponding acts for implementing the functions described in such steps or processes.

[0070] The embodiments herein are not limited to the above described preferred embodiments. Various alternatives, modifications and equivalents may be used. Therefore, the above embodiments should not be construed as limiting.

Claims

CLAIMS1. A method performed by a control unit (101) for adapting processing capacity in processing units (102-105) arranged to serve wireless devices (111 , 112) in a wireless communications network (100), the method comprising obtaining (601) time slot transmission pattern position or scheduling decision for at least one upcoming time slot; and adapting (602) processing capacity in the processing units (102-105) at the time of the at least one upcoming time slot based on a required level of data processing at the time of the at least one upcoming time slot indicated by the obtained time slot transmission pattern position or scheduling decision for the at least one upcoming time slot.

2. The method according to claim 1, further comprising decreasing or increasing processing capacity in the processing units (102-105) at the time of the at least one upcoming time slot in case the indicated required level of data processing at the time of the at least one upcoming time slot is lower or higher than for at least one time slot preceding the at least one upcoming time slot, respectively.

3. The method according to claim 2, wherein decreasing or increasing the processing capacity in the processing units (102-105) comprises powering down or up one or more processing resources in the one or more processing units (102-105), and / or decreasing or increasing one or more operating voltages and / or clock frequencies of one or more processing resources in the processing units (102-105), respectively.

4. The method according to any of claims 1-3, further comprising determining an amount of processing capacity in the processing units (102-105) to be adapted based on a determined latency in the processing of the data by the processing units (102-105) and / or on a determined traffic load of the served wireless devices (111, 112).

5. The method according to any of claims 1-4, wherein the at least one upcoming time slot is part of at least one group of determined re-occurring time slots.

6. The method according to claim 5, wherein each group of the at least one group of determined re-occurring time slots is associated with one of at least two different sets of determined processing capacity in the processing units (102-105).

7. The method according to any of claims 1-3, further comprising determining an amount of processing capacity in the processing units (102-105) to be adapted based on a number of processing resources in the processing units (102-105), wherein the number of processing resources in the processing units (102-105) is estimated based on the number of allocated resource blocks, the number of layers, and the number of scheduled served wireless devices (111, 112) for the at least one upcoming time slot .

8. The method according to claim 7, wherein the number of processing resources in the processing units (102-105) is estimated using linear regression.

9. The method according to any of claims 1-8, wherein the one or more processing resources in the one or more processing units (102-105) is a processing core unit within a hardware instance.

10. A control unit (101) for adapting processing capacity in processing units (102-105) arranged to serve wireless devices (111, 112) in a wireless communications network (100), the control unit (101) being configured to obtain time slot transmission pattern position or scheduling decision for at least one upcoming time slot , and adapt processing capacity in the processing units (102-105) at the time of the at least one upcoming time slot based on the required level of data processing at the time of the at least one upcoming time slot indicated by the obtained time slot transmission pattern position or scheduling decision for the at least one upcoming time slot.

11. The control unit (101) according to claim 10, further configured to decrease or increase processing capacity in the processing units (102-105) at the time of the at least one upcoming time slot in case the indicated required level of data processing at the time of the at least one upcoming time slot is lower or higher than for at least one preceding time slot, respectively.

12. The control unit (101) according to claim 11 , further configured to power down or up one or more processing resources in the one or more processing units (102- 105), and / or decrease or increase one or more operating voltages and / or clock frequencies of one or more processing resources in the processing units (102-105).

13. The control unit (101) according to any of claims 10-12, further configured to determine an amount of processing capacity in the processing units (102-105) to be adapted based on a determined latency in the processing of the data by the processing units (102-105) and / or on a determined traffic load of the served wireless devices (111 , 112).

14. The control unit (101) according to any of claims 10-13, wherein the at least one upcoming time slot is part of at least one group of determined re-occurring time slots.

15. The control unit (101) according to claim 14, wherein each group of the at least one group of determined re-occurring time slots is associated with one of at least two different sets of determined processing capacity in the processing units (102-105).

16. The control unit (101) according to any of claims 10-12, further configured to determine an amount of processing capacity in the processing units (102-105) to be adapted based on a number of processing resources in the processing units (102-105), wherein the number of processing resources in the processing units (102-105) is estimated based on the number of allocated resource blocks, the number of layers, and the number of scheduled served wireless devices (111 , 112) for the at least one upcoming time slot.

17. The control unit (101) according to claim 16, wherein the number of processing resources in the processing units (102-105) is estimated using linear regression.

18. The control unit (101) according to any of claims 10-17, wherein the one or more processing resources in the one or more processing units (102-105) is a processing core unit within a hardware instance.

19. The control unit (101) according to any of claims 10-18, comprising at least one processor (1610) and a memory (1620), wherein the memory (1620) is containing instructions executable by the at least one processor (1610).

20. A computer program, comprising instructions which, when executed on at least one processor (101), cause the at least one processor (101) to carry out the method according to any of claims 1-9.

21. A carrier containing the computer program according to claim 20, wherein the carrier is one of an electronic signal, optical signal, radio signal, or computer- readable storage medium.

Images