Scheduling with lower-layer split

Abstract

There is provided techniques for scheduling in an access network node. A method is performed by the distributed unit. The method comprises providing, to a radio unit over a fronthaul interface, input data pertaining to user state parameters of UEs to be scheduled by the access network node. The method comprises receiving, from the radio unit over the fronthaul interface, resource allocation metrics of the UEs that are based on channel information processed at the radio unit. The method comprises determining a scheduling decision for the UEs based on an evaluation of the received resource allocation metrics. The method comprises communicating the scheduling decision for the UEs to the radio unit over the fronthaul interface for implementation.

Description

[0001] SCHEDULING WITH LOWER-LAYER SPLIT

[0002] TECHNICAL FIELD

[0003] Embodiments presented herein relate to methods, a distributed unit, a radio unit, computer programs, and a computer program product for scheduling in an access network node.

[0004] BACKGROUND

[0005] Massive Multiple-Input Multiple-Output (MIMO) communication is a key technology implemented in many types of wireless communication systems. It has been widely deployed on a global scale. Massive MIMO communication is characterized by the use of a large number of antennas on the access network node side. The number of antennas typically exceeds the number of user layers. In frequency range 1 (FRi), which includes sub-6 GHz frequency bands, massive MIMO configurations commonly employ 64 antennas serving 8 or 16 user layers. In frequency range 2 (FR2), covering frequency bands from 24.25 GHz to 52.6 GHz, configurations with 256 or 512 antennas are used to serve 2 or 4 user layers. A user layer refers to an independent downlink or uplink data stream intended for a single user. A user equipment (UE) may be associated with one or multiple user layers. The term “user layer” is also referred to simply as “layer” in the context of the 3rd Generation Partnership Project (3GPP) terminology. Massive MIMO is also known as massive beamforming. This technology enables the formation of narrow beams directed towards specific areas to mitigate increased path loss at higher frequency bands. Additionally, massive MIMO supports multi-user MIMO, allowing simultaneous transmission to or from multiple UEs over separate spatial channels. This capability reduces inter-user interference while maintaining high performance, such as throughput, for each UE. All in all, massive MIMO communication can significantly increase the spectrum efficiency and cell capacity.

[0006] Benefits of massive MIMO communication at the air-interface also introduce new challenges at the access network node side. For example, assume that the functionality, as well as hardware, of access network node is divided between a distributed unit (DU) and a radio unit (RU) which are separated by a fronthaul interface. A legacy Common Public Radio Interface (CPRI) type fronthaul interface can be used to transport time-domain in-phase and quadrature (IQ) samples perantenna branch. However, as the number of antennas scales up in massive MIMO systems, the required fronthaul capacity also increases proportionally, which significantly drives up the fronthaul costs and complexity. A packet -based fronthaul interface, denoted evolved CPRI (eCPRI), was developed to address this challenge. Different functional split options between the DU and RU are supported by the eCPRI, referred to as different lower-layer split (LLS) options. In eCPRI terminologies, the DU and the RU are referred to as eREC (eCPRI Radio Equipment Control) and eRE (eCPRI Radio Equipment), respectively. The basic idea of LLS is to move the frequency-domain beamforming function from the DU to the RU so that frequency samples or data of user-layers are transported over the fronthaul interface. The frequency-domain beamforming is sometimes also referred to as precoding in the downlink direction and equalizing or pre-equalizing in the uplink direction. By doing this, the required fronthaul capacity, and thereby the fronthaul cost and complexity, can be significantly reduced. This is because the number of user layers is typically much fewer than the number of antennas in massive MIMO systems.

[0007] As an example, the access network node may be an open radio access network (O-RAN) network node. An 0-RAN network node is a network node that supports an O-RAN specification (e.g., a specification published by the 0-RAN Alliance, or any similar organization) and may operate alone or together with other network nodes to implement one or more functionalities of any network node, including one or more access network nodes and / or core network nodes. Examples of an 0-RAN network node include an open radio unit (0-RU), an open distributed unit (0-DU), an open central unit (O-CU), including an O-CU control plane (O-CU-CP) or an O-CU user plane (O-CU-UP), a RAN intelligent controller (near-real time or non-real time) hosting software or software plug-ins, such as a near-real time control application (e.g., xApp) or a non-real time control application (e.g., rApp), or any combination thereof (the adjective “open” designating support of an 0-RAN specification). An O-RAN network node may support a specification by, for example, supporting an interface defined by the 0-RAN specification, such as an Al, Fl, Wi, El, E2, X2, Xn interface, an open fronthaul user plane interface, or an open fronthaul management plane interface. Moreover, an 0-RAN network node may be a logical node in a physical node. Furthermore, an 0-RAN network node may be implemented in a virtualization environment in which one or more network functions are virtualized.For example, the virtualization environment may include an O-Cloud computing platform orchestrated by a Service Management and Orchestration Framework via an 0-2 interface defined by the 0-RAN Alliance or comparable technologies.

[0008] Fig. 1 is a schematic diagram illustrating a communication system 100 comprising an access network node no comprising a DU 112 and a RU 116. The DU 112 and the RU 116 are separated by a fronthaul interface 114 according to a lower-layer split. The antenna system 118 (comprising at least one antenna panel, or antenna array) of the access network node 110 is either part of, or coupled to, the RU 116. The access network node no could be any of a radio access network node, radio base station, base transceiver station, node B (NB), evolved node B (eNB), gNB, access point, access node, transmission and reception point (TRP), integrated access and backhaul (IAB) node. The access network node 110 is configured to provide network access to, and thereby serve, UEs 120 over a wireless channel 130. The UEs could be any of portable wireless devices, mobile stations, mobile phones, handsets, wireless local loop phones, smartphones, laptop computers, tablet computers, wireless modems, wireless sensor devices, network equipped vehicles, Internet of Things (loT) devices, game controllers.

[0009] The access network node no needs to schedule its served UEs 120 in an efficient manner. This typically requires the scheduler to have access to channel and noise estimates based on reference signals, such as demodulation reference signals (DMRSs), and / or sounding reference signals (SRSs), as inputs in order to calculate transmission parameters for each UE. The determined transmission parameters can be precoder selection, rank selection, bandwidth adaptation (e.g., physical resource block (PRB) allocation), power control, etc. Based on the determined transmission parameters, the scheduler also creates MU-MIMO groups of co-scheduled UEs. The co-scheduled UEs in the same MU-MIMO group share the same time and frequency resources and are multiplexed in the spatial domain. The grouping results determine how much signal to interference and noise power ratio (SINR) each UE may experience in the upcoming transmission. Further, the expected SINR determines which modulation and coding scheme (MCS) each UE will use.

[0010] However, with some low-layer split combinations, such as the 0-RAN DMRS-BF variant, the DMRS-based channel and noise estimates are obtained only in the RU.As a result, the scheduler, which is located in the DU, may rely solely on SRS-based channel and noise estimates. However, such channel information may suffer from channel aging issues, and also be affected by SRS resource limitations. All in all, this may degrade the scheduler performances. One way to overcome this drawback is to transport DMRS-based channel and noise estimates from the RU to the DU.

[0011] However, this may not be preferred due to increased fronthaul bandwidth requirements. Consider a RU with N antenna elements. The channel estimates contains N complex values for each UE layer per subcarrier whilst the noise covariance estimates contain N • N complex values per PRB bundle, even if symmetry means that only half of those elements need to be conveyed. Transporting those values over the fronthaul interface negates the advantages of the DMRS-BF alternative (e.g., to achieve the best UL performance using the minimum fronthaul bit rate).

[0012] As an alternative to transporting DMRS-based channel and noise estimates from the RU to the DU, the RU may only provide measurements, for example, indicating an estimated SINR per PRB for each UE before beamforming. This estimated SINR per PRB for each UE is based on the channel and the noise estimation as available at the RU. However, such measurements do not reflect the impact of interferences between layers in the MU-MIMO group. In turn, this may lead to sub-optimal selection of the transmission parameters, e.g. MCS, and thereby cause throughput degradation.

[0013] Hence, there is a need for improved scheduling methods in the context of lower-layer splits in an access network node.

[0014] SUMMARY

[0015] An object of embodiments herein is to improve the scheduling in the context of lower-layer splits in an access network node.

[0016] A particular object is to distribute, between the RU and the DU, the processing needed to determine scheduling, based on which channel information is available at the respective unit.

[0017] According to a first aspect there is presented a method for scheduling in an access network node. The access network node comprises a distributed unit and a radio unit separated by a fronthaul interface according to a lower-layer split. The method isperformed by the distributed unit. The method comprises providing, to the radio unit over the fronthaul interface, input data pertaining to user state parameters of UEs to be scheduled by the access network node. The method comprises receiving, from the radio unit over the fronthaul interface, resource allocation metrics of the UEs that are based on channel information processed at the radio unit. The method comprises determining a scheduling decision for the UEs based on an evaluation of the received resource allocation metrics. The method comprises communicating the scheduling decision for the UEs to the radio unit over the fronthaul interface for implementation.

[0018] According to a second aspect there is presented a distributed unit for scheduling in an access network node. The access network node comprises the distributed unit and a radio unit separated by a fronthaul interface according to a lower-layer split. The distributed unit comprises processing circuitry. The processing circuitry is configured to cause the distributed unit to provide, to the radio unit over the fronthaul interface, input data pertaining to user state parameters of UEs to be scheduled by the access network node. The processing circuitry is configured to cause the distributed unit to receive, from the radio unit over the fronthaul interface, resource allocation metrics of the UEs that are based on channel information processed at the radio unit. The processing circuitry is configured to cause the distributed unit to determine a scheduling decision for the UEs based on an evaluation of the received resource allocation metrics. The processing circuitry is configured to cause the distributed unit to communicate the scheduling decision for the UEs to the radio unit over the fronthaul interface for implementation.

[0019] According to a third aspect there is presented a computer program for scheduling in an access network node. The access network node comprises a distributed unit and a radio unit separated by a fronthaul interface according to a lower-layer split. The computer program comprises computer code which, when run on processing circuitry of the distributed unit, causes the distributed unit to perform actions. One action comprises the distributed unit to provide, to the radio unit over the fronthaul interface, input data pertaining to user state parameters of UEs to be scheduled by the access network node. One action comprises the distributed unit to receive, from the radio unit over the fronthaul interface, resource allocation metrics of the UEs that are based on channel information processed at the radio unit. One action comprises the distributed unit to determine a scheduling decision for the UEs based on anevaluation of the received resource allocation metrics. One action comprises the distributed unit to communicate the scheduling decision for the UEs to the radio unit over the fronthaul interface for implementation.

[0020] According to a fourth aspect there is presented a method for scheduling in an access network node. The access network node comprises a distributed unit and a radio unit separated by a fronthaul interface according to a lower-layer split. The method is performed by the radio unit. The method comprises receiving, from the distributed unit over the fronthaul interface, input data pertaining to user state parameters of UEs to be scheduled by the access network node. The method comprises calculating resource allocation metrics of the UEs based on channel information processed at the radio unit. The channel state information is calculated as a function of locally stored channel and noise information of the UEs and the input data. The locally stored channel and noise information is based on reference signals received from the UEs. The method comprises providing, to the distributed unit over the fronthaul interface, the resource allocation metrics of the UEs. The method comprises receiving a scheduling decision for the UEs from the distributed unit over the fronthaul interface. The method comprises implementing radio unit functionalities according to the scheduling decision for the UEs to be scheduled.

[0021] According to a fifth aspect there is presented a radio unit for scheduling in an access network node. The access network node comprises a distributed unit and the radio unit separated by a fronthaul interface according to a lower-layer split. The radio unit comprises processing circuitry. The processing circuitry is configured to cause the radio unit to receive, from the distributed unit over the fronthaul interface, input data pertaining to user state parameters of UEs to be scheduled by the access network node. The processing circuitry is configured to cause the radio unit to calculate resource allocation metrics of the UEs based on channel information processed at the radio unit. The channel state information is calculated as a function of locally stored channel and noise information of the UEs and the input data. The locally stored channel and noise information is based on reference signals received from the UEs. The processing circuitry is configured to cause the radio unit to provide, to the distributed unit over the fronthaul interface, the resource allocation metrics of the UEs. The processing circuitry is configured to cause the radio unit to receive a scheduling decision for the UEs from the distributed unit over the fronthaul interface.The processing circuitry is configured to cause the radio unit to implement radio unit functionalities according to the scheduling decision for the UEs to be scheduled.

[0022] According to a sixth aspect there is presented a computer program for scheduling in an access network node. The access network node comprises a distributed unit and a radio unit separated by a fronthaul interface according to a lower-layer split. The computer program comprises computer code which, when run on processing circuitry of the radio unit, causes the radio unit to perform actions. One action comprises the radio unit to receive, from the distributed unit over the fronthaul interface, input data pertaining to user state parameters of UEs to be scheduled by the access network node. One action comprises the radio unit to calculate resource allocation metrics of the UEs based on channel information processed at the radio unit. The channel state information is calculated as a function of locally stored channel and noise information of the UEs and the input data. The locally stored channel and noise information is based on reference signals received from the UEs. One action comprises the radio unit to provide, to the distributed unit over the fronthaul interface, the resource allocation metrics of the UEs. One action comprises the radio unit to receive a scheduling decision for the UEs from the distributed unit over the fronthaul interface. One action comprises the radio unit to implement radio unit functionalities according to the scheduling decision for the UEs to be scheduled.

[0023] According to a seventh aspect there is presented a computer program product comprising a computer program according to at least one of the third aspect and the sixth aspect and a computer readable storage medium on which the computer program is stored. The computer readable storage medium could be a non-transitory computer readable storage medium.

[0024] Advantageously, these aspects enable the processing needed to determine scheduling to be distributed between the RU and the DU, based on which channel information is available at the respective unit.

[0025] Advantageously, these aspects enable the scheduler to make use of DMRS-based channel and noise estimates even if those estimates are only available in the RU, whilst imposing minor impact on the amount of data transferred over the fronthaul interface at the same time.Other objectives, features and advantages of the enclosed embodiments will be apparent from the following detailed disclosure, from the attached dependent claims as well as from the drawings.

[0026] Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to "a / an / the element, apparatus, component, means, module, step, etc." are to be interpreted openly as referring to at least one instance of the element, apparatus, component, means, module, step, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated.

[0027] BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The inventive concept is now described, by way of example, with reference to the accompanying drawings, in which:

[0029] Fig. 1 is a schematic diagram illustrating a communication system according to embodiments;

[0030] Fig. 2 is a block diagram of an access network node according to an embodiment;

[0031] Figs. 3 and 4 are flowcharts of methods according to an embodiment;

[0032] Figs. 5, 6, and 7 are block diagrams of access network nodes according to embodiments;

[0033] Fig. 8 is a schematic diagram showing structural units of a distributed unit according to an embodiment;

[0034] Fig. 9 is a schematic diagram showing structural units of a radio unit according to an embodiment; and

[0035] Fig. 10 shows one example of a computer program product comprising computer readable means according to an embodiment.

[0036] DETAILED DESCRIPTION

[0037] The inventive concept will now be described more fully hereinafter with reference to the accompanying drawings, in which certain embodiments of the inventive conceptare shown. This inventive concept may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided by way of example so that this disclosure will be thorough and complete, and will fully convey the scope of the inventive concept to those skilled in the art. Like numbers refer to like elements throughout the description. Any step or feature illustrated by dashed lines should be regarded as optional.

[0038] As noted above, there is a need for improved scheduling methods in the context of lower-layer splits in an access network node.

[0039] In Fig. 2 is provided a block diagram of an access network node 200 according to an embodiment. Both SRS- and DMRS-based channel and noise estimates (blocks 204, 206) are available in the DU. The scheduler identifies which UEs have data in the buffer to transmit. Based on the buffer status information (block 202), the scheduler sorts UEs using a priority scheduling algorithm, referred to as UE sorting (block 208). Based on the available channel information, the rank and precoder for each UE is determined, initial MCS values are calculated and accordingly the initial bandwidth allocation for each UE is set (blocks 210, 212). For MU-MIMO, multiple UEs are paired in user groups, referred to as UE grouping (block 214), where UEs in the same user group share the same time and frequency resources and are multiplexed in spatial domain. The grouping can be done, for example, using a greedy algorithm based on a throughput criterion or cosine similarity etc., making use of the channel and noise estimates. More than one user group can be frequency-domain multiplexed over the carrier bandwidth. Accordingly, per-UE SINR values can be calculated (block 216) which accounts for both inter-cell interference and intra-group interference. Such SINR values can be used to calculate the per-UE MCS value (block 218). Based on the buffer status of UEs in a certain user group and the determined MCS for each UE, the bandwidth allocation maybe adjusted (block 220). The scheduling information about which UEs will be scheduled for certain transmission time interval (TTI) using which radio resources is, together with other transmission parameters (e.g., rank, precoder, MCS, etc.) is sent to the UE (block 222).

[0040] In some implementations of the access network node, DMRS-based channel and noise estimates are only available in the RU. Hereinafter will be disclosed differentscheduling determination schemes, aiming to to maximize the utilization of available channel and noise estimates for the scheduling decision. In at least some of the herein disclosed embodiments, it is assumed that the RU stores channel estimates and noise covariance estimates in, for example, a channel state memory. The channel and noise covariance estimates can be stored for one or multiple slots. The scheduling related calculations performed by the RU can be based on triggering signaling from the DU, i.e., upon a request from the DU. In particular, at least some of the herein disclosed embodiments are based on different ways to distribute the scheduling functional blocks in Fig. 2 between the RU and the DU, based on which channel information is available at the respective unit.

[0041] Reference is now made to Fig. 3 illustrating a method for scheduling in an access network node 200 as performed by the distributed unit 112 according to embodiments.

[0042] S102: The distributed unit 112 provides, to the radio unit 116 and over the fronthaul interface 114, input data pertaining to user state parameters of UEs 120 to be scheduled by the access network node no, 200.

[0043] In some embodiments, the user state parameters pertain to at least one of: candidate UE groups, UE rank information, priority information of the UEs 120, buffer status information associated with the UEs 120.

[0044] S104: The distributed unit 112 receives, from the radio unit 116 and over the fronthaul interface 114, resource allocation metrics of the UEs 120 that are based on channel information processed at the radio unit 116. Here, the channel information may be received in packets, each pertaining to a single UE 120, to a pair of UEs 120, or even to a group of UEs 120, or combinations thereof (e.g., where some packets pertain to channel information of single UEs 120 whereas other packets pertain to channel information of two or more UEs 120, etc.).

[0045] In some embodiments, the resource allocation metrics comprise at least one of: per-UE SINR values, candidate UE groups, recommendations for MCS selection for each of the UEs 120, recommendations for transmission parameters for the UEs 120 (such as information of precoder, rank, bandwidth allocation, power control of the UEs 120,matrix indicator reports received from the UEs 120), calculated metrics for candidate UE groups.

[0046] S106: The distributed unit 112 determines a scheduling decision for the UEs 120 based on an evaluation of the received resource allocation metrics.

[0047] In some embodiments, the evaluation of the received resource allocation metrics comprises at least one of: aggregating the received resource allocation metrics, performing centralized comparisons of the resource allocation metrics, determining a final scheduling decision for the UEs 120 based on candidate scheduling decisions for the UEs 120.

[0048] In some embodiments, determining the scheduling decision comprises at least one of: selecting UE groups, assigning radio resources to UEs 120 in UE groups, determining MCS selections for the UEs 120.

[0049] S108: The distributed unit 112 communicates the scheduling decision for the UEs 120 to the radio unit 116 and over the fronthaul interface 114 for implementation.

[0050] Reference is now made to Fig. 4 illustrating a method for scheduling in an access network node 200 as performed by the radio unit 116 according to embodiments.

[0051] S202: The radio unit 116 receives, from the distributed unit 112 and over the fronthaul interface 114, input data pertaining to user state parameters of UEs 120 to be scheduled by the access network node no, 200.

[0052] As above, in some embodiments, the user state parameters pertain to at least one of: candidate UE groups, UE rank information, priority information of the UEs 120, buffer status information associated with the UEs 120.

[0053] S204: The radio unit 116 calculates resource allocation metrics of the UEs 120 based on channel information processed at the radio unit 116. The channel state information is calculated as a function of locally stored channel and noise information of the UEs 120 and the input data. The locally stored channel and noise information is based on reference signals (such as DMRS and / or SRS) received from the UEs 120.As above, in some embodiments, the resource allocation metrics comprise at least one of: per-UE SINR values, candidate UE groups, recommendations for MCS selection for each of the UEs 120, recommendations for transmission parameters for the UEs 120, calculated metrics for candidate UE groups.

[0054] In some embodiments, calculating the resource allocation metrics of the UEs 120 at least comprises calculating per-UE SINR values and / or recommendations for MCS selection for each of the UEs 120.

[0055] In some embodiments, calculating the resource allocation metrics of the UEs 120 at least comprises generating candidate UE groups and calculating radio resource allocated for each of the UEs 120, and therefrom calculating per-UE SINR values, and selecting recommendations for MCS selection for each of the UEs 120 and recommendations for transmission parameters for the UEs 120.

[0056] In some embodiments, calculating the resource allocation metrics of the UEs 120 at least comprises determining at least one of UE rank information, precoder information and priority information of the UEs 120, generating candidate UE groups and calculating radio resource allocated for each of the UEs 120, and therefrom calculating per-UE SINR values.

[0057] In some embodiments, calculating the resource allocation metrics of the UEs 120 at least comprises, selecting recommendations for MCS selection for each of the UEs 120 and recommendations for transmission parameters for the UEs 120.

[0058] In some embodiments, calculating the resource allocation metrics of the UEs 120 at least comprises calculating metrics for candidate UE groups.

[0059] S206: The radio unit 116 provides, to the distributed unit 112 and over the fronthaul interface 114, the resource allocation metrics of the UEs 120.

[0060] S208: The radio unit 116 receives a scheduling decision for the UEs 120 from the distributed unit 112 and over the fronthaul interface 114.

[0061] S210: The radio unit 116 implements radio unit functionalities according to the scheduling decision for the UEs 120 to be scheduled.Further embodiments of scheduling in an access network node 200 as applicable to both the distributed unit 112 and the radio unit 116 will be disclosed next with reference to the block diagrams of Figs. 5, 6, and 7.

[0062] Each block diagram represents one way to distribute the scheduling functional blocks in Fig. 2 between the RU and the DU, based on which channel information is available at the respective unit.

[0063] A first embodiment of scheduling in an access network node 500 with a first lower-layer split, defined by a fronthaul interface 550, between a distributed unit 510 and a radio unit 560 based on at least some of the above disclosed embodiments will now be disclosed in detail with reference to the block diagram of Fig. 5.

[0064] In this embodiment, the DU creates MU-MIMO groups and allocates radio resources to each user group. The grouping information is then sent to the RU. The RU calculates per-UE SINR values accordingly and optionally also selects corresponding an MCS for each UE. The RU sends the calculated SINR values or suggested MCS selection to the DU and the DU makes the final scheduling decision. Therefore, in at least this embodiment, the user state parameters are candidate UE groups, and the resource allocation metrics are per-UE SINR values, or recommendations for MCS selection for each of the UEs 120. Further, in at least this embodiment, calculating the resource allocation metrics of the UEs 120 comprises calculating per-UE SINR values and / or recommendations for MCS selection for each of the UEs 120.

[0065] In further detail, as in the block diagram in Fig. 5, the DU has access to UE buffer status information (block 512) and SRS-based channel and noise estimates (block 514). Optionally, the DU also receives DMRS-based channel information (e.g., compressed channel data) or channel measurements, for example as radio resource management (RRM) and / or Layer 1 (Li) measurements (e.g., SINR values, signal power or interference plus noise power values) (block 516). With those inputs, the DU can conduct UE sorting (block 518), and determine rank, precoder, initial MCS selection (block 520), and which UEs are grouped to share which time and frequency resources. Then, the DU sends information of UE grouping (block 524), for example, in the form of UE indices per co-scheduled user group, and the associated bandwidth allocation (block 522) for each user group to the RU. The RU uses the grouping information from the DU, the stored channel estimates per UE and the noiseestimation (block 564) from the residuals to calculate the SINR values for each UE (block 562), taking into account of uplink beamforming effects. Beamforming weights can be calculated based on the DMRS channel estimates of the UEs in each user group (block 564). The SINR values can represent the SINR after expected beamforming for each user group. In some examples, the calculated SINR values are sent to the DU so that the DU makes the MCS selection. In other examples, the RU continues to make the MCS selection for each UE (block 566), and conveys the MCS selection suggestion to the DU. In these examples, the selected MCS accounts for channel variations, inter-cell interference and intra-group interference from the other co-scheduled MIMO layers. The DU may update the transmission parameters, for example, the bandwidth allocation (block 526), and sends the scheduling information to the RU (block 528).

[0066] To assist scheduler in the DU, the RU optionally also sends updates of channel information or measurements to the DU based on the channel estimates and / or noise covariance estimates of the current slot obtained in the RU. The RU could calculate and signal to the DU compressed values, such as the expected (average) channel or signal power per UE across the entire allocation and the average interference-plus-noise (IPN) power or the average channel. The compressed channel or signal and IPN values could be computed for the whole frequency band or per PRB bundle where each bundle consists of certain number of PRBs. The PRB bundles may include different number of PRBs. In case compressed values per PRB bundle are computed, the RU may also signal the bundle size (resolution) unless the number of PRBs per bundle is the same for all bundles. By increasing the resolution, i.e., computing one average channel or signal power and IPN per bundle, the impact of channel and interference variations in different parts of the frequency band could be captured with even higher accuracy, especially in high traffic loads.

[0067] A second embodiment of scheduling in an access network node 600 with a first lower-layer split, defined by a fronthaul interface 650, between a distributed unit 610 and a radio unit 660 based on at least some of the above disclosed embodiments will now be disclosed in detail with reference to the block diagram of Fig. 6.

[0068] In this embodiment, MU-MIMO groups are created by the RU. To support that, the DU sends UE information, such as a UE lists, per-UE rank to the RU. The UE listsmay, for example, be sorted according to buffer status. After determining the user group and the radio resource allocated for each user group, the RU calculates per-UE SINR values accordingly and / or selects corresponding MCS for each UE. The RU sends a recommendation of MU-MIMO grouping, radio resource allocation, and MCS selection to the DU, and the DU makes the final scheduling decision. Therefore, in at least this embodiment, the user state parameters pertain to at least one of UE rank information and priority information of the UEs 120, and the resource allocation metrics are candidate UE groups, recommendations for MCS selection for each of the UEs 120, and recommendations for transmission parameters for the UEs 120.

[0069] Further, in at least this embodiment, calculating the resource allocation metrics of the UEs 120 comprises generating candidate UE groups and calculating radio resource allocated for each of the UEs 120, and therefrom calculating per-UE SINR values, and selecting recommendations for MCS selection for each of the UEs 120 and recommendations for transmission parameters for the UEs 120.

[0070] In further detail, as in the block diagram in Fig. 6, the scheduler in the DU has access to the UE buffer status information (block 612) and SRS-based channel and noise estimates (block 614). With those inputs, the scheduler conducts UE sorting (block 616), determines rank, precoder and initial bandwidth allocation for each UE (blocks 618, 620). In some examples, the DU only conducts bandwidth allocation for the UE when the rank or precoder selected for the UE has been changed. The determined transmission parameters are sent to the RU. The RU may also determine bandwidth allocation (block 662) for each UE based on the DMRS-based channel and noise estimates. In some examples, the RU only conducts bandwidth allocation for the UE when such information is not received from the DU. In other examples, the RU only conducts bandwidth allocation for the UE when requested by the DU. Based on the DMRS-based channel and noise estimates, the RU determines UE grouping (block 664), calculates, based on the UE grouping and DMRS-based channel and noise estimates (block 668), per-UE SINR values (block 670) and accordingly selects MCS (block 672), accounting for both inter-cell interference and intra-group interference. Then, the RU sends the recommendation for transmission parameters of bandwidth allocation, UE grouping and MCS selection (block 674) to the scheduler in the DU and the scheduler updates the UE bandwidth allocation (block 622) if needed and sends the scheduling decision to the RU (block 624).A third embodiment of scheduling in an access network node 700 with a first lower-layer split, defined by a fronthaul interface 750, between a distributed unit 710 and a radio unit 760 based on at least some of the above disclosed embodiments will now be disclosed in detail with reference to the block diagram of Fig. 7.

[0071] In this embodiment, both DMRS- and SRS based channel and noise estimates are available in the RU. The DU sends relevant UE buffer status information to the RU and the RU, based on UE sorting, calculates further transmission parameters, e.g., rank information, precoder information, bandwidth allocation as well as MU-MIMO grouping, MCS selection for scheduling determination. The recommended transmission parameters are then sent from the RU to the DU for confirmation or adjustment. Therefore, in at least this embodiment, the user state parameters pertain to buffer status information associated with the UEs 120, and the resource allocation metrics are candidate UE groups, recommendations for MCS selection for each of the UEs 120, and recommendations for transmission parameters for the UEs 120.

[0072] Further, in at least this embodiment, calculating the resource allocation metrics of the UEs 120 comprises determining at least one of UE rank information, precoder information and priority information of the UEs 120, generating candidate UE groups and calculating radio resource allocated for each of the UEs 120, and therefrom calculating per-UE SINR values, selecting recommendations for MCS selection for each of the UEs 120 and recommendations for transmission parameters for the UEs 120.

[0073] In further detail, as in the block diagram in Fig. 7, both SRS- and DMRS-based channel and noise estimates are available in the RU (blocks 770, 772). In this case, the DU sends the buffer status information (block 712) of the relevant UEs to the RU. With the received buffer status information, the RU conducts UE sorting (block 762). Then, the RU calculates the remaining transmission parameters of rank and precoder information, as well as bandwidth allocation and UE grouping (blocks 764, 766, 768). Based on the DMRS-based channel and noise estimates, the RU calculates per-UE SINR values (block 774) and accordingly selects MCS (block 776), accounting for both inter-cell interference and intra-group interference, and possibly updates the UE bandwidth allocation (block 778). The transmission parameters are recommended to the DU (block 780) and the DU makes the final scheduling decision (block 714).A fourth embodiment of scheduling in an access network node with a first lower-layer split between a distributed unit and a radio unit based on at least some of the above disclosed embodiments will now be disclosed in detail.

[0074] In this embodiment, the DU sends one or more candidate UE groupings to the RU. Each candidate UE grouping may be represented by a respective list of UE identifiers, and an assumed scheduling frequency band (e.g., defined by a set of PRBs). The RU returns a metric per candidate UE grouping to the DU. The metric may be an indication of channel quality. The metric maybe a proxy for performance had the set of UEs identified by the UE identifiers of the UE grouping been scheduled in the assumed scheduling frequency band. The RU computes this based on stored channel estimates. This allows the DU to test a set of scheduling candidates by comparing the returned metrics. Therefore, in at least this embodiment, the user state parameters pertain to candidate UE groups, and the resource allocation metrics are calculated metrics for the candidate UE groups. Further, in at least this embodiment, calculating the resource allocation metrics of the UEs 120 comprises calculating metrics for the candidate UE groups.

[0075] In further detail, the DU sends UE grouping candidates to the RU. Based on the received UE grouping list, the RU calculates a metric for each candidate UE grouping based on its stored channel information, and sends the calculated metrics to the DU. The DU makes scheduling decision by comparing the feedback metrics for the different candidate UE groupings. This embodiment can be implemented using the block diagram of Fig. 5.

[0076] Any of the herein disclosed embodiments are applicable to scheduling of the UEs 120 in the downlink as well as scheduling of the UEs 120 in the uplink. The scheduling decision determined in step sio6 and communicated to the radio unit in step S108 may thus either be a downlink scheduling decision for the UEs 120 or an uplink scheduling decision for the UEs 120.

[0077] Fig. 8 schematically illustrates, in terms of a number of structural units, the components of a distributed unit 800 according to an embodiment. Processing circuitry 810 is provided using any combination of one or more of a suitable central processing unit (CPU), multiprocessor, microcontroller, digital signal processor (DSP), etc., capable of executing software instructions stored in a computer programproduct 1010a (as in Fig. 10), e.g. in the form of a storage medium 830. The processing circuitry 810 may further be provided as at least one application specific integrated circuit (ASIC), or field programmable gate array (FPGA).

[0078] Particularly, the processing circuitry 810 is configured to cause the distributed unit 800 to perform a set of operations, or steps, as disclosed above. For example, the storage medium 830 may store the set of operations, and the processing circuitry 810 maybe configured to retrieve the set of operations from the storage medium 830 to cause the distributed unit 800 to perform the set of operations. The set of operations maybe provided as a set of executable instructions. Thus the processing circuitry 810 is thereby arranged to execute methods as herein disclosed.

[0079] The storage medium 830 may also comprise persistent storage, which, for example, can be any single one or combination of magnetic memory, optical memory, solid state memory or even remotely mounted memory.

[0080] The distributed unit 800 may further comprise a communications (comm.) interface 820 for communications with other entities, functions, nodes, and devices, such as the radio unit 900. As such the communications interface 820 may comprise one or more transmitters and receivers, comprising analogue and digital components.

[0081] The processing circuitry 810 controls the general operation of the distributed unit 800 e.g. by sending data and control signals to the communications interface 820 and the storage medium 830, by receiving data and reports from the communications interface 820, and by retrieving data and instructions from the storage medium 830. Other components, as well as the related functionality, of the distributed unit 800 are omitted in order not to obscure the concepts presented herein.

[0082] Fig. 9 schematically illustrates, in terms of a number of structural units, the components of a radio unit 900 according to an embodiment. Processing circuitry 910 is provided using any combination of one or more of a suitable central processing unit (CPU), multiprocessor, microcontroller, digital signal processor (DSP), etc., capable of executing software instructions stored in a computer program product 1010b (as in Fig. 10), e.g. in the form of a storage medium 930. The processing circuitry 910 may further be provided as at least one application specific integrated circuit (ASIC), or field programmable gate array (FPGA).Particularly, the processing circuitry 910 is configured to cause the radio unit 900 to perform a set of operations, or steps, as disclosed above. For example, the storage medium 930 may store the set of operations, and the processing circuitry 910 maybe configured to retrieve the set of operations from the storage medium 930 to cause the radio unit 900 to perform the set of operations. The set of operations maybe provided as a set of executable instructions. Thus the processing circuitry 910 is thereby arranged to execute methods as herein disclosed.

[0083] The storage medium 930 may also comprise persistent storage, which, for example, can be any single one or combination of magnetic memory, optical memory, solid state memory or even remotely mounted memory.

[0084] The radio unit 900 may further comprise a communications interface 920 for communications with other entities, functions, nodes, and devices, such as the distributed unit 800. As such the communications interface 920 may comprise one or more transmitters and receivers, comprising analogue and digital components.

[0085] The processing circuitry 910 controls the general operation of the radio unit 900 e.g. by sending data and control signals to the communications interface 920 and the storage medium 930, by receiving data and reports from the communications interface 920, and by retrieving data and instructions from the storage medium 930. Other components, as well as the related functionality, of the radio unit 900 are omitted in order not to obscure the concepts presented herein.

[0086] Fig. 10 shows one example of a computer program product 1010a, 1010b comprising computer readable means 1030. On this computer readable means 1030, a computer program 1020a can be stored, which computer program 1020a can cause the processing circuitry 810 and thereto operatively coupled entities and devices, such as the communications interface 820 and the storage medium 830, to execute methods according to embodiments described herein. The computer program 1020a and / or computer program product 1010a may thus provide means for performing any steps of the distributed unit 800 as herein disclosed. On this computer readable means 1030, a computer program 1020b can be stored, which computer program 1020b can cause the processing circuitry 910 and thereto operatively coupled entities and devices, such as the communications interface 920 and the storage medium 930, to execute methods according to embodiments described herein. The computer program1020b and / or computer program product 1010b may thus provide means for performing any steps of the radio unit 900 as herein disclosed.

[0087] In the example of Fig. 10, the computer program product 1010a, 1010b is illustrated as an optical disc, such as a CD (compact disc) or a DVD (digital versatile disc) or a Blu-Ray disc. The computer program product 1010a, 1010b could also be embodied as a memory, such as a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), or an electrically erasable programmable read-only memory (EEPROM) and more particularly as a non-volatile storage medium of a device in an external memory such as a USB (Universal Serial Bus) memory or a Flash memory, such as a compact Flash memory. Thus, while the computer program 1020a, 1020b is here schematically shown as a track on the depicted optical disk, the computer program 1020a, 1020b can be stored in any way which is suitable for the computer program product 1010a, 1010b.

[0088] The inventive concept has mainly been described above with reference to a few embodiments. However, as is readily appreciated by a person skilled in the art, other embodiments than the ones disclosed above are equally possible within the scope of the inventive concept, as defined by the appended patent claims.

Claims

CLAIMS1. A method for scheduling in an access network node (no, 200, 500, 600, 700), wherein the access network node (110, 200, 500, 600, 700) comprises a distributed unit (112, 510, 610, 710, 800) and a radio unit (116, 560, 660, 760, 900) separated by a fronthaul interface (114, 550, 650, 750) according to a lower-layer split, the method being performed by the distributed unit (112, 510, 610, 710, 800), the method comprising:providing (S102), to the radio unit (116, 560, 660, 760, 900) over the fronthaul interface (114, 550, 650, 750), input data pertaining to user state parameters of user equipment, UEs (120), to be scheduled by the access network node (no, 200, 500, 600, 700);receiving (S104), from the radio unit (116, 560, 660, 760, 900) over the fronthaul interface (114, 550, 650, 750), resource allocation metrics of the UEs (120) that are based on channel information processed at the radio unit (116, 560, 660, 760, 900);determining (S106) a scheduling decision for the UEs (120) based on an evaluation of the received resource allocation metrics; andcommunicating (S108) the scheduling decision for the UEs (120) to the radio unit (116, 560, 660, 760, 900) over the fronthaul interface (114, 550, 650, 750) for implementation.

2. The method according to claim 1, wherein the user state parameters pertain to at least one of: candidate UE groups, UE rank information, priority information of the UEs (120), buffer status information associated with the UEs (120).

3. The method according to claim 1 or 2, wherein the resource allocation metrics comprise at least one of: per-UE SINR values, candidate UE groups, recommendations for MCS selection for each of the UEs (120), recommendations for transmission parameters for the UEs (120), calculated metrics for candidate UE groups.

4. The method according to any preceding claim, wherein the evaluation of the received resource allocation metrics comprises at least one of: aggregating the received resource allocation metrics, performing centralized comparisons of the resource allocation metrics, determining a final scheduling decision for the UEs (120) based on candidate scheduling decisions for the UEs (120).

5. The method according to any preceding claim, wherein determining the scheduling decision comprises at least one of: selecting UE groups, assigning radio resources to UEs (120) in UE groups, determining MCS selections for the UEs (120).

6. The method according to any preceding claim, wherein the user state parameters are candidate UE groups, and wherein the resource allocation metrics are per-UE SINR values, or recommendations for MCS selection for each of the UEs (120).

7. The method according to any preceding claim, wherein the user state parameters pertain to at least one of UE rank information and priority information of the UEs (120), and wherein the resource allocation metrics are candidate UE groups, recommendations for MCS selection for each of the UEs (120), and recommendations for transmission parameters for the UEs (120).

8. The method according to any preceding claim, wherein the user state parameters pertain to buffer status information associated with the UEs (120), and wherein the resource allocation metrics are candidate UE groups, recommendations for MCS selection for each of the UEs (120), and recommendations for transmission parameters for the UEs (120).

9. The method according to any preceding claim, wherein the user state parameters pertain to candidate UE groups, and wherein the resource allocation metrics are calculated metrics for the candidate UE groups.

10. A method for scheduling in an access network node (no, 200, 500, 600, 700), wherein the access network node (110, 200, 500, 600, 700) comprises a distributed unit (112, 510, 610, 710, 800) and a radio unit (116, 560, 660, 760, 900) separated by a fronthaul interface (114, 550, 650, 750) according to a lower-layer split, the method being performed by the radio unit (116, 560, 660, 760, 900), the method comprising:receiving (S202), from the distributed unit (112, 510, 610, 710, 800) over the fronthaul interface (114, 550, 650, 750), input data pertaining to user state parameters of user equipment, UEs (120), to be scheduled by the access network node (no, 200, 500, 600, 700);calculating (S204) resource allocation metrics of the UEs (120) based on channel information processed at the radio unit (116, 560, 660, 760, 900), wherein the channel state information is calculated as a function of locally stored channel and noise information of the UEs (120) and the input data, wherein the locally stored channel and noise information is based on reference signals received from the UEs (120);providing (S206), to the distributed unit (112, 510, 610, 710, 800) over the fronthaul interface (114, 550, 650, 750), the resource allocation metrics of the UEs (120);receiving (S208) a scheduling decision for the UEs (120) from the distributed unit (112, 510, 610, 710, 800) over the fronthaul interface (114, 550, 650, 750); andimplementing (S210) radio unit functionalities according to the scheduling decision for the UEs (120) to be scheduled.

11. The method according to claim 10, wherein the user state parameters pertain to at least one of: candidate UE groups, UE rank information, priority information of the UEs (120), buffer status information associated with the UEs (120).

12. The method according to claim 10 or 11, wherein the resource allocation metrics comprise at least one of: per-UE SINR values, candidate UE groups, recommendations for MCS selection for each of the UEs (120), recommendations for transmission parameters for the UEs (120), calculated metrics for candidate UE groups.

13. The method according to any of claims 10 to 12, wherein calculating the resource allocation metrics of the UEs (120) comprises at least one of:calculating per-UE SINR values and / or recommendations for MCS selection for each of the UEs (120),- generating candidate UE groups and calculating radio resource allocated for each of the UEs (120), and therefrom calculating per-UE SINR values, and selecting recommendations for MCS selection for each of the UEs (120) and recommendations for transmission parameters for the UEs (120),- selecting recommendations for MCS selection for each of the UEs (120) and recommendations for transmission parameters for the UEs (120),- determining at least one of UE rank information, precoder information and priority information of the UEs (120), and- calculating metrics for candidate UE groups.

14. The method according to any of claims 10 to 13, wherein the user state parameters pertain to candidate UE groups, wherein calculating the resource allocation metrics of the UEs (120) comprises calculating per-UE SINR values and / or recommendations for MCS selection for each of the UEs (120), and wherein the resource allocation metrics are the per-UE SINR values, or the recommendations for MCS selection for each of the UEs (120).

15. The method according to any of claims 10 to 14, wherein the user state parameters at least pertain to UE rank information and priority information of the UEs (120), wherein calculating the resource allocation metrics of the UEs (120) comprises generating candidate UE groups and calculating radio resource allocated for each of the UEs (120), and therefrom calculating per-UE SINR values, and selecting recommendations for MCS selection for each of the UEs (120) and recommendations for transmission parameters for the UEs (120), and wherein the resource allocation metrics are the candidate UE groups, the recommendations for MCS selection for each of the UEs (120), and the recommendations for transmission parameters for the UEs (120).

16. The method according to any of claims 10 to 15, wherein the user state parameters pertain to buffer status information associated with the UEs (120), wherein calculating the resource allocation metrics of the UEs (120) comprises determining at least one of UE rank information, precoder information and priority information of the UEs (120), generating candidate UE groups and calculating radio resource allocated for each of the UEs (120), and therefrom calculating per-UE SINR values, selecting recommendations for MCS selection for each of the UEs (120) andrecommendations for transmission parameters for the UEs (120), and wherein the resource allocation metrics are the candidate UE groups, the recommendations for MCS selection for each of the UEs (120), and the recommendations for transmission parameters for the UEs (120).

17. The method according to any of claims 10 to 16, wherein the user state parameters pertain to candidate UE groups, wherein calculating the resource allocation metrics of the UEs (120) comprises calculating metrics for the candidate UE groups, and wherein the resource allocation metrics are the calculated metrics for the candidate UE groups.

18. A distributed unit (112, 510, 610, 710, 800) for scheduling in an access network node (no, 200, 500, 600, 700), wherein the access network node (110, 200, 500, 600, 700) comprises the distributed unit (112, 510, 610, 710, 800) and a radio unit (116, 560, 660, 760, 900) separated by a fronthaul interface (114, 550, 650, 750) according to a lower-layer split, the distributed unit (112, 510, 610, 710, 800) comprising processing circuitry (810), the processing circuitry being configured to cause the distributed unit (112, 510, 610, 710, 800) to:provide, to the radio unit (116, 560, 660, 760, 900) over the fronthaul interface (114, 550, 650, 750), input data pertaining to user state parameters of user equipment, UEs (120), to be scheduled by the access network node (no, 200, 500, 600, 700);receive, from the radio unit (116, 560, 660, 760, 900) over the fronthaul interface (114, 550, 650, 750), resource allocation metrics of the UEs (120) that are based on channel information processed at the radio unit (116, 560, 660, 760, 900);determine a scheduling decision for the UEs (120) based on an evaluation of the received resource allocation metrics; andcommunicate the scheduling decision for the UEs (120) to the radio unit (116, 560, 660, 760, 900) over the fronthaul interface (114, 550, 650, 750) for implementation.

19. The distributed unit (112, 510, 610, 710, 800) according to claim 18, further being configured to perform the method according to any of claims 2 to 9.

20. A radio unit (116, 560, 660, 760, 900) for scheduling in an access network node (no, 200, 500, 600, 700), wherein the access network node (no, 200, 500, 600, 700) comprises a distributed unit (112, 510, 610, 710, 800) and the radio unit (116, 560, 660, 760, 900) separated by a fronthaul interface (114, 550, 650, 750) according to a lower-layer split, the radio unit (116, 560, 660, 760, 900) comprising processing circuitry (910), the processing circuitry being configured to cause the radio unit (116, 560, 660, 760, 900) to:receive, from the distributed unit (112, 510, 610, 710, 800) over the fronthaul interface (114, 550, 650, 750), input data pertaining to user state parameters of user equipment, UEs (120), to be scheduled by the access network node (110, 200, 500, 600, 700);calculate resource allocation metrics of the UEs (120) based on channel information processed at the radio unit (116, 560, 660, 760, 900), wherein the channel state information is calculated as a function of locally stored channel and noise information of the UEs (120) and the input data, wherein the locally stored channel and noise information is based on reference signals received from the UEs (120);provide, to the distributed unit (112, 510, 610, 710, 800) over the fronthaul interface (114, 550, 650, 750), the resource allocation metrics of the UEs (120);receive a scheduling decision for the UEs (120) from the distributed unit (112, 510, 610, 710, 800) over the fronthaul interface (114, 550, 650, 750); andimplement radio unit functionalities according to the scheduling decision for the UEs (120) to be scheduled.

21. The radio unit (116, 560, 660, 760, 900) according to claim 20, further being configured to perform the method according to any of claims 11 to 17.

22. A computer program (1020a) for scheduling in an access network node (no, 200, 500, 600, 700), wherein the access network node (110, 200, 500, 600, 700) comprises a distributed unit (112, 510, 610, 710, 800) and a radio unit (116, 560, 660, 760, 900) separated by a fronthaul interface (114, 550, 650, 750) according to a lower-layer split, the computer program comprising computer code which, when runon processing circuitry (810) of the distributed unit (112, 510, 610, 710, 800), causes the distributed unit (112, 510, 610, 710, 800) to:provide (S102), to the radio unit (116, 560, 660, 760, 900) over the fronthaul interface (114, 550, 650, 750), input data pertaining to user state parameters of user equipment, UEs (120), to be scheduled by the access network node (no, 200, 500, 600, 700);receive (S104), from the radio unit (116, 560, 660, 760, 900) over the fronthaul interface (114, 550, 650, 750), resource allocation metrics of the UEs (120) that are based on channel information processed at the radio unit (116, 560, 660, 760, 900);determine (S106) a scheduling decision for the UEs (120) based on an evaluation of the received resource allocation metrics; andcommunicate (S108) the scheduling decision for the UEs (120) to the radio unit (116, 560, 660, 760, 900) over the fronthaul interface (114, 550, 650, 750) for implementation.

23. A computer program (1020b) for scheduling in an access network node (no, 200, 500, 600, 700), wherein the access network node (110, 200, 500, 600, 700) comprises a distributed unit (112, 510, 610, 710, 800) and a radio unit (116, 560, 660, 760, 900) separated by a fronthaul interface (114, 550, 650, 750) according to a lower-layer split, the computer program comprising computer code which, when run on processing circuitry (910) of the radio unit (116, 560, 660, 760, 900), causes the radio unit (116, 560, 660, 760, 900) to:receive (S202), from the distributed unit (112, 510, 610, 710, 800) over the fronthaul interface (114, 550, 650, 750), input data pertaining to user state parameters of user equipment, UEs (120), to be scheduled by the access network node (no, 200, 500, 600, 700);calculate (S204) resource allocation metrics of the UEs (120) based on channel information processed at the radio unit (116, 560, 660, 760, 900), wherein the channel state information is calculated as a function of locally stored channel and noise information of the UEs (120) and the input data, wherein the locally storedchannel and noise information is based on reference signals received from the UEs (120);provide (S206), to the distributed unit (112, 510, 610, 710, 800) over the fronthaul interface (114, 550, 650, 750), the resource allocation metrics of the UEs (120);receive (S208) a scheduling decision for the UEs (120) from the distributed unit (112, 510, 610, 710, 800) over the fronthaul interface (114, 550, 650, 750); andimplement (S210) radio unit functionalities according to the scheduling decision for the UEs (120) to be scheduled.

24. A computer program product (1010a, 1010b) comprising a computer program (1020a, 1020b) according to at least one of claims 22 and 23, and a computer readable storage medium (1030) on which the computer program is stored.

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