Direction-wise traffic distribution among carriers

Abstract

There is provided techniques for direction-wise traffic distribution among carriers in a cell. A method is performed by a network node. The method comprises obtaining downlink and / or uplink quality-of-service requirements for a set of data to be transmitted on the carriers. The set of data belongs to at least one service. The method comprises estimating a maximum traffic level per service, carrier, and direction. The maximum traffic level corresponds to a maximum load level for supporting the downlink and / or uplink quality-of-service requirements. The method comprises allocating the traffic distribution per carrier at least in accordance with the maximum traffic level per service, carrier, and direction. The method comprises enforcing traffic steering in accordance with the allocated traffic distribution in the downlink and the uplink.

Description

[0001] DIRECTION-WISE TRAFFIC DISTRIBUTION AMONG CARRIERS

[0002] TECHNICAL FIELD

[0003] Embodiments presented herein relate to a method, a network node, a computer program, and a computer program product for direction-wise traffic distribution among carriers in a cell.

[0004] BACKGROUND

[0005] In communications networks, there maybe a challenge to obtain good performance and capacity for a given communications protocol, its parameters and the physical environment in which the communications network is deployed.

[0006] For example, traffic steering, generally refers to the dynamic management and optimization of network traffic by directing data flows across different network paths, frequency bands, carriers, or access technologies. One goal of traffic steering is to ensure efficient resource utilization, improved user experience, and enhanced network performance. This is achieved by intelligently distributing the traffic based on factors like network conditions, quality-of-service (QoS) requirements, and user mobility. Basic traffic steering algorithms rely on a single criterion to make a decision with respect to how the data flows, and thus the traffic, should be directed. This criterion maybe the current load percentages of in-range base stations or satisfaction of the bit rate demand, with radio resources available to be allocated by each network node. In further detail, the network node is typically implementing downlink traffic steering based on highest quality (for example received power per resource block) or highest (predetermined) priority. Uplink traffic steering can be based on either highest quality or a probabilistic algorithm (for example randomly, or probabilistically, selecting frequency bands with good enough quality). However, these types of traffic steering may not guarantee user satisfaction for delay-sensitive services. Hence, whilst these approaches may provide adequate efficiency at a low computational cost, they may be sub-optimal, and hence there may be other ways to direct the traffic that, according to some metric, is better.

[0007] In further detail, diversity of frequency bands, diversity of services, and load balancing, may require more advanced traffic steering algorithms. At the same time, delay-sensitive services, such as augmented reality, virtual reality, and cloud gaming,require appropriate treatment that would guarantee the strict delay and reliability requirements.

[0008] Hence, there is still a need for improved traffic steering, especially in scenarios where there are simultaneous users to be served that require different priorities with respect to delay, quality, etc.

[0009] SUMMARY

[0010] An object of embodiments herein is to provide traffic steering that does not suffer from the above issues, or at least where the above issues are reduced or mitigated.

[0011] A particular object is to provide traffic steering in scenarios where there are simultaneous users to be served that require different priorities with respect to delay, quality, etc.

[0012] A particular object is to find the best carrier set for each UE, taking into account different parameters, such as UE capability, network configuration, service requirements, and cell load, as well as to take quality-of-service requirements (such as delay and reliability requirements, or any other criteria for service differentiation) into account.

[0013] According to a first aspect there is presented a method for direction-wise traffic distribution among carriers in a cell. The method is performed by a network node. The method comprises obtaining downlink and / or uplink quality-of-service requirements for a set of data to be transmitted on the carriers. The set of data belongs to at least one service. The method comprises estimating a maximum traffic level per service, carrier, and direction. The maximum traffic level corresponds to a maximum load level for supporting the downlink and / or uplink quality-of-service requirements. The method comprises allocating the traffic distribution per carrier at least in accordance with the maximum traffic level per service, carrier, and direction. The method comprises enforcing traffic steering in accordance with the allocated traffic distribution in the downlink and the uplink.

[0014] According to a second aspect there is presented a network node for direction-wise traffic distribution among carriers in a cell. The network node comprises processing circuitry. The processing circuitry is configured to cause the network node to obtaindownlink and / or uplink quality-of-service requirements for a set of data to be transmitted on the carriers. The set of data belongs to at least one service. The processing circuitry is configured to cause the network node to estimate a maximum traffic level per service, carrier, and direction. The maximum traffic level corresponds to a maximum load level for supporting the downlink and / or uplink quality-of-service requirements. The processing circuitry is configured to cause the network node to allocate the traffic distribution per carrier at least in accordance with the maximum traffic level per service, carrier, and direction. The processing circuitry is configured to cause the network node to enforce traffic steering in accordance with the allocated traffic distribution in the downlink and the uplink.

[0015] According to a third aspect there is presented a computer program for direction-wise traffic distribution among carriers in a cell. The computer program comprises computer code which, when run on processing circuitry of a network node, causes the network node to perform actions. One action comprises the network node to obtain downlink and / or uplink quality-of-service requirements for a set of data to be transmitted on the carriers. The set of data belongs to at least one service. One action comprises the network node to estimate a maximum traffic level per service, carrier, and direction. The maximum traffic level corresponds to a maximum load level for supporting the downlink and / or uplink quality-of-service requirements. One action comprises the network node to allocate the traffic distribution per carrier at least in accordance with the maximum traffic level per service, carrier, and direction. One action comprises the network node to enforce traffic steering in accordance with the allocated traffic distribution in the downlink and the uplink.

[0016] According to a fourth aspect there is presented a computer program product comprising a computer program according to the third 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.

[0017] Advantageously, these aspects provide efficient traffic steering in scenarios where there are simultaneous users to be served that require different priorities with respect to delay, quality, etc.Advantageously, these aspects enable efficient use of available radio resources, enabling the UEs to be served with higher quality-of-service at the same time as enabling the cell to be operated at higher capacity demands.

[0018] 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.

[0019] 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.

[0020] BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The inventive concept is now described, by way of example, with reference to the accompanying drawings, in which:

[0022] Fig. 1 is a schematic diagram illustrating a communication system according to embodiments;

[0023] Fig. 2 is a flowchart of a method according to an embodiment;

[0024] Figs. 3, 4, 5, 6, and 7 show simulation results according to embodiments;

[0025] Fig. 8 is a schematic diagram showing structural units of a network node according to an embodiment; and

[0026] Fig. 9 shows one example of a computer program product comprising computer readable storage medium according to an embodiment.

[0027] DETAILED DESCRIPTION

[0028] The inventive concept will now be described more fully hereinafter with reference to the accompanying drawings, in which certain embodiments of the inventive concept are shown. This inventive concept may, however, be embodied in many differentforms 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.

[0029] Fig. 1 is a schematic diagram illustrating a communication system loo where embodiments presented herein can be applied. The communication system 100 comprises a network node no configured to provide network access to, and thus serve, user equipment (UEs) I2oa:i2od in a cell 140. The network node 110 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. Each of the UEs 120a: i2od could be any of a portable wireless device, mobile station, mobile phone, handset, wireless local loop phone, smartphone, laptop computer, tablet computer, wireless modem, wireless sensor device, network equipped vehicle, Internet of Things (loT) device, game controller. The UEs 120a: I2od are served over carriers 130. In the non-limiting example of Fig. 1 is for illustrative purposes shown two downlink carriers (Carrier A and Carrier B). However, as the skilled person understands, there will also be uplink carriers, and there can be different number of carriers in the uplink compared to the downlink, and also different number of carriers for different UEs I2oa:i2od.

[0030] As noted above, there is still a need for improved traffic steering, especially in scenarios where there are simultaneous users to be served that require different priorities with respect to delay, quality, etc.

[0031] In Fig. 1 is further illustrated one non-limiting example of traffic steering 150 associated with the communication system 100, and where traffic from the UEs 120a, 120b, 120c corresponds to delay-sensitive services. According to the herein disclosed method for direction-wise traffic distribution among the carriers 130 in the cell 140, at least some of the traffic, as represented by packet 160, belonging to UE 120c is moved, as illustrated by arrow 170, from carrier A to carrier B in order to improve thecapacity on carrier A. The capacity can be defined as the maximum total traffic for which the utilization levels are below the maximum values for both carriers.

[0032] In this respect, according to the herein disclosed method for direction-wise traffic distribution among the carriers 130 in the cell 140, either part of or the entire traffic of any given UE can be moved from one carrier to another carrier. Assume for illustrative purposes that that the network node is serving 10 UEs in the cell using two carriers. According to a first non-limiting and illustrative example, all UEs have 30% of their traffic allocated to one of the carriers and 70% of their traffic allocated to the other carrier. According to a second non-limiting and illustrative example, three of the UEs have all their traffic allocated to one of the carriers and the remaining seven UEs have all their traffic allocated to the other carrier.

[0033] This allocation of carriers, either wholly or partly, is based on the network node considering a maximum traffic level per service, carrier, and direction (where the direction is either downlink or uplink). Different examples of such maximum traffic levels as well as different ways in which the maximum traffic level can be selected, or determined, will be disclosed below. This maximum traffic level can be combined with other metrics, or criteria, when distributing the traffic between the carriers. Examples where the maximum traffic level is combined with a baseline traffic steering approach will be disclosed below.

[0034] The embodiments disclosed herein in particular relate to techniques for directionwise traffic distribution among carriers 130 in a cell 140. In order to obtain such techniques, there is provided a network node no, a method performed by the network node no, a computer program product comprising code, for example in the form of a computer program, that when run on a network node no, causes the network node no to perform the method.

[0035] Fig. 2 is a flowchart illustrating embodiments of a method for direction-wise traffic distribution among carriers 130 in a cell 140. Direction-wise here implies that the traffic is distributed with respect to downlink and uplink. The method is performed by the network node 110. The method is advantageously provided as a computer program.The network node no is made aware of downlink and / or uplink quality-of-service requirements, such as downlink and uplink delay and reliability requirements, for a set of data, as in step S102.

[0036] S102: The network node no obtains downlink and / or uplink quality-of-service requirements for a set of data to be transmitted on the carriers 130. The set of data belongs to at least one service.

[0037] The network node no estimates a maximum load level, e.g. a cell utilization threshold, per carrier for enabling the quality-of-service requirements to be fulfilled in downlink and uplink. The maximum load level is transformed to a maximum traffic level, as in step S104.

[0038] S104: The network node no estimates a maximum traffic level per service, carrier, and direction. The maximum traffic level corresponds to a maximum load level for supporting the downlink and / or uplink quality-of-service requirements.

[0039] After deriving the maximum traffic level per service, carrier, and direction, the traffic distribution per carrier is scaled with the corresponding maximum traffic level, as in step S106.

[0040] S106: The network node no allocates the traffic distribution per carrier at least in accordance with the maximum traffic level per service, carrier, and direction.

[0041] Traffic steering can then be enforced in accordance with the allocated traffic distribution per carrier, as in step S108.

[0042] S108: The network node no enforces traffic steering in accordance with the allocated traffic distribution in the downlink and the uplink.

[0043] Embodiments relating to further details of direction-wise traffic distribution among carriers 130 in a cell 140 as performed by the network node 110 will now be disclosed.

[0044] There maybe different types of sets of data. In some embodiments, the set of data represents data of a time-critical communication service. In general terms, the set of data maybe any data set with quality-of-service requirements. For example, the set of data maybe associated with a premium Mobile Broadband (MBB) service. For example, the set of data maybe associated with a cloud gaming service. For example,the set of data maybe associated with an Extended Reality (XR) service. For example, the set of data may be associated with a holographic communication service (HCS), demanding high data rates and low latency. For example, the set of data maybe associated with a tactile Internet service, involving real-time interaction with haptic feedback, requiring ultra-low latency and high reliability. For example, the set of data maybe associated with a Vehicle-to-Everything (V2X) communication service, pertaining to any of vehicle-to-vehicle, vehicle-to-infrastructure, and vehicle-to-pedestrian communication, requiring low latency and high reliability. For example, the set of data may be associated with a high-precision positioning service, having applications in navigation and location-based services, requiring precise and reliable data transmission.

[0045] In general terms, the herein disclosed method for direction-wise traffic distribution among carriers 130 in a cell 140 can be combined with a baseline traffic steering approach. This baseline traffic steering approach may, for example, be based on channel quality and / or predefined priorities. Therefore, in some embodiments, the traffic distribution per carrier further is allocated based on a metric pertaining to channel quality and / or predefined priorities.

[0046] Here, the channel quality may provide the best choice of carrier in terms of received power. Hence, in some embodiments, the channel quality is given in terms of received power per carrier, and, according to the metric, amount of traffic to be allocated to a given carrier increases with increasing received power for the given carrier. In this way, more traffic can be allocated to carriers 130 with high received power than to carriers 130 with low received power.

[0047] In general terms, the predefined priorities may provide a flexible means to direct traffic to wanted carriers 130. Hence, in some embodiments, the predefined priorities pertain to different priorities of the carriers 130, and, according to the metric, amount of traffic to be allocated to a given carrier increases with increasing priority for the given carrier. In this way, traffic will be assigned to the carriers 130 with higher priority first. Hence, more traffic can be allocated to carriers 130 with high priority than to carriers 130 with low priority.

[0048] Further aspects of the maximum load level will be disclosed next.In general terms, the maximum load level may associate properties of the carriers 130 to the quality-of-service requirements for the set of data. In some non-limiting examples, the maximum load level is defined as any, or any combination, of: a cell utilization threshold, a load measure threshold, a resource utilization threshold. For example, the maximum load level may be given by a maximum cell utilization threshold for a time-critical communication service, by a load measure queue length, or by a physical resource block (PRB) utilization mapped to traffic in bits per second. The cell utilization can be defined as resource utilization measured per cell. The maximum load level may be defined by a connection count representing the number of simultaneous connections or sessions being handled by the network node. The maximum load level may be defined by the number of UEs actively using the network at a given time. The maximum load level may be defined by processing and memory usage at the network node, or some other network entity. Hence, the maximum load level may be measured in terms of usage of different resources with respect to their available limits. Some examples of cell usage are the usage of time-frequency resources, such as like PRB, transmit power, congestion. Interference in a cell can also be a load measure. Uplink Received Signal Strength indicator (UL RSSI), handover failure, cell throughput in uplink and downlink can be used as indicators for high interference. Further in this respect, the maximum load level is defined in terms of amount of traffic that can be carried without exceeding any, or any combination, of: a cell utilization threshold, a load measure threshold, a resource utilization threshold.

[0049] Further aspects of the network node obtaining the downlink and / or uplink quality-of-service requirements for a set of data to be transmitted on the carriers 130 will be disclosed next.

[0050] In some aspects, the downlink and / or uplink quality-of-service requirements are provided in terms of quality-of-service parameters and / or are defined by delay and reliability parameters associated with the set of data. Some non-limiting examples of quality-of-service parameters are: latency, which ensures minimal delay in data transmission; jitter, which measures variations in packet delay; packet loss rate, which indicates the percentage of lost data packets; throughput, which defines the maximum data transfer rate; reliability, which ensures consistent and error-free communication; availability, which refers to the network's uptime and servicecontinuity; and priority level, which determines the precedence of different types of traffic based on their importance.

[0051] The service in question could for example be associated with at least one network slice, and the at least one network slice may further be associated with a quality-of-service profile. That is, in some embodiments, the set of data is to be transmitted in at least one network slice, the at least one network slice is associated with a quality-of-service profile, and the downlink and / or uplink quality-of-service requirements are defined by the quality-of-service profile.

[0052] Further aspects of the network node estimating the maximum load level will be disclosed next.

[0053] In general terms, the maximum load level maybe estimated either by means of calculations or based on observed performance.

[0054] In terms of calculations, the network node may estimate probabilities of delays for transmission and queuing for different utilization levels, and set a maximum utilization level that leads to sufficiently low probability of delays beyond what is requested in the quality-of-service parameters. In particular, in some embodiments, the maximum load level is estimated by calculating probabilities of delays for transmission and queuing for different load levels in the cell 140, and the maximum load level is defined as highest load level that, according to the probabilities, yields a delay for transmission and queuing being below a threshold value for the downlink and / or uplink quality-of-service requirements for the set of data.

[0055] In terms of observations, the network node may monitor performance for different load levels, and then based on the monitored performance, determine a maximum load level for which acceptable performance is achieved. In particular, in some embodiments, the maximum load level is estimated by observing network performance for different load levels in the cell 140, and the maximum load level is defined as highest load level that, according to the observed network performance, yields a delay for transmission and queuing being below a threshold value for the downlink and / or uplink quality-of-service requirements for the set of data.Further aspects of how the network node may estimate the maximum traffic level will be disclosed below where the maximum traffic level is referred to as a cell utilization threshold.

[0056] Further aspects of the network node transforming the maximum load level to a maximum traffic level will be disclosed next.

[0057] For example, a maximum resource utilization can be transformed to a maximum number of UEs or traffic in bits per second using table look-up. Hence, in some embodiments, the maximum traffic level corresponds to the maximum load level by a look-up table comprising a mapping between maximum load levels and maximum traffic levels. The look-up table maybe established from observing traffic patterns, or other traffic characteristics, in the cell, or the look-up table maybe preconfigured. The use of such a table look-up may not be needed if the load already is measured in units of traffic, e.g., number of UEs or bits.

[0058] Further aspects of the network node allocating the traffic distribution per carrier will be disclosed next. As disclosed above, the traffic distribution per carrier can be scaled with the maximum traffic level. Hence, in some embodiments, maximum traffic level is used as a scale factor when allocating the traffic distribution per carrier. This may, for example, be achieved by first using a baseline a traffic steering approach that allocates a fraction xknof the traffic of UE n to carrier k, for n = 1, 2, ... , N, and k = 1, 2, ... , K, where N is the number of UEs served by the network node and K is the number of available carriers for the direction of concern (i.e., downlink or uplink).

[0059] Let the fraction of traffic allocated to carrier k of the baseline traffic steering be

[0060]

[0061] According to the herein disclosed embodiments, the desired maximum traffic levels Ckis taken into account by creating new fractions x'knof traffic allocated to the different carriers, formed by multiplying the baseline fractions xknwith factors fk, set by the desired traffic share:

[0062]

[0063] This yields:

[0064] >

[0065]

[0066] Which when solving for fkyields:

[0067]

[0068] For a baseline traffic steering principle with traffic fractions xkn, new traffic fractions x'kncan hence be allocated as x'kn= xknfk, with fkdefined as above.

[0069] As a non-limiting and illustrative examples, a common traffic steering approach is to set

[0070] rkn

[0071] xkn y <

[0072] Lkrkn

[0073] where rknis the bitrate for user n on carrier k, and thus to distribute traffic proportional to the bitrate of carriers. With that as a baseline traffic steering principle, the fractions x'knof traffic allocated to be allocated to the different carriers becomes:

[0074]

[0075] Further aspects of the network node enforcing the traffic steering will be disclosed next. This implies that the fractions of traffic, as given by x'kn, of UE n is allocated to carrier k.

[0076] In general terms, the enforcement generally depends on whether the set of data is to be transmitted in the downlink or in the uplink.

[0077] For enforcement in the downlink, the network node may directly allocate the set of data to the carriers 130. Hence, in some embodiments, the set of data is downlink data, and enforcing the traffic steering comprises allocating the set of data to the carriers 130 in accordance with the allocated traffic distribution per carrier in the downlink.For enforcement in the uplink, the actual traffic steering maybe regarded as enforced, or at least implemented, by the UEs upon instructions from the network node. In particular, in some embodiments, the set of data is uplink data, and enforcing the traffic steering comprises instructing a set of user equipment I2oa:i2od associated with the set of data to allocate the set of data to the carriers 130 in accordance with the allocated traffic distribution per carrier in the uplink. In this respect, for carrier aggregation, the network node may implicitly control the traffic distribution by scheduling different carriers (e.g., emptying the UE buffers on those carries), and then the UEs fill up the per-carrier buffers.

[0078] Traffic steering over multiple frequencies can be carried out in different ways depending on how the frequencies are combined in the network. Aspects relating thereto will be disclosed next.

[0079] In case frequencies are aggregated by means of carrier aggregation, bits are distributed by the transmitter and aggregated by the receiver on the Medium Access Control (MAC) layer. A scheduler operating on MAC level would hence take bits from incoming Service Data Units (SDUs) from the above layer, i.e., the Radio Link Control (RLC) layer, and place these SDUs in MAC Protocol Data Units (PDUs) that are sent on different frequencies. In the downlink direction, this traffic split is under direct control of the network node (as being responsible for the MAC scheduling). In the uplink direction, the MAC layer in the UEs maintains separate buffers of data ready for transmission, and the network node can, via scheduling commands sent to the UEs for each carrier, control how much data is sent on each carrier.

[0080] In case frequencies are aggregated by means of dual connectivity, bits are distributed by the transmitter and aggregated by the receiver on the Packet Data Convergence Protocol (PDCP) layer. A scheduler operating on PDCP level would hence take bits from incoming SDUs from the above layer, i.e., the Internet Protocol (IP) layer, and place these SDUs in PDUs sent on different frequencies. In the downlink direction, this traffic split is under direct control of the network node (as responsible for PDCP scheduling). In the uplink direction the network can, via Radio Resource Control (RRC) signaling, configure the PDCP layer in the UE to split traffic between the carriers in different ways.In case frequencies are not aggregated, but combined by means of intra-cell, interfrequency handovers, bits for one UE are sent on one frequency at a time. The selection of frequency band, for both downlink and uplink, is controlled at the RRC layer.

[0081] Simulation results will be disclosed next with reference to Figs. 3, 4, 5, 6, and 7. In each of those figures, results will be presented for an example communication system with two carriers. In some of the figures, these two carriers, below referred to as carrier 1 and carrier 2, are denoted to as “Sys 1” and “Sys 2”, respectively.

[0082] Fig. 3(a) shows bitrate as a function of distance for the two carriers. The different plots for each carrier correspond to different interference levels, generated by activity in neighbor cells. N = 100 UEs are served in the cell, at different distances to the network node. The bitrates plots hence correspond to rkn, for n = 1, 2, ... , N, and k = 1,2.

[0083] Fig. 3(b) shows the resource utilization of the two carriers as a function of the traffic for each of the carries. Here the total traffic per carrier is distributed equally over the UEs. In Fig. 3(b), the maximum utilization levels for which the service in question is supported with good enough quality, e.g. low enough delay with high enough reliability, are also marked by “0” and “x”. In other words, for higher traffic than these maximum utilization levels, the utilization increases but the delay for the service in question becomes too high. In this example the maximum utilization is lower for carrier 1 (where the maximum utilization is 0.2) than for carrier 2 (where the maximum utilization is 0.7). These maximum utilization levels correspond to the maximum traffic levels 0.55 and 1.25 for carrier 1 and carrier 2, respectively.

[0084] Fig. 3(c) shows results after allocating traffic using the baseline traffic steering approach with

[0085]

[0086] This results in the resource utilizations in solid and dashed plots. Accordingly, the two carriers have similar resource utilization, and the overall capacity is limited by carrier 1, which reaches its maximum utilization of 0.2 at a total traffic of around1.25- As a comparison, Fig. 3(c) also shows results after allocating traffic according to the herein disclosed embodiments with x'kn= xknfk, where

[0087] 0.55

[0088] f _ Crel i_ _ 0.55 + 1.25 _ Q76

[0089] 710.4 0.4

[0090] and where

[0091] 1.25

[0092] frel 2 0.55 + 1.25 -1 -1 -h =~M=— — =1 16- As per above, the scale factors / i and f2impact the values of xnand x'2 n, respectively. The scale factors / i and f2are selected in a way so that the maximum utilization levels are reached simultaneously (i.e., either same time or same total traffic level) for both carriers. One consequence of this is that having individual carriers being bottlenecks can be avoided, and therefore that the capacity can be maximized. According to the illustrative example in Fig. 3(c), this results in lower utilization for carrier 1, which was previously limiting, and higher utilization on carrier 2. As a result, carrier 1 now reaches its maximum utilization at a total traffic of 1.65. This corresponds to a capacity gain of 1.65 / 1.25 = 1.32, i.e., a capacity gain of 32%.

[0093] In the next examples the traffic steering per individual UEs is implicit. It is assumed that the traffic of the UEs can be controlled to adjust the resource utilization on two carriers; carrier 1 and carrier 2.

[0094] Fig. 4(a) shows how the resource utilization for each carrier increases as a function of the amount of traffic allocated to each carrier. For both carriers, the utilization growth is accelerating (i.e., growing faster than linear, or with a positive second derivative). This is a common phenomenon in multi-cellular system, since increased traffic results in increased interference, which reduces bitrates, and makes bits consume more and more resources. For the same resource utilization, carrier 2 carries more traffic than carrier 1. This can be due e.g., to carrier 2 having a wider bandwidth than carrier 1. In Fig.4(a), maximum utilization levels for which the service in question is supported with good enough quality, e.g., low enough delay with high enough reliability, are also marked by “0” and “x”. In this example themaximum utilization is lower for carrier 2 than for carrier 1. This can be due to, e.g., longer transmission times for carrier 2 than for carrier 1 due to static time-division duplexing (TDD) patterns being used.

[0095] Fig. 4(b) shows the resource utilization as a function of total traffic. The total traffic is split into two fractions, each carried by one of the carriers. The multiple different plots correspond to different shares of traffic carried by carrier i and carrier 2. It can be noted that by controlling the share of traffic that is carried by each carrier, the total traffic at which each carrier reaches its maximum utilization can be controlled.

[0096] Let the capacity be defined as the maximum total traffic for which the utilization levels are below the maximum values for both carriers. Fig. 4(c) shows how the capacity varies as a function of the fraction of traffic allocated to carrier 1. In the extreme point to the left, where no traffic is allocated to carrier 1 and all traffic is allocated to carrier 2, the capacity is equal to the traffic allocated to carrier 2 at its maximum utilization level (see, Fig. 4(a)), In the other extreme point to the far right, all traffic is allocated to carrier 1, and the capacity is equal to the traffic allocated at its maximum utilization. In between these points, the capacity is limited by the carrier that first reaches its maximum utilization. Starting from the left extreme point, where carrier 2 is limiting the capacity, an increase in capacity can be observed as smaller fractions of traffic have to be carried by the limiting carrier (i.e., carrier 2), allowing for a higher total traffic. This trend continues until carrier 1 is allocated so much traffic that it becomes limiting. Beyond that point, the more traffic that is allocated to the limiting carrier (i.e., carrier 1), the lower the total traffic will be supported. The point where the carriers simultaneously reach their maximum utilization levels hence corresponds to a capacity maximum.

[0097] In Fig.4(c) is also marked by “0” the traffic split at the resulting capacity as given by the herein disclosed embodiments. Thus, this traffic split takes into account the maximum utilization levels of the carriers (i.e., a maximum utilization level of 0.7 for carrier 1 and a maximum utilization level of 0.4 for carrier 2 in the present example). The traffic carried by the carriers at that utilization levels are 0.82 for carrier 1 and 1.27 for carrier 2 in the present example. According to the herein disclosed embodiments, traffic is allocated to the carriers based on the ratio of the individual carrier capacities to the sum of them (hence, allocating 0.82 / (0.82+1.27) = 0.39, i.e.,39% of the traffic to carrier 1 and the rest, i.e., 61% to carrier 2). This point coincides with the traffic split yielding the highest capacity in Fig. 4(c). This is different from the baseline traffic steering approach, as in Fig. 4(c) marked by “x”. The baseline traffic steering approach implies that the traffic is allocated to the carriers based on common maximum utilization levels, which would allocate i / (i+2) = 1 / 3, i.e., about 33%, of the traffic to carrier 1 and 67% of the traffic to carriers 2.

[0098] Fig. 4(d) shows the resulting traffic steering as given by the baseline traffic steering approach and the herein disclosed embodiments in the format of Fig 4(b). For the baseline traffic steering approach, it can be seen that the utilization levels in the carriers are practically equal, and that the carrier that reaches its maximum utilization first limits capacity; the dotted plot for carrier 2 reaches the maximum utilization level, as marked by “x”, before carrier 1. According to traffic steering based on the herein disclosed embodiments, more traffic is allocated to carrier 1, and the capacity is thereby improved. The maximum utilization levels, as marked by “0”, are reached for the same total traffic as for the baseline traffic steering approach, but with higher utilization.

[0099] In Figs. 5(a), 5(b), 5(c), and 5(d) are shown the same results as in Figs. 4(a), 4(b), 4(c), and 4(d), but with different maximum utilization thresholds. In Fig. 5 it can also be seen that the capacity is maximized when using traffic steering according to the herein disclosed embodiments, but not when using baseline traffic steering.

[0100] Further simulation results will be disclosed next with reference to Fig. 6 and Fig. 7.

[0101] In general terms, the resource utilization is a function of the generated bitrate and the served traffic load and will impact the number of active UEs served by the network node. As a result, the utilization level should be low enough to guarantee a low number of active UEs in the scheduler and consequently small delay due to queueing. Therefore, the time that resources are shared among many UE is taken into account when deciding on the cell utilization threshold. In general terms, the peak bitrate, the mean bitrate, and latency requirements will depend on the application, or service, its codecs, content type, hardware capabilities, its processes, functions, offloading schemes, and end-user target quality, among other factors. It maybe assumed that these latency requirements are known to the network node, e.g.., via signaling fromthe UEs. One way to select the cell utilization threshold such that the probability that a packet is correctly received is at least pR, where R is some reliability requirement, will be disclosed next.

[0102] During runtime operation, the cell utilization can be estimated as a combination of the number of active UEs served in the cell by the network node, scheduling policies, and available network resources. Outside runtime operation, the network node can be trained to observe the utilization that breaks any service requirements. For example, the network node may perform simulations, involving iterations over different utilization values until it finds the maximum value that still fulfils the reliability requirement for a given service. This value can then be stored in the network node. As a non-limiting and illustrative example, assume that the network node receives information of the failure probability requirement to meet a certain delay target for a given service, the packet delay distributions of UEs served by the network node at a given utilization level. At each iteration step the network node checks the failure probability. If the failure probability exceeds the required value, the utilization threshold is lowered. The iterations stop when the difference between the two utilization values that results in a failure probability closer to the target is below a required accuracy. Fig. 6 shows an example of the utilization threshold estimation for a low-band system. The two sub-plots correspond to the downlink and uplink directions, respectively. Fig. 7 shows an example of the utilization threshold estimation for a mid-band system. The two sub-plots correspond to the downlink and uplink directions, respectively.

[0103] Fig. 8 schematically illustrates, in terms of a number of structural units, the components of a network node 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 program product 910 (as in Fig. 9), 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).

[0104] Particularly, the processing circuitry 810 is configured to cause the network node 800 to perform a set of operations, or steps, as disclosed above. For example, the storagemedium 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 network node 800 to perform the set of operations. The set of operations maybe provided as a set of executable instructions.

[0105] Thus the processing circuitry 810 is thereby arranged to execute methods as herein disclosed. 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. The network node 800 may further comprise a communications (comm.) interface 820 at least configured for communications with other entities, functions, nodes, and devices, such as UEs 120a: i2od, other network nodes, and core network entities. As such the communications interface 820 may comprise one or more transmitters and receivers, comprising analogue and digital components. The processing circuitry 810 controls the general operation of the network node 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 network node 800 are omitted in order not to obscure the concepts presented herein.

[0106] The network node 800 maybe provided as a standalone device or as a part of at least one further device. For example, the network node 800 maybe provided in a node of the radio access network or in a node of the core network. Alternatively, functionality of the network node 800 may be distributed between at least two devices, or nodes. These at least two nodes, or devices, may either be part of the same network part (such as a radio access network or a core network) or may be spread between at least two such network parts. In general terms, instructions that are required to be performed in real time may be performed in a device, or node, operatively closer to the cell than instructions that are not required to be performed in real time. Thus, a first portion of the instructions performed by the network node 800 may be executed in a first device, and a second portion of the of the instructions performed by the network node 800 maybe executed in a second device; the herein disclosed embodiments are not limited to any particular number of devices on which the instructions performed by the network node 800 maybe executed. Hence, themethods according to the herein disclosed embodiments are suitable to be performed by a network node 8oo residing in a cloud computational environment. Therefore, although a single processing circuitry 810 is illustrated in Fig. 8 the processing circuitry 8io maybe distributed among a plurality of devices, or nodes. The same applies to the computer program 920 of Fig. 9.

[0107] Moreover, a network node 800 is not necessarily limited to an implementation in which a radio portion and a baseband portion are supplied and integrated by a single vendor. Thus, it will be understood that network nodes include disaggregated implementations or portions thereof. For example, in some embodiments, the network node may be an open radio access network (ORAN) network node. An ORAN network node is a network node that supports an ORAN 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 ORAN 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 ORAN specification). An ORAN network node may support a specification by, for example, supporting an interface defined by the ORAN 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 ORAN network node may be a logical node in a physical node. Furthermore, an ORAN 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 O-RAN Alliance or comparable technologies.

[0108] Fig. 9 shows one example of a computer program product 910 comprising computer readable storage medium 930. On this computer readable storage medium 930, a computer program 920 can be stored, which computer program 920 can cause theprocessing circuitry 8io 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 920 and / or computer program product 910 may thus provide means for performing any steps as herein disclosed.

[0109] In the example of Fig. 9, the computer program product 910 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 910 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 920 is here schematically shown as a track on the depicted optical disk, the computer program 920 can be stored in any way which is suitable for the computer program product 910.

[0110] 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 direction-wise traffic distribution among carriers (130) in a cell (140), the method being performed by a network node (no, 800), the method comprising:obtaining (S102) downlink and / or uplink quality-of-service requirements for a set of data to be transmitted on the carriers (130), wherein the set of data belongs to at least one service;estimating (S104) a maximum traffic level per service, carrier, and direction, wherein the maximum traffic level corresponds to a maximum load level for supporting the downlink and / or uplink quality-of-service requirements;allocating (S106) the traffic distribution per carrier at least in accordance with the maximum traffic level per service, carrier, and direction; andenforcing (S108) traffic steering in accordance with the allocated traffic distribution in the downlink and the uplink.

2. The method according to claim 1, wherein the set of data represents data of a time-critical communication service.

3. The method according to claim 1 or 2, wherein the traffic distribution per carrier further is allocated based on a metric pertaining to channel quality and / or predefined priorities.

4. The method according to claim 3, wherein the channel quality is given in terms of received power per carrier, and wherein, according to the metric, amount of traffic to be allocated to a given carrier increases with increasing received power for the given carrier.

5. The method according to claim 3 or 4, wherein the predefined priorities pertain to different priorities of the carriers (130), and wherein, according to the metric, amount of traffic to be allocated to a given carrier increases with increasing priority for the given carrier.

6. The method according to any preceding claim, wherein the maximum load level is defined as any, or any combination, of: a cell utilization threshold, a load measure threshold, a resource utilization threshold.

7. The method according to any preceding claim, wherein the maximum load level is defined in terms of amount of traffic that can be carried without exceeding any, or any combination, of: a cell utilization threshold, a load measure threshold, a resource utilization threshold.

8. The method according to any preceding claim, wherein the maximum load level associates properties of the carriers (130) to the quality-of-service requirements for the set of data.

9. The method according to any preceding claim, wherein the downlink and / or uplink quality-of-service requirements are defined by delay and reliability parameters associated with the set of data.

10. The method according to any preceding claim, wherein the set of data is to be transmitted in at least one network slice, wherein the at least one network slice is associated with a quality-of-service profile, and wherein the downlink and / or uplink quality-of-service requirements are defined by the quality-of-service profile.

11. The method according to any preceding claim, wherein the maximum load level is estimated by calculating probabilities of delays for transmission and queuing for different load levels in the cell (140), and wherein the maximum load level is defined as highest load level that, according to the probabilities, yields a delay for transmission and queuing being below a threshold value for the downlink and / or uplink quality-of-service requirements for the set of data.

12. The method according to any preceding claim, wherein the maximum load level is estimated by observing network performance for different load levels in the cell (140), and wherein the maximum load level is defined as highest load level that, according to the observed network performance, yields a delay for transmission and queuing being below a threshold value for the downlink and / or uplink quality-of-service requirements for the set of data.13- The method according to any preceding claim, wherein the maximum traffic level corresponds to the maximum load level by a look-up table comprising a mapping between maximum load levels and maximum traffic levels.

14. The method according to any preceding claim, wherein the maximum traffic level is used as a scale factor when allocating the traffic distribution per carrier.

15. The method according to any of claims 1 to 14, wherein the set of data is downlink data, and wherein enforcing the traffic steering comprises allocating the set of data to the carriers (130) in accordance with the allocated traffic distribution per carrier in the downlink.

16. The method according to any preceding claim, wherein the set of data is uplink data, and wherein enforcing the traffic steering comprises instructing a set of user equipment (120a: i2od) associated with the set of data to allocate the set of data to the carriers (130) in accordance with the allocated traffic distribution per carrier in the uplink.

17. A network node (no, 800) for direction-wise traffic distribution among carriers (130) in a cell (140), the network node (no, 800) comprising processing circuitry (810), the processing circuitry being configured to cause the network node (no, 800) to:obtain downlink and / or uplink quality-of-service requirements for a set of data to be transmitted on the carriers (130), wherein the set of data belongs to at least one service;estimate a maximum traffic level per service, carrier, and direction, wherein the maximum traffic level corresponds to a maximum load level for supporting the downlink and / or uplink quality-of-service requirements;allocate the traffic distribution per carrier at least in accordance with the maximum traffic level per service, carrier, and direction; andenforce traffic steering in accordance with the allocated traffic distribution in the downlink and the uplink.

18. The network node (no, 8oo) according to claim 17, further being configured to perform the method according to any of claims 2 to 16.

19. A computer program (920) for direction-wise traffic distribution among carriers (130) in a cell (140), the computer program comprising computer code which, when run on processing circuitry (810) of a network node (no, 800), causes the network node (110, 800) to:obtain (S102) downlink and / or uplink quality-of-service requirements for a set of data to be transmitted on the carriers (130), wherein the set of data belongs to at least one service;estimate (S104) a maximum traffic level per service, carrier, and direction, wherein the maximum traffic level corresponds to a maximum load level for supporting the downlink and / or uplink quality-of-service requirements;allocate (S106) the traffic distribution per carrier at least in accordance with the maximum traffic level per service, carrier, and direction; andenforce (S108) traffic steering in accordance with the allocated traffic distribution in the downlink and the uplink.

20. A computer program product (910) comprising a computer program (920) according to claim 19, and a computer readable storage medium (930) on which the computer program is stored.

Images