COMMUNICATION NETWORK

TECHNICAL FIELD Embodiments herein relate to a network node, a communication device and method therein for system capacity estimation. In particular, they relate to estimation of system capacity in a wireless communications network providing Fixed Wireless Access (FWA) for one or more Customer Premise Equipment (CPEs). BACKGROUND

Wireless communication networks or mobile telephony networks, such as Global System for Mobile Communications (GSM) networks, Wideband Code Division Multiple Access (WCDMA) or High Speed Packet Access (HSPA) networks, Long Term Evolution (LTE) or 4 ^th Generation (4G) networks, 5G New Radio (NR) networks, usually cover a geographical area which is divided into cell areas. Each cell area is served by a base station, which may also be referred as a network node, a network access node or an access node etc. A wireless communication network may include a number of base stations, serving a number of cells that can support communications for a number of wireless communication devices or user equipment (UEs). Fixed Wireless Access (FWA) is typically used to denote the usage of a wireless network, also sometimes referred to as a mobile network, e.g. GSM, WCDMA or LTE, or a network based on a proprietary wireless technology, to provide broadband access to fixed users such as households or Small and Mediums sized Enterprises (SME). This is an alternative to other broadband providing techniques like “non-specified” Digital Subscriber Line (xDSL), e.g. Asymmetric Digital Subscriber Line (ADSL), cable or fiber connections.

There are several commercial reasons which make FWA an attractive alternative. For example, in areas where the fixed broadband not yet is built out, fiber, cable or copper wires can be a more expensive alternative than adding resources to a mobile network. In addition, mobile networks are often dimensioned for coverage in order to secure mobility. Hence there are large areas, where the resources are under-utilized, or existing spectrum assets are not deployed, so that the mobile operators can with a very small or limited investment provide FWA services in specific regions. A mobile network serving an FWA subscriber is schematically depicted in Figure 1. At the customer premise, a CPE serves as a node which communicates with the mobile network over the air interface. This may be done using a number of standards but here, without loss of generality, using LTE as an example. The CPE is connected to a router or radio gate way which communicates with user equipment such as smartphones, iPads, computers, TV, etc. over e.g. Ethernet or WiFi. The CPE could also in some cases include the router or radio gate way. On the network side, the signal from/to the CPE is received and transmitted by an antenna handled by a radio and a baseband unit, also referred to as a base station or an access point, in a radio access network (RAN) and via a core network (CN) and an internet gateway, the connection to the internet is made. The mobile network is managed by a number of entities which controls different parts of the network, such as RAN management functionality, CN management functionality, FWA CPE management functionality etc.. In an FWA network, there may be one or more of these entities which controls the CPE via signaling over the air interface. The CPE is thus configured by the network and may be triggered to do specific measurements or take specific actions.

From a consumer or subscriber perspective, a typical FWA subscription is different from a mobile telephony subscription. A FWA subscriber does not expect mobility of the CPE as it is seen as a fixed location connection. Moreover, the subscription is typically different from a mobile subscription in that instead of offering a limited data bucket, e.g. 10GB/month, they are typically data rate oriented, e.g. 100Mbps downlink/10Mbps uplink, which is the rate a normal subscriber may expect at low or medium system load. Thus, the subscription model will be similar to those seen for a fixed broadband e.g. via fiber. At high load, these rates might not be achievable, but the operator usually dimension the network to be able to guarantee most users a specific data rate, e.g. 5Mbps for the 5th percentile user at busy hour which means that at least 95% of the users will, at download speed tests during any time of the day experience this data rate.

One main difference between a fixed broadband connection and FWA is that FWA is using a shared media for the last connection between the network and the subscriber thru a common air interface. This means that the dimensioning of this link will dimension the system and thereby the end users’ experience. Thus, for dimensioning, since the last link is wireless, all the characteristics of a wireless network will apply. Unlike fiber, but similar to xDSL local loop length, there will be varying connection quality to different households depending on locations. And, unlike fixed broadband overall, the last hop is radio and so shared, which means that quality will degrade with load. When dimensioning Mobile Broadband (MBB) networks, user rates in different parts of the cell and under different cell loads are important performance indices, see Figure 2. A network capacity may e.g. be defined as the maximum load in the system or for a given node at which a certain percentile, e.g. 5th percentile, experience a specified data rate, e.g. 5Mbps.

Traditionally in a cellular system one base station serves one cell, thus there is traditionally a one to one relationship. But a base station may in some cases serve more than one cell. As an example there may be 3 sectors if considering Macro towers. Each sector may be considered as a separate cell. Moreover, the sectorization may be different for different frequency band. So it may have an omni antenna on one frequency and three sectors on another. Thus different frequencies may be considered as different cells. To add an additional level of complexity some modern systems utilize beamforming, having multiple antennas and applying different techniques to direct the radio signal in a narrow beam.

In mobile telephony systems a ’cell’ is normally defined as the achieved coverage area by a radio carrier on a specific frequency band. When the system estimates that another cell is a better choice for coverage, capacity or quality, a hand-over is performed. The hand-over can be to a neighbouring cell site or another more suitable frequency band/cell on the same site if that is an alternative.

For the purpose of this application a base station can serve one or more cells. In this latter case one could also chose to regard the base station as several logical base stations serving one cell each, or as one base station serving more than one cell each.

In mobile networks, users will move around with UE, i.e. the mobile phones, resulting in that the signaling conditions will vary due to the different environment. For FWA the user equipment, denoted as Customer Premises Equipment (CPE) is stationary. This means that there is a much smaller variation in signal strength over time for a CPE than for a typical mobile phone. From an operator perspective, it is important to optimize the signal quality as this means that more bits can be sent over a given amount of resources. In NR or LTE, the spectrum and time is divided in physical resource blocks (PRBs) and the better signal strength, the more bits per PRB is achievable. The UE measure the signal quality and reports a Channel Quality Index (CQI) which indicates to the base stations which Modulation and Coding Scheme (MCS) that can be used. The higher modulations and the higher code rate used, the more bits per PRB and thus a more efficient use of the air interface. One difference when managing and dimensioning a network for FWA relative mobile broadband (MBB) users is that since the CPEs are fixed, a user with a poor connection is likely to have a poor connection all or most of the time, whereas for MBB a user moving around will sometimes be in a good and sometimes in a bad position. Thus, the worst percentage of FWA users will typically be the same households over time. A household with a poor signal quality may consume many times the amount of radio resources to download data at a given rate, compared to a household with a more favorable signal quality.

Thus, for FWA deployments where the CPEs are static, it is of utmost importance that the typical signal strength is as high as possible for each specific link. The signal strength may be improved by different measures, e.g. using an outdoor CPE instead of an indoor will limit the path loss. Furthermore, directive antennas on the CPE will be beneficial to improve the signal strength.

Moreover, as the radio link between a base station and CPEs in a specific area is common, all users will be affected if the load becomes too high. Overselling might thus have a significant negative impact of the performance. Thus, it is crucial for the operator to have a good view on how much traffic current subscribers consume and how many more users can be admitted to the system. As the traffic demand is expected to grow over time, the operator needs to plan their network to also handle future increasing demands. This could mean e.g. adding more spectrums by adding more radio equipment, splitting sectors at current base stations and/or adding new base stations so called densification.

Networks used to serve FWA access users are typically limited by the number of users each node can serve during the busiest hour. Hence the system capacity is a crucial measure for the operator to understand how many users can be served. As user behavior varies over time, it is difficult to draw conclusion on how much more traffic a specific node could handle based on statistics of the current user data consumption. The consequences of selling too many subscriptions in an area are significant as it will degrade performance for many of the existing users.

SUMMARY

It is therefore an object of embodiments herein to provide a method to estimate system capacity in a wireless communications network providing Fixed Wireless Access. According to one aspect of embodiments herein, the object is achieved by a method performed in a network node for estimation of system capacity in a wireless communications network providing FWAfor one or more CPEs. The wireless communications network comprises one or more core network nodes and one or more base stations which can be operatively connected to one or more CPEs.

The network node monitors traffic related information in a first cell served by a first base station during a first time period, where the first base station handles a first traffic load, where the first traffic load comprises added emulated traffic making the first traffic load exceed a regular traffic load of a second time period.

The network node calculates capacity related characteristics, based on the obtained traffic related information, for the first base station and/or at least one of the one or more CPEs being operatively connected to the first base station.

The network node estimates system capacity for the second time period, based on the capacity related characteristics.

According to one aspect of embodiments herein, the object is achieved by a method performed in a remote device for assisting estimation of system capacity in a wireless communications network providing Fixed Wireless Access, FWA, for one or more Customer Premise Equipment, CPEs. The wireless communications network comprises one or more core network nodes and one or more base stations which can be operatively connected to one or more CPEs.

The remote device receives a signal and generates and causes transmission of emulated traffic on an uplink towards a first base station serving a first cell.

In other words, according to the embodiments herein, the system capacity estimation is performed by sending and receiving dummy signals over the air interface. By inducing traffic into the system during the first time period typically when there is little or no real traffic, an example could be at off-peak hours, like night time, system capacity for specific cells can be estimated for a second time period, for example for the busy hour/peak traffic. The first and second time period could of course be any chosen time period, and the first and second time period could be the same time period. For example, CPE management functionality in the network can trigger that all users simultaneously receive or sends dummy diagnostic traffic in different patterns to probe the system capacity. Relating these diagnostic data results, including accurate reporting of the actual signal quality situation per household, with the data consumption statistics for current users and estimates of requirement traffic growth, it is possible to get indications in which areas more subscribers may be allowed into the system and in which areas means to improve capacity will be needed.

Therefore, according to the embodiments herein, the resource situation may be estimated using measurements conducted by the UEs in a specific cell in a mobile network and, based on these measurements and statistics of user data, estimation on whether more FWA subscriptions can be added in the specific cell may be made.

The embodiments herein allow the network to analysis and estimate system capacity for each network node, e.g. even if a system is not utilized fully it is possible to know in which areas more subscriptions may be added and where measures are needed to enhance the capacity.

BRIEF DESCRIPTION OF THE DRAWINGS

Examples of embodiments herein are described in more detail with reference to attached drawings in which:

Figure 1 is a schematic block diagram illustrating a wireless communication network used for FWA;

Figure 2 is a diagram illustrating an example of performance indices for a wireless communication network;

Figure 3 is a schematic block diagram illustrating a wireless communication network in which embodiments herein may be implemented;

Figure 4 is a flow chart illustrating a method performed in a network node according to embodiment herein;

Figure 5 is a flowchart illustrating an exemplary algorithm for estimating system capacity according to embodiments herein;

Figure 6 is a flow chart illustrating an example on an algorithm to estimate impact of a new specific potential user;

Figure 7 is a flow chart illustrating a method performed in a remote device according to embodiment herein; and

Figure 8 is a schematic block diagram illustrating embodiments of a network node; and

Figure 9 is a schematic block diagram illustrating embodiments of a UE/CPE.

DETAILED DESCRIPTION Figure 3 depicts an example of a wireless communication network 300 in which embodiments herein may be implemented. The wireless communication network 300 may be any wireless system or cellular network, such as a Long Term Evolution (LTE) network, any 3 ^rd Generation Partnership Project (3GPP) cellular network, a Fourth Generation (4G) or LTE advanced network, 5G NR network etc.

The wireless communication network 300 comprises a plurality of network nodes whereof two, a first network node NN 310 and a second network node NN 320 are depicted in Figure 3. The wireless communication network 300 further comprises a plurality of base stations, whereof two, a first base station BS 312 which serves a first cell 311 and a second base station BS 322 which serves a second cell 322, are depicted in Figure 3. The base station may also be referred as eNB, gNB, eNodeB, gNodeB etc. The first network node 310 and the second network node 320 are network nodes which may also be refereed as network controllers or core networks, it can also be a management unit, which communicate with the first and second base stations, and act as a handling unit, management unit or a controller for different Radio Access Technologies. The network node 310, 320 may be a separate node as depicted in the figure, or its corresponding functionalities may be incorporated within another network node such as e.g. the base stations 312, 322.

A plurality of UEs or CPEs operates in the wireless communication network 300, whereof a UE/CPE 330 is depicted. The CPE 330 may be an UE or any other radio network units capable to communicate with the base station 312, 322 over a radio link in the wireless communication network 300.

UEs, including CPEs, report periodically measurements to the base stations this could happen both in idle mode and in connected mode. In LTE, e.g. the channel quality is reported by a CQI index which then is used by the network to set an appropriate level coding and modulations scheme. Thus, for a low signal to interference and noise situation, a lower coding rate and/or modulation scheme is chosen and vice versa. With a lower CQI, more resources (PRBs) will be used for the same user data. Consequently, there is a direct relation between the reported CQI and the resources required in the down link to serve a specific user.

When the system load is increased, the interference will go up, which will lead to lower CQI and less efficient transmission of data streams to the different users. Thus, there is a relation between system load and reported CQI which is specific for each CPE. Since the CPEs are static, the radio environment is relatively stable compared to the mobile environment. Thus, it is possible to gather statistics on the relation between system load and reported CQI, for the specific users, i.e. at what efficiency, the signaling can be done to a specific user depending on the system load.

Using statistics of how much traffic specific users in a cell consume, at different times of the day, together with knowledge of how the link efficiency for the given system load, it is possible to estimate the impact of adding more subscribers to the cell. This may e.g. be done, either by using average consumption estimates and average users’ relation between system load and resource assumption.

If the signals strength for a new potential customer is known, e.g. thru on-site measurements, these may be used to improve the capacity estimate. The signal strength may be compared to similar measurements for current connected CPEs. These may either be measurements made on site or based on measurement reports done by the CPEs. Replacing the average CPE’s behavior with the behavior a specific CPE with similar characteristics or average behavior of a group of specific CPEs, a more precise estimate may be obtained.

Example of embodiments of a method performed in a network node 310, 320 for estimation of system capacity in a wireless communications network providing FWA for one or more CPEs in a wireless communication network 300 will now be described with reference to Figure 4. As described above, the network node 310, 320 may be a separate node as depicted in Figure 3, or its corresponding functionalities may be incorporated within another network node. The method comprises the following actions, which actions may be separated on more nodes, e.g. management such as monitoring traffic related information may be done in one node while parts of calculations may be done in another node.

Action 410

The network node 310, 320 monitors traffic related information in a first cell 310 served by a first base station 312 during a first time period where the first base station handles a first traffic load. The first time period may be a period when there is little or no regular traffic, e.g. at peak off-hour night time. The first traffic load comprises added emulated traffic making the first traffic load exceed a regular traffic load of a second time period. The first time period may be the same as the second time period or different from the second time period. The second time period may be busy hours, for example during daytime when there are regular traffics.

The traffic related information may comprise be any one of quality indicators such as CQI, user averaged or momentary throughput, Signal to Interference and Noise Ratio (SINR), reference signal received power (RSRP), reference signal received quality, received interference power etc.

According to some embodiments herein, the network node 310, 320 monitoring traffic related information may comprise obtaining information carried in one or more measurement reports sent to the first base station 312 from at least one of the one or more CPEs 330 operatively connected to the first base station 310. For example, the network node 310, 320 may receive from the first base station 312 the one or more measurement reports.

The network node 310, 320 may obtain information on traffic loads with time stamps for the first base station 312 based on the one or more measurements report.

The network node 310, 320 may measure traffic loads with time stamps for at least one of the one or more CPEs 330 operatively connected to the first base station (312) based on the one or more measurements reports.

The network node 310, 320 may also measure traffic loads with quality indicators per data burst received by the CPE 330.

According to some embodiments herein, the network node 310, 320 monitoring traffic related information may comprise obtaining information on the traffic sent between the first base station 312 and at least one of the one and more CPEs 330 being operatively connected to the first base station 312.

According to some embodiments herein, the network node 310, 320 monitoring traffic related information may comprise obtaining information on measurements made by the first base station 312.

According to some embodiments herein, the added emulated traffic, i.e. the part of the first traffic load that exceeds the regular traffic load in the second time period may represent any one or a combination of:

(a) estimated potential increased traffic load, for the second time period, for one or more of the CPEs currently operationally connected to the first base station 312;

(b) estimated traffic load, for the second time period, for one or more potentially additional CPEs not currently operationally connected to the first base station 312;

(c) gradually increased traffic load, e.g. increasing traffic load with a predefined amount. This increased traffic load may not necessarily represent the traffic that “should be added” to the cell, but rather just a stepwise increased traffic related to, e.g. an increased usage of resources in general in a cell.

The added emulated traffic may be generated by different nodes in the network:

According to some embodiments herein, the network node 310, 320 monitoring traffic related information may further comprise contributing to generation of the added emulated traffic, may also be referred to as dummy traffic, by transmitting emulated traffic during the first time period, via the first base station, to any one of or any combination of: at least one of the one or more CPEs being operatively connected to the first base station 312, at least one device being operatively connected to one of the one or more CPEs being operatively connected to the first base station 312.

According to some embodiments herein, the network node 310, 320 monitoring traffic related information may further comprise causing one of the one or more CPEs, being operatively connected to the first base station 312 to contribute, to generation of the added emulated traffic by transmitting emulated traffic during the first time period to the network node 310, 320 via the first base station 312.

According to some embodiments herein, the network node 310, 320 monitoring traffic related information may further comprise causing a device, being operatively connected to one of the one or more CPEs being operatively connected to the first base station 312, to contribute to generation of the added emulated traffic by transmitting emulated traffic during the first time period to the network node 310, 320 via the first base station 312.

When increasing dummy traffic in a cell, it’s desired that neighbouring cells also are fairly loaded, at least representing a normal busy hours’ load. In order to evaluate the system capacity in as real scenario as possible, interferences from neighbour or adjacent cells should be taken into account. In some cases, the neighbour cells may have a certain traffic load that is sufficient, while at other cases it may be preferential that the network node causes some emulated traffic to be sent in the neighbour cells. Interferences may be generated by generating traffic in one or more adjacent cells, e.g. the network node may cause generation of emulated traffic in a second cell.

Therefore according to some embodiments herein, the network node 310, 320 monitoring traffic related information may further comprise generating emulated traffic in a second cell 321 by transmitting emulated traffic during the first time period, via a second base station 322 serving the second cell 321, to any one of or any combination of: at least one of one or more CPEs being operatively connected to the second base station 322, at least one device being operatively connected to one of one or more CPEs being operatively connected to the second base station 322.

According to some embodiments herein, the network node 310, 320 monitoring traffic related information may further comprise causing at least one of one or more CPEs, being operatively connected to a second base station 322 serving a second cell 321, to generate emulated traffic in the second cell 321 by transmitting emulated traffic during the first time period to the network node via the second base station 322.

According to some embodiments herein, the network node 310, 320 monitoring traffic related information may further comprise causing a device, being operatively connected to one of one or more CPEs being operatively connected to a second base station 322 serving a second cell 321, to generate emulated traffic in the second cell 321 by transmitting emulated traffic during the first time period to the network node via the second base station 322.

The emulated traffic may be any random generated pattern as the content is of no importance. It is the system’s and individual CPE’s behaviour at different level of systems load that are interested to check, i.e. the ability to receive and decode data and report the instant quality of reception per time period, loading situation. There may be different alternatives to transmit the emulated traffic:

The emulated traffic may be transmitted as a response to receiving traffic, e.g. a CPE or a device connected to the CPE may generate and transmit emulated traffic upon reception of emulated traffic over the wireless communications network. This maybe useful for a variety of things, like for example emulating application level acknowledgements, emulating application level responses, etc.

The emulated traffic may be transmitted according to a predefined pattern, e.g. a CPE or a device connected to the CPE may generate and transmit messages of different sizes at different times according to a predefined logic or pattern. This may be useful for a variety of things, like for example emulating application level reports, or uploading of data. The emulated traffic may be transmitted according to a received pattern, e.g. as above but the pattern may be received over the wireless communications network.

The emulated traffic may be transmitted according to a random pattern.

The emulated traffic may also be transmitted according to any combination of the above alternatives.

Different implementations may use any of, or any combinations of, the above, or any other techniques for generating and transmitting emulated traffic. The exact implementation of the above, and the mechanisms and computer protocols required to implement them are outside the scope of this description.

The emulated traffic could represent a variety of specific traffic cases or combinations thereof. Such as streaming, downloading and/or uploading, interactive use of services, etc. The use of internet has an enormous amount of use cases.

The discussion above may of course also apply to the node in the network side that generates and transmits emulated traffic.

According to some embodiments, the at least one of the one or more CPEs being operatively connected to the first base station, participating as sender and/or receiver of the emulated traffic, are in a location that is representative of where one or more new CPEs might be installed.

Action 420

The network node 310, 320 calculates capacity related characteristics, based on the obtained traffic related information, for the first base station and/or at least one of the one or more CPEs being operatively connected to the first base station 312.

The network node 310, 320 calculates capacity related characteristics may be performed by making one or more statistical calculations resulting in any one or a combination of:

(a) statistical measure of data transmission efficiency as a function of system load per CPE. The data transmission efficiency may dependent upon associated quality indicator per data burst received by the CPE. Further statistical measure of data efficiency and modulation may also be calculated.

(b) statistical measure of load for the first base station as a function of time. (c) statistical measure of user traffic as function of time for at least one of the one or more CPEs being operatively connected to the first base station.

(d) statistical measure of user traffic as function of time over ensembles of CPEs, of the one or more CPEs operatively connected to the first base station 312.

There are a number of statistical measures, e.g. moment of different orders, standard (std) deviation, standard variance etc. Basically, any function which is an attempt to capture statistics may be used. There may be explicitly defined e.g. like mean or standard deviation or implicitly by some multidimensional function mapping input to output as done by neural networks, machine learning algorithms etc. So the statistical measure may comprise any one or any combination of mathematical mean, mathematical median, mathematical variance, mathematical percentile, etc.

Action 430

The network node 310, 320 estimates system capacity for the second time period based on the calculated capacity related characteristics.

The system capacity may be any one or any combination of the following alternatives:

(a) an amount of free resources for the first cell served by the first base station 312.

(b) node capacity for the first base station 312.

(c) the number of potentially additional CPEs, not currently being operatively connected to the first base station 312, that could be operatively connected to the first base station 312.

(d) the estimated possible increased traffic load, for one or more of the CPEs currently operationally connected to the first base station 312.

(e) how much the capacity can be increased for the first base station 312.

Therefore, according to some embodiments herein, the network node 310, 320 may estimate system capacity for a selected traffic load by estimating any one of or any combination of the above alternatives (a)-(e).

According to some embodiments herein, the network node 310, 320 may estimate system capacity for the second time period, for a selected traffic load, by estimating any one of or any combination of:

(a) capacity for at least one of the one or more CPEs currently being operatively connected to the first base station 312. (b) throughput for at least one of the one or more CPEs currently being operatively connected to the first base station 312.

(c) signaling conditions for at least one of the one or more CPEs currently being operatively connected to the first base station 312.

(d) indication of service level for at least one of the one or more CPEs currently being operatively connected to the first base station 312.

(e) capacity for at least one of the one or more potentially additional CPEs, currently not being operatively connected to the first base station 312.

(f) throughput for at least one of the one or more potentially additional CPEs, currently not being operatively connected to the first base station 312.

(g) signaling conditions for at least one of the one or more potentially additional CPEs, currently not being operatively connected to the first base station 312.

(h) indication of service level for at least one of the one or more potentially additional CPEs, currently not being operatively connected to the first base station 312.

With the estimated system capacity, the network node 310, 320 may determine whether to allow an increased traffic load for a CPE currently operationally connected to the first base station 312, or determine whether to allow a potentially additional CPE, not currently operationally connected to the first base station 312, to be operationally connected to the first base station 312.

To illustrate the method performed in the network node 310, 320 for estimation of system capacity, an exemplary algorithm for estimating system capacity is shown in Figure 5. The algorithm may comprise the following steps:

501. Measurements done by the CPE periodically and reported to the network node 310, 320. The data may be stored together with time stamps in a database 507.

502. The load of one or more cells is monitored and stored with time stamps in the database 507.

503. The consumed traffic for each user for the cell(s) is monitored and stored with time stamps in the database 507.

504. Based on stored data, average statistics of CPEs and BS characteristics is calculated and stored.

Some examples which may be calculated are:

(a) Average efficiency, e.g. in bits per PRB, as a function of system load per CPE. (b) Average load per cell as a function of time of day and/or week.

(c) Average user traffic as function of time of day/week for specific CPEs as well as averaged over ensembles of CPEs.

505. Estimate the average amount of free resources during busy hours, e.g. in PRBs.

506. Estimate number of potential additional subscribers which may be allowed to enter the system depending upon the estimated location and data transmission efficiency.

In order to improve the statistics and by that get better estimates, the network node 310, 320 can induce traffic into the system e.g. when there is little or no regular traffic. As an example, a network node, or other node, may generate and transmit emulated traffic to one or more CPEs, and/or order selected groups CPEs in one or more cells to generate and transmit emulated traffic in the other direction. By monitoring the measurement reports including e.g. CQI and comparing with the achieved throughputs for different CPEs the system capacity for a fully loaded system may be estimated. Moreover, the throughput of each CPE at a given system load may be estimated. These measurements may be used to improve the calculations in the previous algorithm.

As an example, the system may at night time trigger test periods and start with inducing small amounts of data, ramping up gradually until the system capacity is reached.

Therefore according to some embodiments herein, the added emulated traffic, in the first cell, may be gradually ramping up during the first time period.

Then the network node 310, 320 monitors traffic related information, e.g. bitrate, total traffic load, in a first cell served by a first base station where the first base station 312 handles a second traffic load, where the second traffic load comprises added emulated traffic.

The network node 310, 320 further calculates capacity related characteristics, e.g. throughput, and estimate system capacity.

The network node 310, 320 further determines whether the estimated system capacity is lower than a system capacity threshold.

When the system capacity is lower than a threshold, the network node 310, 320 continues monitors traffic related information in a first cell served by a first base station 312 where the first base station handles a third traffic load, where the third traffic load comprises an increased amount of emulated traffic making the third traffic load higher than the second traffic load. That is the emulated traffic is increased gradually by a predefined amount.

The system capacity threshold may e.g. be defined as the maximum load in the system or for a given node, at which a certain percentile, e.g. 5th percentile, experience a specified data rate or throughput, e.g. 5Mbps. So the network node 310, 320 may determine whether the maximum system capacity is reached by increasing traffic load with a predefined amount and continue measuring and comparing the throughput of each CPE with a throughput threshold until the throughputs of a predetermined percentage of CPEs are smaller than the throughput threshold.

Having detailed knowledge on how CPEs behaves, relative different system loads may improve the estimate done in the step 506. In Figure 6, an example on an algorithm to estimate impact of a new specific potential user is shown. The algorithm may comprise the following steps:

601. For a new potential subscriber, the signalling conditions is estimated or measured. This may e.g. be done by on-site measurements at the customer premise, by comparing the locations of the customer with current customers close by or by using coverage maps.

602. Comparing the results from 501 with characteristics of other CPEs or average of groups of CPEs, anticipated characteristics for the new potential subscriber may be obtained.

603. Using the anticipated characteristics from 602, and the results estimated available resources in the network node from step 405, a decision on whether the new potential subscriber can be allowed to enter the system. In addition, precaution measures, such as requiring an outdoor CPE may be taken if deemed necessary or beneficiary. Moreover, indication of service level may be obtained, for example which typical rates maybe expected for the new customer.

At the CPE side, according to some embodiments herein, a method performed in a communication or remote device 330 for assisting estimation of system capacity in a wireless communications network providing FWA for one or more CPE will be described with reference to Figure 7. The communication/remote device may be a CPE 330 operatively connected to the first base station. The communication/remote device may also be a device that is operatively connected to a CPE which is operatively connected to the first base station. The method comprises the following actions: Action 701

The communication/remote device 330 receives a signal. The signal may be sent by a first or second base station. The signal may be instructions or emulated traffic that triggers the communication/remote device 330 to transmit dummy data and the network node measures the quality on these dummy data.

In some embodiments, the communication/remote device 330 may determine whether the received traffic is emulated traffic. The determination may in some embodiments be performed by the communication/remote device receives the traffic utilising a communications protocol associated with only emulated traffic. It may also be performed by receiving traffic with a flag or tag that indicates that this is emulated traffic. A variety of other versions may be imagined, e.g. that the communications/remote device is programmed or instructed to understand that traffic received at certain times is emulated traffic, etc.

Action 702

The communication/remote device generates and causes transmission of emulated traffic or dummy data on an uplink towards a first base station serving a first cell.

The communication/remote device 330 may generate and cause transmission of emulated uplink traffic based on any one of or any combination of the received emulated traffic, received instructions, a predefined pattern, a received pattern or a random pattern.

To summarize, the embodiments herein describes means and methods for operators who provides FWA to measure and estimate system capacity and based on the actual system capacity decide on whether new customers can be added to the system without overloading the system or degrading current users experience. Furthermore, the system diagnostics may be used for planning network improvement such as densification, adding bandwidth etc.

It is not necessary to make uplink and downlink estimates at the same time. These may be made independently. For example, data may be sent in the down link and the CPE may report the quality parameters, or the communication/remote device, the CPE or a device connected to the CPE, may be instructed or ordered to transmit emulated traffic and the network node measures the quality on these and stores and analyses. These two options above may be performed in sequence or these two options above may be performed simultaneously. To perform the method actions in a network node 310, 320 for estimation of system capacity in a wireless communications network 300 providing FWAfor one or more CPEs, the network node 310, 320 comprises circuits or units as depicted in Figure 8. The network node 310, 320 comprises e.g. a receiving unit 802, a determining unit 804, a transmitting unit 806, a processor 808 and a memory 810.

According to the embodiments herein, the network node 310, 320 is configured to, e.g. by means of the receiving unit 802 being configured to, monitor traffic related information in a first cell served by a first base station during a first time period.

According to the embodiments herein, the network node 310, 320 is further configured to, e.g. by means of determining unit 804 being configured to, calculate capacity related characteristics, based on the obtained traffic related information.

According to the embodiments herein, the network node 310, 320 is further configured to, e.g. by means of the determining unit 804 being configured to, estimate system capacity for the second time period based on the calculated capacity related characteristics.

Those skilled in the art will appreciate that the receiving unit 802, the determining unit 804 and the transmitting unit 806 described above in the network node 310, 320 may be referred to one circuit/unit, a combination of analog and digital circuits, one or more processors configured with software and/or firmware and/or any other digital hardware performing the function of each circuit/unit. One or more of these processors, the combination of analog and digital circuits as well as the other digital hardware, may be included in a single application-specific integrated circuitry (ASIC), or several processors and various analog/digital hardware may be distributed among several separate components, whether individually packaged or assembled into a system-on-a-chip (SoC).

The embodiments herein for estimation of system capacity in a wireless communications network 300 may be implemented through one or more processors, such as the processor 808 in the network node 310, 320 together with computer program code for performing the functions and actions of the embodiments herein. The program code mentioned above may also be provided as a computer program product, for instance in the form of a data carrier 812 carrying computer program code 814, as shown in Figure 8, for performing the embodiments herein when being loaded into the network node 310, 320. One such carrier may be in the form of a CD ROM disc. It is however feasible with other data carriers such as a memory stick. The computer program code may furthermore be provided as pure program code on a server or a cloud and downloaded to the network node 310, 320. The memory 810 in the network node 310, 320 may comprise one or more memory units and may be arranged to be used to store received information, measurements, statistics, data, configurations and applications to perform the method herein when being executed in the network node 310, 320.

To perform the method actions in the communication device 330 for assisting estimation of system capacity in a wireless communications network 300 providing FWA for one or more CPE, the communication device 330 comprises circuits or units as depicted in Figure 9. The communication device 330 comprises e.g. a receiving unit 902, a determining unit 904, a transmitting unit 906, a processor 908 and a memory 910.

According to the embodiments herein, the communication device 330 is configured to, e.g. by means of the receiving unit 902 being configured to, receive traffic from the network node.

According to the embodiments herein, the communication device 330 is further configured to, e.g. by means of determining unit 904 being configured to, determine whether the received traffic is emulated traffic.

According to the embodiments herein, the communication device 330 is further configured to, e.g. by means of the transmitting unit 906 being configured to, generate and cause transmission of emulated traffic on an uplink towards a first base station serving a first cell.

Those skilled in the art will appreciate that the receiving unit 902, the determining unit 904 and the transmitting unit 906 described above in the communication device 330 may be referred to one circuit/unit, a combination of analog and digital circuits, one or more processors configured with software and/or firmware and/or any other digital hardware performing the function of each circuit/unit. One or more of these processors, the combination of analog and digital circuits as well as the other digital hardware, may be included in a single application-specific integrated circuitry (ASIC), or several processors and various analog/digital hardware may be distributed among several separate components, whether individually packaged or assembled into a system-on-a-chip (SoC).

The embodiments herein for assisting estimation of system capacity performed in the communication device 330 may be implemented through one or more processors, such as the processor 908 in the communication device 330 together with computer program code for performing the functions and actions of the embodiments herein. The program code mentioned above may also be provided as a computer program product, for instance in the form of a data carrier 912 carrying computer program code 914, as shown in Figure 9, for performing the embodiments herein when being loaded into the communication device 330. One such carrier may be in the form of a CD ROM disc. It is however feasible with other data carriers such as a memory stick. The computer program code may furthermore be provided as pure program code on a server or a cloud and downloaded to the communication device 330.

The memory 910 in the communication device 330 may comprise one or more memory units and may be arranged to be used to store received information, measurements, statistics, data, configurations and applications to perform the method herein when being executed in the communication device 330.

When using the word "comprise" or “comprising” it shall be interpreted as non limiting, i.e. meaning "consist at least of". The embodiments herein are not limited to the above described preferred embodiments. Various alternatives, modifications and equivalents may be used. Therefore, the above embodiments should not be taken as limiting the scope of the invention, which is defined by the appended claims.