Improving network service in a telecommunications networks

Abstract

There is described a method of identifying one or more ways of improving network service in a telecommunications network. The telecommunications network comprises a macro base station and a plurality of aerial micro base stations. Each aerial micro base station comprises an unmanned aerial vehicle (UAV) carrying a telecommunications apparatus for transmitting and / or receiving signals over the telecommunications network, such that each aerial micro base station has telecommunications apparatus characteristics and UAV characteristics. The plurality of aerial micro base stations comprises different types of aerial micro base stations. Each type of aerial micro base station possesses a distinct set of telecommunications characteristics and UAV characteristics. The method comprises analysing data characterising the service of the telecommunications network to identify one or more network service issues affecting one or more geographical areas. The method further comprises, based on the analysed data, searching records of the different types of aerial micro base stations to identify at least one type of aerial micro base station that has a set of telecommunications apparatus characteristics and UAV characteristics able to improve the one or more identified network service issues. The method further comprises identifying one or more aerial micro base stations from the identified at least one type of aerial micro base station to deploy to the one or more geographical areas to improve the one or more identified network service issues. A network orchestrator for identifying one or more ways of improving the telecommunications network is also described.

Description

[0001] IMPROVING NETWORK SERVICE IN TELECOMMUNICATIONS NETWORKS

[0002] FIELD OF THE INVENTION

[0003] The present invention relates to methods and systems for identifying ways of improving network service of telecommunications networks, for example the quality and coverage of telecommunications networks. In particular, the present invention relates to methods and systems that make use of aerial micro base stations to improve the network service of a telecommunications network.

[0004] BACKGROUND

[0005] Telecommunications networks, such as a fixed network or a wireless cellular network, are an integral part of daily life across the globe. For a variety of different reasons, telecommunications networks can have geographical areas of poor network service, often called weak spots. For example, there may be a reduced level of signal coverage or intermittent / unreliable service in an area within the network, or there may be a higher demand for network coverage in an area at particular times of the day.

[0006] In order to provide a telecommunications network capable of handling the demands of today’s technological world, it is important that network operators are able to identify and improve any such weak spots / areas of poor network service in an efficient and effective manner.

[0007] Unmanned aerial vehicles (often called drones) can be used in conjunction with macro base stations in a network to identify and support areas of poor network service. For example, GB 2628115 describes the operation of a fleet of drones to support a wireless cellular network comprising a plurality of fixed macro cell base stations located at cell sites throughout a geographical area for providing wireless connections to user equipment within the geographical area. Drone fleet status data and quality data for the wireless cellular network are received by a computer apparatus and used to determine a set of drone despatch instructions for despatching drones in the fleet to provide ad hoc wireless connections to improve the coverage or capacity of the wireless cellular network at locations in the geographical region.

[0008] However, providing the drones in an efficient and effective manner in a network, which can span vast geographical regions and potentially have many areas requiring different types of network service support, can be challenging. As such, there is need to provide better methods and systems for improving the network service of telecommunications networks.

[0009] SUMMARY

[0010] In one aspect of the present invention, there is provided a method of identifying one or more ways of improving network service in a telecommunications network. The telecommunications network comprises a macro base station and a plurality of aerial micro base stations. Each aerial micro base station comprises an unmanned aerial vehicle (UAV) carrying a telecommunications apparatus for transmitting and / or receiving signals over the telecommunications network, such that each aerial micro base station has telecommunications apparatus characteristics and UAV characteristics. The plurality of aerial micro base stations comprises different types of aerial micro base stations. Each type of aerial micro base station possesses a distinct set of telecommunications characteristics and UAV characteristics. The method comprises analysing data characterising the service of the telecommunications network to identify one or more network service issues affecting one or more geographical areas; based on the analysed data, searching records of the different types of aerial micro base stations to identify at least one type of aerial micro base station that has a set of telecommunications apparatus characteristics and UAV characteristics able to improve the one or more identified network service issues; and identifying one or more aerial micro base stations from the identified at least one type of aerial micro base station to deploy to the one or more geographical areas to improve the one or more identified network service issues.

[0011] The method may further comprise deploying the identified one or more aerial micro base stations to the one or more geographical areas to improve the one or more identified network service issues.

[0012] The step of, based on the analysed data, searching records of the different types of aerial micro base stations to identify at least one type of aerial micro base station that has a set of telecommunications apparatus characteristics and UAV characteristics able to improve the one or more identified network service issues may further comprises accounting for characteristics of the telecommunications network. The characteristics of the telecommunications network may comprise one or more of: geographical coverage, network capacity, user density, data rate, interference management, scalability, power efficiency, backhaul mechanism, spectrum availability, inter base station coordination, macro base station fault status, and fixed broadband connection fault status.

[0013] The telecommunications apparatus characteristics may comprise one or more of: geographical coverage, network capacity, user density, data rate, interference management, scalability, power efficiency, backhaul mechanism, and spectrum availability. The UAV characteristics may comprise one or more of: battery status, wing type, propeller kind, flight mode / control method, flight speed, flight duration, flight altitude, weight, dimensions, lighting, safety systems, payload, and energy source.

[0014] The identified one or more of the aerial micro base stations may be deployed according to deployment instructions, the deployment instructions comprising: the identified one or more aerial micro base stations; coordinates of the one or more geographical areas; and a backhauling mechanism for the identified one or more aerial micro base stations.

[0015] The method may further comprise, before analysing the data characterising the service of the telecommunications network, receiving the data characterising the service of the telecommunications network from the telecommunication network.

[0016] The data characterising the service of the telecommunications network may comprise one or more of: macro base station coordinates, mobile coordinates, received signal levels, received signal quality, interference levels, time advance, propagation delays, throughput and latency of the telecommunications network. The data characterising the service of the telecommunications network may be real-time data characterising the service of the telecommunications network.

[0017] Analysing the received data may comprise analysing the received data using a machine learning algorithm, for example a support vector regression machine learning algorithm or a deep neural network machine learning algorithm. Features of the analysed data may comprise one or more of: inter-site distance, angle of arrival, timing advance, propagation delay, and reference signals received power.

[0018] Analysing the data characterising the service of the telecommunications network to identify the one or more network service issues affecting one or more geographical areas in the telecommunications network may comprises identifying one or more of: reduced coverage in an area of the telecommunications network; no coverage in an area of the telecommunications network; reduced capacity in an area of the telecommunications network; network interference in an area of the telecommunications network; a load balancing need in an area of the telecommunications network; a fixed network outage in an area of the telecommunications network; and an on-demand aerial micro base station connection request in an area of the telecommunications network.

[0019] The method may further comprise identifying the battery status of a deployed first aerial micro base station. If the battery status of the deployed first aerial micro base station is below a battery threshold, the method may further comprise identifying the battery status of a second aerial micro base station that is of the identified at least one type of aerial micro base station; if the battery status of the second aerial micro base station is above the battery threshold, deploying the second aerial micro base station to the one or more geographical areas to improve the identified one or more network service issues; and sending the first aerial micro base station for recharging.

[0020] In a second aspect of the present invention, there is provided a network orchestrator for identifying one or more ways of improving network service in the telecommunications network. The network orchestrator comprises one or more computer processing means configured to carry out the above method.

[0021] In a third aspect of the present invention, there is provided a telecommunications network comprising a macro base station, a plurality of aerial micro base stations, and the network orchestrator described above that is configured to carry out the method described above. Each aerial micro base station comprises an unmanned aerial vehicle (UAV) carrying a telecommunications apparatus for transmitting and / or receiving signals over the telecommunications network, such that each aerial micro base station has telecommunications apparatus characteristics and UAV characteristics. The plurality of aerial micro base stations comprises different types of aerial micro base stations. Each type of aerial micro base station possesses a distinct set of telecommunications characteristics and UAV characteristics.

[0022] BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order that the invention can be more readily understood, reference will now be made, by way of example only, to the accompanying drawings in which: Figure 1 illustrates an exemplary telecommunications network including macro base stations, aerial micro base stations, a network orchestrator and user equipment.

[0024] Figure 2 illustrates an example of an aerial micro base station deployed from a macro base station to assist user equipment in the telecommunications network of Figure 1.

[0025] Figures 3 A - 3F illustrate exemplary aerial micro base stations for supporting telecommunications networks.

[0026] Figure 4 illustrates a schematic diagram of an exemplary method of identifying one or more ways to improve network service in a telecommunications network.

[0027] Figure 5 illustrates a schematic diagram of exemplary data collection for use in the method of Figure 4.

[0028] Figure 6 illustrates an exemplary schematic diagram relating to the method of Figure 4.

[0029] Figure 7 illustrates an exemplary flow diagram relating to the method of Figure 4.

[0030] Figure 8 illustrates an example of a multiple hop to extend network coverage based on the exemplary method of Figure 4.

[0031] DETAILED DESCRIPTION OF THE INVENTION

[0032] An aim of the present invention is to identify one or more ways to improve network service of a telecommunications network, e.g., the quality and coverage of the telecommunications network. Such a telecommunication network may be a fixed network, a wireless cellular network (e.g. a radio access network), or any other suitable telecommunications network.

[0033] An exemplary telecommunications network 100 is illustrated in Figure 1. The telecommunication network 100 here is a wireless cellular network and comprises macro base stations 110 (sometimes called macro nodes) located throughout a geographical region 120 and arranged to allow communications to and between user equipment 130 within the geographical region 120. Macro base stations 110 are typically high powered base stations at set locations in the geographical region 120. Typical user equipment 130 includes devices such as a smart phones, tablets, laptops etc.

[0034] The network 100 also comprises aerial micro base stations 140, which are usually lower powered base stations than the macro base stations 110 and which can provide local service coverage in areas of the geographical region 120 (e.g., across one or more individual cells 170). The aerial micro base stations 140 may nest on one or more of the macro base stations 110, or be located nearby to one or more of the macro base stations 110 (e.g., the aerial micro base stations 140 could be located in a depot or warehouse nearby to the one or more macro base stations 110, or located in any other suitable location). The aerial micro base stations 140 are configured to be deployed away from and back to the macro base stations 110 / depots / warehouses etc. as needed.

[0035] An aerial micro base station 140 comprises an unmanned aerial vehicle (UAV) carrying a telecommunications apparatus for transmitting and / or receiving signals over the telecommunications network 100. The telecommunications apparatus is configured to transmit and / or receive signals over the telecommunications network 100 so as to allow communications to and between user equipment 130. For example, the telecommunications apparatus may forward, reflect, repeat or transmit a new signal over the telecommunications network 100. The telecommunications apparatus may receive signals from user equipment 130 and forward the signals onto a macro base station 110. The telecommunications apparatus may also forward signals between other aerial micro base stations 140 in the telecommunications network 100, and so on. The telecommunications apparatus may also have means for coordinating with other telecommunication apparatuses that are carried on other UAVs, for example when multiple aerial micro base stations 140 are used in cooperation. As such, the telecommunications apparatus enables the aerial micro base station 140 to act as a micro base station within the network 100 and provide local service coverage in areas of the geographical region 120 (e.g., across one or more of the individual cells 170). In other words, when operative, the aerial micro base stations 140 extend the telecommunications network 100, e.g., by forwarding / reflecting / repeating / transmitting signals. An example of an aerial micro base station 140 is a UAV carrying a radio access node. Other examples are described below (e.g., in relation to Figures 3 A - 3F).

[0036] UAVs, also often known as drones, have unique properties, such as high degrees of freedom in positioning and trajectories in three-dimensional space and the ability to establish clear line-of-sight links with other nodes in a network, which make them particularly useful for helping to improve network performance.

[0037] The network 100 also comprises a network orchestrator 150 in communication with the macro base stations 110 (the dashed lines in Figure 1 are representative of exemplary communications between the network orchestrator 150 and the macro base stations 110). The network orchestrator 150 comprises computer processing means for controlling the aerial micro base stations 140 (amongst other controls). The computer processing means comprise one or more computer processors, memory for storing instructions to be carried out by the one or more computer processors, and communication modules enabling communication between macro base stations 110, aerial micro base stations 140 and / or user equipment 130. The network orchestrator 150 receives (via the macro base stations 110) data that characterises the network service, and other network-related information, and analyses the data for use in selecting and controlling the aerial micro base stations 140 in order to provide support to the network 100. The network orchestrator 150 may be a centralised orchestrator, for example in a server in a core network of the wireless cellular network or in a server remotely connected to the wireless cellular network. The network orchestrator 150 may instead be provided in one or more of the macro base stations 110 and / or by any other suitable means.

[0038] As shown in Figure 1, a macro base station 110 provides a macro cell 160 covering the geographical region 120 within which that macro base station 110 can provide wireless connections to user equipment 130. Network service is dependent on many different factors, including user demand, network topology, weather, landscape, interference, peak traffic times etc., and it can be common for users to experience inconsistent network coverage and other network service issues in one or more areas of the geographical region 120. For example, some areas within the geographical region 120 may have fewer wireless connections than other areas, or user demand in one area may exceed the signal strength / capacity that can be provided by the macro base station 110 to that area. For example, an area of forest land might have reduced (e.g., patchy) network coverage as compared to an open plain and therefore require additional network service support. Reduced coverage may include that the network coverage is intermittent (temporally) and / or non-continuous (geographically). An area could also have reduced capacity relative to another area (where capacity is how much throughput can reach a macro base station).

[0039] As such, network service across the geographical region 120 can often require support and / or improvement. For example, the network signal in the geographical area 120 might need improvement if the network signal is below a set threshold or is insufficient for the network 100 to provide wireless connections for the user equipment 130. Additionally / alternatively, a network or user throughput threshold can be used to identify areas with reduced network capacity. Similarly, a threshold of signal-to-interference-plus- noise ratio or block error rate for interference and Random Access Attempts for load balancing can also be used.

[0040] Aerial micro base stations 140 can be used to provide support in the geographical areas 120 needing network service improvement. Each aerial micro base station 140 is able to pair with a macro base station 110 to form a wireless connection, thereby enabling wireless connections between user equipment 130 and the macro base station 110. The aerial micro base stations 140 can move around within the geographical region 120 covered by the macro cell 160 (and further afield, if needed) responsive to network orchestrator 150 commands and user equipment 130 requirements. The aerial micro base stations 140 may be stationed on (or nearby to) one or more of the macro base stations 110 and are deployed to target areas based on deployment instructions that include details of a required mission to improve the network service in the target areas (e.g., target location of the area(s), band, time etc. for addressing an identified network service issue). The macro base stations 110 can also provide charging points for the aerial micro base stations 140.

[0041] Figure 2 illustrates an exemplary macro base station 110 in part of the telecommunications network 100 of Figure 1. The macro base station 110 provides the macro cell 160 for providing wireless connections for user equipment 130. An aerial micro base station 140 can move (e.g., in the direction of the dashed arrow) from the macro base station 110, under command of the network orchestrator 150, to locations (e.g., individual cells 170) within the macro cell 160 in order to provide additional wireless connections 180 to the user equipment 130.

[0042] As mentioned earlier, providing aerial micro base stations 140 in an efficient and effective manner to support / improve the network service can be challenging. Networks can span a vast geographical region 120, the network service can vary dramatically across the geographical region 120 depending on a number of local factors, and so there are often many areas of the region requiring different types of network service support (dependent on the network service issue(s) at hand).

[0043] Aerial micro base stations 140 can be provided with different characteristics to make them particularly useful for improving network service in such cases as described above. One particular type of aerial micro base station with certain characteristic(s) may be better suited to addressing a specific network service issue compared to another type of aerial micro base station which has different characteristic(s). As such, selecting aerial micro base stations for deployment based on their individual characteristics (e.g., selecting the most suitable aerial micro base station type for a network service issue) helps optimise the network service throughout the geographical region 120. The characteristics vary between individual aerial micro base stations 140 (e.g., a first aerial micro base station is of a different type as compared to a second aerial micro base station). Providing such variation in the aerial micro base station characteristics allows network operators to better select optimised aerial micro base station(s) 140 for deployment than would otherwise be possible, dependent on the network service issue(s) faced, the group of aerial micro base stations 140 available for deployment, and the telecommunications network 100 itself. More details about the aerial micro base station 140 selection is provided below. But first, further details of the aerial micro base station characteristics are described.

[0044] The aerial micro base station characteristics are features / traits of the aerial micro base station 140. Each aerial micro base station 140 has telecommunications apparatus characteristics and UAV characteristics, i.e., characteristics specific to the telecommunications apparatus, and characteristics specific to the UAV. Several types of aerial micro base station 140 exist, and the types of aerial micro base station 140 are defined by the set of telecommunications apparatus characteristics and UAV characteristics possessed by an individual aerial micro base station 140 (e.g., see Figures 3A - 3F for example aerial micro base station types). In other words, each type of aerial micro base station 140 possesses a distinct set of telecommunications apparatus characteristics and UAV characteristics.

[0045] The telecommunications apparatus characteristics define the capabilities of the telecommunications apparatus to transmit and / or receive signals over the telecommunications network 100. Examples of telecommunications apparatus characteristics include geographical coverage (i.e., cell size), network capacity (e.g., capability to handle a number of simultaneous connections), user density, data rate (i.e., how fast data can be sent / received), interference management, scalability, power efficiency, backhaul mechanism, spectrum availability, and any other suitable telecommunications apparatus characteristics.

[0046] The UAV characteristics define the capabilities of the UAV (which carries the telecommunications apparatus) to move the UAV around within the telecommunications network 100. Examples of UAV characteristics include battery status, wing type (e.g., fixed- wing and rotary-wing), propeller kind (e.g., tricopter, quadcopter etc.), flight mode / control method (e.g., autonomous, remote control), flight speed, flight duration, flight altitude, weight, dimensions, lighting, safety systems, payload, energy source and any other suitable UAV characteristics.

[0047] The aerial micro base station characteristics have an influence / impact on the missions that an aerial micro base station 140 may serve. As such, it is advantageous to select an aerial micro base station 140 having characteristics best suited for addressing a specific network service issue in order to optimise network service of a telecommunications network 100.

[0048] Figures 3 A - 3F illustrate exemplary aerial micro base stations (referred to as drones in this section for brevity, i.e., the terms aerial micro base station and drone are used synonymously in this section. The term aerial micro base stations is used throughout the rest of the description and in the claims). The aerial micro base stations of Figures 3 A - 3F are examples of different types of aerial micro base stations / drones, i.e., each drone has a distinct set of telecommunications apparatus characteristics and UAV characteristics. Figure 3 A shows an airborne base transceiver station (BTS) drone. Figure 3B shows an intelligent reflecting surface drone. Figure 3C shows a relay drone. Figure 3D shows an uplink only BTS drone. Figure 3E shows a Wi-Fi drone. Figure 3F shows a non-terrestrial network backhauled drone (i.e., via a satellite 305). Many other aerial micro base station / drone types also exist. Each drone 140 has one or more characteristics that make that drone 140 more or less suited to addressing particular network service issues as compared to other drones.

[0049] The drones can work as a base station with full transmit and receive functionalities in different spectrum bands, including mm-waves that serve for very short range. Some examples of advantageous characteristics of the different drone types include the following. Intelligent reflecting surface drones use intelligent reflecting surface technology to reflect the signal and improve coverage. Relay drones can act as active repeaters of the signal in certain spectrum bands based upon user needs. Uplink only base transceiver station (BTS) drones amplify / enhance the uplink signal only, and so are advantageous in scenarios where only lightweight equipment is needed (less energy consumption). Wi-Fi drones provide a Wi-Fi spot based on cognitive radio technology to transmit on the available unused Wi-Fi spectrum. The drones can also be backhauled using any wireless network terrestrial and / or non-terrestrial network, e.g., a drone may be backhauled from a terrestrial node or from a satellite connection 305. Alternatively, the backhauling can be done through a fixed network over a Wi-Fi connection. Accordingly, network service issues in a network 100 can be better addressed by selecting a drone 140 which exhibits characteristics suited to addressing the network service issue(s) at hand.

[0050] Such characteristics may be conferred by the aerial micro base station’s (drone’s) specific hardware or software capabilities. The aerial micro base station’s software may be dynamically reconfigurable so that the aerial micro base station 140 has more than one capability / functionality, i.e., so as to make that aerial micro base station 140 suitable for addressing a variety of different network service issues / scenarios.

[0051] Additionally / altematively, hardware may vary between individual aerial micro base stations 140, so that aerial micro base stations 140 with one hardware setup are more suitable for addressing a network service issue / scenario compared to a different hardware setup. As an example, an uplink only drone could have either 1) hardware that is distinct from an uplink / downlink drone, or 2) could be an uplink / downlink drone with duplexing capabilities set for uplink only. Depending on the particular network issue, an uplink only drone in a group of available aerial micro base stations 140 could be selected because the uplink only drone’s characteristics make it more suitable for addressing that network issue as compared to a relay drone, for example. Further examples of aerial micro base station selection are provided below.

[0052] The telecommunications apparatus characteristics are of primary importance when selecting the aerial micro base station type for deployment, as the selected aerial micro base station type must be a type able to actually improve the specific network issue at hand. It can also be useful to take the UAV characteristics into consideration too when selecting which aerial micro base station type to deploy. For example, using battery status as a simple example, it is helpful to know the battery status before deployment of an aerial micro base station 140 of the desired type (because the battery status indicates remaining flight time, available time to perform network operations etc.). If there are multiple available aerial micro base stations 140 of the desired type, but only one has enough current battery life to enable that aerial micro base station 140 to carry out a required mission, the network orchestrator 150 can select that aerial micro base station 140 to carry out the required mission over the other aerial micro base stations 140 which do not have enough battery life. Figure 4 illustrates an exemplary method 400 of identifying one or more ways to improve network service in a telecommunications network 100, such as the wireless cellular network of Figures 1 and 2, or in a fixed network or any other suitable telecommunications network. The telecommunications network 100 has at least one macro base station 110 and a plurality of aerial micro base stations 140, each aerial micro base station 140 having its own characteristics, as described above. In particular, each aerial micro base station has telecommunications apparatus characteristics and UAV characteristics. The plurality of aerial micro base stations comprises different types of aerial micro base stations. Each type of aerial micro base station possesses a distinct set of telecommunications characteristics and UAV characteristics.

[0053] In a first optional step of the method, data characterising the service of the network 100 is received 410 from the network 100. For example, the data is received at the network orchestrator 150 via the macro base stations 110 and / or by crowd sourcing of user equipment 130 within the network 100. Figure 5 illustrates a diagram 500 of the data collection from the macro base stations 110 and / or by crowd sourcing of user equipment 130 within the network 110. The received data provides network service information across part of, or all of, the geographical region covered by the network 100, e.g., information relating to signal strength, quality, capacity, demand etc. In more detail, this data may comprise one or more of the macro base station coordinates, mobile coordinates, received signal levels, received signal quality, interference levels, time advance, propagation delays, throughput and / or latency of the network 100. This data may be live / real-time data characterising the service of the telecommunications network, and can be received continuously, periodically and / or on demand so as to facilitate a dynamic response by the aerial micro base stations 140. Examples of real-time data include network congest! on / utilization, number of active users, battery status of a deployed aerial micro base station 140, as well as the mobile coordinates, received signal levels, received signal quality, interference levels, time advance, propagation delays, throughput and / or latency of the network 100, and other suitable real-time data.

[0054] After receiving the data characterising the service of the network 100, the method analyses 420 the data to identify one or more network service issues affecting one or more geographical areas in the telecommunications network 100. For example, the network orchestrator 150 compiles and assesses the received data to identify network service issues in geographical areas where network service support is needed, e.g., due to reduced coverage or capacity etc. Identifying the one or more geographical areas for improvement of the telecommunications network service may comprise identifying one or more areas suffering from a particular network service issue / scenario within the network 100. Such network service issues / scenarios can include coverage and capacity issues, interference issues, load balancing requirements, network outages and / or on-demand aerial micro base station connection, to name a few. As such, identifying the one or more network service issues affecting the one or more geographical areas may include identifying one or more of: reduced coverage (or no coverage) in an area of the network 100, reduced capacity in an area of the network 100, network interference in an area of the network 100, a load balancing need / demand in an area of the network 100, a fixed network outage in an area of the network 100 and an on-demand aerial micro base station connection request in an area of the network 100. As mentioned previously, some aerial micro base stations 140 are more or less suitable for improving the network service, dependent upon the network service issues / scenarios at hand and the aerial micro base station type / characteristics. It is advantageous to choose the aerial micro base stations 140 with characteristics most suited to the network issue at hand in order to provide a better / improved network service.

[0055] Based on the analysed data, the method searches 430 records of the different types of aerial micro base station 140 to identify at least one type of aerial micro base station that has a set of telecommunications apparatus characteristics and UAV characteristics able to improve the one or more identified network service issues in the one or more geographical areas. The method then identifies 440 one or more aerial micro base stations 140 from the identified at least one type of aerial micro base station to deploy to the one or more geographical areas to improve the one or more network service issues. In more detail, when choosing aerial micro base stations 140 for deployment, the network orchestrator 150 compares the network service issue(s) in the area(s) against the group of aerial micro base stations 140 available for assistance. For example, the network orchestrator 150 first accesses records of the aerial micro base station types within the telecommunications network 100 and searches through such records to identify the aerial micro base station types suitable to address the network service issue(s) at hand. The records may comprise a list of all the types of aerial micro base station 140 in the telecommunications network 100. One or more of the aerial micro base stations 140 of the suitable type can then be chosen for deployment. For example, matching tables of the identified network service issue(s) and the aerial micro base station types can be used to identify the aerial micro base station type(s) suitable to address the network service issue at hand. E.g., if Wi-Fi capability is needed to address the network service issue, the records are searched for all types of aerial micro base stations 140 that have Wi-Fi capability. Then, one or more of the aerial micro base stations 140 with Wi-Fi capability can be deployed to address the network service issue.

[0056] The step of searching 430 records of the different types of aerial micro base stations to identify at least one type of aerial micro base station 140 that has a set of telecommunications apparatus characteristics and UAV characteristics able to improve the one or more identified network service issues may further comprise accounting for characteristics of the telecommunications network 100 itself, e.g., the nature of the communications links used in the telecommunications network 100. Characteristics of the telecommunications network 100 may comprise one or more of: geographical coverage, network capacity, user density, data rate, interference management, scalability, power efficiency, telecommunications network backhaul mechanism, spectrum availability, inter base station coordination, macro base station fault status (e.g., faulty macro base stations), fixed broadband connection fault status (e.g., fault fixed broadband connection), or any other suitable characteristic of the telecommunications network 100. In such cases, an aerial micro base station type is chosen that both improves the network service issue at hand and is compatible with the telecommunications network 100. For example, there may be more than one aerial micro base station type suitable for addressing a network service issue. However, not all of the suitable aerial micro base station types may be compatible with the telecommunications network 100 itself, e.g., a drone with Wi-Fi backhauling may be well suited to addressing the network service issue, but if the telecommunications network 100 does not have any suitable Wi-Fi connections, then another aerial micro base station type should be chosen to better suit the situation.

[0057] As mentioned, the network orchestrator 150 matches network service issues / scenarios and network requirements against records of the aerial micro base station types so that suitable aerial micro base station(s) 140 can be deployed to assist in an area needing network service improvement Such aerial micro base stations 140 may be deployed from nearby macro base stations 110 / depots / warehouses etc. If there are no suitable aerial micro base stations 140 nearby, then aerial micro base stations 140 of the suitable type, but which are located further afield, can be deployed instead.

[0058] The method may further comprise deploying 450 the identified one or more aerial micro base stations 140 to the one or more geographical areas to improve the one or more identified network service issues. Deploying 450 the identified aerial micro base stations 140 is in accordance with deployment instructions generated by the network orchestrator 150 (based on the analysed data). The network orchestrator 150 communicates the deployment instructions to the aerial micro base station(s) 140 via the macro base station 110 so as to move the aerial micro base station(s) 140 to the one or more geographical areas. The deployment instructions include a set of the identified aerial micro base stations to be deployed, and coordinates of the target areas for improvement of the network service (i.e., the target area coordinates to which the identified aerial micro base stations 140 are to be deployed). The deployment instructions could also include the backhauling mechanism for the identified aerial micro base stations 140, and any other relevant information. The deployment instructions may be based on a decision / orders matrix that is generated in the network orchestrator 150 (e.g., see the matrix 690 of Figure 6). The matrix 690 may include 1) the type of aerial micro base station to be deployed, 2) the current 3D location of the aerial micro base station (and this location may be determined based on the shortest distance between an identified area for network service improvement and the closest macro base station 110), 3) the trajectory to place the aerial micro base station 140 at the target area(s) for network service improvement, and 4) any mission objectives or other suitable information specified by the network orchestrator 150.

[0059] The network orchestrator 150 comprises statistical platforms for all deployment decisions, including time stamps, type of aerial micro base station 140 selected (i.e., characteristics-based), desired / target locations, deployment decision fulfillment, duration of aerial micro base station in service, aerial micro base station swapping based on battery life, performance assessment after successful deployment of the aerial micro base station to the desired location. These statistics help operators using the network orchestrator 150 to more accurately select from the group of aerial micro base stations 140 based on dynamic network needs and thereby improve aerial micro base station type selection algorithms.

[0060] The network orchestrator 150 may use machine learning / artificial intelligence to better analyze the received data. As mentioned, the network orchestrator 150 controls deployment of various aerial micro base stations 140 to different locations in the network 100 based on the identified network service issues / scenarios. Based on the received data (and optionally also network topology and coverage maps), the network orchestrator 150 can select the ‘best fit’ aerial micro base station type for a required mission from the group of available aerial micro base stations 140 to enhance network service performance. Data characterising the network service are constantly received and used to update the deployment instructions, thereby more accurately reflecting changes in the network service over time and throughout the geographical region. Analysing the data may comprise analysing the data using a machine learning algorithm in the network orchestrator 150, for example a support vector regression machine learning algorithm or a deep neural network machine learning algorithm. Features of the analysed data may comprise inter-site distance, angle of arrival, timing advance, propagation delay, and / or reference signals received power. Using machine learning algorithm(s) helps the network orchestrator 150 to learn from the received data (and correct itself) when geolocating network service issues in the network so as to more accurately deploy the aerial micro base stations 140 by generating optimized deployment instructions based on the available aerial micro base stations 140 and the identified network service issue(s). As mentioned, the decision to deploy a specific aerial micro base station 140 can be based on matching tables between the network issue(s) and aerial micro base station types (and optionally, network characteristics), and such matching tables can be automatically refined based on learnings from previous missions on the same or a similar geographic area and / or network service issue, thereby providing an optimised network 100.

[0061] An exemplary schematic diagram 600 relating to the method 400 of network service improvement of Figure 4 is shown in Figure 6. As can be seen, data characterising the wireless cellular network is collected and sent to the network orchestrator 150 via macro base stations 110 (step A). The network orchestrator 150 analyses the data to geolocate area(s) in the network 100 requiring support from the aerial micro base stations 140, assesses the aerial micro base stations 140 available, and assesses characteristics of the available aerial micro base stations 140 to identify suitability for addressing particular network service issue(s) (step B). The network orchestrator 150 then generates an instructing matrix 690 for deployment of selected aerial micro base stations 140 to the areas needing support (step C). The selected aerial micro base stations 140 can then be deployed to the areas needing support based on the identified needs and available aerial micro base station types (step D).

[0062] In a group of available micro base stations 140, the comparison between network service issues and aerial micro base station characteristics could be any one or more of the following combinations. In an area having a reduced coverage (e.g., in a forest), the network coverage can be extended by deploying an aerial micro base station of a type suitable to extend the network coverage in that area. Similarly, in an area having a reduced capacity, the network quality can be enhanced by deploying an aerial micro base station of a type suitable to enhance the network quality in that area. For an area having network interference, the network interference can be mitigated by deploying an aerial micro base station of a suitable type (e.g., by using Coordinated Multi-Point transmission and reception). In an area having a fixed network outage or a mobile network outage, the network service can be mitigated by deploying an aerial micro base station of a suitable type. A particular type of aerial micro base station can also be deployed to serve an on- demand coverage request by user equipment in the network. Furthermore, a particular type of aerial micro base station can be deployed to provide load balancing of network traffic between macro base stations in the network.

[0063] In more specific examples, for an area of reduced / low or no coverage (whether based on an on-demand request or not), the network orchestrator 150 instructs an aerial micro base station of a type where the backhaul is performed by a satellite connection 305 to be deployed to the area of reduced / low or no coverage. Depending on the capacity / coverage target, the network orchestrator 150 may instruct an aerial micro base station where the backhaul is performed by a satellite connection 305 with an extended radio chain.

[0064] For an area covered by terrestrial network where capacity is not enough, the network orchestrator 150 instructs an aerial micro base station of a type with backhaul from a terrestrial node to be deployed to the area where capacity is not enough. If Wi-Fi connectivity is available in that area, an aerial micro base station where the backhaul is performed through a fixed network over the Wi-Fi connection may be deployed instead.

[0065] For an area where a fixed outage is detected, the network orchestrator 150 instructs an aerial micro base station of a type where the backhaul is performed through a fixed network over a Wi-Fi connection to be deployed to the area where a fixed outage is detected. This may be automatically or on-demand.

[0066] For an area with limited indoor coverage, but stronger outdoor coverage, the network orchestrator 150 instructs (on-demand or not) an aerial micro base station of a type with backhaul from a terrestrial node or a repeater drone to the area.

[0067] For an area with high uplink interference, the network orchestrator instructs an uplink only drone type to be deployed to the area with high uplink interference.

[0068] For an area where there is a faulty macro base station 110, the network orchestrator 150 instructs an aerial micro base station of a type where the backhaul is performed by a satellite connection 305.

[0069] For an area where there are many tall buildings (e.g., skyscrapers), the network orchestrator 150 instructs an aerial micro base station of a type where the backhaul is performed through a fixed network over the Wi-Fi connection, or of a type that uses intelligent reflecting surface technology.

[0070] Figure 7 illustrates an exemplary flow chart 700 relating to the method 400 of Figure 4. As can be seen from the flow chart, the method looks for different network issues in areas of the network 100 (e.g., weak coverage spots, low capacity spots, interference spots, potential load balancing spots etc.) so as to generate a matrix (e.g., matrix 690 of Figure 6) for deployment instructions. The method may consider any or all of these network service issues, in no particular order. The network orchestrator 150 may carry out the steps shown in the flow chart 700 of Figure 7 for one or more of the macro base stations 110 within the network 100 in parallel, so as to enable a better representation of the network service state across the entire geographical region covered by the network 110.

[0071] Once aerial micro base stations 140 of a suitable type have been deployed based on the matrix, the battery life of the deployed aerial micro base stations 140 may be detected and compared to a battery threshold in order to determine if additional aerial micro base stations 140 are required to improve the network service. For example, the deployment instructions may include a calculation of the aerial micro base station’s battery lifetime and order an aerial micro base station 140 to a nearby macro base station 110 (or depot / warehouse etc., as appropriate) to charge if the battery status is too low, i.e., below the battery threshold. The deployment instructions may further include instructions to replace a deployed aerial micro base station 140 currently providing network service improvement / support in an area with another aerial micro base station 140 based on the battery status of the deployed aerial micro base station 140. For example, the method 400 of Figure 4 may further comprise identifying the battery status of the deployed aerial micro base station 140. If the battery status of the deployed aerial micro base station 140 is below the battery threshold, the method may send the deployed aerial micro base station 140 for recharging, e.g., to a nearby macro base station 110 / depot / warehouse etc. The battery status of a second aerial micro base station 140 in the group is then identified. The second aerial micro base station’s type is also assessed. If the second aerial micro base station 140 is of the identified at least one type (i.e., has the same or similar telecommunications apparatus characteristics and UAV characteristics as the first aerial micro base station 140), and if the battery status of the second aerial micro base station 140 is above the battery threshold, then the method deploys the second aerial micro base station 140 to the relevant area for improvement of the network service issue(s). The second aerial micro base station 140 does not need to be an exact replica of the deployed aerial micro base station 140, but it must be able to provide the same functionality type as the deployed aerial micro base station 140 (as mentioned previously, aerial micro base stations 140 may be capable of multiple functionalities, dependent on their software / hardware setups). If the battery status of the second aerial micro base station 140 is below the battery threshold, the method then identifies and compares the battery status (and aerial micro base station type) of a third aerial micro base station 140 in the group to the battery threshold, and so on until an aerial micro base station 140 of the suitable type in the group with a battery status above the battery threshold is found and can be deployed. If there are no aerial micro base stations 140 of the suitable type nearby the area, then another suitable aerial micro base station 140 from further afield in the telecommunications network 100 can be selected and deployed.

[0072] The deployment instructions may also include an estimation of the number and types of aerial micro base station 140 necessary to perform a mission. The deployment instructions may also include an order for a set of aerial micro base stations 140 to construct a multiple hop to extend network coverage across several geographical areas and / or to provide network services outside of the macro cell 160 (as shown in Figure 8). For example, as shown in Figure 8, a multiple hop is provided by two aerial micro base stations 140 so as to extend the network services to an area 195 beyond the macro cell 160. As mentioned, the network orchestrator 150 controls deployment of the aerial micro base stations 140 based on their characteristics and the particular network service requirements. As such, the present invention thereby works as an overlay network that complements the different coverage and capacity services the network 100 already provides. The network orchestrator 150 is able to produce a variety of statistical insights for network service improvement, including: how many decisions are taken to dispatch an aerial micro base station 140 (per aerial micro base stations type), how many decisions are taken to dispatch an aerial micro base station per geographical grid, how many times the decision was not met because a suitable aerial micro base station 140 was not nested on / nearby the nearest macro base station 110 to the area for network service improvement, how many times the deployed aerial micro base station 140 was able to meet the network needs, and which macro base station 110 is the nearest to the area for network service improvement, etc. Network operators can use these statistics in order to better decide whether or not to add more aerial micro base stations 140 to the group so as to better enhance network performance across the geographical region.

[0073] These statistics help the network orchestrator 150 optimize the method to minimize travel distance of the aerial micro base stations 140 between the macro base station 110 and the area for network service improvement (or between a depot / warehouse etc. and the area for network service improvement). As mentioned above, usually the aerial micro base stations 140 are deployed from sites nearby to the area(s) requiring network service support, e.g., from the closest macro base station 110. In some situations, there may not be an aerial micro base station 140 of the desired type located at (or nearby) the closest macro base station 110 / depot / warehouse etc. In such situations, an aerial micro base station 140 of the desired aerial micro base station type can instead be deployed from a different macro base station 110 / depot / warehouse located further away in order to address the particular network service issue in the area for improvement.

[0074] Most of the examples above relate to a wireless cellular network. However, as mentioned, the present invention is also suitable for improving network service of a fixed network. Where for a wireless cellular network, the present invention aims to support coverage / capacity issues, for a fixed network, the present invention aims to fix faults / outages (redundancy). To solve a fixed network fault / outage, using the received data characterising the network service, the location(s) of the fault / outage can be identified and addressed in a similar manner as for supporting coverage / capacity issues in wireless cellular networks.

[0075] Although specific embodiments have been described above, the skilled person will understand that various modifications and variations are possible without departing from the scope of the present invention that is defined by the appended claims.

Claims

CLAIMS:

1. A method of identifying one or more ways of improving network service in a telecommunications network, the telecommunications network comprising a macro base station and a plurality of aerial micro base stations, wherein: each aerial micro base station comprises an unmanned aerial vehicle (UAV) carrying a telecommunications apparatus for transmitting and / or receiving signals over the telecommunications network, such that each aerial micro base station has telecommunications apparatus characteristics and UAV characteristics, the plurality of aerial micro base stations comprises different types of aerial micro base stations, and each type of aerial micro base station possesses a distinct set of telecommunications characteristics and UAV characteristics, and the method comprises: analysing data characterising the service of the telecommunications network to identify one or more network service issues affecting one or more geographical areas; based on the analysed data, searching records of the different types of aerial micro base stations to identify at least one type of aerial micro base station that has a set of telecommunications apparatus characteristics and UAV characteristics able to improve the one or more identified network service issues; and identifying one or more aerial micro base stations from the identified at least one type of aerial micro base station to deploy to the one or more geographical areas to improve the one or more identified network service issues.

2. The method of claim 1 further comprising deploying the identified one or more aerial micro base stations to the one or more geographical areas to improve the one or more identified network service issues.

3. The method of claim 1 or claim 2, wherein the step of, based on the analysed data, searching records of the different types of aerial micro base stations to identify at least one type of aerial micro base station that has a set of telecommunications apparatus characteristics and UAV characteristics able to improve the one or more identified networkservice issues further comprises accounting for characteristics of the telecommunications network.

4. The method of claim 3, wherein the characteristics of the telecommunications network comprise one or more of: geographical coverage, network capacity, user density, data rate, interference management, scalability, power efficiency, backhaul mechanism, spectrum availability, inter base station coordination, macro base station fault status, and fixed broadband connection fault status.

5. The method of any preceding claim, wherein the telecommunications apparatus characteristics comprise one or more of: geographical coverage, network capacity, user density, data rate, interference management, scalability, power efficiency, backhaul mechanism, and spectrum availability, and wherein the UAV characteristics comprise one or more of: battery status, wing type, propeller kind, flight mode / control method, flight speed, flight duration, flight altitude, weight, dimensions, lighting, safety systems, payload, and energy source.

6. The method of any one of claims 2 - 5, wherein the identified one or more of the aerial micro base stations are deployed according to deployment instructions, the deployment instructions comprising: the identified one or more aerial micro base stations; and coordinates of the one or more geographical areas; and optionally, a backhauling mechanism for the identified one or more aerial micro base stations.

7. The method of any preceding claim further comprising, before analysing the data characterising the service of the telecommunications network, receiving the data characterising the service of the telecommunications network from the telecommunication network.

8. The method of claim 7, wherein the data characterising the service of the telecommunications network comprises one or more of: macro base station coordinates,mobile coordinates, received signal levels, received signal quality, interference levels, time advance, propagation delays, throughput and latency of the telecommunications network.

9. The method of any preceding claim, wherein the data characterising the service of the telecommunications network is real-time data characterising the service of the telecommunications network.

10. The method of any preceding claim, wherein analysing the received data comprises analysing the received data using a machine learning algorithm, for example a support vector regression machine learning algorithm or a deep neural network machine learning algorithm.

11. The method of claim 10, wherein features of the analysed data comprise one or more of: inter-site distance, angle of arrival, timing advance, propagation delay, and reference signals received power.

12. The method of any preceding claim, wherein analysing the data characterising the service of the telecommunications network to identify the one or more network service issues affecting one or more geographical areas in the telecommunications network comprises identifying one or more of: reduced coverage in an area of the telecommunications network; no coverage in an area of the telecommunications network; reduced capacity in an area of the telecommunications network; network interference in an area of the telecommunications network; a load balancing need in an area of the telecommunications network; a fixed network outage in an area of the telecommunications network; and an on-demand aerial micro base station connection request in an area of the telecommunications network.

13. The method of any one of claims 2 - 12, further comprising: identifying the battery status of a deployed first aerial micro base station, andif the battery status of the deployed first aerial micro base station is below a battery threshold: identifying the battery status of a second aerial micro base station that is of the identified at least one type of aerial micro base station; if the battery status of the second aerial micro base station is above the battery threshold, deploying the second aerial micro base station to the one or more geographical areas to improve the identified one or more network service issues; and optionally, sending the first aerial micro base station for recharging.

14. A network orchestrator for identifying one or more ways of improving network service in a telecommunications network, the network orchestrator comprising one or more computer processing means configured to carry out the method of any preceding claim.

15. A telecommunications network comprising: a macro base station; a plurality of aerial micro base stations, wherein: each aerial micro base station comprises an unmanned aerial vehicle (UAV) carrying a telecommunications apparatus for transmitting and / or receiving signals over the telecommunications network, such that each aerial micro base station has telecommunications apparatus characteristics and UAV characteristics, the plurality of aerial micro base stations comprises different types of aerial micro base stations, and each type of aerial micro base station possesses a distinct set of telecommunications characteristics and UAV characteristics; and the network orchestrator of claim 14 that is configured to carry out the method of any one of claims 1 - 13.

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