EP2989818A1

EP2989818A1 - Area/cell availability evaluation

Info

Publication number: EP2989818A1
Application number: EP14715928.9A
Authority: EP
Inventors: Martin Kollar; Yi Zhi Yao
Original assignee: Nokia Solutions and Networks Oy
Current assignee: Nokia Solutions and Networks Oy
Priority date: 2013-04-25
Filing date: 2014-04-08
Publication date: 2016-03-02
Also published as: WO2014173677A1

Abstract

A system, apparatus, method and computer program product for evaluating a cell/area availability from an end user perspective is provided. One method may comprise evaluating a cell availability (CA) of a cell or an area availability (AA) of an area in a communications network. The evaluating may comprise calculating a cell availability from an end user perspective (CAS) or an area availability from the end user perspective (AAS). The calculating of the CAS or AAS may comprise multiplying the CA or AA with a weighted coefficient of all neighboring cells to the cell or all neighboring areas to the area, and the weighted coefficient represents an availability ratio of each of the neighboring cells or areas.

Description

DESCRIPTION TITLE

AREA/CELL AVAILABILITY EVALUATION

BACKGROUND:

Field:

[0001] Embodiments of the invention generally relate to mobile communications networks, such as, but not limited to, the Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (UTRAN), Long Term Evolution (LTE) Evolved UTRAN (E-UTRAN), and/or LTE- A.

Description of the Related Art:

[0002] Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (UTRAN) refers to a communications network including base stations, or Node Bs, and for example radio network controllers (RNC). UTRAN allows for connectivity between the user equipment (UE) and the core network. The RNC provides control functionalities for one or more Node Bs. The RNC and its corresponding Node Bs are called the Radio Network Subsystem (RNS). In case of E-UTRAN (enhanced UTRAN), no RNC exists and most of the RNC functionalities are contained in the enhanced Node B (eNodeB or eNB).

[0003] Long Term Evolution (LTE) or E-UTRAN refers to improvements of the UMTS through improved efficiency and services, lower costs, and use of new spectrum opportunities. In particular, LTE is a 3GPP standard that provides for uplink peak rates of at least 50 megabits per second (Mbps) and downlink peak rates of at least 100 Mbps. LTE supports scalable carrier bandwidths from 20 MHz down to 1.4 MHz and supports both Frequency Division Duplexing (FDD) and Time Division Duplexing (TDD).

[0004] As mentioned above, LTE may also improve spectral efficiency in networks, allowing carriers to provide more data and voice services over a given bandwidth. Therefore, LTE is designed to fulfill the needs for high-speed data and media transport in addition to high-capacity voice support. Advantages of LTE include, for example, high throughput, low latency, FDD and TDD support in the same platform, an improved end-user experience, and a simple architecture resulting in low operating costs.

[0005] Further releases of 3GPP LTE (e.g., LTE Rel-10, LTE Rel-1 1 , LTE Rel- 12) are targeted towards future international mobile telecommunications advanced (IMT-A) systems, referred to herein for convenience simply as LTE- Advanced (LTE-A).

[0006] LTE-A is directed toward extending and optimizing the 3GPP LTE radio access technologies. A goal of LTE-A is to provide significantly enhanced services by means of higher data rates and lower latency with reduced cost. LTE- A will be a more optimized radio system fulfilling the international telecommunication union-radio (ITU-R) requirements for I MT- Advanced while keeping the backward compatibility.

SUMMARY:

[0007] A first embodiment is directed to a method comprising evaluating a cell availability (CA) of a cell or an area availability (AA) of an area in a communications network. The evaluating comprises calculating a cell availability from an end user perspective (CAS) or an area availability from the end user perspective (AAS). The calculating of the CAS or AAS comprises multiplying the cell availability (CA) or area availability (AA) with a weighted coefficient of all neighboring cells to the cell or all neighboring areas to the area, and the weighted coefficient represents an availability ratio of each of the neighboring cells or areas.

[0008] A second embodiment is directed to an apparatus comprising at least one processor and at least one memory comprising computer program code. The at least one memory and the computer program code are configured, with the at least one processor, to cause the apparatus at least to evaluate a cell availability (CA) of a cell or an area availability (AA) of an area in a communications network, and calculate a cell availability from an end user perspective (CAS) or an area availability from the end user perspective (AAS) by multiplying the cell availability (CA) or area availability (AA) with a weighted coefficient of all neighboring cells to the cell or all neighboring areas to the area. The weighted coefficient represents an availability ratio of each of the neighboring cells or areas.

[0009] A third embodiment is directed to an apparatus comprising evaluating means for evaluating a cell availability (CA) of a cell or an area availability (AA) of an area in a communications network. The apparatus also comprises calculating means for calculating a cell availability from an end user perspective (CAS) or an area availability from the end user perspective (AAS) by multiplying the CA or AA with a weighted coefficient of all neighboring cells to the cell or all neighboring areas to the area. The weighted coefficient represents an availability ratio of each of the neighboring cells or areas.

[00010] The method of the first embodiment or the apparatus of the second or third embodiment,

wherein the cell availability from the end user perspective (CAS) may be calculated according to the following equation:

_{CAS =} CA.M + {l - CA).M.K

M

where M may represent a number of attempts, Kmay be a factor representing what part of the attempts during the cell unavailability is served by the neighboring cells, CAM may represent a number of successful attempts during a time the cell is available, and (1-CA).M may represent a number of attempts during the cell unavailability.

wherein Kmay be calculated according to the following equation:

K = l - _N ^Load (2)

'^ CA_i.Load_i

=1

where Load represents a load of the cell, and Load: represents a load of the cell's /-th neighbor.

wherein combining equation 2 with equation 1 may provide the following equation:

which may also be expressed in the following from:

CAS = l - {l - CA)W (4)

W may be a weighted factor of the cell to its neighbors and given as:

Load

W =^■ (5)

^ CA_; .Load_i wherein the area availability from the end user perspective (AAS) may be calculated according to the following equation:

AAS = \ - {l - AA)W (6) where AA may be estimated with the following equation:

AA =∑CA_}WA_} (7) where CA_j may be a cell availability of the y^'-th cell which is part of the area, and WA, may be its weighted coefficient.

wherein the weighted coefficient, WA may be given by the following equation:

Load■

ΨΑ_} = - _} (8)

Load _j where Load_j may be a load of the y-th cell from the observed area and J may represent a number of cells belonging to the area.

wherein, when l V=1 , the area availability from the end user perspective (AAS) may be given by the following :

AAS = AA =∑CA_]WA_j (9)

j=i

wherein the weighted coefficient may be obtained from measurements provided by neighbor cells or areas.

wherein the weighted coefficient may be obtained from true overlapping of the cell or area with neighboring cells or areas.

[00011] The apparatus of the second or third embodiment,

wherein the apparatus may be a performance network management node.

[00012] A fourth embodiment is directed to a computer program, embodied on a computer readable medium, the computer program configured to control a processor to perform a process. The process comprises evaluating a cell availability (CA) of a cell or an area availability (AA) of an area in a communications network. The evaluating comprises calculating a cell availability from an end user perspective (CAS) or an area availability from the end user perspective (AAS). The calculating of the CAS or AAS comprises multiplying the CA or AA with a weighted coefficient of all neighboring cells to the cell or all neighboring areas to the area, and the weighted coefficient represents an availability ratio of each of the neighboring cells or areas.

[00013] A fifth embodiment is directed to a computer program product comprising computer-executable computer program code which, when the program is run on a computer, is configured to cause the computer to carry out the method according to the first embodiment.

[00014] The computer program product of the fifth embodiment, wherein the computer program product may comprise a computer-readable medium on which the computer-executable computer program code may be stored, and/or wherein the program may be directly loadable into an internal memory of the processor.

BRIEF DESCRIPTION OF THE DRAWINGS: [00015] For proper understanding of the invention, reference should be made to the accompanying drawings, wherein:

[00016] Fig. 1 illustrates a system according to one example embodiment;

[00017] Fig. 2 illustrates a system according to another example embodiment;

[00018] Fig. 3 illustrates an example graph showing the weighted factor as a function of area size;

[00019] Fig. 4 illustrates an apparatus according to an example embodiment;

[00020] Fig. 5 illustrates an apparatus according to another example embodiment; and

[00021] Fig. 6 illustrates a flow diagram of a method according to an example embodiment.

DETAILED DESCRIPTION:

[00022] It will be readily understood that the components of the invention, as generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of embodiments of systems, methods, apparatuses, and computer program products for area/cell availability evaluation as represented in the attached figures, is not intended to limit the scope of the invention, but is merely representative of selected embodiments of the invention.

[00023] If desired, the different functions discussed below may be performed in a different order and/or concurrently with each other. Furthermore, if desired, one or more of the described functions may be optional or may be combined. As such, the following description should be considered as merely illustrative of the principles, teachings and embodiments of this invention, and not in limitation thereof.

[00024] As will be discussed below, some embodiments generally relate to a method for area/cell availability evaluation. Cell unavailability directly impacts the quality of services provided to end users. Therefore, the monitoring of cell availability is a requirement for each operator. 3GPP 32.450 (chapter 6.4) defines a cell availability ratio key performance indicator (KPI) which provides results from the network's point of view. However, from the end user point of view, if the cell that the UE is currently camping on becomes unavailable, then the UE may access one of the neighboring cells such that no problems may be experienced from the point of view of the end user.

[00025] If, for some reason, a cell and its neighbor cell are not available, the effect of the cell unavailability may be counted twice (in the cell itself and its neighbors). On the other hand, the UE may be camping in the center of a big cell not covered by any other cell, and availability may be completely lost when the big cell is no longer available. In general, it is very problematic to predict if a given cell's unavailability directly affects the end user or its neighbor cells. Currently, there are no known methods for evaluating the cell availability ratio applicable to monitoring from the end user point of view with compensation for the above mentioned double counting for an unavailable cell and its neighbors.

[00026] In view of the above, embodiments of the invention provide a method for evaluation of the cell/area availability ratio from an end user point of view in such a way that, on the cell level, the cell availability ratio KPI may be multiplied with a weighted coefficient of all the neighbor cells to the observed cell respecting the availability ratio of each neighbor. For example, on an area level comprised of N cells, a weighted estimation of the area availability is obtained, which comprise an availability ratio of each cell of the area calculated according to the cell availability ratio KPI, multiplied with a weighted coefficient of all the neighbors to the observed area respecting the availability ratio of each neighbor.

[00027] A cell may be considered available when the UE can request for either signaling or data service in the cell. Logically, the cell may be unavailable when the UE cannot request for any service in the cell. A cell's unavailable may be classified into the following two categories: 1 . the cell is planned unavailable (classified as a manual intervention according to 3GPP 32.425); or 2. the cell is unplanned unavailable (classified as a fault according to 3GPP 32.425). [00028] The planned unavailability category may comprise all the causes the operator is aware of, such as a planned operations and maintenance (O&M) with a software (SW) update and/or hardware (HW) upgrade, but may also consider a concept of LTE heterogeneous networks deploying LTE capacity-booster cells on top of cells that give wide-area coverage. The function enables the capacity- booster cells to be switched off when their capacity is no longer needed, and to be re-activated from a dormant state on a per-need basis.

[00029] On the other hand, the unplanned unavailability category may comprise all the causes leading to a fault or erroneous situation resulting in an unplanned capacity/traffic and/or services loss. Typical examples can comprise when the cell has been suddenly switched off due to some HW or SW problems or due to power down.

[00030] Due to fact that cell unavailability directly impacts the quality of the provided services, the monitoring of cell availability is a requirement for each operator.

[00031] As mentioned above, due to the impact of the cell availability on the quality of the services provided to end users, the monitoring cell availability should be performed for each operator. As such, the cell availability ratio KPI was defined in the 3GPP 32.450 (chapter 6.4) with related use cases discussed in 3GPP 32.451 (chapter 5.4), and respective performance measurements introduced in 3GPP 32.425 (chapter 4.5.6). One problem is that the proposed cell availability ratio KPI according to 3GPP 32.450 provides the results from network point of view. It should be noted that today's users take telecommunications- grade service performance for granted and judge operators and service providers by price and the quality of their service portfolios. Thus, for each operator, it is crucial to understand how the quality of the provided services is perceived by the end user. In relation to cell availability, this means measuring availability from the end user's point of view may also be very beneficial for operators to understand how quality is perceived form the user's perspective.

[00032] Currently, the cell availability KPI is calculated according to its definition in the 3GPP 32.450 (chapter 6.4), which tends to provide the results from network point of view. From the end user perspective, if the cell is unavailable, then the UE usually accesses one of the neighboring cells and, therefore, no problems may be experienced from the end user's perspective.

[00033] Even when all the neighboring cells are overloaded and do not have enough resources to also serve UEs from an unavailable cell, the UE may try to request service on one of them, which in this case may be a visibly worse service as measured by RRC Connection Success Ratio, E-RAB Establishment Success Ratio, and/or E-RAB Drop Ratio. So, if the unavailability of a given cell actually causes issues that are perceived by the end user, these issues should also be visible in the neighboring cells. Thus, the effect of the cell unavailability may be counted twice in the cell itself and in its neighbors. For instance, the issue of double counting may complicate the obtaining of reliable results of a so called super KPI which combines cell availability, RRC Connection Success Ratio, E- RAB Establishment Success Ratio or even in E-RAB Drop Ratio into one formula.

[00034] In addition, there may be some scenarios when the UE cannot camp on any cell. This may occur when a cell covering a big geographical area is unavailable, for example. This usually happens when the UE is located at the middle of this big cell (not close to its boundary). Therefore, it is very challenging to predict if the given cell unavailability directly affects the end user and/or neighbor cells.

[00035] As will be discussed in detail below, certain example embodiments provide a method and apparatus configured to evaluate the cell/area availability ratio from an end user point of view in such a way that, on the cell level, the cell availability ratio KPI may be multiplied with a weighted coefficient of all the neighbor cells to the observed cell respecting the availability ratio of each neighbor. For example, on an area level comprised of N cells, a weighted estimation of the area availability is obtained, which may comprise an availability ratio of each cell of the area calculated according to the cell availability ratio KPI, multiplied with a weighted coefficient of all the neighbors to the observed area respecting the availability ratio of each neighbor.

[00036] As discussed above, the cell availability ratio KPI that is calculated according to 3GPP 32.450 (chapter 6.4) may not reflect the real situation perceived by the end user, in addition to the effect of cell unavailability on neighboring cells which may also be expected to partly compensate for the unavailability.

[00037] Considering a cell of which availability is provided with a currently defined KPI denoted as CA (according to 3GPP 32.450, chapter 6.4), the cell having N neighboring cells, each with a cell availability CAi with i being from 1 to N. According to an example embodiment, the cell availability may be defined from the end user point of view (denoted as CAS) as the number of successful attempts (the UE may camp on the cell or when the UE camps on one of the neighboring ones in case of its unavailability) divided by the number of attempts. Mathematically the CAS can be expressed in the following form:

Considering the attempts are both uniformly distributed in time and geographical area of the cell, where M represents the number of attempts and K is a factor representing what part of the attempts during the cell unavailability is served by its neighboring cells¹. In one example embodiment, the factor Kma range from 0 to 1 . The CAM represents the number of successful attempts as they appear during the time the cell is available while the (1-CA).M represents the number of attempts appearing during the cell unavailability.

[00038] According to an example embodiment, the factor K may then in fact reflect how large the cell is both in terms of its geographical size and from a loading point of view in comparison to its neighboring cells. It is clear that when the observed cell is a small one in comparison to its neighbors and those neighbors are available during its unavailability, then the majority of the traffic/services can be served by them. Therefore, the best approximation of the coefficient K may be given by the following formula:

¹ The obtained cell availability ratio represents a probability the user can request for a service anywhere and anytime in the observed cell with a uniform probability of distribution, i.e. there are not any sub areas nor time frames that are more prioritized than other ones. K = l - _N (2)

'^ CA_i.Load_i

i=l

where Load represents a load of the observed cell wile Loadi represents the load of its /-th neighbor. The load in general may reflect the number of active UEs, sessions/E-RABs, data volume, etc².

[00039] Inserting Equation 2 into Equation 1 provides the following:

which can also be expressed in the following from:

CAS = \ - {\ - CA)W (4) where W is a weighted factor of the observed cell to its neighbors (for example ranging from 0 to 1 ) and given as:

CA_i .Load_i

i=l

[00040] The Cell Availability for Super KPI purposes (CAS) as expressed in Equation 4 was checked against some extreme scenarios in order to show its reliability and applicability. In this example embodiment, it is assumed that the observed cell is a very small one in comparison to its neighbors, as illustrated in Fig. 1 . It is assumed that the observed cell 4 illustrated in Fig. 1 is unavailable for the whole measurement period duration. Due to the above assumption that the observed cell 4 may be considered as having negligible size and loading in comparison to its neighbors (cells 1 , 2, and 3), the weighted factor W according to Equation 5 would lead to zero. Therefore, the CAS according to Equation 4 is one, which is acceptable as all the traffic/sessions of this small cell during its unavailability can be served with its neighbors.

[00041] There may also be a case when, despite the observed cell being

² As this approach represents the easiest way how to estimate the K from the traffic or number of small, all its neighbors are unavailable. In this case, the factor W according to Equation 5 would lead to infinity, i.e., equal to 1 as it ranges only from 0 to 1 , and Equation 4 would result in CA. This means that the observed cell is unavailable for the whole measurement period (as CA=0 in this example) which is also fine from the end user's point of view.

[00042] As mentioned above, a number of options are possible for calculating the weighted factor W. According to one example embodiment, since for cell availability the root case seems to be a cell's size, the approach is to use it as event based, i.e., the number established E-RABs as Load, which represents the easiest way for estimating the weighted factor W.

[00043] In another example embodiment, it is assumed that the observed cell is a very large cell in comparison to its neighbors, as illustrated in Fig. 2. It is assumed that the observed cell 6 illustrated in Fig. 2 is unavailable for the whole measurement period duration. Due to the above assumption that the observed cell 6 may be considered as having a large size and loading in comparison to its neighbors (cells 1 -5 and 7), the weighted factor W according to Equation 5 would lead to one. As a result, the CAS according to Equation 4 becomes zero which is acceptable as most of the traffic/sessions of this cell during its unavailability cannot be served with its neighbors.

[00044] It should be noted that, for the factor W calculation, the Loads from the long period observation periods may be used, as the intention is to catch the relationship between the observed cell and its neighbors from a size and loading perspective. For example, performing the calculation from the night measurement observation period when there is a lack of traffic may not provide a true picture about this relationship.

[00045] The cell availability from an end user point of view (CAS) as expressed in Equation 4 deals with how to perform the calculation on a per cell basis. Example embodiments can extend the calculation to provide the CAS for a bigger area than the cell, as discussed below. active users or sessions there can be an error in the obtained results. [00046] In this case, a similar approach as used for the cell level can be applied. For example, the evaluated area can be considered as a cell and then neighbor areas to this area can be considered as they were for the cell level. This approach yields a similar equation to that of Equation 4, which is given as follows:

AAS = \ - {\ - AA)W (6) the difference from Equation 4 is that CAS is replaced with AAS (Area Availability from end user point of view) and CA is replaced with AA (Area Availability) which may be estimated with the following formula:

AA =∑CA_JWA_J (7) where CA, is a cell availability of the y-th cell (calculated according to 3GPP 32.450, chapter 6.4) which is part of the observed area, and WA_j is its weighted coefficient and is calculated as:

Load■

WA_j = - ^]— (8)

Load _j

j=i

where Load_j is load, e.g., number of established E-RABs, of the y-th cell from the observed area and J represents number of cells belonging to the observed area. The factor W in the above Eq. 6 is calculated in the same way as for cell level with the Eq. 5 with the only difference that Load in the numerator of the formula represents the total load (number of E-RABs) of the observed area.

[00047] The area availability from the end user point of view (AAS) as expressed in Equation 6 tends to follow one important pattern in that as the area is increased (as a maximum area we can consider the public land mobile network (PLMN)) the weighted factor W in limit case leads to infinity, i.e., the W is equal to one, as it ranges from 0 to 1 , which transforms the Eq. 6 into the following :

J

AAS = AA =∑CA_]WA_j (9) j=i

which is equal to Eq. 7.

[00048] For example, for an area equal to PLMN it is clear that the W will in fact lead to infinity as the Load for this area is significantly higher than the load of its neighbors. In addition, it may also be taken into account then there may be no neighbors for the PLMN area for the given operator.

[00049] As an example, the weighted factor W for the area availability from the end user point of view may tend to follow the graph illustrated in Fig. 3. In particular, the example of Fig. 3 illustrates a graph showing the weighted factor W as a function of the area size. In Fig. 3, Size represents the size of the observed area and Sizel < Size 2 < Size 6.

[00050] In another example embodiment of the invention, the way that the weighted factors, as given by Equations 5 and 8, are obtained can be modified. In this embodiment, the weighted factors are not estimated from the Load but instead obtained from neighbouring cells' measurements to the observed cell (or area). In particular, this embodiment takes into consideration that the eNB creates a service map for each observed cell (area) representing how large a part (geographical area) of the observed cell/area can be covered with its neighbours. In order to create the service map, the eNB may need to know some standard measurements, like reference signal received power (RSRP) or reference signal received quality (RSRQ), in order to determine the boundary of the neighbouring cell(s) able to cover the services within the observed cell (area) in case of its unavailability. In addition to the RSRP and RSRQ measurements, which are part of the measurement report provided by the UE, the eNB may also need to know the UE's position.

[00051] The approach provided by this embodiment may be more precise in calculation of the CAS (AAS) using Equation 4 (or Equation 6) when compared to the example embodiments in which the weighted factors are estimated from the Load. On the other hand, this embodiment may require some additional algorithm(s) to be implemented within the eNB to create the service maps and also requires running an UE positioning method. It should be noted that the precision of the method used to determine the UE position may be important for applicability of this embodiment.

[00052] Yet another example embodiment also modifies the way that the weighted factors, as given by Equations 5 and 8, are obtained. In this embodiment, the weighted factors are not estimated from the Load but instead obtained depending on true overlapping of the observed cell (area) with its neighbors (e.g., from network planning phase using the path loss models and drive tests).

[00053] This embodiment may be more precise in calculation of the CAS (AAS) using Equation 4 (or Equation 6) as compared to the example embodiments discussed above, because this embodiment can exactly reflect how large a part of the observed cell (area) can be covered with its neighbouring cells. On the other hand, this embodiment may be more costly as the weighted factors are obtained manually and inserted into the system, in addition to being recalculated whenever a new cell has been introduced.

[00054] Example embodiments in which the weighted factors are estimated from the Load may work fully autonomously, in real time, and without any additional operator's intervention. However, some operators may prefer applying the more precise options which calculate the weighted factors from a service map or the overlapping of the observed cell with its neighbors.

[00055] Although the example embodiments described above may focus on E- UTRAN, embodiments of the invention are equally applicable to any mobile communication technology.

[00056] Fig. 4 illustrates an example of an apparatus 10 according to an embodiment. In one example embodiment, apparatus 10 may be a performance network management apparatus. The performance network management apparatus may be for example part of a network management system and/or part of a node performing network management functions. Further the performance network management appratus may comprise network management functions. It should be noted that one of ordinary skill in the art would understand that apparatus 10 may comprise components or features not shown in Fig. 4. Only those components or feature necessary for illustration of the invention are depicted in Fig. 4. [00057] As illustrated in Fig. 4, apparatus 10 comprises a processor 22 for processing information and executing instructions or operations. Processor 22 may be any type of general or specific purpose processor. While a single processor 22 is shown in Fig. 4, multiple processors may be utilized according to other embodiments. In fact, processor 22 may comprise one or more of general- purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs), field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), and processors based on a multi-core processor architecture, as examples.

[00058] Apparatus 10 further comprises a memory 14, which may be coupled to processor 22, for storing information and instructions that may be executed by processor 22. Memory 14 may be one or more memories and of any type suitable to the local application environment, and may be implemented using any suitable volatile or nonvolatile data storage technology such as a semiconductor- based memory device, a magnetic memory device and system, an optical memory device and system, fixed memory, and removable memory. For example, memory 14 can be comprised of any combination of random access memory (RAM), read only memory (ROM), static storage such as a magnetic or optical disk, or any other type of non-transitory machine or computer readable media. The instructions stored in memory 14 may comprise program instructions or computer program code that, when executed by processor 22, enable the apparatus 10 to perform tasks as described herein.

[00059] Apparatus 10 may also comprise one or more antennas 25 for transmitting and receiving signals and/or data to and from apparatus 10. Apparatus 10 may further comprise a transceiver 28 configured to transmit and receive information. For instance, transceiver 28 may be configured to modulate information on to a carrier waveform for transmission by the antenna(s) 25 and demodulates information received via the antenna(s) 25 for further processing by other elements of apparatus 10. In other example embodiments, transceiver 28 may be capable of transmitting and receiving signals or data directly.

[00060] Processor 22 may perform functions associated with the operation of apparatus 10 including, without limitation, precoding of antenna gain/phase parameters, encoding and decoding of individual bits forming a communication message, formatting of information, and overall control of the apparatus 10, including processes related to management of communication resources.

[00061] In an example embodiment, memory 14 stores software modules that provide functionality when executed by processor 22. The modules may comprise, for example, an operating system that provides operating system functionality for apparatus 10. The memory may also store one or more functional modules, such as an application or program, to provide additional functionality for apparatus 10. The components of apparatus 10 may be implemented in hardware, or as any suitable combination of hardware and software.

[00062] As mentioned above, according to one example embodiment, apparatus 10 may be a performance network management node which may be for example part of a network management system and/or part of a node performing network management functions. According to one example embodiment, apparatus 10 may be controlled by memory 14 and processor 22 to evaluate a cell availability (CA) of a cell or an area availability (AA) of an area in a communications network, such as E-UTRAN. In this embodiment, apparatus 10 may be controlled by memory 14 and processor 22 to evaluate the CA or AA by calculating a cell availability from the end user perspective (CAS) or an area availability from the end user perspective (AAS). The calculating of the CAS or AAS may comprise multiplying the CA or AA with a weighted coefficient of all neighboring cells to the cell or all neighboring areas to the area. In one example embodiment, the weighted coefficient represents the availability ratio of each of the neighboring cells or areas.

[00063] In one example embodiment, apparatus 10 may calculate the CAS according to Equations 1 -4 outlined above. According to this embodiment, the weighted coefficient, W, may be calculated according to Equation 5 discussed above.

[00064] In one example embodiment, apparatus 10 may calculate the AAS according to Equations 6 and 7 outlined above. In this embodiment, the weighted coefficient, W, may be calculated according to Equation 8 discussed above.

[00065] According to another example embodiment, the weighted coefficient, W, may be obtained from neighboring cells' or areas' measurements that are provided to the cell, which may be reflected in a service map created by apparatus 10. In another example embodiment, the weighted coefficient, W, may be obtained based on the true overlapping of the cell or area with its neighbors.

[00066] Fig. 5 illustrates an example of an apparatus 30 according to an example embodiment. In one embodiment, apparatus 30 may be a performance network management node. The performance network management node may be for example part of a network management system and/or part of a node performing network management functions. Further the performance network management node may comprise network management functions. It should be noted that one of ordinary skill in the art would understand that apparatus 30 may comprise components or features not shown in Fig. 5. Only those components or feature necessary for illustration of the invention are depicted in Fig. 5.

[00067] As illustrated in Fig. 5, apparatus 30 comprises processing means 35 for processing information and executing instructions or operations. Apparatus 30 may further comprise transceiving means 45 for transmitting and receiving signals and/or data to and from apparatus 30. Apparatus 30 can also comprise storing means 50 for storing information and instructions that may be executed by processing means 35.

[00068] In one example embodiment, processing means 35 may comprise calculating means 40 for calculating a cell availability from the end user perspective (CAS) or an area availability from the end user perspective (AAS). The calculating of the CAS or AAS may comprise multiplying the CA or AA with a weighted coefficient of all neighboring cells to the cell or all neighboring areas to the area. In one example embodiment, the weighted coefficient may represent the availability ratio of each of the neighboring cells or areas.

[00069] In one example embodiment, calculating means 40 of apparatus 30 may calculate the CAS according to Equations 1 -4 outlined above. According to this embodiment, the weighted coefficient, W, may be calculated according to Equation 5 discussed above.

[00070] In one example embodiment, calculating means 40 of apparatus 30 may calculate the AAS according to Equations 6 and 7 outlined above. In this embodiment, the weighted coefficient, W, may be calculated according to Equation 8 discussed above.

[00071] According to another example embodiment, the weighted coefficient, W, may be obtained from neighboring cells' or areas' measurements that are provided to the cell, which may be reflected in a service map created by apparatus 30. In another example embodiment, the weighted coefficient, W, may be obtained based on the true overlapping of the cell or area with its neighbors.

[00072] Fig. 6 illustrates an example of a flow diagram of a method that comprises, at 600, evaluating, for example by a network management apparatus, a cell availability (CA) of a cell or an area availability (AA) of an area in a communications network, such as E-UTRAN. In this embodiment, the evaluating may comprise calculating, at 610, a cell availability from the end user perspective (CAS) or an area availability from the end user perspective (AAS). The calculating of the CAS or AAS may comprise multiplying the CA or AA with a weighted coefficient of all neighboring cells to the cell or all neighboring areas to the area. In one example embodiment, the weighted coefficient represents the availability ratio of each of the neighboring cells or areas.

[00073] According to an example embodiment, the calculating of the CAS comprises calculating the CAS according to Equations 1 -4 outlined above. According to this embodiment, the weighted coefficient, W, may be calculated according to Equation 5 discussed above.

[00074] In one example embodiment, the calculating of the AAS may comprise calculating the AAS according to Equations 6 and 7 outlined above. In this embodiment, the weighted coefficient, W, may be calculated according to Equation 8 discussed above.

[00075] According to another example embodiment, the weighted coefficient, W, may be obtained from neighboring cells' or areas' measurements that are provided to the cell, which may be reflected in a service map created by the network management apparatus. In another example embodiment, the weighted coefficient, W, may be obtained based on the true overlapping of the cell or area with its neighbors.

[00076] In some embodiments, the functionality of any of the methods described herein, such as that illustrated in Fig. 6 discussed above, may be implemented by software and/or computer program code stored in memory or other computer readable or tangible media, and executed by a processor. In other embodiments, the functionality may be performed by hardware, for example through the use of an application specific integrated circuit (ASIC), a programmable gate array (PGA), a field programmable gate array (FPGA), or any other combination of hardware and software.

[00077] One having ordinary skill in the art will readily understand that the invention as discussed above may be practiced with steps in a different order, and/or with hardware elements in configurations which are different than those which are disclosed. Therefore, although the invention has been described based upon these preferred embodiments, it would be apparent to those of skill in the art that certain modifications, variations, and alternative constructions would be apparent, while remaining within the spirit and scope of the invention. In order to determine the metes and bounds of the invention, therefore, reference should be made to the appended claims.

Claims

WE CLAIM:

1. A method, comprising:

evaluating a cell availability (CA) of a cell or an area availability (AA) of an area in a communications network,

wherein the evaluating comprises calculating a cell availability from an end user perspective (CAS) or an area availability from the end user perspective (AAS),

wherein the calculating of the CAS or AAS comprises multiplying the cell availability (CA) or area availability (AA) with a weighted coefficient of all neighboring cells to the cell or all neighboring areas to the area, and

wherein the weighted coefficient represents an availability ratio of each of the neighboring cells or areas.

2. The method according to claim 1 , wherein the cell availability from the end user perspective (CAS) is calculated according to the following equation:

_{CAS =} CA.M ₊ (l - CA).M.K

M where M represents a number of attempts, K \s a factor representing what part of the attempts during the cell unavailability is served by the neighboring cells, CAM represents a number of successful attempts during a time the cell is available, and (1-CA).M represents a number of attempts during the cell unavailability.

3. The method according to claims 1 or 2, wherein K is calculated according to the following equation:

^ CA_i .Load_i

=1

where Load represents a load of the cell, and Loadi represents a load of the cell's /-th neighbor.

4. The method according to claims 2 or 3, wherein combining equation 2 with equation 1 provides the following equation:

which can also be expressed in the following from:

CAS = \ - {\ - CA)W (4), where W is a weighted factor of the cell to its neighbors and given as:

Load

W = - (5).

^ CA_i .Load_i

5. The method according to claim 1 , wherein the area availability from the end user perspective (AAS) is calculated according to the following equation:

AAS = l - {l - AA)W (6), where AA is estimated with the following equation:

AA ^ CAJWAJ (7),

7=1

where CA, is a cell availability of the y^'-th cell which is part of the area, and WA_j is its weighted coefficient.

6. The method according to claim 5, wherein the weighted coefficient, WA_j, is given by the following equation:

Load■

WA ^"7_; = 7 (8)

Load _j

7=1

where Load_j is a load of the y-th cell from the observed area and J represents a number of cells belonging to the area.

7. The method according to claim 6, wherein, when l V=1 , the area availability from the end user perspective (AAS) is given by the following : j

AAS = AA = CA WA; (9).

8. The method according to claims 1 -3 or 5, wherein the weighted coefficient is obtained from measurements provided by neighbor cells or areas.

9. The method according to claims 1 -3 or 5, wherein the weighted coefficient is obtained from true overlapping of the cell or area with neighboring cells or areas.

10. An apparatus, comprising:

at least one processor; and

at least one memory comprising computer program code,

the at least one memory and the computer program code configured, with the at least one processor, to cause the apparatus at least to

evaluate a cell availability (CA) of a cell or an area availability (AA) of an area in a communications network, and

calculate a cell availability from an end user perspective (CAS) or an area availability from the end user perspective (AAS) by multiplying the cell availability (CA) or area availability (AA) with a weighted coefficient of all neighboring cells to the cell or all neighboring areas to the area, and

1 1 . The apparatus according to claim 10, wherein the cell availability from the end user perspective (CAS) is calculated according to the following equation:

CAM + (l - CA).M.K

CAS = (1 ),

12. The apparatus according to claims 10 or 1 1 , wherein K is calculated according to the following equation:

Load

K = l— (2),

CA_i .Load_i where Load represents a load of the cell, and Loadi represents a load of the cell's /-th neighbor.

13. The apparatus according to claims 1 1 or 12, wherein combining equation 2 with equation 1 provides the following equation:

which can also be expressed in the following from:

CAS = \ - {\ - CA)W (4), where W is a weighted factor of the cell to its neighbors and g

Load

W = - (5).

^ CA_i .Load_i

14. The apparatus according to claim 10, wherein the area availability from the end user perspective (AAS) is calculated according to the following equation:

AAS = l - {l - AA)W (6), where AA is estimated with the following equation:

where CA_j is a cell availability of the y^'-th cell which is part of the area, and WA_j is its weighted coefficient.

15. The apparatus according to claim 14, wherein the weighted coefficient, WA_j, is given by the following equation:

Load■

WA_j = - ^]— (8)

Load _j

j=i

16. The apparatus according to claim 15, wherein, when W=1 , the area availability from the end user perspective (AAS) is given by the following:

J

AAS = AA =∑CA_jWA_j (9).

17. The apparatus according to claims 10-12 or 14, wherein the weighted coefficient is obtained from measurements provided by neighbor cells or areas.

18. The apparatus according to claims 10-12 or 14, wherein the weighted coefficient is obtained from true overlapping of the cell or area with neighboring cells or areas.

19. The apparatus according to any of the claims 10 to 18, wherein the apparatus is a performance network management node.

20. An apparatus, comprising:

evaluating means for evaluating a cell availability (CA) of a cell or an area availability (AA) of an area in a communications network, and

calculating means for calculating a cell availability from an end user perspective (CAS) or an area availability from the end user perspective (AAS) by multiplying the CA or AA with a weighted coefficient of all neighboring cells to the cell or all neighboring areas to the area, and

21 . A computer program, embodied on a computer readable medium, the computer program configured to control a processor to perform a process, comprising:

wherein the calculating of the CAS or AAS comprises multiplying the CA or AA with a weighted coefficient of all neighboring cells to the cell or all neighboring areas to the area, and

22. A computer program product comprising computer-executable computer program code which, when the program is run on a computer, is configured to cause the computer to carry out the method according to any one of claims 1 to 10.

23. The computer program product according to claim 21 , wherein the computer program product comprises a computer-readable medium on which the computer- executable computer program code is stored, and/or wherein the program is directly loadable into an internal memory of the processor.