Modelling of cellular communication systems

MODELLING OF CELLULAR COMMUNICATION SYSTEMS

Field of the invention

The invention relates to modelling of a cellular communication system and in particular, but not exclusively, to modelling of cellular communication systems for performance evaluation.

Background of the Invention

Currently, the most ubiquitous cellular communication system is the 2nd generation communication system known as the Global System for Mobile communication (GSM) .

Further description of the GSM TDMA communication system can be found in "The GSM System for Mobile

Communications' by Michel Mouly and Marie Bernadette Pautet, Bay Foreign Language Books, 1992, ISBN

2950719007.

3rd generation systems have recently been rolled out in man and the will y areas to further enhance the communication services provided to mobile users. One such system is the Universal Mobile Telecommunication System (UMTS) , which is currently being deployed. Further description of CDMA and specifically of the Wideband CDMA (WCDMA) mode of UMTS can be found in ¹WCDMA for UMTS', Harri Holma (editor) , Antti Toskala (Editor) , Wiley & Sons, 2001, ISBN 0471486876. The core network of UMTS is built on the use of SGSNs and GGSNs thereby providing commonality with GPRS. The performance evaluation of a cellular communication system in a variety of scenarios is at best a complex and time-consuming activity. In order to evaluate the effect and impact of various parameter changes, it is frequently used to evaluate a reduced model of the cellular communication system. This allows an easy and practical evaluation of many different configurations and parameter settings without impacting the real-time performance of a cellular communication system and can be used for assessing suitable configurations and settings for a system which is yet to be rolled out.

However, in order to achieve reliable performance results, it is essential that the model provides a realistic modelling of the physical characteristics and conditions of the cellular communication system. In order to achieve this, the model must be an accurate model that considers many of the characteristics and operational conditions of the cellular communication system including propagation characteristics, base station locations, user equipment movement, transmit characteristics for the individual base stations (such as transmit powers and radiation patterns) etc.

At the same time, it is desirable to reduce the complexity of the model in order to substantially reduce the computational resource requirement and the computational processing time required for evaluating the performance of the system. For this reason, it is advantageous for some performance evaluations to use a model that comprises relatively few cells. For example, for many performance evaluations a cell layout comprising around e.g. 25 cells (say in a 5x5 cell layout) can provide reliable results while achieving a low model complexity and thus a low computational resource requirement and computational processing time. Also, small models may be particularly suitable for evaluating performance of small critical areas.

However, a problem for models of cellular communication systems is that the boundary effects can degrade the accuracy of the performance results obtained.

Specifically, a number of cells at the boundary or edge of the modelled area do not have any neighbours and thus the carried load or the interference conditions cannot be considered homogeneous . For a very large model based on large number of cells, the boundary effects may be insignificant by the inner cells. In such cases, the outer cells adjacent to the boundary may be ignored and the performance results for the inner cells can be used directly. However, for smaller models it is not practical to ignore the outer cells and the boundary effects in the inner cells may still be significant.

A solution which has been proposed to this problem is to use a wrap-around technique whereby the cell layout is wrapped around itself to eliminate boundaries. Thus, a cell at one boundary is considered to be adjacent to the cell at the opposite boundary corresponding to the modelled area being modelled as a three dimensional torus rather than as a flat two-dimensional area. Although such an approach may reduce the boundary effects, it has some disadvantages. Specifically, it creates problems with respect to interference computation and users mobility, given that the real network is still "flat" and mobiles can only be connected to a real cell and not one of the image cells.

Also, using a conventional model tends to result in a high computational burden as it typically involves using all the mobiles and all the cells in the system (including the wrap-around cell representations) to compute the uplink and downlink interference levels at performance evaluation time .

Hence, an improved model of a cellular communication system would be advantageous and in particular a model allowing increased flexibility, facilitated performance evaluation, improved accuracy of the representation of the cellular communication system and the physical configuration and performance requirements, reduced computational resource requirement, reduced computational processing time and/or improved performance would be advantageous .

Summary of the Invention

Accordingly, the Invention seeks to preferably mitigate, alleviate or eliminate one or more of the above mentioned disadvantages singly or in any combination.

According to a first aspect of the invention there is provided method of generating a model of a cellular communication system, the method comprising: generating a first cell layout for a first area; generating a displaced set of cell layouts, each cell layout of the displaced set corresponding to the first cell layout displaced in a different direction such that it borders the first cell layout, each cell of the first cell layout being uniquely associated with a corresponding cell in each cell layout of the displaced set; generating a model location set for the first area, the model location set comprising a plurality of locations within the first area; determining a first model for the cellular communication system by for each location of the model location set and for a plurality of cells of the first cell layout performing the steps of: evaluating an interference characteristic for each cell of a cell group comprising the cell of the first cell layout and at least one corresponding cell of the displaced set of cell laycuts, and selecting a first cell from the cell- group as an interfering cell for the location in response to the interference characteristics.

The invention may provide an improved model of a cellular communication system. An improved accuracy of the model may be achieved and in particular the effect of boundary effects may be reduced. A low complexity model may be obtained and in particular a model with a reduced number of modelled cells may be used in many embodiments. A reduced computational resource requirement and/or processing time for a performance evaluation based on the model may be achieved.

According to an optional feature of the invention, the method further comprises determining a performance interference characteristic from the first cell to the location. This may provide improved accuracy and/or reduced computational burden.

The performance interference characteristic may be the same as the interference characteristic used for selecting the first cell. The performance characteristic may specifically be calculated taking into account the displaced location of the first cell.

According to an optional feature of the invention, the method further comprises storing the first model in a data storage.

This may provide improved accuracy and/or reduced computational burden. Specifically, the feature may facilitate the reuse of the model for a plurality of performance evaluations .

According to an optional feature of the invention, the method further comprises simulating a dynamic operation of the cellular communication system in response to the first model .

This may provide a dynamic performance evaluation of the cellular communication system with improved accuracy and/or reduced computational burden.

According to an optional feature of the invention, the method further comprises performing a plurality of simulations of a dynamic operation of the cellular communication system with different operating characteristics in response to the first model. This may provide a dynamic performance evaluation of the cellular communication system with improved accuracy and/or reduced computational burden. In particular, the invention may allow that high accuracy performance evaluation can be achieved while maintaining a low computational burden by allowing accurate but demanding operations to be performed only once for a plurality of simulations .

According to an optional feature of the invention, the method further comprises estimating performance parameters for the plurality of locations in response to cell traffic variations and the first model.

This may provide a dynamic performance evaluation of the cellular communication system with improved accuracy and/or reduced computational burden. Specifically, a performance evaluation may be achieved by using a traffic characteristic for the first cell for each location which is identical to the traffic characteristic for the corresponding cell of the first cell layout while using interference characteristics determined for the first cell .

According to an optional feature of the invention, the displaced set comprises eight cell layouts.

This may provide for a particular advantageous model in many embodiments and may in particular allow an efficient reduction of boundary effects for the model . The eight cells layouts may specifically be offset in directions offset by substantially forty-five degrees. The first area may specifically be substantially rectangular with the eight displaced cell layouts being located on each side and corner of the first area.

According to an optional feature of the invention, the displaced set comprises cell layouts surrounding the first area.

This may provide for a particular advantageous model in many embodiments and may in particular allow an efficient reduction of boundary effects for the model.

According to ar; optional feature of the invention, the interference characteristic is a path loss indication.

This may provide particularly advantageous performance and may in particular allow an accurate selection of the first cell as the most significant cell of the corresponding cells.

According to an optional .feature of the invention, the interference characteristic is determined for predetermined transmit characteristics for each cell of the first cell layout.

This may provide particularly advantageous performance and may in particular allow an accurate selection of the first cell as the most significant cell of the corresponding cells. The predetermined transmit characteristics may for example be transmit powers and/or traffic characteristics of the different cells in the first cell layout. According to an optional feature of the invention, the interference characteristic is a carrier to interference indication.

This may provide particularly advantageous performance and may in particular allow an accurate selection of the first cell which is the most significant cell of the corresponding cells.

According to an optional feature of the invention, the interference characteristic is an interference level indication.

This may provide particularly advantageous performance and may in particular allow an accurate selection of the first cell as the most significant cell of the corresponding cells.

According to an optional feature of the invention, the interference characteristic for a given cell is determined in response a directional radiation pattern for a base station of the given cell .

This may provide particularly advantageous performance and may in particular allow an accurate selection of the first cell as the most significant cell of the corresponding cells .

According to an optional feature of the invention, the model location set corresponds to a grid with substantially equidistant locations . This may provide particularly advantageous performance and may in particular allow an accurate model for the first area.

According to another aspect of the invention, there is provided a computer program product enabling the carrying out of a method as described above. The computer program product may e.g. be a computer program or a data carrier comprising a computer program.

According to another aspect of the invention, there is provided an apparatus for generating a model of a cellular communication system, the apparatus comprising: means for generating a first cell layout for a first area; means for generating a displaced set of cell layouts, each cell layout of the displaced set corresponding to the first cell layout displaced in a different direction such that it borders the first cell layout, each cell of the first cell layout being uniquely associated with a corresponding cell in each cell layout of the displaced set; means for generating a model location set for the first area, the model location set comprising a plurality of locations within the first area; and means for determining a first model for the cellular communication system by, for each location of the model location set and for a plurality of cells of the first cell layout, performing the steps of: evaluating an interference characteristic for each cell of a cell group comprising the cell of the first cell layout and at least one corresponding cell of the displaced set of cell layouts, and selecting a first cell from the cell group as an interfering cell for the location in response to the interference characteristics. These and other aspects, features and advantages of the invention will be apparent from and elucidated with reference to the embodiment (s) described hereinafter.

Brief Description of the Drawings

Embodiments of the invention will be described, by way of example only, with reference to the drawings, in which

FIG. 1 illustrates a method of generating a model of a cellular communication system in accordance with some embodiments of the invention;

FIG. 2 illustrates an example of a cell layout for an area of a cellular communication system;

FIG. 3 illustrates an example of a combined cell layout in accordance with some embodiments of the invention; and

FIG. 4 illustrates an example of performance evaluation in accordance with some embodiments of the invention.

Detailed Description of Some Embodiments of the Invention

The following description focuses on embodiments of the invention applicable to modelling and simulating a GSM cellular communication system. However, it will be appreciated that the invention is not limited to this application but may be applied to many other cellular communication systems including for example UMTS or cellular Wireless Local Area Networks .

FIG. 1 illustrates a method of generating a model of a cellular communication system in accordance with some embodiments of the invention. The method addresses the problems of how to reduce computational burden (processing resource requirement and processing time) and how to accurately represent and evaluate the physical conditions and parameters experienced in cellular communication systems.

The method starts in step 101 wherein a first cell layout is determined for the area of the cellular communication system which is to be modelled. Fig. 2 illustrates an example of a cell layout for an area of the cellular communication system. In the example, a cell layout comprising twenty-five cells arranged in a 5x5 pattern of identical hexagonal cells covering substantially square area of Δx by Δy (which are identical for the square area) . It will be appreciated that in other embodiments, a different number of cells may be used for the x and y direction resulting in a possibly substantially rectangular area .

Step 101 is followed by step 103 wherein a displaced set of cell layouts is generated. Each of the displaced cell layouts in this set is a copy of the first cell layout which has been geographically moved such that it is adjacent the original first cell layout. Thus, there is a unique association between cells of the different cell layouts as these are all copies of the same original first cell layout. For example, cell 12 of the first cell layout of FIG. 2 has a corresponding cell in each of the displaced cell layouts corresponding to the copy of cell 12 in each of the cell layouts. The displaced cell layouts may thus in the specific example be considered logical cells which are not representing the cells to be modelled but are copied cells that are used to mitigate the boundary effects of the model .

Each of the displaced cell layouts is displaced in a different direction such that it borders the first cell layout. For example, a first displaced cell layout is created by displacing the first cell layout by a value of Δx in the positive x-direction. Thus, this first displaced cell layout is obtained by copying the cells of the first cell layout of FIG. 2 and changing the location of all the cells by Δx. Accordingly, the first displaced cell layout is located such that it immediately borders the first cell layout and specifically such that the copied cells from the opposite border become neighbour cells for the cells at the border to which the first cell layout is displaced (i.e. in the example of FIG. 2, the copy of cell 20 becomes a neighbour of cell 24, the copy of cell 15 becomes a neighbour of cell 19, etc) .

Using the same approach, a second displaced cell layout can be achieved by copying the first cell layout and displacing it by -Δx in the x-direction. Furthermore, a similar approach can be used to generate a third and fourth displaced cell layout by displacing a copy of the first cell layout by approximately Δy or -Δy in the y direction. However, as can be seen from FIG. 2, the displacement in the y direction is preferably accompanied by a displacement in the x direction of one half cell width in order to ensure that the hexagonal cells along the border are properly aligned. It will be appreciated that this displacement may depend on the cell geometry used for the model .

In the specific example, the same approach is used to generate copied logical cell layouts at the corners (diagonals) of the original cell layout. These cell layouts can be obtained by copying the cells of the original cell layout and displacing them by approximately ±Δx and ±Δy. Again the displacement may be modified to ensure an alignment of the cells.

Thus in the example a combined cell layout comprising a total of nine cell layouts is generated where one cell layout is the original cell layout and eight cell layouts are copies of the original cell layout surrounding the original cell layout and displaced such that the copied cell layouts are immediately adjacent to the first cell layout. FIG. 3 illustrates an example of such a combined cell layout. As illustrated in FIG. 3 some of the copied cell layouts (2, 3, 4, 6, 7, 8) are furthermore shifted to provide an alignment of the cells along the boundaries .

Step 103 is followed by step 105 wherein a model location set is generated for the first area i.e. for the area to be modelled and which is covered by the first cell layout. The model location set comprises a plurality of locations within the first area for which data for the model is to be generated and which specifically may be used for simulations of the system. It will be appreciated that any suitable approach or criteria for selecting such locations may be used. In the specific example, a location grid comprising substantially equidistant locations are used to provide a homogenous coverage of the area. However, in other embodiments other approaches may be used such as for example a finer grid of locations in areas known to be more critical or e.g. have higher user concentrations than other areas .

Step 105 is followed by steps 107 to 117 wherein all locations of the location grid are sequentially evaluated. For each location, each cell of the first cell layout is considered sequentially. For each of the cells, the interference impact from the original cell and for the copied cells on the location is determined. The cell of the group of cells made up by the original cell and the copied cell which has the highest interference impact is then selected and will be used for the model.

Thus, a model is developed which for each location and for each original cell identifies a cell which provides the highest impact at the specific location. For example, for a location in cell 14 of FIG. 2, the impact of cell 10 in the first cell layout is insignificant as it is attenuated by the large distance between them (made up by cells 11, 12 and 13) . However, the copy of cell 10 in the first displaced layout (e.g. layout 1 of FIG. 3) is adjacent to cell 14 and will have a significant interference impact due to the low distance.

Thus, the model allows for an efficient wrap-around effect that provides for an accurate modelling of even very small cell layouts and allows impact of the traffic characteristics etc of the individual cells to be effectively taken into account. Furthermore, the model provides for low computational burden of performance evaluations or simulations based on the model . Specifically, although an efficient wrap around representation is achieved which corresponds to a large increase in the effective interference area considered, the number of cells that is considered for each location point is reduced by the selection of the most significant interferer in the wrap around.

In more detail, step 105 is followed by step 107 wherein the next location of the location grid to be evaluated is selected. Step 107 is followed by step 109 wherein a cell of the first cell layout is selected. Thus, the following steps 111 and 113 are performed for each location and for each physical cell (i.e. for each cell to be simulated) .

Step 109 is followed by step 111 wherein an interference characteristic is determined for the original selected cell as well as all copies of the cell. Thus, an interference characteristic is determined for the group of cells comprising all the corresponding cells in the different cell layouts.

For example, the interference characteristic may be a path loss between the base station of the corresponding cell and the location. The lower the path loss, the higher the interference to the location from the cell will be. In this example, the path loss can be calculated taking into account the distance between the individual cell being considered and the location. As a specific example, if a location in cell 14 is considered and the interference from the group of corresponding cells for cell 11 is considered, a path loss is determined from the base station of cell 11 in the first cell layout, from cell 11 in the first displaced cell layout, from cell 11 in the second displaced cell layout etc. The path loss is calculated taking into account the displaced location of each cell. The determined interference characteristic is thus an indication of the relative interference impact of each of the corresponding cells on the location.

Step 111 is followed by step 113 wherein one of the corresponding cells is selected as the cell having the most significant interference impact. Specifically, the cells may be arranged in order of the determined interference characteristic and the one indicating the highest interference is selected as the most significant interference source out of the group of corresponding cells. Accordingly, this cell is assigned to the location as the main interfering cell corresponding to the considered cell of the first layout.

For example, for the location in cell 14 it is likely that cell 11 of the first displaced layout has a lower path loss than for cell 11 of the original cell layout or indeed of any cell 11 in any other displaced cell layout. Accordingly, cell 11 of the first displaced cell layout is selected.

It will be appreciated that in some embodiments only the single highest interferer is selected. However, in other embodiments, other criteria can be used to select the cell (or cells) that are used for the model for that location. For example, all corresponding cells for which the interference characteristic meets a given interference criterion (e.g. above a given threshold) can be selected.

In the specific example where only one cell from the group is selected for each cell location, the unique mapping between a logical cell and a physical cell together with the fact that a physical cell can only be represented once (potentially through an associated logical cell of the displaced cell layouts) for a location ensures that it is not possible for a user to be connected more than once to a physical cell. This is consistent with practical considerations for performance evaluation dependent on the radio resource management of the system as each individual user can only be connected once to each physical cell in a real system.

Step 113 is followed by step 115 wherein it is determined if all cells of the first cell layout have been considered for the specific location. If not, the method returns to step 109 wherein a new cell in the first cell layout is selected.

If all cells have been considered for the location, step 115 is followed by step 117 wherein it is determined if all locations of the location grid have been considered. If not, the method returns to step 107 wherein the next location is selected and the cell selection process is repeated for this location. If all locations have been considered, the method continues in step 119. In this case a model of the cellular communication system has been created which for each model location of the first area defines a set of interfering cells corresponding to the cells in the first cell layout but having locations that reflect the wraparound and specifically having the locations which have the highest interference impact. Furthermore, the model has low complexity and can be used for simulation or other performance evaluation with a low computational burden. Specifically, if only one corresponding cell is selected for each location, the total number of cells considered for each location is not increased by the wrap around as the total number is maintained equal to the number of cells in the first cell layout. In step 119 the generated model is stored in a suitable storage such as a solid state data memory or data record carrier.

In the example, a path loss was used as the interference characteristic. However, it will be appreciated that other parameters or measures may additionally or alternatively be considered.

For example, in some embodiments the interference characteristic can be an interference level for the location point from the individual cells. This interference level can be calculated based on a path loss calculation and an assumed transmit power for the base station of the cell. As another example, in some embodiments, a carrier to interference characteristic can be determined for each location by considering the signal level from the base station of the cell within which the location is (the serving based station) relative to the interference generated by other cells assuming the currently evaluated cell is selected.

It will be appreciated that many other transmit characteristics may be considered by assigning predetermined values. For example, a traffic loading may be assumed for the different cells and the interference characteristic may be determined for this traffic loading.

In some embodiments, the interference characteristic takes into account a directional radiation pattern for a base station of the given cell. For example, for a sectored cell, the antenna beam pattern is taken into account when calculating the interference level at the location. This allows a much more accurate modelling. For example, the impact on cell 14 from cell 12 of the first cell layout may be insignificant and the impact on cell 14 from cell 12 of the first displaced cell layout can be highly significant if the sectorisation (i.e. the radiation direction of the sector antenna) is in the positive x-direction. If the sectorisation is in the negative x-direction, the exact opposite is the case. Thus, the selection of the most appropriate cell to consider depends strongly on the radiation pattern.

The directional radiation pattern can simply be taken into account by determining the angle between the base station and the location and adding the gain/loss of the antenna radiation pattern in this direction to the calculated path loss . In the specific embodiment, the actual path loss (including antenna gains, shadowing and propagation loss) is taken into calculated thereby giving a much better cell selection criterion than, say, the distance between a cell and the grid point. Although this is more complicated to compute, these computations need only be performed when developing the model and not during each simulation.

In some embodiments, only the selected cell is stored in the model for each location. However, in most embodiments, a performance interference characteristic is also stored for each location and for each selected cell . This performance interference characteristic can specifically be the same as the interference characteristic used to select the cell.

For example, the calculated attenuation between the base station of the selected cells and the location can be stored for each location. This attenuation can be a relatively accurate calculation based on antenna patterns, relative locations, distance and propagation calculations. Such a calculation is computationally expensive but as it needs to be performed only once for the model rather than during performance evaluation, this is acceptable and can result in a significant overall reduction in computational burden allowing an increased accuracy of the performance evaluation.

It will be appreciated that although the above description of the method of FIG. 1 focussed on all locations being considered, all original cells being considered for each location and all corresponding cells being considered for each original cell, other embodiments may utilise subsets of these for the evaluation.

The model is particularly suitable for performance evaluation and simulation of the cellular communication system. Specifically, the dynamic operation of the cellular communication system considering cell traffic variations and e.g. radio resource management can effectively be evaluated using the model.

For example, during a system simulation, the list of selected cells associated with the location grid points are \ised to determine which cells (on the downlink) and which mobiles (on the uplink) are taken into account when computing the total interference on the downlink and on the uplink respectively. Specifically, this calculation can use the accurate path loss determined during the model generation and stored with the list of selected cells.

From a Radio Resource Management point of view, only the physical cells of the first cell layout exist in the simulation space. The concept of the logical cells of the displaced cell layouts is only used to compute the interference using the position of the logical cell (rather than that of the physical cell) thereby providing an accurate interference computation with low computational burden.

FIG. 4 illustrates an example of performance evaluation in accordance with some embodiments of the invention. The evaluation initiates in step 401 wherein the model generated by the method of FIG. 1 is retrieved from the data storage.

Step 401 is followed by step 403 wherein a new location for which the system is evaluated. For example, in some embodiments, all locations of the location grid may be sequentially selected. In some embodiments, the current position of a mobile station may be determined and the location closest thereto may be selected.

Step 403 is followed by step 405 wherein the selected cells for the specific location are retrieved from the model .

Step 405 is followed by step 407 wherein the interference condition at the location for these selected cells is considered. For example, a carrier to interference relationship for a mobile at the location and served by a specific cell can be calculated using the accurate path loss calculations stored in the model. The carrier to interference relationship can be calculated taken into account the actual current dynamically changing transmit characteristics determined on the basis of the current traffic and radio resource management for the individual cells .

Step 407 is followed by step 409 wherein it is determined if all the locations to be considered have been evaluated. For example, in some embodiments it may be determined if all locations of the location grid have been evaluated. In some embodiments, it may be determined if locations for all simulated mobile stations have been evaluated. If not, the method returns to step 403 wherein the next location is selected.

When all locations have been considered the method continues in step 411 wherein the performance characteristics are evaluated. For example, the quality of service (e.g. the error rate) for the individual mobile stations may be determined and/or the number of dropped calls etc may be evaluated.

It will be appreciated that the performance evaluation illustrated by FIG. 4 for brevity and clarity is very simple and that many other approaches to performance evaluation or simulation based on the derived model may be used.

It will also be appreciated that the described approach allows the same model to be used for different simulations with e.g. different operating parameters without requiring that a new model is created. Rather, the selection of the interfering cell location and the path loss values are independent of most operating parameters and are specifically independent of transmit powers and radio resource management. Thus, accurate and complex determination of the appropriate interfering cell and of the path loss can be achieved without significantly increasing the overall computational burden of the performance evaluation.

It will be appreciated that the above description for clarity has described embodiments of the invention with reference to different functional units and processors. However, it will be apparent that any suitable distribution of functionality between different functional units or processors may be used without detracting from the invention. For example, functionality illustrated to be performed by separate processors or controllers may be performed by the same processor or controllers. Hence, references to specific functional units are only to be seen as references to suitable means for providing the described functionality rather than indicative of a strict logical or physical structure or organization.

The invention can be implemented in any suitable form including hardware, software, firmware or any combination of these. The invention may optionally be implemented at least partly as computer software running on one or more data processors and/or digital signal processors. The elements and components of an embodiment of the invention may be physically, functionally and logically implemented in any suitable way. Indeed the functionality may be implemented in a single unit, in a plurality of units or as part of other functional units. As such, the invention may be implemented in a single unit or may be physically and functionally distributed between different units and processors .

Although the present invention has been described in connection with some embodiments, it is not intended to be limited to the specific form set forth herein. Rather, the scope of the present invention is limited only by the accompanying claims. Additionally, although a feature may appear to be described in connection with particular embodiments, one skilled in the art would recognize that various features of the described embodiments may be combined in accordance with the invention. In the claims, the term comprising does not exclude the presence of other elements or steps .

Furthermore, although individually listed, a plurality of means, elements or method steps may be implemented by e.g. a single unit or processor. Additionally, although individual features may be included in different claims, these may possibly be advantageously combined, and the inclusion in different claims does not imply that a combination of features is not feasible and/or advantageous . Also the inclusion of a feature in one category of claims does not imply a limitation to this category but rather indicates that the feature is equally applicable to other claim categories as appropriate.

Furthermore, the order of features in the claims does not imply any specific order in which the features must be worked and in particular the order of individual steps in a method claim does not imply that the steps must be performed in this order. Rather, the steps may be performed in any suitable order.