TRACKING AREA MANAGEMENT METHOD AND APPARATUS FOR LONG TERM EVOLUTION TELECOMMUNICATION SYSTEMS Cross Reference to Related Applications [0001] This application claims the benefit of U.S. provisional application number 60/150,499 filed on February 6,2009, which is fully incorporated herein by reference. Field of the Invention [0002] The invention pertains to tracking area management in long term evolution telecommunication systems. Background of the Invention [0003] The third generation partnership project (3GPP) has developed a specification for advancements in wireless telecommunication systems commonly known as Long Term Evolution or LTE. LTE has many improvements and advancements over the previous generations of wireless telecommunication networks and systems. Among them is dynamic tracking area management. Particularly, user equipment (UE) such as cell phones, laptop computers, wireless personal digital assistants, etc. are, by definition mobile and can move between cells over time. Accordingly, wireless communication networks typically have a technique or protocol for maintaining data on the locations of the user equipment for that network. [0004] The LTE specification sets forth a protocol for maintaining data as to the locations of UEs on the network. Particularly, LTE provides for dynamic management of UE locations. [0005] In this specification, a basic knowledge of LTE is assumed. In LTE, a UE interfaces to the network through an evolved node B (eNB). A Mobility Management Entity (MME) in the main signaling node in the network is responsible for initiating paging and authentication of UEs. It also maintains the location information of the UEs. [0006] LTE introduces the concept of tracking areas (TAs). A tracking area is a subset of the volume of space within the wireless network in which any given UE may be located. A tracking area may comprise the area covered by one eNB (e.g., a cell) or multiple eNBs (multiple cells). [0007] In accordance with the LTE specification, when a UE is idle (e.g., not in active communication over the network, such as on an active telephone call) the location of the UE is known at the MME on a granularity at the TA level. Each UE maintains a tracking area (TA) list which may comprise one or more TAs within which the UE is likely to be located. Only when the UE leaves the area covered by the TAs in its TA list does the UE initiate a tracking area update (TAU) operation to notify the MME of its new location. In response to a TAU, the MME typically returns an updated TA list to the UE. [0008] In short, the tracking area update is a communication between the UE and the MME (e.g., through an eNB) informing the MME of the new tracking area of the UE. The MME also may transmit data to the UE in connection with tracking area management. [0009] When a call is made to a UE (e.g., a voice call to a cellular telephone), the UE is paged by the network in the TAs in Its last known assigned TA list. Consequently, if the UEs in a network tend to have larger TA lists, then the TAU traffic level should tend to be relatively low, but the paging traffic level should tend to be relatively higher. Particularly, the larger the number of TAs in the list, the more likely the UE will stay within the area covered by the TAs in its TA list. Therefore, it will need to perform TAUs less often. On the other hand, if the TA lists are kept relatively smaller, then there should be greater TAU traffic, but lesser paging traffic. Particularly, if a UE's TA list is small, then it is relatively more likely to leave the area covered by the TAs in the TA list, and, therefore, will need to perform TAUs more often. Further, because the number of TAs in the list is small, every time the UE is paged by the network, there are fewer TAs in which it potentially must be paged before it is located, thus tending to reduce paging traffic. [0010] Prior generation wireless network technologies such as GSM (Global System for Mobile communication) utilized static routing area or location area management mechanisms, which presented a complex offline network design problem. Furthermore, even if well-engineered at the time of network design, changing network mobility characteristics over time during the operating lifetime of the network could quickly render the network design less than optimal for the given usage of the network. In addition, such static tracking area management mechanisms cannot be adapted to produce the optimal signaling load results for each individual UE. Therefore, regardless of changes in network mobility characteristics, the performance of a static tracking area management mechanism is still inferior to a dynamic tracking area management approach such as enabled by LTE. Summary of the Invention [0011] In accordance with the invention, an MME keeps track of the network tracking mobility characteristic by periodically updating a TA transition probability matrix, which is derived from a global table that maintains data of UE movement in the network by noting the current TA and most recently known previous TA of each UE for every TAU event and paging event. The MME also maintains data as to the number of paging events and TAUs performed by each UE and stores a paging ratio (the ratio of pages versus TAUs) for each UE. The UE characteristics, UE paging ratio, and network mobility characteristic are utilized in an algorithm that constructs a TA list for each UE designed to minimize the total traffic cost function for paging events and TAU events for that UE and for the overall network. Optionally, the TA list for each EU may be constrained to meet certain minimum performance characteristics such as a predetermined paging success rate target and/or a predetermined delay bound target. Brief Description of the Drawings [0012] Figure 1 is a conceptual diagram of a LTE network comprising a plurality of tracking areas. [0013] Figure 2 is a diagram illustrating a transition probability matrix, M, in accordance with the principals of the present invention. [0014] Figure 3 is a diagram illustrating a row-wise normalized version, P, of the transition probability matrix, M. [0015] Figure 4 is a diagram illustrating a further modified version, Q, of the transition probability matrix, M. [0016] Figure 5 is a graph illustrating how the cost function, L1, normally changes as a function of the number of TAs in the TA list, ni, in accordance with the principles of the present invention. [0017] Figure 6 is a flow chart illustrating operation in accordance with one embodiment of the present invention. Detailed Description of the Embodiments [0018] Figure 1 is a basic diagram of an exemplary LTE network comprising twelve eNBs 1041 -10412, each having an approximately circular coverage zone (or cell) 1021 - 10212 surrounding it. As is typical, there is some overlap between the cells so that users can travel between cells without a loss of service or drop in quality of service. The network further comprises an MME 112 in communication with the eNBs. Of course, there are many other components to the network system 100. However, the Figure illustrates only the components most significant to the discussion herein. Furthermore, the communication links between the MME and each of the eNBs is abbreviated in the Figure so as not to obfuscate the illustration. [0019] In any event, each eNB 1041 -10412 can communicate with the MME 112 in order to exchange network management information, including information such as tracking area lists, UE locations, etc. For purposes of simplifying this discussion, we shall assume that each zone 1021 - 10212 corresponding to an eNB 1041 - 10412 is a tracking area (TA). However, as previously noted, the invention can be applied in a network in which the tracking areas comprised multiple eNBs 104. [0020] As noted above, in an LTE network, each UE maintains a TA list comprised of one or more TAs in which it is registered. Furthermore, each time it enters a TA not in its TA list, it executes a TAU. [0021] In accordance with the present invention, the MME maintains in a computer memory a transition probability matrix, such as transition probability matrix, M, illustrated in Figure 2, a normalized transition probability matrix, such as normalized transition probability matrix P illustrated in Figure 3 and an ordered transition probability matrix, such as ordered transition probability matrix Q illustrated in Figure 4. Particularly, the transition probability matrix, M, comprises a sum of the tracking area management events count in the network. The tracking area management events, for instance, are paging events and tracking area update TAU) events. The table is updated at predetermined intervals, such as every week. The value in each cell of the matrix M corresponds to the number of UEs that have changed location from the TA represented by the corresponding row number (the most recent previous TA) to a new TA represented by the corresponding column number (the present TA). These numbers, for instance, may represent the combined sum of UE-initiated TAUs and MME initiated UE pages. For example, according to the table, 187 UEs have moved from network cell 1026 to network cell 1022,213 UEs have moved from cell1028 to cell 1023, 0 UEs have moved from cell area 1025 to cell area 1028, etc. [0022] This matrix may be generated anew each interval based only on the TA tracking area management events occurring since the last update interval or may comprise a moving window compilation of data, including both the new data and the data from a predetermined number of previous intervals. The network operator may select whichever scheme it believes is likely to provide data that is better predictive of future movement of the UEs in that particular network. It may be desirable to apply an exponential weighting factor, A, where A is between 0 and 1 in order to keep the numbers from becoming unnecessarily large, especially if the moving window scheme is elected, since the events counts may get rather large. [0023] Generally, A should be chosen to be close to 0 when data suggests slow time varying network mobility characteristics and should be set close to 1 when data suggests fast time varying mobility characteristics in a network. Hence, assuming the use of an exponential weighting factor, the exponential weighted values filled into the cells of the transition probability matrix M can be expressed as mg(t) = hig(t)+{l-X}n9(t-V) where0 and having no constraint on average paging success rate. [0053] Thus, as one moves from left to right in any row i of matrix Q, the last row for which equation 16 is true yields not only the desired TA list size for a particular UE, i.e., ni, but also the specific TAs that comprise the list, i.e., the TAs corresponding to columns j=1 to column j = rij of row i. [0054] Figure 6 is a flow chart illustrating operation to construct a TA list for a UE in a given TA for the following conditions: (1) paging strategy 1, (2) Dmax set to one retry, and (3) no minimum average paging success rate constraint. This flow chart represents the process in determining the number of TAs in the TA list as well as the specific TAs to put in that list for a single UE. The process would be performed for each UE in the network as indicated. [0055] The MME starts the process at step 301. In step 303, the MME initializes the matrices M, P, Q, and V to zero. It also will need for purposes of the procedure, values for (1) the paging ratio, g, (2) the paging success rate, r, (3) the weighting factor p, for weighting the real time cost of a TAU event as compared to a paging event, and (4) the number, N, of TAs in the network served by the MME. The values of 0 and N generally are fixed values as they typically only change when the operator reconfigures the network. However, g and r change over time and should be calculated at each interval by the MME. Each UE will have a unique g. Merely as a few examples, initialization of the matrices and other parameters, i.e., steps 301 and 303, may be performed (1) at predetermined intervals during the operation of the network (e.g., once a week or once a month), (2) only upon start up of the network and upon the occurrence of special events (e.g., the Olympics are being held in the locality serviced by the network), or (3) only once upon start up of the network (e.g., especially if an exponential weighting function is employed) [0056] Next, in step 305 it is determined if it is time to perform the next update of the TA lists of a UE. The update instance can be virtually anything. Typically, whenever the MME receives a TAU event from a UE, it will update that UE's TA list. So each TAU performed by a UE would trigger such an instance. However, the MME also may update the TA lists of UEs responsive to other criteria, such as (1) the expiration of some period since the last TA list update for that UE, (2) a predetermined time at which all UEs are updated, (3) special occasions, etc. In any event, whatever the triggering instances are, if one has not occurred, the system simply waits for one to occur. When a triggering instance occurs,, flow proceeds to step 307, where all tracking area management event data (e.g., TAUs and pages) since the last update are factored in to update the matrices M and P as well as the paging ratio g for that UE. [0057] Next, in step 309, the MME finds the TA in which the UE is located, TAicu[Tent-In step 311, the row of each of matrices Q and V is updated. Particularly, values for Mi current, j and vLcurrentj are calculated for j = 1,2,..., N. [0058] With the row i of the matrix Q corresponding to the selected TA now updated, the TA list to use for the UEs in this TA can be determined. Thus, in step 313, the column number j is set to 1, which guarantees that the TA list will include the selected TA itself (since, according to the definition of matrix Q, the first column of matrix Q corresponds to the same TA, TAj_current)- Next, in step 315, j is set to j + 1. [0059] In step 317, the value for qicurrentj (as determined in step 311) is compared to the value generated by Equation 16. If qicurrent, j is greater than or equal to that value, it means that Lj as a function of the number of TAs in the TA list, ni, is still decreasing and, therefore, the TA corresponding to column j in row icurrent of the matrix Q should be added to the TA list. Specifically, because the columns in row i of matrix Q are arranged in descending order by likelihood of finding a UE previously found in TAuamem in TAj, we can simply add the TAs corresponding to the columns in row i_current of matrix Q to the TA list in order from left to right. Accordingly, flow will proceed from step 317 to step 319 where the TA that corresponds to qicurrentj is added to the TA list for the TAicurrent- On the other hand, if qicurrent, j is less than the value calculated by Equation 16, then the cost function Lj is increasing as a function of adding more TAs to the TA list, which means that the TA list is finished and flow would instead proceed from step 317 back to step 305 to await the next updating instance. [0060] Returning to step 319, when the TA corresponding to qicurrent, j is added to the list in step 319, flow proceeds to step 321 where it is determined if the last column of a row i_current has been reached. If not, flow returns through steps 315-319 to determine if another TA should be added to the TA list. If so, the TA list is finished and flow returns to step 305 to await the next update instance to occur [0061] The scheme described herein can be implemented at the MME and requires no assistance from other nodes (except for the receipt of the traffic data and the transmission of the TA lists to the other nodes of the network). Furthermore, the algorithm itself is computationally simple with low memory requirements, which, when combined with the reduced signaling traffic level achievable, implies an even greater capacity improvement for the MME. [0062] Furthermore, while the invention has been described in connection with a 3GPP LTE network, the principles set forth herein are applicable to any network comprising a plurality of sub-areas in which a mobile node may be paged by a base node. [0063] The processes described above may be implemented by any reasonable circuitry, including, but not limited to, computers, processors, microprocessors, digital signal processors, state machines, software, firmware, hardware, analog circuits, digital circuits, field programmable gate arrays, combinational logic circuitry, or any combination of the above, including a computer or other processor running software stored on any computer readable medium, including, but not limited to, compact disc, digital versatile disk, RAM, ROM, PROM, EPROM, EEPROM, and magnetic tape. The data to be stored at the MME or elsewhere in accordance with this invention may be stored in any reasonable computer memory, including any of the aforementioned forms of computer memory. [0064] The flow could be largely the same for other paging strategies and/or constrains, except that the equation in step 317 would need to be modified in accordance with the particular paging strategy and/or constraints. [0065] Having thus described a few particular embodiments of the invention, alterations, modifications, and improvements will readily occur to those skilled in the art. Such alterations, modifications, and improvements as are made obvious by this disclosure are intended to be part of this description though not expressly stated herein, and are intended to be within the spirit and scope of the invention. Accordingly, the foregoing description is by way of example only and not limited. The invention is limited only as defined in the following claims and equivalents thereto. CLAIMS 1. A method of building a tracking area list for a user equipment in a network having a plurality of tracking areas and a plurality of user equipments capable of being moved between tracking areas of the network, comprising: maintaining in a computer memory data disclosing a frequency of tracking area management events of user equipments between every pair of tracking areas of the network over a time period, the tracking area management events comprising paging events and tracking area update events; receiving relative cost data of a paging event relative to a tracking area update event in the network; determining, using a processor, a ratio of paging events to tracking area update events in the network for at least one user equipment; predicting, using a processor, based on the frequency data, the relative cost data, and the ratio, a number of tracking areas, n, to include in a tracking area list for the at least one user equipment, which number predictively reduces a sum cost of paging events and tracking area update events in the network; and constructing, using a processor, a tracking area list for the at least one user equipment having n tracking areas. 2. The method of claim 1 wherein the predicting comprises calculating the number, n, of tracking areas to include in the tracking area list separately for each individual user equipment. 3. The method of claim 2 wherein the network further comprises a Mobility Management Entity (MME) and wherein the maintaining, determining the ratio, predicting, and constructing are performed at the MME. 4. The method of claim 2 wherein the constructing comprises, for each individual user equipment, placing in the tracking area list at least the n-1 tracking areas having the highest frequency of tracking area management events from the tracking area in which the corresponding user equipment is currently located to another tracking area. 5. The method of claim 4 wherein the constructing further comprises, for each individual user equipment, placing the individual tracking area in its own tracking area list. 6. The method of claim 5 wherein the constructing comprises: building a matrix comprising N rows and N columns, wherein N is the number of tracking areas in the network, each row corresponding to a previous tracking area in which a user equipment was located and each column corresponding to a current tracking area in which a user equipment is located; placing in each cell of the matrix a value corresponding to a number of tracking area management events of user equipment from the tracking area of the corresponding row to the tracking area of the corresponding column; ordering each row so that the column corresponding to the same tracking area as the tracking area to which the row corresponds is first and is followed by all other columns in descending order as a function of the values in the cells of the matrix. 7. The method of claim 6 wherein the constructing comprises placing in each tracking area list the tracking areas corresponding to the first n columns of the row corresponding to the tracking area in which the corresponding user equipment is currently located. 8. The method of claim 2 wherein the calculating the number n comprises, for each user equipment, determining the number of tracking areas i that yields the lowest value for Lj using the equation : where P is the relative cost of a paging event to a tracking area update event; i is the individual tracking area in which the corresponding user equipment is currently located; j is a tracking area to which user equipment may transition from tracking area i; N is the number of tracking areas of the network; NTAU, i is a traffic cost function of tracking area update events for the corresopnding user equipment as a function of n,; and Npage, i is a traffic cost function of paging events for individual tracking area i. 9. The method of claim 6 wherein the calculating the number n for each individual user equipment comprises determining the number of tracking areas i that yields the lowest value for Li in the equation : where (3 is the relative cost of a paging event to a tracking area update event; i is the individual tracking area in which the corresponding user equipment is currently located; j is a tracking area to which user equipment may transition from individual tracking area i; N is the number of tracking areas of the network; NTAU, I is a traffic cost function of tracking area update events for the corresponding user equipment as a function of n*; and Npage, i is a traffic cost function of paging events for individual tracking area i; where g is the ratio of a number of paging events to a number of tracking area update events for the corresponding user equipment; and qy is the data disclosing the frequency of tracking area management events from tracking area i to tracking area j, where tracking area j is the tracking area corresponding to the j* column of row i of the matrix. 10. The method of claim 9 wherein calculating the number n for each individual user equipment further comprises selecting the value n for which Li is the lowest value that maintains a predetermined paging success ratio. 11. The method of claim 9 wherein Npage, i is a function of a particular paging strategy used in the network. 12. The method of claim 9 wherein Npage, i is selected from the set comprising: where r is a predetermined paging success ratio; and qimj is the data disclosing the frequency of tracking area management events from tracking area i to tracking area m, where tracking area m is the tracking area corresponding to the m"1 column of row i of the matrix. 13. The method of claim 12 wherein the frequency data is occasionally reset to zero. 14. The method of claim 12 wherein the frequency data is exponentially weighted. 15. A method, in a network comprising a plurality of base nodes and a plurality of mobile nodes capable of being moved between a plurality of sub-areas of the network, of determining a collection of sub-areas of a network in which to perform primary paging of mobile network nodes so as to reduce the sum cost of mobile node sub-area management events in the network, the method comprising: receiving from at least one of the base nodes and the mobile nodes data disclosing a frequency of sub-area management events of mobile nodes between every pair of sub-areas of the network, the sub-area management events comprising paging events, in which one or more stationary nodes page a mobile node, and tracking area update events, in which a mobile node informs a stationary node of its location; receiving relative cost data of a paging event relative to a sub-area update event in the network; determining, using a processor, a ratio of paging events to tracking area update events for each mobile node; for each mobile node, predicting, using a processor, based on the frequency data, the relative cost data, and the ratio data, a number of sub-areas, n, to include in a sub-area list for each mobile node, the sub-area list comprising a list of sub-areas to page when a base station pages a mobile node, which number predictively reduces a sum cost of paging events and tracking area update events in the network; and constructing, using a processor, a sub-area list having n tracking areas for each mobile node. 16. The method of claim 15 wherein the constructing comprises, for each mobile node, placing in the sub-area list at least the n-1 tracking areas having the highest frequency of sub-area management events from the individual sub-area to another sub-area. 17. The method of claim 16 wherein the constructing further comprises, for each mobile node, placing the individual sub-area in its own sub-area list. 18. The method of claim 17 wherein the constructing comprises: building a matrix comprising N rows and N columns, wherein N is the number of sub-areas in the network, each row corresponding to a previous sub-area in which a mobile node was located and each column corresponding to a current sub-area in which a mobile node is located; placing in each cell of the matrix a value corresponding to a number of sub-area management events of mobile nodes from the sub-area of the corresponding row to the sub-area of the corresponding column; ordering each row so that the column corresponding to the same sub-area as the sub-area to which the row corresponds is first and is followed by all other columns in descending order as a function of the values in the cells of the matrix. 19. The method of claim 18 wherein the constructing the sub-area lists comprises placing in each sub-area list the sub-areas corresponding to the first n columns of the row corresponding to the individual sub-area in which the corresponding mobile node is currently located. 20. The method of claim 18 wherein calculating the number n for each individual sub-area comprises, for each individual sub-area, determining the number of sub-areas i that yields the lowest value for Li in the equation : where P is the relative cost of a paging event relative to a sub-area update event in the network; i is the individual sub-area in which the corresponding mobile node is currently located; j is a sub-area to which user equipment may transition from individual sub-area i; N is the number of sub-areas of the network; NTAU, I is a traffic cost function of sub-area update events for the corresponding mobile node as a function of n,; and Npage, i is a traffic cost function of paging events for individual sub-area i; where g is the ratio of a number of paging events to a number of sub-area update events for the corresponding mobile node; and qij is the data disclosing the frequency of sub-area management events from sub-area i to sub-area j, where sub-area j is the sub-area corresponding to the j* column of now i of the matrix. 21. A computer program product embodied on a computer readable medium for building a tracking area list in a network having a plurality of tracking areas and a plurality of user equipments capable of being moved between tracking areas of the network comprising: computer executable instructions for maintaining data disclosing a frequency of tracking area management events of user equipment between every pair of tracking areas of the network over a time period, the tracking area management events comprising paging events and tracking area update events; computer executable instructions for determining a ratio of paging events to tracking area update events for at least one user equipment; computer executable instructions for predicting, based on the frequency data, a relative cost of a paging event relative to a tracking area update event in the network; and the ratio data, a number of tracking areas, n, to include in a tracking area list for the at least one user equipment, which number predictively reduces a sum cost of paging events and tracking area update events in the network; and computer executable instructions for constructing a tracking area list for the at least one user equipment having n tracking areas. 22. The computer program product of claim 21 wherein the computer executable instructions for constructing comprises computer executable instructions for placing in the tracking area list at least the n-1 tracking areas having the highest frequency of tracking area management events from the tracking area in which the at least one user equipment is currently located to another tracking area. 23. The computer program product of claim 22 wherein the computer executable instructions for constructing further comprises computer executable instructions for placing the tracking area in which the at least one user equipment is currently located in its own tracking area list. 24. The computer program product of claim 22 wherein the computer executable instructions for constructing comprises: computer executable instructions for building a matrix comprising N rows and N columns, wherein N is the number of tracking areas in the network, each row corresponding to a previous tracking area in which a user equipment was located and each column corresponding to a current tracking area in which a user equipment is located; computer executable instructions for placing in each cell of the matrix a value corresponding to a number of tracking area management events of user equipment from the tracking area of the corresponding row to the tracking area of the corresponding column; computer executable instructions for ordering each row so that the column corresponding to the same tracking area as the tracking area to which the row corresponds is first and is followed by all other columns in descending order as a function of the values in the cells of the matrix. 25. The computer program product of claim 24 wherein the computer executable instructions for constructing comprises computer executable instructions for placing in the tracking area list the tracking areas corresponding to the first n columns of the row corresponding to the individual tracking area. 26. The computer program product of claim 21 wherein the computer executable instructions for calculating the number n comprises computer executable instructions for determining the number of tracking areas i that yields the lowest value for U for the at least one user equipment, using the equation : where B is the relative cost of a paging event relative to a tracking area update event in the network;; i is the individual tracking area in which the at least one user equipment is currently located; j is a tracking area to which user equipment may transition from individual tracking area i; N is the number of tracking areas of the network; NTAU,I is a traffic cost function of tracking area update events for user equipment in tracking area i as a function of ni; and Npage, i is a traffic cost function of paging events for individual tracking area i. 27. The computer program product of claim 24 wherein the computer executable instructions for calculating the number n comprises computer executable instructions for determining the number of tracking areas i that yields the lowest value for Li in the equation: where B is the relative cost of a paging event relative to a tracking area update event in the network; i is the individual tracking area; j is a tracking area to which user equipment may transition from individual tracking area i; N is the number of tracking areas of the network; NTAU, i is a traffic cost function of tracking area update events for user equipment in tracking area i as a function of ni; and NPage, i is a traffic cost function of paging events for individual tracking area i; where g is the ratio of a number of paging events to a number of tracking area update events for the at least one user equipment; and qij is the data disclosing the frequency of tracking area management events from tracking area i to tracking area j, where tracking area j is the tracking area corresponding to the jth column of row i of the matrix. 28. A Mobility Management Entity (MME) adapted to build tracking area lists for a network having a plurality of tracking areas and a plurality of user equipments capable of being moved between tracking areas of the network, the MME comprising: circuitry for maintaining in a memory data disclosing a frequency of tracking area management events of user equipments between every pair of tracking areas of the network over a time period, the tracking area management events comprising paging events and tracking area update events; circuitry for determining a ratio of paging events to tracking area update events for each user equipment; circuitry for predicting, based on the frequency data, a relative cost of a paging event relative to a tracking area update event in the network, and the ratio data, numbers of tracking areas, n, to include in tracking area lists for each user equipment, which number predictively reduces a sum cost of paging events and tracking area update events; and circuitry for constructing tracking area lists for each user equipment having n tracking areas. 29. The MME of claim 28 wherein the circuitry for constructing comprises circuitry for placing in each tracking area list at least the n-1 tracking areas having the highest frequency of tracking area management events from the tracking area in which the corresponding user equipment is currently located to another tracking area. 30. The MME of claim 29 wherein the circuitry for constructing further comprises circuitry for placing the tracking area in which the corresponding user equipment is currently located in its own tracking area list. 31. The MME of claim 29 wherein the circuitry for constructing comprises: circuitry for building a matrix comprising N rows and N columns, wherein N is the number of tracking areas in the network, each row corresponding to a previous tracking area in which a user equipment was located and each column corresponding to a current tracking area in which a user equipment is located; circuitry for placing in each cell of the matrix a value corresponding to a number of tracking area management events of user equipment from the tracking area of the corresponding row to the tracking area of the corresponding column; circuitry for ordering each row so that the column corresponding to the same tracking area as the tracking area to which the row corresponds is first and is followed by all other columns in descending order as a function of the values in the ceils of the matrix. 32. The MME of claim 31 wherein the circuitry for constructing comprises circuitry for placing in each tracking area list the tracking areas corresponding to the first n columns of the row corresponding to the individual tracking area in which the corresponding user equipment is located. 33. The MME of claim 28 wherein the circuitry for calculating the number n comprises computer executable instructions for determining the number of tracking areas i that yields the lowest value for Li, for the corresponding user equipment, using the equation : where p is the relative cost of a paging event relative to a tracking area update event in the network; i is the individual tracking area in which the corresponding user equipment is currently located; j is a tracking area to which user equipment may transition from individual tracking area i; N is the number of tracking areas of the network; NTAU.I is a traffic cost function of tracking area update events for user equipment in tracking area i as a function of ni; and Npage, i is a traffic cost function of paging events for individual tracking area i. 34. The MME of claim 31 wherein the circuitry for calculating the number n comprises circuitry for determining the number of tracking areas i that yields the lowest value for Li in the equation : where B is the relative cost of a paging event relative to a tracking area update event in the network; i is the individual tracking area; j is a tracking area to which user equipment may transition from individual tracking area i; N is the number of tracking areas of the network; NTAU. i is a traffic cost function of tracking area update events for user equipment in tracking area i as a function of ni; and Npage, i is a traffic cost function of paging events for individual tracking area i; where g is the ratio of a number of paging events to a number of tracking area update events for the corresponding user equipment; and qy is the data disclosing the frequency of tracking area management events from tracking area i to tracking area j,, where tracking area j is the tracking area corresponding to the jth column of row i of the matrix.