FR2880231A1 - Cellular mobile telephone network e.g. CDMA network, resource allocating method for mobile telecommunication terminal, involves assigning optimal value of consumed resources for terminals based on function representing consumed resources - Google Patents

Abstract

The method involves assigning minimal and maximum cellular mobile telephone network resource values for each of mobile telecommunication terminals (T). A function representative of the resources consumed by the terminal is computed for each terminal. An optimal value of consumed resources is assigned for each terminal according to the values of the computed function. Independent claims are also included for the following: (A) an equipment for allocating resources of a cellular mobile telephone network to a set of mobile telecommunication terminals of the network (B) a software module stored on a medium including instruction codes for the execution of a cellular mobile telephone network resource allocating method.

Description

Method and equipment for allocating resources of a cellular network of

  telecommunication for mobile terminals

  The invention generally relates to mobile-type telecommunication networks, and more particularly relates to the allocation of the available resources of a cellular telephone network to mobile terminals of a network telephone.

  By allocation of resources means the provision of the means proposed by the network to allow a terminal located in a cell of the network to exchange data.

  Thus, a particularly advantageous application of the invention relates to the optimal and fair allocation of rates to mobiles of a telecommunication network.

  In fact, telecommunication network operators generally seek to maximize the number of users that can be served by a given network. In CDMA-type telephony networks, for a given user, the other users, in the upstream direction, or the base stations other than those with which it communicates, in the downstream direction, constitute sources of noise which disturb the user. If the number of users becomes too large, the noise increases and causes a drop in quality, or even a blocking of communication. Mobile data rate control can control and limit this noise and thus improve performance.

  It is for these reasons that one of the constant concerns of telecommunication operators is to optimize the management of mobile speeds and optimize the admission of new terminals in the cells so as to maximize the number of terminals in each cell, while ensuring a given quality of service (QoS).

  Generally, the algorithms implemented to control the data rate of the terminals in the cells as well as to control the admission of new terminals are based on the control of the charge level. For example, if the admission of a mobile into a cell causes an increase in the charge level such that the total charge exceeds a given threshold, the incoming mobile is forced to reduce its rate to be admitted. Beyond a certain threshold, all new incoming terminals are rejected.

  Thus, in the state of the art, when the load of a cell is too large to allow the admission of a new terminal, the authorized bit rate for this terminal is reduced, which causes a drop in the quality of service for the incoming terminal. Terminals already in communication are not affected.

  Admission policies for new terminals can be implemented in a variety of ways. For example, it is possible to adapt the flow of the incoming mobile by guaranteeing a given rate. This implementation induces relatively large rejection rates and therefore limits the capacity of the network. It is also possible to adapt the rate of the incoming terminal so as to always admit it, even with a zero flow. This implementation does not guarantee the quality of service (QoS).

  Finally, these various strategies are not optimal, to the extent that it is possible to increase the speed of a mobile without necessarily reducing that of another.

  Thus, conventional flow allocation techniques do not allow to allocate rates to terminals in a network optimally and equitably. They generally do not allow exploring the full range of equitable strategies for dynamic management of mobile bit rates in the network. Nor do they allow the full range of mobile admission management strategies to achieve a rejection rate between extreme values, one for guaranteed quality of service and one for guaranteed quality of service. unsecured quality of service.

  To overcome these drawbacks, it has been proposed to calculate the bit rates allocated to each terminal, when a new terminal enters a cell, so as to maximize a utility function. Various techniques can be used to solve such an equation. Calculation algorithms using Lagrangian relaxation, positive semi-definite programming or linear / whole mixed programming can be used to solve such an equation. Maximizing a utility function to allocate resources to terminals in a network involves the use of additional constraints related to network resources. For example, the resources assigned to users can not be less than the respective minimum threshold values assigned to users. Similarly, they can not be greater than respective maximum threshold values assigned to the users. Finally, the sum of the resources allocated to the users can not be greater than the overall capacity of the system.

  However, known calculation techniques used to maximize the utility function taking into account these constraints all have the disadvantage of being very slow in computing time and limited reliability. However, the use of equations to maximize the utility function while taking into account constraints related to network resources is based on real-time constraints and reliable responses. In practice, it is a matter of determining what will be a new bit rate allocation each time a mobile enters the network, in real time.

  In view of the foregoing, the object of the invention is to make it possible to allocate resources of a telecommunication cellular network to mobile telecommunication terminals located in the network in real time and reliably.

  The subject of the invention is therefore a method for allocating resources of a telecommunication cellular network for a set of mobile telecommunication terminals of the network, according to which the resource is allocated to the terminals so as to maximize a global utility function. developed from a summation of utility functions specific to each user, while satisfying constraints related to network resources made available to users.

  According to a general characteristic of the invention, the method of resource allocation comprises the steps of: - allocation of minimum and maximum resources for each terminal; calculating a function representative of the resources consumed by each terminal; and assigning an optimum value of resources for each terminal from the values of said calculated function.

  In one embodiment, to calculate the function representative of the resources consumed by each terminal, the value of the derivatives of the utility function specific to each user is calculated for each minimum and maximum value; - we sort the calculated values of the derivative of the utility function specific to each user; an interval is sought in which is located a pivot value of the calculated values which corresponds to an optimal value of resource; and, - in the interval sought, the pivot value is calculated, the optimum value assigned to the terminals of the users corresponding to either the minimum resource value or the maximum resource value, or to a value calculated from the pivot value.

  For example, the calculated resource value (Xi) from the pivot value is calculated, for users i for which the pivot value is used to determine the optimal value, from the following relation: = (f'i) - '(p *) where (f';) - 'represents the inverse of the derivative of the utility function and p denotes a real dual coefficient.

  Similarly, for example, the calculated values are sorted by increasing values.

  According to another characteristic of the invention, the constraints related to the resources of the network require that a resource value assigned to a user must be greater than the minimum resource value.

  In addition, network resource constraints dictate that a resource value assigned to a user must be less than the maximum resource value.

  Finally, the sum of resource values assigned to users must be less than the overall capacity of the system.

  According to yet another characteristic of the invention, the representative function of the resources consumed by each terminal is determined from the utility functions of all the users. For example, the function representative of the resource consumed by each user i is given by the relation: cP (y) = + EMi + (f ')' - "(y) in which: lm, corresponds to the sum of the resources allocated to users to whom the minimum resource value is assigned, is the sum of the resources allocated to the users to whom the maximum resource value is assigned; (f ') -' represents the inverse of the utility function derivative f.

  In addition, the pivot value that corresponds to the optimal values of the resources can be given by the relation: p * = [E (fi-1 (C Em, IM,) in which C denotes the global capacity of the network.

  The subject of the invention is also a method for managing the resources of a telecommunication cellular network for a set of mobile telecommunication terminals of the network, characterized in that, at each new terminal entering the network, a detection is carried out overloading a cell of the network and, in the case where one of the cells of the network is overloaded, a resource allocation is carried out by implementing the allocation method as defined above, to accept the incoming terminal .

  According to a third aspect, the invention relates to a resource allocation equipment of a telecommunication cellular network for a set of mobile telecommunication terminals of the network, characterized in that it comprises means for calculating a representative function resources consumed by each terminal and means for allocating an optimal resource value for each terminal from the value of said calculated function.

  Finally, according to a fourth aspect, the invention relates to a software module recorded on a medium, characterized in that it comprises instruction codes for the execution of a resource allocation method as defined. above.

  Such a data medium may be a hardware storage medium, for example a CD-ROM, a magnetic diskette or a hard disk, or a mobile medium such as an electrical, optical or radio signal.

  Other objects, features and advantages of the invention will become apparent on reading the following description, given solely by way of nonlimiting example, and with reference to the appended drawings, in which: FIG. 1 schematically illustrates the architecture of FIG. a telecommunication cellular network implementing a method according to the invention; FIG. 2 is a diagram illustrating the main phases of a resource management method of a cellular network according to the invention; FIG. 3 is a table showing examples of resource values assigned to users; FIG. 4 illustrates the main phases of the flow allocation method according to the invention; FIG. 5 is a table illustrating the calculation of the assigned resource values; and FIGS. 6 and 7 show curves illustrating the evolution of the resources consumed.

  In Figure 1, there is shown the general architecture of a cellular mobile network implementing a resource allocation method according to the invention.

  This method is intended to be applied to the CDMA or W-CDMA type network.

  In this figure, only three cells have been represented, for the sake of clarity.

  As can be seen, the territory to be served is broken down into cells C1, C2, and C3. A cell is linked to a base station BS (or "node B"), which has an antenna for transmitting to terminals, such as T, and receiving signals from them.

  As seen in the figure, the base stations are managed by a radio resource controller or RNC ("Radio Network Controller" in English) that manages the radio interface. In particular, the RNC controller comprises all the hardware and software means and is duly programmed to allocate resources to each terminal of the cells C1, C2 and C3 of the radio subsystem which it manages. For this purpose, it comprises in particular the hardware and software means and is programmed to calculate a function which represents the resources consumed by the terminals of the network and to allocate optimal values of resources, in particular of the bit rate, from this function, as will be discussed later.

  This allocation is an optimal allocation of resources, which results in the renegotiation of the resources allocated to each terminal in order to obtain a maximum resource value for the terminals as it can be used. It is no longer possible to increase the resources allocated to one of the terminals without having to reduce the resources of one or more other terminals.

  For example, it involves renegotiating the flows in order to optimize the capacity of the network.

  According to one characteristic of the invention, the calculation of the resources goes through the maximization of a utility function. In particular, it is a question of maximizing the following function: P f (A 1) (1) It is moreover a question of satisfying the following constraints> 0 di E 11,..., P (2) M; -X ; z 0 di E 11, ..., p (3)

P

  C-; Li z 0 di E 11, ..., p (4) In these relations (1) to (4): -?, Is a variable in the set of positive reals and denotes resources assigned to the user i, - m; is a datum in the set of positive reals and denotes a minimum resource bound assigned to the user i, - M; is a datum in the set of positive reals and denotes a maximum resource bound assigned to the user i, - C is a datum in the set of positive reals and denotes the overall capacity of the system, and - f; is a function of the set of positive reals in the set of positive reals and denotes a utility function associated with the resources for the user i.

  Moreover, in these relations (1) to (4), we suppose that p is a positive integer, that the function f; is a concave function, and that C, m, M, are positive reals for i belonging to (1, ..., p).

  The constraints defined by the relations (2) to (4) impose that a resource assigned to a user must be between a minimum bound m; and a maximum terminal M, and the sum of the resources allocated to the users must remain less than the overall capacity C of the system.

  Thus, with reference to FIG. 2, at each new input of a terminal in a cell of the network (step 10), it is detected whether there exists in the network an overloaded cell (step 12) in a manner known in the art. itself. If this is not the case, the terminal is accepted (step 14).

  On the other hand, if there is an overloaded cell, allocation of the resources of the network is carried out by reallocating the rates of mobiles to the cell (step 16). If, during the next step 18, the calculation of the reallocation of the flows makes it possible to complete, the procedure returns to the previous step 12. In the opposite case, the mobile is refused (step 20).

  We will now describe the procedure for allocation of resources to the terminal, when a cell is overloaded.

  As indicated above, the overloading of a cell can be detected during the admission of a mobile, that is to say, in general, when a terminal enters a cell, for example when the establishment of a call or when passing a terminal from one cell to another.

  This resource allocation procedure is implemented within the base station controller which comprises all the appropriate hardware and software means to implement this procedure.

  Such a procedure consists in calculating a new rate value for the terminals of the cell in order to maximize the following global utility function F F = J (2) which corresponds to the sum of the functions of utilities f1 (21) affected to each user i.

  These functions of individual utilities f; characterize economic or private interests to receive, for a user i, a resource X,. Thus, the global utility function makes it possible to take into account all the users.

  However, this procedure requires above all compliance with the aforementioned constraints related to the operation of the cell. In particular, it is therefore necessary to check that the load of each station, in particular that of the station in which the mobile enters, does not exceed a maximum permissible load. Moreover, the power demanded at a set of base stations, in particular at the station of the cell in which the mobile enters, must not exceed a maximum permissible power. Finally, the sum of resources allocated to users must not exceed the overall capacity of the system.

  Thus, the constraints to be satisfied correspond to the relations (2) to (4) mentioned above.

  Note that, in a cell, each user receives a bounded resource X according to the values of the table of FIG. 3. In other words, each resource value X is between the threshold values m; and M;. In the set of embodiments considered, a utility coefficient (3) is allocated to each user for calculating the utility function f; (x), for example, in the case illustrated in the table of FIG. , the total capacity C of the system is equal to 100. Before the arrival of the user 4, the cell is not saturated and each mobile i receives its maximum flow demand M;

  We will now describe, with reference to Figure 4, the resource allocation procedure implemented in step 16 previously mentioned. This procedure consists first of all in assigning to each user i a utility function f, and values of the minimum and maximum resources m, and M, (step 22). In particular, the utility function f; can be expressed as: fi (x) = x'-a 1 a where a denotes a strictly positive real coefficient different from 1.

  The value of the derivative of the utility function is then calculated for the values m; and M; for each user i (step 24).

  In the next step 26, the values calculated in the preceding step 24 are sorted by increasing values.

  For this purpose, a conventional fast sorting algorithm is used to obtain the sorted list of values. A list is obtained which gives for each k belonging to the interval 11, ..., 2p the following information on the k-th value: Users (k) = i Terminal (k) = m; or M; Value (k) = f '; (Terminal (k)).

  We will have Value (1) s Value (2) s ... s Value (2p) and for each user i, there are two values k, <k2 with User (kl) = User (k2) = i, Terminal (kl ) = M; and Bound (k2) = m ;. Note in this case Debut (i) = (k1) and End (i) = (k2).

  In the next step 28, the interval of the pivot value is determined, which corresponds to an optimum value of the flow rates. This value corresponds almost to a value that is used for value for money and gives a global index of user satisfaction. It is calculated based on the capacity that can be provided to the users.

  To locate the interval of the pivot value we use the previous list and we search by dichotomy. We then assign the values Low: = 1 and High: = 2p, and we apply the following algorithm: 12 (5) 2880231 13 As long as High Low> 1 Medium: = (High + Low) / 2 Phi: = 0 all users i If Start (i)> Middle phi: = phi + Mi If End (i) <Middle phi: = phi + mi If Debut (i) Middle and End (i) z Middle phi: = phi + (f 'i)' '(Medium) If phi z C then Low: = Medium if not High: = Middle Outputs are set to High and Low, with High-Low = 1 and High, Low in range 1 , ..., 2p In the following step 30, the actual value of the pivot value p is calculated from the relation p * _ 'tJi' (Rest) where (6) The value Rest is in particular calculated from the following algorithm: Rest: = C For all users i If Start (i)> Low Remain: = Rest - Mi If End (i) <High Remain: = Remain -mi 4, then designate the sum of functions (fi ')' for i satisfying Start (i) s Low and End (i) z High.

  Finally, the calculated values are assigned (step 31).

  For each user i, the value of resources assigned to it is given by: If Debut (i)> Low, then X; : = M; If Fin (i) <High, then X; : = m; Otherwise, X; : = (f ';) - 1 (p *).

   c Or p * = [(f?) 1] (C-1m, i I M,) As will now be demonstrated later, the resources allocated to the users thus calculated constitute an optimal resource allocation solution.

  Suppose that the functions f ;, for i included in the interval 1,

  ., p are strictly concave, that the constraint p C z 0 is checked at equality by an optimal solution, and that the function f '; is computable in one operation. Suppose we can calculate the inverse of any sum of inverses of f '; for i included in the interval 11, ..., p in M operations. Then the resources, that is to say the solution to relations (1) to (4), are computable in M + O (p log (p)), where O denotes the Landau notation ... DTD: By application of the conditions of Kuhn-Tucker, we obtain, for the optimal solution To; for i belonging to the interval 11, p and the positive real coefficients duaux p; v; for i included in 11, ..., petp, f '(Xr), + v, + p = 0 Life 11, ..., pv; (M;,, *) = 0 d; E 11, .. For each i in the range 1, ..., p, three cases may occur.

  1)); = Mi. In this case v; = O. Therefore - f '(.) + P = 0, which gives f' (;) p. 2)); = Mi. In this case; = 0. Therefore - f '(Ai) + v; + p = 0, which gives f '(2) z p. 3)? E m, M. We then have v; = 0 and; = 0, ie f '(Ai) = p In other words, if f' is strictly decreasing and continuous with i belonging to the interval 1, ..., it is invertible and, at each real value of p, we can associate a "consumed" capacity defined by cp (P) m; +) M; + (f) -1 (P) É (7) i: p> (m;) i: p <(M;) i: f '(M) sp f (m;) As we understand it, cp is a decreasing function of p. An optimal solution is then given by a value p * which satisfies: cp (p *) = C. (8) The algorithm for calculating the solution to relations (1) to (4) above can be performed as follows .

  Let X = {m;, ... mp} U {M ,, ... Mp}. We have 2p. We first calculate all the values from the relation: Y = {f '(x), x E X}.

  The set Y is then sorted. This sorting is done in O (p log (p)) operations. We then reason by dichotomy on Y. For a value y EY, one computes cp (y) in 0 (p) operations, and in O (log (p)) stages one finds two consecutive values y, <y2, such that cp (y,) zC and cp (y2) <C In limiting cases, y2 is 0, where y is infinite.

  If cp (y,) = C, then the equation p * = y, gives a solution. Otherwise, the network resources consumed by a user i are given by Vy E _Y1, Y2 [q7 (Y) = mi + Mi + (f 1 (Y) i: Y> (m1), y, (Mr) i: .ft (Mi) sY, <Yzsf '(mr) The pivot value p * is then given by the following relation: p * = (f') - il (C miMil. (9) i: f, (M, y1 <Yzsff '(ml) \ i: Yz> fi (m,) t: Y, <fi (M,) The utility function fi (x) assigned to users can be of various forms.

  In the case where fi (x) = 1 a, for a E] 0; 1 [U] 1, + oo [, then 1 the resource allocation is computable in O (plog (p)).

  In this case, f '(x) = f2, x-a and f, · l -1 (y) = -1 y-11a. Therefore, for JE {1, ..., p} if we put r (Y) = fi y), then 1E] then 20., '(X) _ _, x For J given, this function is computable in 0 ( p) operations.

  In the case where fi (x) = ln (x), then the resource allocation is computable in O (p log (p)).

  In this case, f '(x) = x and fi-1 (y) = -. So, for JE {1, ... p}, if we put PJ (Y) = fy 1 (Y) iEJ then IJIx Finally, if fi (x) = (3; x, then the solution is computable in 10 O (p log (p)).

  In this case, f '(x) = (3 ;. By reasoning similarly to the result above, consider Y = {(3;: i E {1, ..., p}}, and (Y; ) = mi + Mi i: Y> Pi i: Ysfi, cp is a descending step function We search for two consecutive values y, and Y2 of Y, such that y, <y2, with cp (yl) zC and cp (y2 ) <C. In this case, an optimal resource X., is given by: mi if / 3i <y, Mi mi + (Mi mi) Mi mi i: / Ji Yh if pi 'Y, if / 3i = y1 De Concretely, and referring now to FIGS. 5x1-a to 7, we first consider the case where f1 (x) = ', for a = 1/2, 1 a f' (x) _ J The calculation of the optimal resource values is done, as indicated previously, in several steps.

  It is first necessary to calculate the value of the utility function derivative for each minimum value and each maximum value of resources, and for each user i. The values in this table are then obtained in O (p log (p)), and we obtain: f4 (M4) = f3 (M3) <f '(M1 ) <f4 (m4) = f3 (m3) <J11 (mi) <f2 (M2) <f2 (m2).

  The function cp is described as follows: for x E [0.91; 1.58] for x E [1.58; 2.24] for x E [2.24; 3.16] for x E [3.16; 4.47] for x E [4.47; 8.94] cp (x) = 60 + 50 / x 2; cp (x) = 20 + 150 / x 2; cp (x) = 30 + 100 / x 2; cp (x) = 40; and cp (x) = 20 + 400 / x 2.

  This function is represented in FIG. 6. It is a question of locating the position where cp (x) = 100.

  The pivot value is then in the range [0.91, 1.58], where the function cp is given by cp (x) = 60 + 50 / x2, giving a pivot for 25 x = 0.73. The bit rates obtained will therefore reduce the users 3 and 4 to the common value of 20.

  Similarly, referring again to FIG. 5, in the case where f1 (x) = 1n (x), the calculated values for f 'are as follows: f11 (M1) <f3 (M3 ) = f4 (M4) <f21 (M2) <f '(m1) <f2 (m2) = f31 (m3) = f4 (m4).

  The function cp, plotted in FIG. 7, is described as follows: for x E [0.025; 0.033] cp (x) = 80 + 1 / x; for x E [0.033; 0.050] cp (x) = 20 + 3 / x; for x E [0.050; 0.100] cp (x) = 4 / x; and for x E [0.100; 0.200] cp (x) = 10 + 3 / x, which gives a range for the pivot value of [0.033; 0, 050], and a final value of 0.0375.

  Finally, if f; (x) = m; x, the values of f 'can be sorted as follows: f3 (m3) = f3 (M3) = f> 14) = f4 (M4) <J 1, \ m7) = f '(M1) <f2 (m2) = f2 M2E The function cp (x) is then a function constant at intervals given by: for x E [5; 10] cp (x) = 70; and for x E [10; 20] cp (x) = 40, the pivot value is then in the range of [5; 10]. 10

Claims (13)

  A method for allocating resources of a telecommunication cellular network (C 1, C 2, C 3) for a set of mobile telecommunication terminals (T) of the network, the resources being allocated to the terminals so as to maximize a function of global utility corresponding to a sum of utility functions specific to each user, while satisfying constraints related to the network resources made available to the users, characterized in that it comprises the steps of: - assignment of the resource values minimum and maximum for each terminal (T); calculating a function representative of the resources consumed by each terminal; and - assigning an optimum value of resources for each terminal from the values of said calculated function.   2. Method according to claim 1, characterized in that it comprises the steps of: calculating the values of the derivative of the utility function specific to each user for each minimum and maximum value; sorting the calculated values of the derivative of the utility function specific to each user; searching for the interval in which a pivot value of the calculated values is located which corresponds to an optimal value of resource; and calculating, in the sought interval, the pivot value, the optimal value assigned to the terminals of the user corresponding to either the minimum resource value or the maximum resource value, or to a value calculated from the pivot value.   3. Method according to claim 2, characterized in that the calculated resource value (?) From the pivot value is calculated, for the users i for which the pivot value is used to determine the optimal value, from the following relation: k; = (f) - p), where (f ') -' represents the inverse of the derivative of the utility function and p * denotes a real dual coefficient.   4. Method according to one of claims 2 and 3, characterized in that the calculated values are sorted by increasing values.   5. Method according to any one of claims 1 to 4, characterized in that the constraints related to network resources require that a resource value assigned to a user must be greater than the minimum resource value.   6. Method according to any one of claims 1 to 5, characterized in that the constraints related to network resources require that a resource value assigned to a user must be less than the maximum resource value.   7. Method according to any one of claims 1 to 6, characterized in that the sum of the resource values assigned to the users must be less than the overall capacity of the system.   8. Method according to any one of claims 1 to 7, characterized in that the function representative of the resources consumed by each terminal is determined from the utility functions of all users.   9. Method according to claim 8, characterized in that the function cp (y) representative of the resource consumed by each user i is given by the relation: cp (y) = 1mi + + (f ';) c- (y ) where: is the sum of the resources assigned to users to whom the minimum resource value is assigned; ENI, is the sum of resources assigned to users who are assigned the maximum resource value; and (f ') -' represents the inverse of the derivative of the utility function f ;.   10. Method according to claim 9, characterized in that the pivot value which corresponds to the optimal values of the resources is given by the relation: p * = [s (f)) - 'T' C gym, M1) in whichJJC designates the overall capacity of the network.   11. A method for managing the resources of a telecommunication cellular network (C1, C2, C3) for a set of mobile telecommunications terminals (T) of the network, characterized in that at each new terminal entering the network, one performs an overload detection of a cell of the network and, in the case where one of the cells of the network is overloaded, a resource allocation is carried out by implementing the allocation method according to any one of the Claims 1 to 9 for accepting the incoming terminal.   12. Equipment for allocating the resources of a cellular telecommunication network for a set of mobile telecommunication terminals of the network, characterized in that it comprises means for calculating a function representative of the resources consumed by each terminal and means for assigning an optimum resource value for each terminal from the value of said calculated function.   13. Software module recorded on a medium, characterized in that it comprises instruction codes for the execution of a resource allocation method according to any one of claims 1 to 11.