Abstract:
Systems and methods of automatically optimizing an operational radio access network are provided. Objective and operational cost functions for the radio access network are generated, and a deviation between the generated cost functions is determined. At least one aspect of the radio access network is adjusted in order to minimize the determined deviation between cost functions.

Description:
BACKGROUND OF THE INVENTION 
       [0001]    Wireless communication networks are very complicated, and expensive to deploy. Prior to deploying a wireless communication network, extensive computer simulations are performed in order to optimize the parameters and placement of networks elements. Computer simulations cannot, however, account for the real-world conditions in which the network is deployed. Accordingly, once a wireless communication network is installed, additional testing is performed in order to account for real-world conditions. Furthermore, as wireless communication networks are expanded with additional base stations to provide additional capacity or coverage, the network must again be tested to optimize the base stations. 
       SUMMARY OF THE INVENTION 
       [0002]    Exemplary embodiments of the present invention are directed to systems and methods of automatically optimizing an operational radio access network using the system&#39;s key performance parameters and desired service outcome. An exemplary method involves receiving information related to operational coverage, capacity and handoffs in a radio access network and generating an operational cost function based on the received information related to operational coverage, capacity and handoffs. Information related to objective coverage, capacity and handoffs in a radio access network is received and an objective cost function based on the received information related to objective coverage, capacity and handoffs is generated. A deviation between the operational and objective cost functions is determined and an aspect of at least one of the operational coverage, capacity and handoffs is automatically adjusted to minimize the determined deviation. 
         [0003]    Other objects, advantages and novel features of the present invention will become apparent from the following detailed description of the invention when considered in conjunction with the accompanying drawings. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWING FIGURES 
         [0004]      FIG. 1  is a block diagram of an exemplary network in accordance with the present invention; 
           [0005]      FIG. 2  is a block diagram of an exemplary service optimizer system in accordance with the present invention; and 
           [0006]      FIG. 3  is a flow diagram of an exemplary method in accordance with the present invention. 
       
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       [0007]      FIG. 1  is a block diagram of an exemplary network in accordance with the present invention. The illustrated network is a WiMAX network that includes a radio access network  105  and a connectivity service network  150 . The radio access network includes a plurality of cells  110   A - 110   n . Each cell includes a plurality of base stations  115   A1 - 115   nx  coupled to an application service node-gateway (ASN-GW)  120   A - 120   n . Each ASN-GW  120   A - 120   n  is coupled to the connectivity service network  150 . 
         [0008]    Connectivity service network  150  includes a home agent  152 , Internet Protocol multimedia system (IMS)  154 , customer relationship manager (CRM)  156 , billing component  158 , authentication, authorization and accounting component  160  and dynamic host control protocol/domain name server (DHCP/DNS)  162 . Additionally, connectivity service network  150  includes service optimizer system (SOS)  164 , which as will be described in more detail below, receives information from ASN-GWs  120   A - 120   n  and provides information back that is used to control the radio access network. Although exemplary embodiments are described in connection with the WiMAX network, the present invention is equally applicable to other types of networks, such as CDMA, GSM, iDEN, EV-DO, EDGE, etc. Furthermore, although  FIG. 1  illustrates a particular number of base stations within each cell and a particular number of cells, the present invention can be employed with a different number of base stations per cell and a different number of cells. 
         [0009]      FIG. 2  is a block diagram of an exemplary service optimizer system  164  in accordance with the present invention. Service optimizer system  164  includes a communication interface  205  for communicating with ASN-GWs  120   A - 120   n , as well as other components of the connectivity service network  150 . Communication interface is coupled to processor  210 , which in turn is coupled to memory  250 . Processor  210  includes logic  212 - 220 , which will be described in more detail below in connection with the method of  FIG. 3 . Processor  210  can be a microprocessor, field programmable gate array (FPGA) and/or application specific integrated circuit (ASIC). When processor  210  is a microprocessor, logic  212 - 220  can be processor-executable code loaded from memory  250 . 
         [0010]      FIG. 3  is a flow diagram of an exemplary method in accordance with the present invention. Initially, service optimizer system  164  receives information related to operational parameters from one or more ASN-GWs  120   A - 120   n  via communication interface  205  (step  305 ). Logic  212  generates an operational cost function using the received information (step  310 ). An exemplary cost function (CF Op ) is 
         [0000]    
       
      
       CF 
       Op 
       =A*X 
       Cov 
       +B*Y 
       Cap 
       +C*Z 
       HO  
      
     
         [0011]    where X Cov  is the coverage function, Y Cap  is the capacity function, Z HO  is a handoff function, and A, B and C are weights that can be adjusted depending upon whether the optimization is being performed during the busy hour or normal operating hours. Thus, the cost function during normal hours is expressed as CF nh  and the cost function during busy hours is expressed as CF bh . 
         [0012]    The Coverage function X Cov  depends on several parameters as follow:
   X Cov =F bh [BTS EIRP, MAP repetition, CINR, Paging Cycle, ARQ Block Size, CPE EIRP, RSSI, user throughput, average sector throughput]   
 
         [0014]    The coverage function includes some parameters that can be adjusted by the network administrator and other parameters that are dependent upon the network environment. The administrator adjustable parameters include BTS EIRP (which is a function of the transmit power minus the cable loss plus the antenna gain), MAP repetition (a constant that can be dynamic), Paging Cycle (a constant that can be dynamic), ARQ Block Size (a constant that can be dynamic), and CPE EIRP (which is a function of the transmit power plus the antenna gain). The environmental dependent parameters include CINR, RSSI, user throughput and average sector throughput. Although particular parameters are described above, the cost function can include a greater or less number of parameters or different parameters. 
         [0015]    The capacity function Y Cap  depends on several parameters as follow:
   Y Cap =F bh [Sleep Timer, Idle Timer, Throughput CAP, ARQ Block Size, CINR, RSSI]   
 
         [0017]    The administrator adjustable parameters include the sleep timer, idle timer, MAP repetition (a constant that can be dynamic) and ARQ block size (a constant that can be dynamic). The environmental-dependent parameters include CINR, RSSI and throughput capacity. Although particular parameters are described above, the cost function can include a greater or less number of parameters or different parameters. 
         [0018]    The HO function Z HO  depends on several parameters as follow:
   Z HO =F bh [HO Delay Timer, Add Threshold, Delete Threshold, Trigger CINR, RSSI, Neighbor List]   
 
         [0020]    The administrator adjustable parameters include handover delay timer, neighbor add threshold, neighbor delete threshold, trigger CINR and neighbor list. The environmental dependent parameters include CINR and RSSI. Although particular parameters are described above, the cost function can include a greater or less number of parameters or different parameters. 
         [0021]    Referring again to  FIGS. 2 and 3 , processor  210  then receives information related to objective parameters (step  315 ) and logic  214  generates an objective cost function using the received information (step  320 ). The objective cost function is as follows: 
         [0000]    
       
      
       CF 
       Obj 
       =A*X 
       Cov 
       +B*Y 
       Cap 
       +C*Z 
       HO  
      
     
         [0022]    The coverage, capacity and handoff functions for the objective cost functions use the same parameters as those described above in connection with the operational cost function, but the data for the parameters is based on objective values. The objective values can be derived by a simulation of the network and/or one or more of the values can be set by a network administrator. 
         [0023]    The objective parameters can be received from memory  250 . Logic  216  then determines a deviation between the operational and objective cost functions (step  325 ) and logic  218  automatically adjusts at least one parameter of the cost functions in order to minimize the deviation (step  330 ). 
         [0024]    The minimization of the deviations of the cost functions can be expressed as [CF Op −CF Obj ] 2 , where the minimized cost function for the busy hour is: 
         [0000]        CF=Σ   i   A   bh   X   i +Σ i   B   bh   Y   i +Σ i   C   bh   Z   i  
 
         [0025]    Accordingly, the minimization of the cost function becomes 
         [0000]    
       
         
           
             
               
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         [0026]    Processor  210  then receives updated information related to the operational parameters that account for the automatic adjustment (step  335 ) and logic  212  generates an updated operational cost function (step  340 ). Logic  216  then determines a deviation between the updated operational cost function and the objective cost function (step  345 ). Logic  220  then determines whether the deviation is minimized (step  350 ). When the deviation is not minimized (“No” path out of decision step  350 ), then the process is immediately repeated. When the deviation is minimized, then the process is repeated after a predetermined delay or an event trigger from the service network (step  355 ). Accordingly, the present invention provides an iterative technique for automatically adjusting parameters of, and in turn performance in, a live radio access network in order to converge the parameters to optimum values. The method of  FIG. 3  can be performed on an entire network basis, and/or on a per sector, cell or location area basis. 
         [0027]    Although the present invention has been described above in connection with particular parameters used in the cost functions, the present invention can use other parameters in addition to, or as an alternative to, those discussed above. These additional parameters can be, for example:
       operational and performance information, including number of radio channels, size of radio channels, transmitted power, coding, modulation;   system statistics, including call admissions, dropped calls/sessions, network entry attempts;   operator parameters, including backhaul capacity, available spectrum, service policy;   geographical information, including ground cover, land use, location of base stations, minimum acceptable service quality; and   historical performance information, including utilization of each of the network resources, faults and alarms indicating service quality issues, number of active and dormant users during each time interval, location of served mobile stations relative to the base station, amount of traffic demand, traffic successfully delivered to the mobile stations.       
 
         [0033]    The foregoing disclosure has been set forth merely to illustrate the invention and is not intended to be limiting. Since modifications of the disclosed embodiments incorporating the spirit and substance of the invention may occur to persons skilled in the art, the invention should be construed to include everything within the scope of the appended claims and equivalents thereof.