Abstract:
WI-FI/3GPP access selection techniques are used to control selection by a user terminal between cellular network cells and WI-FI cells. Cellular network cells providing overlapping coverage with WI-FI cells are correlated with the WI-FI cells. A received signal strength threshold is determined for each WI-FI cell based on an average throughput of the cellular network cells correlated with the WI-FI cell. The WI-FI user terminal admit threshold is used to control the effective coverage of the WI-FI cell. A user terminal operating within a cellular network cell is admitted to a WI-FI only if it is within the effective coverage area of the WI-FI cell as determined by the received signal strength threshold. Increasing the threshold shrinks the effective coverage area of the WI-FI cell to allow user terminal only of strong RSSI to make connection to the cell, and steers user terminal of weak RSSI away from the WI-FI cell. In contrary, decreasing the threshold expands the effective coverage area of the WI-FI cell and effectively allows more user terminal making connection to the WI-FI cell.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     The present application is a divisional of U.S. patent application Ser. No. 14/042,493, which was filed on Sep. 30, 2013, which claims the benefit of U.S. Provisional Patent Application Ser. No. 61/816,301 filed Apr. 26, 2013, the entire contents of each of which are incorporated herein by reference. 
    
    
     TECHNICAL FIELD 
     The disclosure relates generally to wireless communications and, more particularly, to controlling selection by a user terminal between two access networks, such as a cellular network and wireless local area network. 
     BACKGROUND 
     Wireless user terminals, such as smartphones, tablets, and laptop computers, are designed to favor a Wireless Fidelity (WI-FI) connection as opposed to a cellular network connection. Whenever a user terminal is able to connect to a WI-FI cell in a Wireless Local Area Network (WLAN), it will automatically switch its network connection for Internet services to the WLAN from the cellular network such as a Third Generation Partnership Project (3GPP) network. This approach helps offload data traffic from the cellular network and is used by most cellular phones on the market. 
     This network selection bias favoring WLAN does not always provide the user with the best possible service. It does not take into consideration the network conditions for the two types of access networks (WLAN and cellular). Even when the WI-FI cell is very congested and the cellular network is lightly loaded, the user terminal will still select the WI-FI cell. Similarly, when a user terminal is further away from a WI-FI cell with marginal signal quality and the quality of service with WI-FI is poor, the user terminal will still connect through the WI-FI cell even though the cellular network can provide better service (e.g., higher data throughput). 
     SUMMARY 
     This disclosure describes techniques for controlling access selection by a user terminal between first and second access networks. In one exemplary embodiment, the access selection techniques are applied to control selection by a user terminal between a cellular network and a WLAN. Cellular network cells providing overlapping coverage with WI-FI cells in the WLAN are correlated with the WI-FI cells. A Received Signal Strength Indicator (RSSI) threshold is determined for each WI-FI cell based on an average throughput of the cellular network cells correlated with the WI-FI cell. The WI-FI RSSI Admit threshold is used to control the effective coverage area of the WI-FI cell. A user terminal operating within a cellular network is admitted to a WI-FI cell only if it is within the effective coverage area of the WI-FI cell as determined by the RSSI threshold. Increasing the threshold shrinks the effective WI-FI cell coverage area and turns user terminal of weaker signal strength away from the WI-FI Cell. Decreasing the threshold expands the effective WI-FI cell coverage area and moves user terminal of weaker signal strength towards WI-FI cell. 
     Exemplary embodiments of the disclosure comprise methods of WI-FI/3GPP access selection between a first access network (e.g., WLAN) and a second access network (e.g., 3GPP cellular network) providing overlapping coverage with the first access network. In one exemplary embodiment, a performance measurement (e.g., average throughout) is obtained for a group of one or more cells in the second access network that are correlated with a cell in the first network. An admission threshold is computed for the cell in the first access network based on the performance measurement for the corresponding group of cells in the second access network that are correlated with the cell in the first access network. Admission of a user terminal operating in the second access network to the cell in the first access network is controlled based on the admission threshold. 
     In one exemplary embodiment, the admit threshold comprises a minimum received signal strength for the user terminal allowed by the cell in the first access network. 
     In some embodiments, computing the admission threshold based on a performance measurement comprises computing the admission threshold based on an average throughput for the group of cells in the second access network. 
     In some embodiments, computing the admission threshold based on an average throughput for the group of cells in the second access network comprises computing the admission threshold as a function of the average throughput of the cell in the first access network and the average throughput for the group of cells in the second access network. 
     In some embodiments, computing the admission threshold as a function of the average throughput of the cell in the first access network and the average throughput for the group of cells in the second access network comprises applying an adjustable bias factor to favor one of the first and second access networks. 
     In some embodiments, computing an average throughput for the group of cells in the second access network comprises computing a weighted average throughput for the group of cells in the second access network. 
     In some embodiments, computing a weighted average throughput for the group of cells in the second access network comprises computing a weighting factor for each cell in the group of cells, computing a weighted sum of the individual cell throughputs based on the weighing factors, and dividing the weighted sum by the number of cells in the group of cells. 
     In some embodiments, computing a weighting factor for each cell in the group comprises computing the weighting factors based on hit counts. 
     In some embodiments, the group of cells in the second network comprises cells of two or more different types, and the hit counts for cells of different types are multiplied by corresponding bias factors based on cell type. 
     In some embodiments of the invention, computing an admission threshold is further based on the cell loads or other network conditions in the first and second access networks. 
     In some embodiments, computing the admission threshold is carried out at a central access control node in the first access network. 
     In some embodiments, controlling the admission of a user terminal operating in the second access network to the cell in the first access network based on the admission threshold comprises sending the admission threshold from the centralized access control node to an access point serving the cell in the first access network. 
     In some embodiments, obtaining a performance measurement for a group of one or more cells in the second access network that are correlated with the cell in the first network comprises sending a request from the access control node in the first access network to a network node in the second access network; receiving, responsive to the request, performance statistics for the group of cells in the second access network correlated with the cell in the first access network; and computing the performance measurement based on the performance statistics. 
     In some embodiments, the method further comprises correlating the group of one or more cells of the second access network with the cell in the first access network. 
     In some embodiments, correlating the group of one or more cells of the second access network with the cell in the first access network comprises sending a cell identification request from the first access network to the second access network, the cell identification request including a user terminal identification of a user terminal connected to the cell in the first access network; receiving, responsive to the cell identification request, a cell identification of a last known cell in the second access network in which the user terminal was present; and correlating the received cell identification with the cell in the first access network. 
     In some embodiments, the admission threshold for the cell in the first access network is computed by an access point for the cell in the first access network. 
     In some embodiments, controlling the admission of a user terminal operating in a cell of the second access network to the cell in the first access network based on the admission threshold comprises measuring a received signal strength of a signal received from a user terminal attempting to access the cell in the first access network; admitting the user terminal to the cell in the first access network based on a comparison of the received signal strength with the admission threshold. 
     In some embodiments, the method further comprises silently rejecting the attempt by a user terminal to connect to the first cell by ignoring connection requests to the access point. 
     In some embodiments, obtaining a performance measurement for a group of one or more cells in the second access network that are correlated with the cell in the first network comprises receiving performance statistics for the group of cells in the second access network correlated with the cell in the first access network; and computing the performance measurement based on the performance statistics. 
     In some embodiments of the invention, the method further comprises using an adaptive control loop to continuously adjust the admission threshold based on current conditions and monitoring the results. For example, the adaptive control loop may re-compute the admission threshold at predetermined intervals or as conditions in the two access networks change. 
     Exemplary embodiments of the disclosure comprise a network node in a first access network configured to control access selection by a user terminal between a first access network (e.g. WLAN) and a second access network (e.g. cellular network) providing overlapping coverage with the first access network. In one exemplary embodiment, the network node includes a network interface and processing circuit. The processing circuit is configured to obtain a performance measurement (e.g., average user terminal throughput) for a group of cells in the second access network that are correlated with the cell in the first access network. The processing circuit is further configured to compute an admission threshold for the cell in the first access network based on the performance measurement for the group of cells in the second access network, and to control admission of a user terminal operating in the second access network to the cell in the first access network based on the admission threshold. 
     In one exemplary embodiment, the admission threshold comprises a minimum received signal strength (RSSI) for the user terminal allowed by the cell in the first access network. 
     In some embodiments, the processing circuit is configured to compute the admission threshold based on an average throughput for the group of cells in the second access network. 
     In some embodiments, the processing circuit is configured to compute the admission threshold as a function of the average throughput for the group of cells in the second access network and the average throughput of the cell in the first access network. 
     In some embodiments, computing the admission threshold by the processing circuit further comprises applying bias factors to favor one of the first and second access networks. 
     In some embodiments of the invention, computing the admission threshold by the processing circuit further comprises computing the admission threshold based on cell load factors or other network conditions in the first and second access networks. 
     In some embodiments, computing an average throughput for a group of cells in the second access network by the processing circuit comprises computing a weighted average throughput for the group of cells in the second access network. 
     In some embodiments, computing a weighted average throughput for the group of cells in the second access network by the processing circuit comprises computing a weighting factor for each cell in the group, computing a weighted sum of the individual cell throughputs based on the weighing factors, and dividing the weighted sum by the number of cells in the group of cells. 
     In some embodiments, computing a weighting factor for each cell in the group by the processing circuit comprises computing the weighting factors based on hit counts. 
     In some embodiments, the group of cells in the second network comprises cells of two or more different types, and the processing circuit is configured to multiply the hit counts for cells of different types by corresponding bias factors based on cell type. 
     In some embodiments, network node comprises a centralized access control node configured to compute admission thresholds for two or more cells in the first access network. 
     In some embodiments, to control the admission of a user terminal operating in a cell of the second access network to the cell in the first access network based on the admission threshold, the processing circuit is configured to send the admission threshold from the centralized access control node to an access point. 
     In some embodiments, to obtain a performance measurement for a group of one or more cells in the second access network that are correlated with the cell in the first network, the processing circuit is configured to send a request from the access control node in the first access network to a network node in the second access network; receive, responsive to the request, performance statistics for the group of cells in the second access network correlated with the cell in the first access network; and compute the performance measurement based on the performance statistics. 
     In some embodiments, the processing circuit is further configured to correlate the group of one or more cells of the second access network with the cell in the first access network. 
     In some embodiments, to correlate the group of one or more cells of the second access network with the cell in the first access network, the processing circuit is configured to send a cell identification request from the first access network to the second access network, the cell identification request including a user terminal identification of a user terminal connected to the cell in the first access network; receive, responsive to the cell identification request, a cell identification of a last known cell in the second access network in which the user terminal was present; and correlate the received cell identification with the cell in the first access network. 
     In some embodiments, the network node comprises an access point in a cell of the first access network. 
     In some embodiments, to control the admission of a user terminal operating in a cell of the second access network to the cell in the first access network based on the admission threshold, the processing circuit is configured to measure a received signal strength of a signal received from a user terminal attempting to access the cell in the first access network; and admit the user terminal to the cell in the first access network based on a comparison of the received signal strength to the admission threshold. 
     In some embodiments, the processing circuit is further configured to silently reject the attempt by a user terminal to connect to the first cell by ignoring data transmissions from the user terminal to the access point. 
     In some embodiments, to obtain a performance measurement for a group of one or more cells in the second access network that are correlated with the cell in the first network, the processing circuit is configured to receive performance statistics for the group of cells in the second access network correlated with the cell in the first access network; and compute the performance measurement based on the performance statistics. 
     In some embodiments, the processing circuit is configured to implement an adaptive control loop to continuously adjust the admit threshold based on current conditions and monitor the results. For example, the adaptive control loop may re-compute the admission threshold at predetermine intervals or as conditions in the two access networks change. 
     Other embodiments of the disclosure comprise methods of correlating cells in first and second access networks that provide overlapping coverage. The method is performed when a user terminal attempts to connect to a cell in the first access network. The method comprises sending a cell ID request from the first access network to the second access network. The cell identification request includes a user terminal identification of a user terminal connected to a cell in the first access network. The method further comprises receiving, responsive to the cell ID request, a cell ID of a last known cell in the second access network in which the user terminal was present. The received cell ID is then correlated with a connecting cell in the first access network. 
     In some embodiments, the method further comprises receiving the user identification of the user terminal from an authentication server. 
     In some embodiments, the cell correlation process is performed on an on-going basis in order to detect changes in network configuration. 
     In some embodiments of the invention, the cell correlation information is stored in a cell correlation table. 
     Other embodiments of the disclosure comprise a network node including a network interface circuit and processing circuit for correlating cells in first and second access networks that provide overlapping coverage. In one exemplary embodiment, the processing circuit is configured to send a cell ID request to the second access network; receive, responsive to the cell ID request, a cell ID of a last known cell in the second access network in which the user terminal was present; and correlate the received cell ID with a connecting cell in the first access network. 
     In some embodiments, the processing circuit if further configured to receive the user identification from an authentication server. 
     In some embodiments, the processing circuit is configured to perform the cell correlation process on an on-going basis in order to detect changes in network configuration. 
     In some embodiments of the invention, the processing circuit is configured to store the cell correlation information in a cell correlation table. 
     Other embodiments of the disclosure comprise methods of determining a user terminal identity (e.g., IMSI) in a second access network by a first access network and of associating the user terminal identity in the second access network with the corresponding identity in the first access network. 
     Other embodiments of the disclosure comprise a network node (e.g., OSSRC) including a network interface circuit and processing circuit for determining a user terminal identity (e.g. IMSI) in a second access network (e.g., cellular network) by a first access network (e.g., WLAN) and of associating the user terminal identity in the second access network with the corresponding identity in the first access network. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  illustrates a communication network implementing the traffic steering approach as described herein. 
         FIGS. 2A and 2B  illustrate switching by a user terminal between a cellular network cell and WI-FI cell. 
         FIG. 3  illustrates the WI-FI/3GPP access selection approach based on use of an admission threshold to control the effective size of a WI-FI cell. 
         FIG. 4  illustrates an exemplary method of correlating cellular network cells with WI-FI cells. 
         FIG. 5  illustrates a correlation method implemented by a network node in the WLAN. 
         FIG. 6  illustrates an exemplary method of steering traffic between cellular network cells and WI-FI cells. 
         FIG. 7  illustrates a WI-FI/3GPP access selection method implemented in a WLAN. 
         FIG. 8  illustrates exemplary processing performed by an access control node in a WLAN. 
         FIGS. 9A and 9B  graphically illustrate a method of computing a weighted average user terminal throughput used for traffic steering. 
         FIG. 10  illustrates a method of predicting a current user terminal throughput from historical data. 
         FIG. 11  illustrates an exemplary method of predicting a current value of a performance measurement. 
         FIG. 12  illustrates an exemplary network node. 
     
    
    
     DETAILED DESCRIPTION 
     The present disclosure describes techniques for steering traffic between two different access networks. The techniques described herein are generally applicable to any type of wireless communication network. As an aid in understanding the disclosure, exemplary embodiments of the steering techniques will be described in the context of WI-FI/3GPP access selection between a cellular network and a wireless network based on the Institute of Electrical and Electronics Engineers (IEEE) 802.11 family of standards. 
       FIG. 1  illustrates an exemplary communication environment comprising first and second access networks in which the access selection techniques may be employed. The first access network comprises a Wireless Local Area Network (WLAN)  50  operating according to the IEEE 802.11 family of standards. The WLAN  50  includes one or more access points (APs)  55  that provide coverage in respective WI-FI cells  60 . A single AP  55  may serve multiple WI-FI cells  60 . The second access network comprises a cellular network  10 , such as a Global System for Mobile Communication (GSM) network, Wideband Code Division Multiple Access (WCDMA) network, Long Term Evolution (LTE) network, or other cellular network. The cellular network  10  includes a packet core network  15  and radio access network (RAN)  20 . The RAN  20  includes one or more base stations (BSs)  25  that provide coverage in respective cells  30  of the cellular network  10 . A single base station  25  may serve multiple cellular network cells  30 . The packet core network  15  provides connection to external networks, such as the Internet  40  and IP Multimedia Subsystem (IMS) networks  45 . 
     A dual mode user terminal  100  is also shown that is capable of communicating with both the base stations  25  in the cellular network  10  and the APs  55  in the WLAN  50 . The user terminal  100  is identified in the cellular network  10  by an International Subscriber Identity (IMSI). The user terminal  100  is identified in the WLAN  50  by a Medium Access Control (MAC) address. 
     The WLAN  50  includes an Access Control (AC) node  70  with an Access Network Supervisor (ANS) function that controls admission to the WLAN  50 . The AC node  70  communicates with an Operation and Support System (OSS)  35  in the cellular network  10  as will be hereinafter described in more detail. Although shown separately, the OSS  35  may be located in the core network  15  of the cellular network  10 . In one exemplary embodiment, the AC node  70  sends requests for information to the OSS  35 . For example, the AC node  70  may request a cell ID or performance measurements for a cellular network cell  30  or a group of cells. In response to the request for information, the OSS  35  may send the requested information to the AC node  70 . 
       FIG. 2A  illustrates the current traffic steering approach in use today where a user terminal  100  favors a WLAN connection over a cellular network connection. A user terminal  100  having a cellular network connection will switch to a WI-FI cell  60  as soon as it is able to connect to the WI-FI  60  cell even though the cellular network  10  provides higher throughput than the WLAN  50 . There is no coordination between the cellular network  10  and the WLAN  50 . The immediate switching to the WI-FI cell  60  by the user terminal  100  as soon as it is able to establish a connection with the WI-FI cell  60  results in a significant drop in data throughput for the user terminal  100 . This approach becomes more problematic with the increasing number of WI-FI cells  60 . 
       FIG. 2B  illustrates an alternative approach according to one embodiment of the disclosure. As shown in  FIG. 2B , the user terminal  100  does not immediately switch to the WI-FI cell  60  as soon as it is able to establish a connection to the WI-FI cell  60 . Rather, switching from the cellular network  10  to the WI-FI cell  60  is based on expected performance of the WI-FI Cell  60  relative to the cellular network cell  30 . In one embodiment, switching from the cellular network  10  to the WI-FI cell  60  is delayed until the data throughput for the WI-FI cell  60  is roughly equal to the data throughput for cellular network  10 . This approach provides a better experience for the user. 
     The traffic steering in one embodiment has two major components. First, the cellular network cells  30  providing overlapping coverage with a WI-FI cell  60  are identified and correlated with the WI-FI cell  60 . Second, adaptive steering control is provided by adjusting a Received Signal Strength Indicator (RSSI) threshold used for admitting user terminals  100  to the WI-FI cell  60 . The threshold is referred to herein as the RSSI-Admit threshold or admission threshold. 
     The cellular network cells  30  may, for example, comprise GSM cells, WCDMA cells, LTE cells, or a combination thereof. In one embodiment, up to nine cellular network cells  30  can be correlated with a single WI-FI cell  60 . Any additional cellular network cells  30  of lesser significance are ignored. The correlation of cellular network cells  30  to WI-FI cells  60  is performed automatically on an ongoing basis so that changes in network configuration are detected and accounted for. Changes in network configuration may, for example, be due to cell splitting, addition of cells, deletion of cells, etc. 
     The RSSI-Admit threshold is used to control the effective coverage area or effective size of a WI-FI cell  60 . A user terminal  100  is admitted when the RSSI-Admit threshold is met and is not admitted otherwise. Lowering the RSSI-Admit threshold increases the effective coverage area of the WI-FI cell  60 . Raising the RSSI-Admit threshold decreases the effective coverage area of the WI-FI cell  60 . 
     The adjustment of the RSSI-Admit threshold may be performed for all WI-FI cells  60  in the WLAN  50  by a centralized access control (AC) node  70  in the WLAN  50 . Alternatively, each AP  55  in the WLAN  50  network may separately determine the RSSI-Admit threshold for WI-FI cells  60  served by the AP  55 . 
     Predicted average throughput for the WI-FI cell  60  is used to set the RSSI-Admit threshold and thus control the effective cell size. In one exemplary embodiment, the RSSI-Admit threshold is set so that the predicted average throughput for the WI-FI cell  60  is roughly equal to the cellular network cell  30 . In some embodiments, a carrier configurable bias may be used to allow a carrier to favor either the cellular network  10  connection or the WLAN  50 . The bias can be dynamically adjusted depending on current conditions. For example, when the cellular network  10  is congested, the carrier may favor the WLAN  50  over the cellular network  10  to reduce the load on the cellular network  10 . When the load in the cellular network  10  is light, the carrier may want to favor the cellular network  10 . 
       FIG. 3  illustrates how the RSSI-Admit threshold is used to control access selection.  FIG. 3  shows the actual radio coverage area (RCA) of three WI-FI cells  60  within the coverage area of a cellular network cell  30 . Each WI-FI cell  60  also has an effective coverage area (ECA) that is determined by the RSSI-Admit threshold. A user terminal  100  is admitted to the WI-FI cell  60  only if the user terminal  100  is within the effective coverage area as determined by the RSSI-Admit threshold. As shown in  FIG. 3 , the RSSI-Admit threshold can be adjusted dynamically to vary the effective coverage area of the WI-FI cell  60 . The effective coverage area may be increased by lowering the RSSI-Admit threshold, which will increase the number of user terminals  100  admitted to the WI-FI cell  60 . Conversely, the effective coverage area may be decreased by lowering the RSSI-Admit threshold, which will decrease the number of user terminals  100  admitted to the WI-FI cell  60 . 
       FIG. 4  illustrates signaling involved in the correlation of cellular network cells  30  to WI-FI cells  60 . A user terminal  100  sends an association request to the AP  60  in a WI-FI cell  60  to switch its connection from a cellular network cell  30  to the WI-FI cell  60  (step  1 ). In this example, it is assumed that the RSSI is high and that the association request is accepted. In this case, the AP  55  in the WI-FI cell  60  sends an association response to the user terminal  100  (step  2 ). The user terminal  100  then initiates an authentication procedure with an Authentication, Authorization, and Accounting (AAA) server  65  in the WLAN  50  (step  3 ). The authentication procedure may, for example, use the Extensible Authentication Protocol Subscriber Identity Module (EAP-SIM) method or the Authentication and Key Agreement (AKA) authentication method. If the user terminal  100  is successfully authenticated by the AAA server  65 , the AAA server  65  sends an Access Accept message to the AC node  70  in the WLAN  50  (step  4 ). The Access Accept message includes an authentication response message, such as on EAP Success message, and the IMSI of the user terminal  100 . The AC node  70  associates the IMSI of the user terminal  100  with the MAC address of the user terminal  100 . The AC node  70  then sends the authentication response message (e.g., EAP Success message) to the user terminal  100  to indicate successful authentication (step  5 ). Also, upon receipt of the Access Accept message from the AAA server  65 , the AC node  70  sends a Cell Identification (ID) Request message to the OSS  35  (step  6 ). The Cell ID Request message includes the IMSI of user terminal  100  provided by the AAA server  65 . In response to the Cell ID Request message, the OSS  35  sends a Cell ID Response message to the AC node (step  7 ). The Cell ID Response message includes the cell ID of the last known cell  30  in which the user terminal  100  was present. The AC node  70  then performs a cell correlation procedure to map the cell ID to the WI-FI cell  60  and update a cell correlation table stored and maintained by the AC node  70 . The cell correlation table includes a list of WI-FI cells  60  and corresponding cell IDs for cellular network cells  30  that have been correlated with each WI-FI cell  60 . 
     Table 1 below lists functions performed by the OSS  65  and AC node  70  related to cell mapping. 
     
       
         
               
             
               
               
               
             
           
               
                 TABLE 1 
               
             
             
               
                   
               
               
                 Cell Correlation Requirements 
               
             
          
           
               
                 Node 
                 Requirement 
                 Comments 
               
               
                   
               
               
                 OSS 
                 Create table with IMSI, Cell ID, 
                   
               
               
                   
                 Cell Type and Timestamp when 
               
               
                   
                 mapping event are received 
               
               
                 OSS 
                 Respond to IMSI−&gt;Cell ID mapping 
                 Current time is used 
               
               
                   
                 queries over a GOOGLE Buf based 
                 for AC to compensate 
               
               
                   
                 interface to AC with 
                 for clock differences 
               
               
                   
                 Latest Cell ID the user terminal was 
               
               
                   
                 known to be in 
               
               
                   
                 Type of the cell (GSM/WCDMA/ 
               
               
                   
                 LTE) 
               
               
                   
                 Coordinated Universal Time (UTC) 
               
               
                   
                 timestamp for latest time of validity 
               
               
                   
                 UTC current time 
               
               
                 AC 
                 Select user terminals with IMSI 
                 Must select appropriate 
               
               
                   
                 availability to query for cell ID 
                 time to query, taking 
               
               
                   
                 mapping with the following input: 
                 into consideration event 
               
               
                   
                 IMSI of the user terminal 
                 updating on OSS is delayed 
               
               
                   
                 Basic Service Set Identification 
               
               
                   
                 (BSSID) the user terminals is in 
               
               
                 AC 
                 Create and maintain an AP−&gt;Cell ID 
                 Table updating may be 
               
               
                   
                 mapping table 
                 once a day or twice a day. 
               
               
                   
                 Allow up to 9 cells to be mapped 
                 Cell weight is to be used in 
               
               
                   
                 to an AP 
                 calculating weighted 
               
               
                   
                 Calculate and maintain a weight 
                 average of user terminal 
               
               
                   
                 on each mapped cell based on 
                 100 average throughput 
               
               
                   
                 primary cell mapping count 
               
               
                   
               
             
          
         
       
     
       FIG. 5  illustrates an exemplary cell correlation method  200  implemented by a network node in the WLAN  50  for correlating cells in first and second access networks. The network node may, for example, comprise an AC node  70  in the WLAN  50 . The network node in the WLAN  50  sends a cell ID request to the cellular network  10  (block  210 ). The Cell ID request includes a user terminal ID (e.g., IMSI) that is used by the user terminal  100  in the cellular network  10 . Responsive to the cell identification request, the network node receives a cell ID of a last known cell in the cellular network  10  in which the user terminal  100  was present (block  220 ). The network node in the WLAN  50  then correlates the received cell ID with a WI-FI cell  60  in the WLAN  50  to which the user terminal  100  is currently connected (block  230 ). The correlation may store in a cell correlation table (block  240 ). 
       FIG. 6  illustrates signaling between the cellular network  10  and WLAN  50 . The AC node  70  sends a Cell Performance Measurement (PM) Query to the OSS  35  to request performance measurements for the cellular network cells  30  correlated with the WI-FI cells  60  within its domain (step  1 ). The Cell PM Query includes the cell IDs of the cellular network cells  30  correlated with one or more WI-FI cells  60  in the WLAN  50 . The Cell PM Query may be sent at periodic intervals (e.g., at 1 minute intervals), or may be event triggered. In response to the Cell PM Query, the OSS  35  sends the requested performance measurements for the identified cells to the AC node  70  (step  2 ). In one exemplary embodiment, the performance measurements comprise the average user terminal throughput T a  for each cellular network cell  30  identified by the request. Alternatively, other performance data could be provided enabling the AC node  70  to compute the average user terminal throughput T a  for each cellular network cell  30 . The APs  55  in the WLAN  50  also calculate and report the average user terminal throughput T w  at the same time interval for the respective WI-FI cells  60  in the WLAN  50 . For each WI-FI cell  60 , the AC node  70  calculates a weighted average user terminal throughput T c  for the cellular network cells  30  correlated with each WI-FI cell  60  and compares it with the average user terminal throughput T w  for the WI-FI cell  60  (step  4 ). Based on the comparison, the AC node  70  adjusts the RSSI-Admit threshold for the WI-FI cell  60  and sends the adjusted RSSI-Admit threshold to the AP  55  for the WI-FI cell  60  (step  5 ). The RSSI-Admit threshold is thereafter used by the AP  55  to control admission of user terminals  100  to the WI-FI cell  60 . Equivalently, the AC node  70  could send the adjustment to the RSSI-Admit threshold to the AP  55  and the AP  55  could add the adjustment to the current RSSI-Admit threshold to obtain the new RSSI-Admit threshold. When the AP  55  receives a request message such as an Authentication Request, Probe Request, or association request from a user terminal  100  (step  6 ), the AP  55  measures the RSSI for the user terminal  100  and compares the measured RSSI to the RSSI-Admit threshold. If the measured RSSI is less than the threshold, the AP  55  silently rejects the user terminal  100  by dropping the received request messages (step  7 ). If the RSSI is above the threshold, the AP  55  sends a corresponding response message to the user terminal  100  (step  8 ). 
     Table 2 below provides further details regarding the functions performed by the OSS  35  and AC node  70  related to WI-FI/3GPP Access Selection. 
     
       
         
               
             
               
               
             
           
               
                 TABLE 2 
               
             
             
               
                   
               
               
                 Access Selection Requirements 
               
             
          
           
               
                 Node 
                 Requirement 
               
               
                   
               
               
                 OSS 
                 Provide external SQL interface for AC to query performance 
               
               
                   
                 measurements so as to derive average user terminal throughput 
               
               
                 AC 
                 Query performance measurements through SQL for deriving 
               
               
                   
                 average user terminal throughput 
               
               
                 AC 
                 Calculate on-going daily trend of average user terminal 
               
               
                   
                 throughput for each cell using actual data only 
               
               
                 AC 
                 Make a statistic prediction of current value of average user terminal 
               
               
                   
                 throughput from a daily trend and the latest actual values 
               
               
                 AC 
                 Calculate a predicted current value of weighted user terminal 
               
               
                   
                 throughput 
               
               
                 AC 
                 Adaptive RSSI-admit level control loop 
               
               
                 AC 
                 Communicate with AP to collect user terminal average 
               
               
                   
                 throughput info and push new RSSI-Admit value to AP 
               
               
                 AP 
                 Calculate average user terminal throughput and 
               
               
                   
                 communicate with AC for reporting. 
               
               
                 AP 
                 Execute commands from AC to activate new RSSI-Admit levels 
               
               
                   
               
             
          
         
       
     
       FIG. 7  illustrates an exemplary method  300  of user network access selection between the WLAN  50  and a cellular network  10  that provides overlapping coverage with the WLAN  50 . The method  300  may be performed by AC node  70  in the WLAN  50  or by an AP  55 . A performance measurement is obtained for a group of cellular network cells  30  in the cellular network  10  that are correlated with a WI-FI cell  60  in the WLAN  50  (block  310 ). The performance measurement may, for example, comprise the aggregate average user terminal throughput, T c , for the cellular network cells  30  that are correlated with the WI-FI cell  60 . An admission threshold (e.g., RSSI-Admit threshold) for the WI-FI cell  60  is computed based on the performance measurement for the group of cellular network cells  30  in the cellular network  10  that are correlated with the WI-FI cell (block  320 ). Admission of user terminal  100  attempting to connect to the WI-FI cell  60  to the WLAN  50  is controlled based on the admission threshold for the WI-FI cell  60  (block  330 ). 
     In some embodiments, the AC node  70  correlates the group of one or more cells  30  in the cellular network  10  with a WI-FI cell  60  in the WLAN  50 . The AC node  70  may obtain the performance measurement for the cells  30  in the cellular network  10  by requesting individual performance statistics (e.g., per cell average user terminal throughput, T a ) for the correlated cells  30  in the cellular network  10  and computing the performance measurement (e.g., aggregate average user terminal throughput, T c ) for the correlated cellular network cells  30  based on the individual performance statistics. The AC node  70  may further use the performance measurement to compute the admission threshold. To compute the admission threshold, the AC node  70  may also receive a performance measurement (e.g., average user terminal throughput, T w ) for the WI-FI cell  60  from the AP  55 . The AC node  70  may further control the admission of user terminals  100  to the WI-FI cell  60  by sending the computed admission threshold to the AP  55 . The AP  55  may then use the admission threshold to determine whether to admit user terminals  100  to the Wi-Fi cell  60 . Alternatively, admission control decisions may be made by the AC node  70 . In this case, the AP  55  may send RSSI measurements associated with a user terminal  100  to the AC node  70 . The AC node  70  may decide whether to admit the user terminal  100  by comparing the RSSI measurements to the admission threshold. 
     In other embodiments, the AP  55  may receive the performance measurement (e.g., aggregate average user terminal throughput, T c ) of the correlated cellular network cells  30  from the AC node  70  and use the performance measurement to compute the admission threshold as previously described. Alternatively, the AP  55  may receive individual performance statistics (e.g., per cell average user terminal throughput, T a ) for correlated cells  30  in the cellular network  10  from either the AC node  70 , or from the OSS  35  in the cellular network  10 . The AP  55  in this embodiment may compute the performance measurement (e.g. aggregate average user terminal throughput, T c ) for the correlated cellular network cells  30  based on the performance statistics. In embodiments where the admission threshold is computed by the AP  55 , the AP  55  may further control admission to the WI-FI cell  60  by comparing RSSI measurements for a user terminal  100  attempting to connect to the WI-FI cell  60  with the admission threshold. 
       FIG. 8  illustrates an adaptive control loop for adjusting the admission threshold used for steering traffic between the cellular network  10  and WLAN  50 . The average user terminal throughput T a  for cellular network cells  30  correlated with a WI-FI cell  60  are input to a processing circuit within the AC node  70 . The processing circuit computes the weighted average user terminal throughput, T c  for the cells  30  of the cellular network  10  correlated with a WI-FI cell  60 . The processing circuit receives the average user terminal throughput, T w , for the WI-FI cell  60  from the AP  55 . The processing circuit compares the weighted average throughput T c  for the cellular network cells  30  with the average throughput T w  of the WI-FI cell  60 . The average user terminal throughput T w  for the WI-FI cell  60  may be multiplied by a bias factor b. Based on the comparison, the processing circuit either increments or decrements the RSSI-Admit threshold. In one exemplary embodiment, the RSSI-Admit threshold is incremented or decremented in small steps to avoid oscillation. When the bias factor b is equal to 1, the RSSI-Admit threshold is incremented when T w  is less than T c  and decremented when T w  is greater than T c . A bias factor b greater than 1 favors the WI-FI cell  60 , while a bias factor b less than 1 favors the cellular network  10 . In one exemplary embodiment, a RSSI-Admit threshold is changed only when the difference between bT w  and T c  meets a threshold (e.g. 20% difference). The adjusted RSSI-admit threshold is provided to the AP  55 . 
     For WCDMA networks, the weighted average user throughput T c  may be computed from the average user throughputs T a (s) for the individual cellular network cells  30  according to: 
                       T   c     =       ∑     i   =   1     n     ⁢           ⁢       w   i     ⁢       T   a     ⁡     (   i   )             ,           Eq   .           ⁢     (   1   )                 
where n is the number of cellular network cells  30  correlated to the WI-FI cell  60 , w i  is a normalized weighting factor for the ith cellular network cell  30 , and T a (i) is the average user terminal throughput of the ith cellular network cell  30 . The weighting factor w i  for cell i may be computed according to:
 
                     w   i     =       h   i         ∑   1   n     ⁢           ⁢   h               Eq   .           ⁢     (   2   )                 
where h i  is the hit count for cell i and the summation in the denominator is the sum of the hit counts for cells  1  through n. The hit count h i  for a cellular network cell  30  reflects the degree of overlap between the cellular network cell  30  and the WI-FI cell  60  and is computed based on number of times that a user terminal  100  moves from a given cellular network cell  30  to the WI-FI cell  60  in a given time interval (e.g., the past one hour or one day). The hit count h i  is maintained by the AC node  70  for each cellular network cell  30  that is correlated with a WI-FI cell  60 . In one exemplary embodiment, the hit count h i  for a cellular network cell  30  is incremented each time the cell ID of the cellular network cell  30  is returned by the OSS  35  in response to a Cell ID Request.
 
     Because the hit counts h i  for cellular network cells  30  in the different types of networks may not be directly comparable, the hit counts h i  for the cellular network cells  30  may be multiplied by different bias factors depending on the type of the cellular network cells  30 . The bias factor may comprise an integer between 1 and 10. A default bias factor of 1 may be used when not otherwise specified. The bias factors are applied to the hit counts before determining the weighting factors for the cellular network cells  30 . 
       FIGS. 9A and 9B  graphically illustrates the weighted average for the cellular network cells  30  correlated with a WI-FI cell  60 .  FIG. 9A  shows the average user terminal throughput for three cellular network cells  30  identified as Cell  1 , Cell  2  and Cell  3 .  FIG. 9B  shows a weighted average user terminal throughput for the same three cellular network cells  30 . 
     To be comparable to the average user throughput for the cellular network cells  30 , the average user terminal throughput for the WI-FI cell  60  is based on downlink (DL) data throughput. The downlink data throughput T d  and the number of active users is measured and reported every one second. The average user terminal throughput T w  is then calculated every one minute. 
     Those skilled in the art will appreciate that although the average user terminal throughput T a  for a cellular network cell  30  and the average user throughput T w  for a WI-FI cell  60  may be computed every minute, a longer time window may be used to compute the average. For example, the average user terminal throughputs T a  and T w  may be computed every one minute based on the traffic occurring over the last 15 minutes. 
     In actual practice, the latest measurements of the average user terminal throughputs T a (s) for the cellular network cells  30  available to the AC node  70  for computing the weighted average user terminal throughput T c  may not always be current. The availability of the data may be delayed by as much as 45 minutes for a number of reasons. 
     According to one aspect of the present disclosure, a method is provided for predicting the current average user terminal throughput for individual cellular network cells  30  of the cellular network  10  in situations where the available data is not current. The predicted average user terminal throughput for a cell, denoted {hacek over (T)} a , may then be used to compute the weighted average throughput T c  by substituting the predicted average user terminal throughput {hacek over (T)} a  for the average user terminal throughput T a  in Eq. (1) to obtain: 
     
       
         
           
             
               
                 
                   
                     
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       FIG. 10  graphically illustrates the prediction of the current average user terminal throughput {hacek over (T)} a  for a cellular network cell  30  in one exemplary embodiment. In this embodiment, an on-going daily trend T tr  is calculated for the average user terminal throughput. The latest average user terminal throughout T a , together with the daily trend T tr , is then used to predict the current user terminal throughput {hacek over (T)} a . 
     In one exemplary embodiment, the daily trend is computed from the average user terminal throughput values collected over a period of days, weeks or months. The daily trend comprises a set of data points at different times t during a one day period. In one exemplary embodiment, the daily trend is computed every one minute by averaging T a  at the same time t over a predetermined number of days. In one exemplary embodiment, the daily trend is computed over a 7 day time window. In some embodiments, a daily trend T tr  may be calculated separately for weekdays, Saturday, and Sunday. Also, a separate daily trend T tr  may be computed for each day of the week if the traffic varies significantly from day to day. A daily trend based on weekdays only is referred to herein as a weekday trend. A daily trend based on the same day of week over a plurality of weeks is referred to herein as a calendar day trend. For example, a daily trend based on data collected each Saturday over a plurality of Saturday is a calendar day trend. The daily trend T tr  at time t is given by: 
                       T   tr     ⁡     (   t   )       =         ∑     i   =   1     n     ⁢       T   a     ⁡     (   t   )         n             Eq   .           ⁢     (   4   )                 
where n is the number of days over which the daily trend is computed.
 
     The most recent data for the average user throughput T a  and the daily trend is used to predict a current value of the average user terminal throughput {hacek over (T)} a . The most recent measurements of the average user terminal throughput T a  are averaged over a predetermined time period (e.g. one hour) to obtain a composite average throughput T avg  for the most recent time window. The daily trend is then averaged over the same time window to obtain an average of the daily trend T tr   _   avg . The difference between the current value of the daily trend T tr   _   current  at time t and the average of the daily trend T tr   _   avg  is computed to obtain ΔT tr . The predicted average user terminal throughout {hacek over (T)} a  is given by:
 
 {hacek over (T)}   a ( t )= T   avg   +ΔT   tr   Eq. (5)
 
Other ways of computing the predicated average user terminal throughput could also be used.
 
     Although the prediction techniques described above were used to predict current average user terminal throughput, those skilled in the art will appreciate that the same techniques can be applied in other contexts and that the prediction techniques can be applied to other situation where the most recent available data is not current. 
       FIG. 11  illustrates an exemplary method  400  implemented by an AC node  70  or other network node for predicting a current value of a performance measurement indicative of network performance. The AC node  70  or other network node obtains a daily trend in a series of performance measurements (block  410 ). The daily trend comprises a set of data points at different times of day, wherein each data point represents an average value of the performance measurements at a corresponding time of day over a plurality of days. The AC node  70  or other network node also obtains one or more recent performance measurements over a recent time interval (block  420 ). Based on the daily trend and the recent performance measurements, the AC node  70  or other network node predicts the current value of the performance measurement (block  430 ). 
       FIG. 12  illustrates an exemplary network node  500  for implementing traffic steering as herein described. The network node  500  comprises a network interface circuit  510  for connecting to a communication network and communicating over the network with other network nodes, and a processing circuit  520  configured to perform one or more of the methods described herein. In one embodiment, the network node  500  functions as an AC node  70  as herein described. In other embodiments, the network node  500  functions an AP  55  in the WLAN  50  as herein described and further includes a transceiver  530  for communicating with user terminals  100  over a radio interface. In other embodiments, the network node  200  comprises an OSS  35  in the cellular network  10  and the processing circuit  220  is configured to provide an AC node  70  or AP  55  in the WLAN  50  with cell IDs and performance statistics as herein described.