Abstract:
Systems and techniques for managing delivery of data to a device are described. Conditions are analyzed relating to delivery of data to a wireless communication device and, based on the analysis, needed adjustments are made to data delivery, such as pre-delivering data before it is needed. The analysis may include analysis of channel conditions and estimates of user behavior, such as stopping consumption of data—as in the case of a user watching a video and abandoning the video before it is finished.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
       [0001]    This patent application claims priority under 35 U.S.C. 119(e) from Provisional Patent Application No. 61/655,688, filed on 5 Jun. 2012, the disclosure oft which is incorporated by reference herein in its entirety. 
     
    
     TECHNICAL FIELD 
       [0002]    The exemplary and non-limiting embodiments of this invention relate generally to wireless communications and more specifically to controlling retrieval of data, such as video data, by user equipment from a wireless network while the data is used by the user equipment. 
       BACKGROUND 
       [0003]    The following abbreviations that may be found in the specification and/or the drawing figures are defined as follows:
       3GPP Third Generation Partnership Project   CDMA Code Division Multiple Access   CAN Content Aware Network   CAN-EG Content Aware Network-Enabling Gateway   CDN Content Distribution Network   C-SON Centralized Self Optimizing Network   DL Downlink   E-UTRA Evolved Universal Terrestrial Radio Access   eNB or eNodeB Evolved Node B/Base Station in an E-UTRAN System   EPC Enhanced Packet Core   E-UTRAN Evolved UTRAN (LTE)   FDD Frequency Division Duplex   FDM Frequency Division Multiplexing   GPS Global Positioning System   GSM Global System for Mobile Communications   GPRS General Packet Radio Service   GTP GPRS tunneling protocol   HetNET Heterogeneous Network   HO Handoff   IP Internet Protocol   IRP Interface Reference Point   LTE Long Term Evolution   LTE-A Long Term Evolution Advanced   MAC Medium Access Control   MDT Minimization of Drive Tests   MME Mobility Management Entity   MO Media Optimizer   MR Measurement Report   PCRF Policy and Charging Rule Function   PDN-GW Packet Data Network Gateway   QAM Quadrature Amplitude Modulation   QPSK Quadrature (Quaternary) Phase Shift Keying   RRC Radio Resource Control   RAN Radio Access Network   RF Radio Frequency   Rx Reception   SGW Serving Gateway   SON Self Optimizing Network   TDD Time Division Duplex   TDM Time Division Multiplexing   Tx Transmittance   UCI Uplink Control information   UE User Equipment (e.g. mobile terminal)   UL Uplink   UMTS Universal Mobile Telecommunications System   UTRAN Universal Terrestrial Radio Access Network       
 
         [0050]    The use of mobile wireless devices for receiving data is gaining in importance, and the delivery of video data is consuming a larger and larger share of available wireless capacity, both because of its popularity and because video applications inherently consume relatively great amounts of data. In the case of video data, various techniques such as media optimization and adaptive streaming servers promise to significantly increase system capacity and video quality in wireless networks such as 3GPP LTE networks. For example, media optimizer and adaptive streaming servers can manage downloading of video to user equipment, such as a camera phone, smart phone, tablet computer, media play with wireless capability, or the like, just in time to be played. Such an approach avoids waste of resources when a user abandons a video before it is complete, because it avoids transferring data that will never be used. However, a user may frequently be expected to experience a gap in coverage or impaired coverage, so that under some circumstances video will be not be available at the moment it is needed. Delivering data before it is needed, which may be referred to as pre-filling data, will avoid interruption or degradation of video quality. This discussion will be presented primarily in terms of video data, but it will be recognized that the mechanisms described here may be applied to any circumstances in which data is typically delivered as needed in order to use transmission capacity efficiently, but in which conditions are evaluated to determine whether data should be delivered before it is immediately needed. 
         [0051]    The need for pre-filling of data will vary based on the particular circumstances of a UE. In addition, turning to the example of video data, much video data is configured so as to be playable only by a single UE, as in the case in which video is encrypted with a key provided only to a single UE or a few UEs, or in the case in which digital rights management (DRM) is used, so that video is configured to be transferable only to a single UE. 
         [0052]    If video data is to be reliably delivered, however, accommodations must be made for areas experiencing poor coverage or significant loads, interfering with the ability of a UE to receive data just in time for playback. Under such circumstances, it is desirable for the UE to receive data during times when it may be efficiently delivered, so that the data will be available for playback during a period of slow or no delivery. 
       SUMMARY 
       [0053]    In one embodiment of the invention, an apparatus comprises at east one processor and memory storing computer program code. The memory storing the computer program code is configured to, with the at least one processor, cause the apparatus to at least analyze conditions affecting a wireless communication device receiving data from a data communications network and, based on the analysis of the conditions, determine needed adjustments to delivery of the data to the wireless communication device. 
         [0054]    In another embodiment of the invention, a method comprises analyzing conditions affecting a wireless communication device receiving data from a data communications network and, based on the analysis of the conditions, determining needed adjustments to delivery of the data to the wireless communication device. 
         [0055]    In another embodiment of the invention, a computer readable medium stores a program of instructions, execution of which by a processor configures an apparatus to at least analyze conditions affecting a wireless communication device receiving data from a data communications network and, based on the analysis of the conditions, determine needed adjustments to delivery of the data to the wireless communication device. 
         [0056]    These and other embodiments of the invention are described below with particularity. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0057]    For a better understanding of the nature and objects of the present invention, reference is made to the following detailed description taken in conjunction with the following drawings, in which: 
           [0058]      FIG. 1  illustrates an exemplary wireless communication system according to an embodiment of the present invention; 
           [0059]      FIG. 2  illustrates network elements according to an embodiment of the present invention; and 
           [0060]      FIG. 3  illustrates a process according to an embodiment of the present invention. 
       
    
    
     DETAILED DESCRIPTION 
       [0061]    A new method, apparatus, and software related product, such as a computer readable medium, are presented for controlling pre-filling of video data to a user equipment by a wireless network for playback by the user equipment. It is noted that in the following, for the purpose of this invention, the term “video data” may be equivalent to “video clips”, “video”, “video/audio data”, “media”, “media data”, “video and audio data” or “audio data”. It will be recognized that while the network provides data, the decisions for when data is to be requested are generally made by the UE, and one or more embodiments of the present invention provide mechanisms to deliver predictions and other information to the UE that the UE may use to determine when pre-filling of data should be requested. The UE may determine when to request pre-filling of information based on the predictions and other information received from the network. 
         [0062]    In an exemplary embodiment, a macro network such as a third generation preferred partnership (3GPP) long term evolution (LTE) network may comprise a content aware network (CAN) gateway. Such a gateway may, for example create a content aware network enabling gateway (CAN-EG.) The network may also comprise a media optimizer or content servers, evolved Node B (eNB) and other network entities of the radio access network or the core network. It is also noted that the term eNB is commonly applied to LTE networks. However, the exemplary embodiments are not limited to LTE and may be applied to other radio access technologies such as GSM/UMTS (global system for mobile communications/universal mobile telecommunications system), CDMA (code division multiple access) and LTE-A (LTE-advanced). 
         [0063]      FIG. 1  illustrates a block diagram of an exemplary system comprising elements and using techniques according to one or more embodiments of the present invention.  FIG. 1  presents an example of a video server-radio access network (RAN) interfaced architecture for a macro cell. The architecture shows a user equipment  110  communicating via a wireless connection  105  (including uplink and downlink) to a network  100 . The network  100  includes an eNode B  120 , a (centralized) self optimizing network (SON or C-SON) server  112 , a serving gateway (SGW)  125 , a mobility management entity (MME)  115 , an operations and management entity  118 , a policy and charging rules function (PCRF) network element  130 , a packet data network gateway (PDN-GW)  135 , a content aware network-enabling gateway (CAN-EG)  145 , a media optimizer  150 , and video server(s)  160 . The network  100  is coupled to the Internet  140  and in particular to a content source  165  in the Internet  140 . The self-optimizing network is connected to the CAN-EG  145  using an interface  112 A and to the PCRF element  130  using an interface  112 B. 
         [0064]    The eNodeB  120  is connected to the SGW  125 . The connection may be accomplished, for example, by an S1-U interface  181 . The SGW  125  is connected to the PDN-GW  135 , for example, by an S5/S8 interface  182 . The SGW  125  is also connected to the PCRF  130 , for example, by a Gxx/Gxa interface  184 . The SGW  125  is further connected to the MME  115  for example, by an S11 interface  186 . The PDN-GW  35  is connected to the PCRF  130 , for example, by a Gx interface  188 . The Internet  140  is connected to the CAN-EG  145 , the media optimizer  150 , the video server(s)  160 , and the PDN-GW  135  via multiple networks  166  implementing at least internet protocol (IP) interfaces. A network  175  implements, for example, a diameter protocol (providing, for example an authentication, authorization and accounting (AAA) framework) over a stream control transmission protocol (SCTP) and a transport layer protocol. A network  170  between the CAN-EG and the eNodeB  120  may implement a GTP-U interface. GTP-U is a GPRS tunneling protocol user plane. As is known, GTP-U protocol is used over S1-U, X2, S4, S5, and S8 interfaces of the Evolved Packet System (EPS). The network  100  may also include an Interface Reference Point (IRP) manager  180  and an IRP agent  182 . The IRP manager  180  will be able to control self-optimization functions, and the IRP agent  182  will provide for a capability for the IRP manager to know the success or failure of self-optimization functions. 
         [0065]    It is noted that the entities in the network  100  are merely exemplary, and there may be different, fewer, or more entities. Also network elements shown in  FIG. 1  may be located in different parts of the network. Furthermore, the various networks and the corresponding implementation of interfaces and/or protocols are also merely exemplary. It should also be noted the elements of the “radio access network” (RAN) are radio access technology (RAT) specific. For instance, in LTE, network is defined as EUTRAN/EPC (Enhanced UTRAN/Enhanced Packet Core). The eNodeB may be the only component of the RAN/EUTRAN, whereas the MME, SON (or C-SON), SGW, PDN-GW, PCRF may be parts of the EPC. In UMTS, the Node B and the RNC (radio network controller) are part of the RAN while the SSGN, GGSN, PCRF are part of the core. 
         [0066]    In this example, the UE  110  may connect to the content source  165  in the Internet  140  to download video via the media optimizer  150 . Optimized content is streamed from the media optimizer  150  or video server  160  to the PDN-GW  135  which forwards the content to the SGW  125  and finally through the eNodeB  120  to the UE  110 . The CAN-EG may allow the video server  160  and media optimizer  150  to establish and modify the bearer characteristics between the PDN-GW  135  and the UE  110  by making the requests via the CAN-EG  145 . The CAN-EG  145  may also collect network metrics from the eNodeB  120  and other network elements and report these to the media optimizer  150  and video server  60 . Additionally the media optimizer  150  and video servers  160  may communicate with the eNodeB  120  using the network  170  via the CAN-EG. The video server(s)  60  in this example act to cache video from the content source(s)  165 . As such, the video server(s)  160  may be considered surrogate servers, since these servers  160  contain cached copies of the videos in the content source  165 . 
         [0067]    Also “small” cell architectures, such as pico or femto cells (e.g., for LTE-A) may be used for practicing exemplary embodiments of the invention, using, for instance, “zone” eNB (ZeNB) controller (controlling multiple eNBs) and content delivery network (CDN) surrogate. 
         [0068]    In one embodiment of the invention an SON algorithm residing on at least one network element, such as a C-SON server, Node B or eNB, or MME of a wireless network such as the wireless network  100  of  FIG. 1  may monitor and determine conditions affecting a UE when the UE is receiving and playing video data. Conditions may be associated with or may affect an information capacity, load, or throughput, of a communication channel, or with a cost of transmitting information from an application through the wireless network to the UE. Such a cost may depend on factors such as the modulation scheme being used, and may be expressed, for example, in terms of cost per bit of information. 
         [0069]    The wireless network  100  serves a plurality of UEs such as the UE  110 , which will be discussed here as an exemplary UE receiving video data, and the UEs  172 A- 172 E, which are also receiving network services and whose use of resources affects the resources available to the UE  110 . The UEs  110  and  172 A- 172 E may have different relationships to the network  100 , such as different guaranteed service levels, and may also experience conditions and events that change over time and that differ among the different UEs. The wireless network  100  may implement a policy administered by the operations and management entity (OME)  118 , the IRP manager  180 , and the IRP agent  182 . The IRP agent  180  may support the capability for the IRP manager to define policy directions in case self-optimizing network functions request conflicting parameter values. If no policy directions are given, the IRP agent may apply default policy directions. 
         [0070]    A policy direction describes an expected behavior from the IRP agent  182 . Examples for such policy directions include prioritizing SON functions in case of conflicts, prohibiting further changes of a parameter for a specific amount of time, selecting preferred value ranges, or directing the IRP agent  182  to report conflicts. If the IRP agent  182  does not resolve the case in which SON functions request conflicting values for parameters, the IRP agent  182  allows for a capability for the IRP manager  182  to determine parameter values. 
         [0071]    The IRP agent  182  may support a capability allowing the IRP manager  180  to configure the SON coordination policy. The coordination includes coordination between different self-optimizing functions and coordination between different targets within one self-optimizing function. 
         [0072]    The policy may define the conditions that are taken into account when making predictions and the UEs to which predictions are delivered. If a prediction causes video data to be delivered to a UE for pre-filling, the making of the prediction and its delivery to the UE and the UE&#39;s subsequent action in response to the prediction may have a significant impact on the availability of resources to other UEs. 
         [0073]    Therefore, mechanisms according to one or more embodiments of the present invention define the conditions under which a prediction relating to pre-filling of data should be delivered to a UE and mechanisms for such delivery. In addition, one or more embodiments of the present invention define mechanisms for the UE to interpret and act on such predictions. 
         [0074]    A number of factors taken into account in making predictions may have to do with factors such as the quality of service to which the UE is entitled, the likelihood that the particular UE in question will encounter degraded conditions that will impair timely delivery of data, or that the UE will encounter above-average conditions so that it can receive buffered data without excessive impact on others. The predictions may vary based on the time period taken into account, and the time for which the predicted events or conditions are expected to last. Predictions may be made based at least in part on specific network rules for self-optimization. Predictions may be made at the level of the network as a whole, at a cell, taking into account both conditions in the macro cell and in overlapping smaller cells such as micro and pico cells, and the performance of a specific eNodeB, and the conditions affecting its operation. 
         [0075]    In one or more embodiments of the invention, the eNB  120  may perform its own measurements and receive measurements from UEs such as a UE that is receiving or will receive video data. In the present example, this may be the UE  110 . The eNB  120  may also receive measurements from other UEs in the environment, such as the UEs  172 A- 172 E. Appropriate network elements analyze the measurements and make predictions based, for example on service levels. A service level involves factors such as a rate and quality of data delivery that can be provided to the UE  110 . Predictions relating to changes in service, which may constitute either degradations or improvements in service, are communicated to a UE that is receiving or will receive video data. In the present example this may be the UE  110 . 
         [0076]    For example, a network element may determine based on measurements made by the UE  110 , that the UE is approaching a coverage hole. A coverage hole may be defined as an area of significantly diminished coverage relative to the network average. The network element may determine that the UE should pre-fill data while still in an area of greater coverage, based at least in part on a cost calculation in which communication in an area of low coverage is assigned a higher cost than in an area of higher coverage. Similarly, areas or times of high network loading may be assigned a higher cost than areas or times of low network loading, and a network element may determine that the UE should pre-fill data while in an area of low network loading or at a time of low network loading. Numerous other factors influencing decisions relating to the desirability of pre-filling data by the UE may be taken into account, exemplary ones of which are discussed below. 
         [0077]    The network  100  delivers information that can be interpreted by the UE as indicating a need to pre-fill data or otherwise take steps to maintain the quality of the user&#39;s experience. Upon receiving the information, which may include predictions of impairment or explicit indications that data should be pre-filled, the UE makes the information available to mobile applications through an application programming interface. 
         [0078]    One or more network elements may be used to make predictions that can be used to determine when a UE should request data. Such predictions may be specific to a particular UE, and may depend, for example, on the status of a UE. Various specific network entities may enter into the decisions relating to how the predictions are made and communicated. For example, the network may use or create specific controls, targets, or key performance indicators determining specific characteristics of the predictions that are to be made. Such predictions may be provided to specific UEs based on determinations made by appropriate network elements. For example, the operations and management entity (OME)  118  may set a policy controlling which predictors are disclosed to which UEs. 
         [0079]    For example, if a UE is entitled to an elevated level of service, more network resources may be dedicated to delivering video data to the UE, so that the prediction increases the likelihood that the UE will receive data before it is needed. Predictions may also take into account specific events associated with particular UEs, such as movement of the UE toward a location providing poor coverage or, on the other hand, movement of a UE into or out of a location providing unusually good coverage. 
         [0080]    The desirability of pre-filling video may be evaluated based on expected communication costs, with the cost being expressed in terms of the communications resources needed to deliver the video. If the UE  110  is in an area of good coverage, pre-delivering video, even if that video is abandoned, may be less costly than delivering video just in time for playback. 
         [0081]    Predictions may include or be based on a number of factors or events. Factors may include anticipated call drop, which may be based on radiofrequency conditions, measurements, UE reports, and the like. Another factor ma include anticipated quality of service degradation, that is, that the network is unable to support the UEs required quality of service in terms of throughput, time budget, or similar parameters. Possible events may be energy savings events, such as cell shutdown, or anticipated handover, which might be inter-radio access technology (iRAT) or other similar events, leading to temporary degradation. 
         [0082]    In a distributed self-optimizing network such as the network  100 , the IRP agent  182  may support a capability for the IRP manager  180  to define the UE notification policy by SON functions, where an SON function may predict a service degradation or improvement affecting a UE such as the UE  110 . The policy may include specific event types, might provide targets, key performance indicators (KPIs) and thresholds, controls, and the like. The policy may also include a specific depth of prediction, expressed in terms of time, and specific self-optimizing network functions. The policy may also include an architectural level of prediction, such as the eNodeB, cell, or other level of prediction, and may designate specific UE groups, for example, based on quality of service level. 
         [0083]    For centralized or hybrid SON, OME and C-SON servers, and the IRP manager  180  and IRP agent  182  might provide higher level or higher scale predictions, such as energy savings, cell or system boundaries, and the like. In one or more embodiments of the invention, the predictions are provided as part of a premium service, such as a general higher level of service or a specific service directed to providing and acting on predictions so as to prevent interruption of a user&#39;s video. 
         [0084]    Once the UE has determined that a service degradation is expected or that, for other reasons, it should take actions to maintain the quality of the user&#39;s experience or to minimize transmission costs, it can take any of a number of actions. One possible action is pre-filling video or audio data while still experiencing satisfactory or better than usual conditions. Another possible action that can be taken is to postpone activities requiring heavy data usage until poor conditions have ended. One condition under which such an action may be particularly appropriate is during or on the threshold of a handover. The UE can be expected to be at the edge of a cell, and may expect to experience better conditions while in its new cell. 
         [0085]    An appropriate network element, such as the operations and management entity  118 , may prepare a message for the UE  110  indicating that the UE should pre-fill data. The message may include information such as estimated time until impairment, estimated duration of impairment, or other relevant information. The amount of pre-fill will be influenced by the amount of video watched so far, and the probability of abandonment will also change depending on the amount of video watched. Another factor may be the setup and loading time, because if a user has waited through a longer setup time, he or she will be more likely to watch the video all the wax through. Another factor that may be taken into account includes abandonment history for a particular user. If a user has a history of abandoning videos after a short time, the likelihood that the UE will need to pre-fill data can be substantially reduced by comparison to users that tend to watch videos to the end. 
         [0086]    A radio access network predicts an impairment of the air interface and the UE  110  is notified of the prediction, such as by an eNodeB. The prediction may come in the form of a message including information such as an estimated time until the impairment, the estimated duration of the impairment, and other related information. As an example, the message can be a radio resource control message, and the UE passes the indication, as well as any additional information included in or with the indication, to upper layers for handling. 
         [0087]    In one example of the operation of a network such as the network  100 , the following assumptions may be made: 
         [0088]    Cell radius—0.6 km 
         [0089]    Cell to cell distance—approximately 1 km. 
         [0090]    Mobility model
       30% “mobile users” (traveling at &gt;30 kmph)   70% “static users” (traveling at &lt;30 kmph)       
 
         [0093]    Number of access attempts overall (all users in all RF conditions) N 
         [0094]    Cost of initiating a service: Y information bits 
         [0095]    Modulation: QPSK and QAM 
         [0096]    QPSK—“bad” RF 
         [0097]    QAM—“good” RF 
         [0098]    “bad RF”—QPSK—average symbols/information bit=1.9 
         [0099]    “good RF”—QAM—average symbols/information bit=0.4 
         [0100]    Pre-filling video allows for the carrying of services in good RF conditions, when without pre-filling, such services would be carried in bad RF conditions. For example, assume that an average “mobile” user, currently in good RF conditions, will be in bad RF conditions within approximately the next two minutes or less, which is the time required to travel 1 km at 30 kmph. If 30% of the users are mobile users, then allowing pre-filling of video allows for 30% of services to be carried under good RF conditions, that would otherwise be carried under bad RF conditions. 
         [0101]    Defining differences in terms of an RF cost of access attempts, then the cost of access attempts without pre-filing is: 
         [0000]      ( N/ 3*0.4 Y )+(2 N/ 3*1.9 Y )=1.4 *N*Y.    
         [0102]    The costs of access attempts with pre-filing allowed is: 
         [0000]      ( N/ 3*0.4 Y )+(0.3*2 N/ 3*0.4 Y )+(0.7*2 N/ 3*1.9 Y )=1.1 *N*Y.    
         [0000]    Allowing pre-filling of data according to embodiments of the present invention thus allows for a 21% improvement. 
         [0103]    In one or more embodiments of the present invention, evaluations may be conducted to determine when a UE such as the UE  110  is in an area of favorable coverage, such as in close proximity to an eNB or in a less loaded cell, that is, a cell with fewer user devices competing for resources provided by the eNB. Under such circumstances, pre-filling may be desirable because if the UE  110  is in an area of exceptionally favorable conditions, it is likely that the UE will shortly move to an area of less favorable coverage. This is true because if conditions are above average or well above average, any change is likely to lead to conditions nearer the average. Under these circumstances, the savings in cost is similar to that determined in the scenario above, and it will be recognized that differences in conditions, such as a different number of mobile versus static users, or a difference in the average symbols per information bit in bad RF versus good RF, will result in changes in the comparative costs. 
         [0104]    An additional mechanism for improving a user&#39;s experience is compression of video in areas of poorer service. When a UE such as the UE  110  is expected to experience degradation of service, one response, which can be undertaken as an alternative or in addition to pre-filling data, is an increase in the compression of data. Compression of data may be performed by the eNB or other network elements before transmission, decreasing the transmission resources required. Effective compression of data such as video data is likely to require some loss of data, leading to a degradation in quality, so one approach is to increase compression only when the UE is in, or is expected to enter, a cell-edge area. 
         [0105]      FIG. 2  illustrates details of a UE  201  and a network element, such as an LTE element,  202 . The network element  202  may be a SON, C-SON, eNB, CAN-EG MME, OME, IRP agent, IRP manager, or other appropriate network element. The UE  201  comprises a transmitter  203 , receiver  204 , radiocontroller  206  and antenna  208 . The UE  201  also includes a processor  210 , memory  212 , and storage  214 , communicating with one another and with the radiocontroller  206  over a bus  216 . The UE  201  employs data  218  and programs  220 , suitably residing in storage  214  and transferred to memory  212  as needed for use by the processor  210 . The network element  202  comprises a transmitter  222 , receiver  224 , radiocontroller  226  and antenna  228 . The network element  202  also includes a processor  230 , memory  232 , and storage  234 , communicating with one another and with the radiocontroller  226  over a bus  236 . The network element  202  employs data  238  and programs  240 , suitably residing in storage  234  and transferred to memory  232  as needed for use by the processor  230 . 
         [0106]    Among the programs  240  employed by the network element  202  comprise an information collection module  241  for monitoring conditions affecting a UE of interest, such as the UE  201  and an information analysis module  242 , which may analyze information to make predictions relating to future conditions and determine if the UE should pre-fill data. The network element  202  also includes a signal generating module  244  for generating appropriate signals. The network element  202  includes a video delivery module  246 , which responds to requests from the UE and delivers video data to fulfill the requests. 
         [0107]    The UE  201  comprises a conditions reporting module  250 , reporting channel conditions to the network element  202 , as well as an eNB signal analysis module  252 , which receives signals from the network element  202  such as signals indicating predictions that channel conditions will be impaired or simply that a UE should take steps to improve or maintain the user&#39;s video experience, such as by pre-filling data, compressing data, or pausing activities requiring heavy data use. The network element signal analysis module  252  examines the signals from the network element  202  and chooses an appropriate response. The UE  201  further comprises a video management module  254 , which directs appropriate actions, such as requesting additional video data, increasing compression, pausing activities requiring a heavy data load, and so on. The video management module  254  manages receiving and playing of video data as needed to provide for a smooth video delivery to the user. 
         [0108]    Various embodiments of the memory  212  and  232  and storage  214  and  234  may include any data storage technology type which is suitable to the local technical environment, including but not limited to semiconductor based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory, removable memory, disc memory, flash memory, DRAM, SRAM, EEPROM and the like. Various embodiments of the processor  210  and  230  include but are not limited to general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) and multi-core processors. 
         [0109]    The various modules  242 - 246  and  250 - 254  may each be implemented as an application computer program stored, for example in the memory  212  and  232  and storage  214  and  234 , but in general they may be implemented as software, firmware or hardware modules or a combination thereof. In particular, in the case of software or firmware, one embodiment may be implemented using a software related product such as a computer readable memory such as a non-transitory computer readable memory, computer readable medium or a computer readable storage structure comprising computer readable instructions such as program instructions using a computer program code. The computer program code may be, for example, the software or firmware) stored on the computer readable memory and may be thereon to be executed by a computer processor. 
         [0110]    Furthermore, the modules  242 - 246  and  250 - 254  may be implemented as separate blocks or may be combined with any other modules or blocks of the module may be split into several blocks according to their functionality. Moreover, it is noted that all or selected modules of the module may be implemented using an integrated circuit by, for example, using an application specific integrated circuit, or ASIC. 
         [0111]      FIG. 3  illustrates a process  300  according to an embodiment of the present invention. It will be noted that the particular order of steps illustrated here is exemplary only and that steps may be skipped, different steps may be added or substituted, or selected steps or groups of steps may be performed in different processes. At step  302 , elements of a network such as a self-optimizing network similar to the network  100  of  FIG. 1  make and receive measurements relating to network conditions affecting at least one UE as the conditions affect the receiving of video data by the at least one UE. At step  304 , network elements evaluate the conditions, taking into account factors such as coverage, the motion of the UE in question into an area of better service or worse service, demands by other UEs for resources, and other relevant factors. One or more network elements make determinations as to whether actions need to be taken to maintain the user&#39;s experience, such as by pre-fling video, compressing video, suspending applications presenting a higher demand for data, and the like. The determination may be made in part based on an expected likelihood that the user will abandon the video. At step  306 , network elements signal the UE, providing the UE with an indication and relevant information as to whether there is a need to take action to maintain the user&#39;s video experience. At step  308 , the UE makes information received in the signal available to mobile applications using video, suitably through an application programming interface. At step  310 , applications request video data from the network for pre-tilling or take other action as needed. 
         [0112]    An apparatus according to an embodiment of the invention analyzes conditions affecting a user equipment receiving data from a data communications network, analyzes the conditions to determine if the UE should take measures to maintain or improve data delivery, or to take advantage of favorable conditions, and sends information to the UE indicating if the UE should take such measures. 
         [0113]    In one embodiment of the invention, the apparatus analyzes present conditions. 
         [0114]    In one embodiment of the invention, the apparatus analyzes predicted conditions. 
         [0115]    In one embodiment of the invention, the apparatus analyzes future conditions. 
         [0116]    In one embodiment of the invention, the apparatus analyzes at least one of present, predicted, and future conditions. 
         [0117]    In one embodiment of the invention, the data is video data. 
         [0118]    In one embodiment of the invention, sending of information to the UE is performed according to a notification policy. 
         [0119]    In one embodiment of the invention, the notification policy is defined by at least one self-optimizing network function. 
         [0120]    In one embodiment of the invention, at least one self-optimizing network function predicts a service degradation affecting the UE. 
         [0121]    In one embodiment of the invention, at least one self-optimizing network function predicts a service improvement affecting the UE. 
         [0122]    In one embodiment of the invention, the policy defines at least one specific event type. 
         [0123]    In one embodiment of the invention, the policy defines a performance of at least one action based on at least one target. 
         [0124]    In one embodiment of the invention, the policy defines at least one key performance indicator. 
         [0125]    In one embodiment of the invention, the policy defines at least one threshold. 
         [0126]    In one embodiment of the invention, the policy defines at least one control. 
         [0127]    In one embodiment of the invention, the policy includes a specific depth of prediction. 
         [0128]    In one embodiment of the invention, the depth of prediction is expressed in terms of time. 
         [0129]    In one embodiment of the invention, the policy is expressed in terms of at least one specific self-optimizing network function. 
         [0130]    In one embodiment of the invention, the policy includes an architectural level of prediction. 
         [0131]    In one embodiment of the invention, the policy designates at least one user equipment group. 
         [0132]    In an apparatus according to one embodiment of the invention, the information is sent to the UE in the form of a signal. 
         [0133]    In an apparatus according to one embodiment of the invention, maintaining data delivery by the user equipment comprises requesting data to be delivered before it is needed so that the data will be available during slow or interrupted service. 
         [0134]    In an apparatus according to one embodiment of the invention, the data to be delivered is video data and the data is delivered before it is needed for playback. 
         [0135]    In an apparatus according to one embodiment of the invention, maintaining data delivery by the user equipment comprises requesting data during favorable conditions. 
         [0136]    In an apparatus according to an embodiment of the invention, analyzing conditions comprises determining if the user equipment is likely to encounter degraded service. 
         [0137]    In an apparatus according to an embodiment of the invention, analyzing conditions comprises taking into account a likelihood that a user will abandon receiving the data. 
         [0138]    In an apparatus according to an embodiment of the invention, the information comprises air interface signaling. 
         [0139]    In an apparatus according to an embodiment of the invention, the information comprises a radio resource control message. 
         [0140]    In an apparatus according to another embodiment of the invention, the information comprises a media access control message. 
         [0141]    In an apparatus according to one embodiment of the invention, the information is delivered in an application layer. 
         [0142]    In an apparatus according to one embodiment of the invention, the information is delivered in a network layer. 
         [0143]    In an apparatus according to one embodiment of the invention, delivery of the information comprises using an application for delivery. 
         [0144]    In an apparatus according to one embodiment of the invention, the information is received and processed using an application residing in the user equipment. 
         [0145]    In one embodiment, the message comprises an indication that an air interface with the user equipment is expected to become impaired. 
         [0146]    In another embodiment, the information relates to the impairment. 
         [0147]    In another embodiment, the information comprises information relates to an estimated time until impairment. 
         [0148]    In another embodiment, the apparatus selects a user equipment to receive the information based on a level of service to which the user equipment is entitled. 
         [0149]    In another embodiment, the analysis takes into account anticipated quality of service degradation. 
         [0150]    In another embodiment, the analysis takes into account anticipated handover. 
         [0151]    In an embodiment of the invention, an apparatus receives a signal from a network element indicating a need to take measures to maintain delivery of data and responds to the signal by managing data retrieval from the network so as to continue delivery of data under conditions indicated by the signal. 
         [0152]    In an embodiment of the invention, the apparatus responds to the signal by requesting the network to deliver data for pre-filling. 
         [0153]    In an embodiment of the invention, the apparatus responds to the signal by requesting increased data compression. 
         [0154]    In an embodiment of the invention, the apparatus responds to the signal by suspending activities of high data demand. 
         [0155]    In an embodiment of the invention, the signal includes a prediction of degradation of channel conditions. 
         [0156]    In an embodiment of the invention, the signal includes information indicating that the apparatus is experiencing favorable conditions. 
         [0157]    In an embodiment of the invention, information relating to quality of channel conditions is based at least in part on a cost measurement. 
         [0158]    It is noted that various non-limiting embodiments described herein may be used separately, combined or selectively combined for specific applications. 
         [0159]    Further, some of the various features of the above non-limiting embodiments may be used to advantage without the corresponding use of other described features. The foregoing description should therefore be considered as merely illustrative of the principles, teachings and exemplary embodiments of this invention, and not in limitation thereof. 
         [0160]    It is to be understood that the above-described arrangements are only illustrative of the application of the principles of the present invention. Numerous modifications and alternative arrangements may be devised by those skilled in the art without departing from the scope of the invention, and the appended claims are intended to cover such modifications and arrangements.