Abstract:
An adaptive handover method in a heterogeneous network environment collects estimation information for a channel environment and integrates with a wireless device&#39;s geographic information to decide two groups of recursive parameters and a channel theoretical signal model. The model and the first group of recursive parameters are used to execute recursive iteration for a signal strength decay theoretical value. The obtained actual signal strength decay value from channel estimation, the second group of recursive parameters and the signal strength decay estimation value at previous iteration are used to execute channel-tracking recursive iteration for obtaining a signal strength decay tracking value. The current network status and the signal strength decay tracking value are used to predict and analyze system performance of heterogeneous networks. A decision is made based on each heterogeneous network&#39;s analyzed result, and an adaptive handover procedure is prepared by following the decision.

Description:
FIELD OF THE INVENTION 
     The present invention generally relates to an adaptive handover apparatus and method in a heterogeneous network environment. 
     BACKGROUND OF THE INVENTION 
     The rapid progress of wireless communication in recent years extends the information and communication services from digital homes to mobile lives. Different types of wireless communication technologies are widely applied to daily lives so that the demands in accessing internet resources through wireless devices also increase. 
     The current wireless communication technologies follow three major trends. First, wireless communication service providers are moving from providing pure voice service, such as GSM, to IP-based network service, including integrating voice, high speed data and multimedia streaming, such as GPRS and 3.5G. Second, broadband network communication providers are moving from providing local packet-switched internet service, such as ADSL, WiFi, to providing mobile communication/internet full service, such as DSRC, WiMAX. Third, information communication service system integrators are using information and communication technology (ICT) to provide new applications and services and IT-enabled service-based service integration technology and extend to the developments of all types of handheld mobile devices to offer real time streaming services in heterogeneous network environments. 
     The personal mobile service market is also expanding from three major directions, including first, the provision of real time multimedia entertainment on demand service, such as the user using portable device to request service from a remote server individually and ubiquitously and obtaining multimedia service, such as audiovisual replay and global positioning system (GPS); second, having the integration capability of multiple communication network interfaces, such as portable devices with different network communication interfaces able to switch in different environment to maintain optimal communication state; and third, the provision of seamless roaming in heterogeneous network environment, such as user of portable device able to obtain personal service at home, community or in mobility, towards the ubiquity and quality of service regardless of the change of network access. 
     Take the implementation of adaptive handover mechanism of service roaming in heterogeneous network as an example. U.S. Patent Publication No. 2007/0133472 disclosed a method of vertical handoff to predict the received signal strength (RSS) of a single system to realize the handoff in heterogeneous network. As shown in  FIG. 1 , the method of vertical handoff aims at the wireless network of a single small area and uses the least square (LS) algorithm, i.e., least square line  120 , to predict the future RSS transition pattern  110  to achieve the handoff in heterogeneous network. 
     However, to achieve ubiquitous roaming in short, medium and long range heterogeneous network, one of the important issues is how to achieve seamless handover in different heterogeneous networks effectively and rapidly. Based on the integration service technology of mobile heterogeneous networks and targeting different heterogeneous network environments, it is important to integrate the channel estimation information to estimate the change of adaptive signal-tracking decay in addition to designing algorithm so as to improve the estimation handover correctness and reduce the system computation load. 
     SUMMARY OF THE INVENTION 
     The disclosed exemplary embodiments of the present invention may provide an adaptive handover apparatus and method, applicable to different heterogeneous network environments. 
     In an exemplary embodiment of the present invention, the disclosed is directed to an adaptive handover apparatus in a heterogeneous network environment. The adaptive handover apparatus comprises an adaptive model control unit, a power gain prediction unit, a heterogeneous networks analysis unit and a handover decision unit. 
     When a wireless device is activated, the adaptive model control unit collects the estimation information of the channel environment and integrates the geographic information of the wireless device to determine two groups of recursive parameters and a channel theoretical signal model. The power gain prediction unit executes recursive iteration for a signal strength decay theoretical value according to the channel theoretical signal model and the first group of recursive parameters. The power gain prediction unit also executes recursive iteration on channel-tracking for obtaining a signal strength decay tracking value through the obtained actual signal strength decay value from channel estimation, second group of recursive parameters and the signal strength decay estimation value at previous iteration. The heterogeneous networks analysis unit predicts and analyzes system performance of heterogeneous networks via the current network status and the signal strength decay tracking value. Based on the analyzed result, prediction time is also regulated. The handover decision unit makes a final decision based on each heterogeneous network&#39;s analyzed result, and an adaptive handover procedure is prepared by following the decision. 
     In another exemplary embodiment of the present invention, the disclosed is directed to an adaptive handover method in heterogeneous network environments. The adaptive handover method comprises: collecting channel environment estimation information and integrating with a wireless device&#39;s geographic information to decide a first and a second groups of recursive parameters and a channel theoretical signal model; based on the model and the first group of recursive parameters, executing recursive iteration for a signal strength decay theoretical value, and based on the obtained actual signal strength decay value from channel estimation, second group of recursive parameters and the signal strength decay estimation value at previous iteration, executing recursive iteration on channel-tracking for obtaining a signal strength decay tracking value; based on the current network status and the signal strength decay tracking value, predicting and analyzing system performance of heterogeneous networks, and based on the analyzed result, regulating prediction time of estimating heterogeneous network signal strength decay; and based on each heterogeneous network&#39;s analyzed result, making a final decision and based on the decision, preparing for an adaptive handover procedure. 
     The foregoing and other features, aspects and advantages of the present invention will become better understood from a careful reading of a detailed description provided herein below with appropriate reference to the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  shows a schematic view of an exemplary vertical handoff method. 
         FIG. 2  shows an exemplary schematic view of an adaptive handover apparatus in a heterogeneous network environment, consistent with certain disclosed embodiments of the present invention. 
         FIG. 3  shows an exemplary schematic view illustrating the operation of the adaptive handover apparatus of  FIG. 2  in heterogeneous network environment, consistent with certain disclosed embodiments of the present invention. 
         FIG. 4  shows an exemplary schematic view of the detailed structure and operation of the power gain prediction unit, consistent with certain disclosed embodiments of the present invention. 
         FIG. 5  shows an exemplary schematic view illustrating the operation flow of an adaptive handover method, by using an exemplary algorithm like least mean square (LMS), consistent with certain disclosed embodiments of the present invention. 
         FIG. 6  shows a schematic view of a comparison of exemplary simulated performances between the present invention and a conventional vertical handoff method. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       FIG. 2  shows an exemplary schematic view of an adaptive handover apparatus  200  in a heterogeneous network environment, consistent with certain disclosed embodiments of the present invention. As shown in  FIG. 2 , adaptive handover apparatus  200  comprises an adaptive model control unit  201 , a power gain prediction unit  203 , a heterogeneous networks analysis unit  205  and a handover decision unit  207 . 
     Adaptive handover apparatus  200  is applicable to diverse heterogeneous network environment, such as, IP-based network, packet-switched network, and so on, and is applicable to predict the signal strength decay in the handover process in the heterogeneous network environment. The exemplary embodiment of the present invention uses an algorithm, such as least mean square (LMS), as a core to establish a mathematical recursive model, and integrates channel estimation information to estimate the signal strength decay as the basis of performance analysis of heterogeneous network system, as well as prepares adaption switch of communication physical layer and network layer for the channel change to achieve the handover in the diverse heterogeneous network environment effectively and rapidly. 
       FIG. 3  shows an exemplary operation flow of the adaptive handover apparatus  200 , consistent with certain disclosed embodiments of the present invention. The following description refers to both  FIGS. 2 and 3 . When a wireless device starts up, adaptive model control unit  201  first collects estimation information of channel environment  211 , such as signal strength, sign-to-noise ratio (SNR), bandwidth, and so on, and integrates the geographical information of the wireless device, such as through a GPS  212  to obtain the moving speed, relative location of the wireless device, and so on. Then, adaptive model control unit  201  determines a first group and a second group of recursive parameters and a channel theoretical signal model, as shown in step  301 . 
     The first group and the second group of recursive parameters and channel theoretical signal model information may be recorded in an environment information table  213  to provide the required information to the next iteration of power gain prediction unit  203  and heterogeneous networks analysis unit  205 . Adaptive model control unit  201  may be based on the current moving speed of the wireless device for screening usable network systems. 
     Based on the channel theoretical signal model and the first group of recursive parameters, such as recursive parameter μ 1 , power gain prediction unit  203  executes recursive iteration for a signal strength decay theoretical value, as shown in step  302   a . For example, an algorithm is used as a core to establish a mathematic recursive model for recursive computation on the signal strength decay theoretic value. The estimated actual signal strength by channel environment  211 , second group of recursive parameters, such as recursive parameter μ 2  and μ 3 , and the signal strength decay estimation value at previous iteration are used to execute recursive iteration on channel tracking for obtaining a signal strength decay tracking value, as shown in step  302   b . For example, an algorithm is used as a core to establish another mathematic recursive model for the recursive computation on channel tracking. 
     In step  302   a , the recursive computation of the signal strength decay theoretic value may use a least mean square (LMS) algorithm to rectify the signal strength decay estimated value. The signal strength decay estimated value is rectified by referring to the previous iteration of channel theoretical signal model and recursive parameter change estimated by the channel so that the signal strength decay estimated value may be closer to the actual environment. The following equation is an exemplary mathematic recursive model established for the theoretic recursive computation.
 
 Ĝ ( t+Δt )= Ĝ ( t )+μ 1 *( Ĝ   Theory ( t+Δt )− Ĝ ( t ))
 
where Ĝ is the signal strength decay estimated value, Ĝ Theory  is the signal decay theoretic value, t is the current time, Δt is the time difference, and μ 1  is a first group recursive parameter.
 
     In step  302   b , the recursive computation on channel tracking may use LMS algorithm to fine tune the signal strength decay tracking value. The fine tune refers to the aforementioned rectified signal strength decay estimated value and actual measured signal strength decay value, and performs recursive computation on signal strength decay tracking value. With the adaptive tracking channel change, the precise prediction of the signal decay value may be obtained. The following equation is an exemplary mathematic recursive model established for the recursive computation on channel tracking.
 
 Ĝ   Tracking ( t+Δt )= Ĝ   Tracking ( t )+μ 2 *(RSS( t )/TSS( t )− Ĝ   Tracking ( t ))+μ 3 *( Ĝ ( t+Δt )− Ĝ   Tracking ( t ))
 
where Ĝ Tracking  is the signal strength decay tracking value, RSS is the received signal strength, TSS is the transmitted signal strength, and μ 2  and μ 3  are both second group recursive parameters.
 
     Based on the signal strength decay tracking value obtained by power gain prediction unit  203  and the current wireless network state information, such as current network bandwidth and SNR, heterogeneous network analysis unit  205  predicts and analyzes the heterogeneous network performance, as shown in step  303 , to provide the basis for next iteration handover. Based on the result of the prediction and analysis, heterogeneous network analysis unit  205  also adjusts the prediction time of estimating the change on signal strength decay of heterogeneous networks, as shown in step  304 . The prediction time is adjustable. 
     As shown in step  305 , handover decision unit  207  integrates all the result of heterogeneous network performance analysis into a decision and, based on the decision, prepares for the adaptive switch of the heterogeneous network, such as preparing the adaptive switch between the communications physical layer and network layer of heterogeneous networks. 
     After switching to target network, adaptive handover apparatus  200  of the present invention returns to step  301 . In this manner, adaptive handover apparatus  200  and its operation may dynamically adjust the algorithm parameters for the time-dependent environment of the wireless communication to achieve establishing the channel estimation mathematic recursive model and the adaptive signal decay estimation mechanism. 
     Following the above description, power gain prediction unit  203  may be divided into two parts. The first part is to realize the recursive computation on theoretic value and the second part is to realize the recursive computation on channel tracking, marked as  203   a  and  203   b  in  FIG. 2 , respectively.  FIG. 4  further shows an exemplary schematic view of the detailed structure and operation of the power gain prediction unit  203 , consistent with certain disclosed embodiments of the present invention. As shown in  FIG. 4 , power gain prediction unit  203  includes a channel-tracking recursive computation module  403   a  and a theoretic recursive computation module  403   b.    
     Based on channel theoretic model Ĝ Theory  and the first group parameter, such as, μ 1,  provided by step  301  to serve as the input to the mathematic recursive model established for the recursive computation on signal strength decay theoretic value, theoretic recursive computation module  403   b  executes the update of estimated value of the signal strength decay, i.e., Ĝ(t+Δt), so that the signal decay model may be close to the actual environment. 
     Based on the actual signal strength decay value (i.e., RSS(t)/TSS(t)) obtained by channel estimation, second group recursive parameters, such as, μ 2  and μ 3 , and the signal strength decay estimation value Ĝ(t+Δt) estimated at previous iteration to serve as the input to the mathematic recursive model established for recursive computation on channel tracking, channel tracking recursive computation module  403   a  executes signal strength decay prediction tracking Ĝ Tracking (t+Δt). 
     Inputting signal strength decay prediction tracking Ĝ Tracking (t+Δt) to heterogeneous network analysis unit  205  and integrating with the current wireless network state information, as aforementioned, the heterogeneous network performance analysis may be executed. Based on the analysis result, the prediction time of estimating heterogeneous network signal strength decay change may be adjusted. 
     Following the above description,  FIG. 5  shows an exemplary schematic view illustrating the operation flow of an adaptive handover method, by using an exemplary algorithm like LMS, consistent with certain disclosed embodiments of the present invention, where the recursive parameters are (μ 1 , μ 2 , μ 3 ), and the mathematic recursive models are as aforementioned. Therefore, the details of the operation will not be described. 
     It may be seen that the adaptive handover apparatus and method of the present invention uses a plurality of system signals to realize the handover in heterogeneous network environment. Because a plurality of wireless network signal decay ratios is referenced, the stability of handover in heterogeneous network environment may be enhanced. In addition, the use of channel prediction information for mathematic model recursive computation also adaptively tracks the signal decay change; therefore, the correctness rate of the handover in heterogeneous network environment is improved. The use of recursive computation to perform the prediction of mathematic model algorithm also reduces the system computation load and improves the efficiency. 
       FIG. 6  shows a schematic view of a comparison of exemplary simulated performances between the present invention and a conventional vertical handoff method, where the x-axis is the prediction time (s) and y-axis is the matching ratio. The matching means that the network selected by the algorithm is the optimal among all the networks. The matching ratio is the number of matches by the algorithm in a time unit divided by the number of computations by the algorithm in a time unit. 
     The simulation parameters are: 3.5G and WiFi wireless communication interfaces are used, signal strength is the sample for performance analysis by collecting the signal strength change of 3.5G and WiFi in actual environment, and according to different prediction times, the matching ratios for conventional vertical handoff method and the present invention are computed. 
     As shown in  FIG. 6 , compared to the conventional vertical handoff method, the present invention has a higher matching ratio in diverse heterogeneous network environment. In other words, the handover mechanism of the present invention has a better correctness rate for handover prediction. 
     In summary, the disclosed exemplary embodiments of the present invention provide a mechanism for predicting signal strength decay in the handover process applicable to a heterogeneous network environment, such as LMS algorithm, and integrate with the channel estimation information to fine tune the signal strength decay estimation to serve as a basis for heterogeneous network performance analysis. The disclosed exemplary embodiments of the present invention also target the channel change to prepare in advance the adaptive switch between the communication physical layer and network layer so as to achieve the object of handover in the diverse heterogeneous network environment effectively and rapidly. 
     Although the present invention has been described with reference to the exemplary embodiments, it will be understood that the invention is not limited to the details described thereof. Various substitutions and modifications have been suggested in the foregoing description, and others will occur to those of ordinary skill in the art. Therefore, all such substitutions and modifications are intended to be embraced within the scope of the invention as defined in the appended claims.