Patent Publication Number: US-9906898-B2

Title: Method, systems and/or device for adjusting expected received signal strength signature values

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of, and claims the benefit of priority from, U.S. application Ser. No. 13/736,910, entitled “Method, System and/or Device for Adjusting Expected Received Signal Strength Signature Values,” filed on Jan. 8, 2013, which such application is incorporated herein by reference in its entirety. 
    
    
     FIELD 
     Embodiments described herein are directed to mobile navigation techniques. 
     Information: 
     GPS and other like satellite positioning systems have enabled navigation services for mobile handsets in outdoor environments. Since satellite signals may not be reliably received and/or acquired in an indoor environment, different techniques may be employed to enable navigation services. For example, mobile devices may typically obtain a position fix by measuring ranges to three or more terrestrial wireless access points which may positioned at known locations. Such ranges may be measured, for example, by obtaining a MAC ID address from signals received from such access points and measuring one or more characteristics of signals received from such access points such as, for example, received signal strength indicator (RSSI), round trip delay (RTT), just to name a few examples. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Non-limiting and non-exhaustive aspects are described with reference to the following figures, wherein like reference numerals refer to like parts throughout the various figures unless otherwise specified. 
         FIG. 1  is a system diagram illustrating certain features of a system containing a mobile device, in accordance with an implementation. 
         FIG. 2  is a diagram illustrating one embodiment of a heat map. 
         FIG. 3  is a flow diagram illustrating a method by a device in accordance with an implementation. 
         FIG. 4  is a flow diagram illustrating a method by a server in accordance with an implementation. 
         FIG. 5  is a schematic block diagram illustrating an exemplary device, in accordance with an implementation. 
         FIG. 6  is a schematic block diagram of an example computing platform in accordance with an implementation. 
     
    
    
     SUMMARY 
     Briefly, particular implementations are directed to a method for estimating transmission power comprising, at a server: obtaining a measurement of a travel time of a first signal transmitted between a mobile device and a second device; obtaining a measurement of a signal strength of a second signal transmitted by the second device and received at the mobile device; and computing an estimated transmission power of the second device to adjust one or more expected signal strength signature values for application to subsequent signals acquired from the second device, wherein the estimated transmission power is based, at least in part, on the measurement of the travel time and the measurement of the signal strength. 
     Another particular implementation is directed to a server comprising: a memory; and one or more processors in communication with the memory, wherein the one or more processors are configured to: obtain a measurement of a travel time of a first signal transmitted between a mobile device and a second device; obtain a measurement of a signal strength of a second signal transmitted by the second device and received at the mobile device; and compute an estimated transmission power of the second device to adjust one or more expected signal strength signature values for application to subsequent signals acquired from the second device, wherein the estimated transmission power is based, at least in part, on the measurement of travel time and the measurement of the signal strength. 
     Another particular implementation is directed to a non-transitory, computer-readable, storage medium comprising machine-readable instructions stored thereon which are executable by a server to: obtain a measurement of a travel time of a first signal transmitted between a mobile device and a second device; obtain a measurement of a signal strength of a second signal transmitted by the second device and received at the mobile device; and compute an estimated transmission power of the second device to adjust one or more expected signal strength signature values for application to subsequent signals acquired from the second device, wherein the estimated transmission power is based, at least in part, on the measurement of travel time and the measurement of the signal strength. 
     Another particular implementation is directed to a server comprising: means for obtaining a measurement of a travel time of a first signal transmitted between a mobile device and a second device; means for obtaining a measurement of a signal strength of a second signal transmitted by the second device and received at the mobile device; and means for computing an estimated transmission power of the second device to adjust one or more expected signal strength signature values for application to subsequent signals acquired from the second device, wherein the estimated transmission power is based, at least in part, on the measurement of travel time and the measurement of the signal strength. 
     It should be understood that the aforementioned implementations are merely example implementations, and that claimed subject matter is not necessarily limited to any particular aspect of these example implementations. 
     DETAILED DESCRIPTION 
     As pointed out above, a mobile device may apply any one of several techniques for obtaining a position fix based, at least in part, on measurements obtained from acquisition of signals while in an indoor environment. One particular indoor navigation technique involves application of measured characteristics of acquired signals to expected signature values stored in a “radio heatmap.” In one application, a radio heatmap may store expected signature values for multiple discrete locations over an area of interest. These signature values may comprise expected values of received signal strength or round trip time for signals acquired at a mobile device and transmitted by local transmitters. A location of the mobile device may be estimated or approximated as a location indicated in the heatmap associated with the expected signature values providing the closest match with measurements obtained at the mobile device from acquiring signals. 
     A radio heatmap for applying an RSSI value of a signal acquired from a transmitter to an expected RSSI signature value for use in obtaining a position fix may presume a known, predictable or stable transmission power applied at the transmitter. In practice, however, transmission power at a transmitter (e.g., at an IEEE Std. 802.11 access point) may vary or drift over time. For example, transmission power of a transmitter at an IEEE Std. 802.11 access point may vary up to 21.0 dBm (−1.0 dBm to 20.0 dBm). This process of drift in transmit power often occurs slowly over hours or days. Nevertheless, such a variation in transmission power at a transmitter may affect accuracy of received signal strength indicator RSSI expected signature values in a radio heatmap. 
     According to an embodiment, a radio heatmap for signal strength signature values may be updated from time to time based, at least in part, on measurements obtained by mobile devices capable of obtaining both RTT measurements and RSSI measurements. These values may be based, at least in part, on observed changes in transmission power at a transmitter. A mobile device may obtain an RTT measurement with respect to a transceiver by transmitting a probe signal and receiving an acknowledgement message from the transceiver in response to probe signal. In the absence of multi-path and with knowledge of a processing latency at the transceiver in acquiring the probe signal and transmitting the acknowledgement message, a range from the mobile device to the transceiver may be accurately measured. Even in the presence of multipath conditions, outlier detection techniques may be used to remove erroneous multipath detections. A comparison of a range computed based on an RTT range measurement with a range computed based on an RSSI measurement of a signal transmitted by a particular transmitter may be used to update expected signature values for RSSI of the signal transmitted by the transmitter (e.g., following transmission power drift as discussed above). The comparison of the range computed based on the RTT range measurement with the range computed based on the RSSI measurement may be used to update an expected transmission power of the transmitter. Based, at least in part, on the updated transmission power, expected RSSI signature values for a transmitter in a radio heatmap may be adjusted to be consistent with the current, updated transmission power level. 
     In certain implementations, as shown in  FIG. 1 , a mobile device  100  may receive or acquire satellite positioning system (SPS) signals  159  from SPS satellites  160 . In some embodiments, SPS satellites  160  may be from one global navigation satellite system (GNSS), such as the GPS or Galileo satellite systems. In other embodiments, the SPS Satellites may be from multiple GNSS such as, but not limited to, GPS, Galileo, Glonass, or Beidou (Compass) satellite systems. In other embodiments, SPS satellites may be from any one several regional navigation satellite systems (RNSS&#39;) such as, for example, Wide Area Augmentation System (WAAS), European Geostationary Navigation Overlay Service (EGNOS), Quasi-Zenith Satellite System (QZSS), just to name a few examples. 
     In addition, mobile device  100  may transmit radio signals to, and receive radio signals from, a wireless communication network. In one example, mobile device  100  may communicate with a cellular communication network by transmitting wireless signals to, or receiving wireless signals from, base station transceiver  110  over wireless communication link  123 . Similarly, mobile device  100  may transmit wireless signals to, or receive wireless signals from local transceiver  115  over wireless communication link  125 . 
     In a particular implementation, local transceiver  115  may be configured to communicate with mobile device  100  at a shorter range over wireless communication link  125  than at a range enabled by base station transceiver  110  over wireless communication link  123 . For example, local transceiver  115  may be positioned in an indoor environment. Local transceiver  115  may provide access to a wireless local area network (WLAN, e.g., IEEE Std. 802.11 network) or wireless personal area network (WPAN, e.g., Bluetooth network). In another example implementation, local transceiver  115  may comprise a femto cell transceiver capable of facilitating communication on link  125  according to a cellular communication protocol. Of course it should be understood that these are merely examples of networks that may communicate with a mobile device over a wireless link, and claimed subject matter is not limited in this respect. 
     In a particular implementation, base station transceiver  110  and local transceiver  115  may communicate with servers  140 ,  150  and/or  155  over a network  130  through links  145 . Here, network  130  may comprise any combination of wired or wireless links. In a particular implementation, network  130  may comprise Internet Protocol (IP) infrastructure capable of facilitating communication between mobile device  100  and servers  140 ,  150  or  155  through local transceiver  115  or base station transceiver  110 . In another implementation, network  130  may comprise cellular communication network infrastructure such as, for example, a base station controller or master switching center (not shown) to facilitate mobile cellular communication with mobile device  100 . 
     In particular implementations, and as discussed below, mobile device  100  may have circuitry and processing resources capable of computing a position fix or estimated location of mobile device  100 . For example, mobile device  100  may compute a position fix based, at least in part, on pseudorange measurements to four or more SPS satellites  160 . Here, mobile device  100  may compute such pseudorange measurements based, at least in part, on pseudonoise code phase detections in signals  159  acquired from four or more SPS satellites  160 . In particular implementations, mobile device  100  may receive from server  140 ,  150  or  155  positioning assistance data to aid in the acquisition of signals  159  transmitted by SPS satellites  160  including, for example, almanac, ephemeris data, Doppler search windows, just to name a few examples. 
     In other implementations, mobile device  100  may obtain a position fix by processing signals received from terrestrial transmitters fixed at known locations (e.g., such as base station transceiver  110 ) using any one of several techniques such as, for example, advanced forward trilateration (AFLT) and/or observed time difference of arrival (OTDOA). In these particular techniques, a range from mobile device  100  may be measured to three or more of such terrestrial transmitters fixed at known locations based, at least in part, on pilot signals transmitted by the transmitters fixed at known locations and received at mobile device  100 . Here, servers  140 ,  150  or  155  may be capable of providing positioning assistance data to mobile device  100  including, for example, locations and identities of terrestrial transmitters to facilitate positioning techniques such as AFLT and OTDOA. For example, servers  140 ,  150  or  155  may include a base station almanac (BSA) which indicates locations and identities of cellular base stations in a particular region or regions. 
     In particular environments such as indoor environments or urban canyons, mobile device  100  may not be capable of acquiring signals  159  from a sufficient number of SPS satellites  160  or perform AFLT or OTDOA to compute a position fix. Alternatively, mobile device  100  may be capable of computing a position fix based, at least in part, on signals acquired from local transmitters (e.g., WLAN access points, femto cell transceivers, Bluetooth devices, etc., positioned at known locations). For example, mobile devices may obtain a position fix by measuring ranges to three or more indoor terrestrial wireless access points which are positioned at known locations. Such ranges may be measured, for example, by obtaining a MAC ID address from signals received from such access points and obtaining range measurements to the access points by measuring one or more characteristics of signals received from such access points such as, for example, received signal strength (RSSI) or round trip time (RTT). In alternative implementations, mobile device  100  may obtain an indoor position fix by applying characteristics of acquired signals to a radio heatmap indicating expected RSSI and/or RTT signatures at particular locations in an indoor area. In particular implementations, a radio heatmap may associate identities of local transmitters (e.g., a MAC address which is discernible from a signal acquired from a local transmitter), expected RSSI from signals transmitted by the identified local transmitters, an expected RTT from the identified transmitters, and possibly standard deviations from these expected RSSI or RTT. It should be understood, however, that these are merely examples of values that may be stored in a radio heatmap, and that claimed subject matter is not limited in this respect. 
     In a particular implementation, mobile device  100  may also apply signals received from a magnetometer to signatures in a magnetic heatmap indicating expected magnetic signatures at particular locations in an indoor area. In particular implementations, for example, a “magnetic heatmap” may associate expected magnetic signatures or compass deviations with locations in an indoor area allowing a mobile device to estimate its location based, at least in part, on an association of magnetic heatmap values with compass or magnetometer measurements obtained at the mobile device. 
     In particular implementations, mobile device  100  may receive positioning assistance data for indoor positioning operations from servers  140 ,  150  or  155 . For example, such positioning assistance data may include locations and identities of transmitters positioned at known locations to enable measuring ranges to these transmitters based, at least in part, on a measured RSSI and/or RTT, for example. Other positioning assistance data to aid indoor positioning operations may include radio heatmaps, magnetic heatmaps, locations and identities of transmitters, routeability graphs, just to name a few examples. Other assistance data received by the mobile device may include, for example, local maps of indoor areas for display or to aid in navigation. Such a map may be provided to mobile device  100  as mobile device  100  enters a particular indoor area. Such a map may show indoor features such as doors, hallways, entry ways, walls, etc., points of interest such as bathrooms, pay phones, room names, stores, etc. By obtaining and displaying such a map, a mobile device may overlay a current location of the mobile device (and user) over the displayed map to provide the user with additional context. 
     In one implementation, a routeability graph and/or digital map may assist mobile device  100  in defining feasible areas for navigation within an indoor area and subject to physical obstructions (e.g., walls) and passage ways (e.g., doorways in walls). Here, by defining feasible areas for navigation, mobile device  100  may apply constraints to aid in the application of filtering measurements for estimating locations and/or motion trajectories according to a motion model (e.g., according to a particle filter and/or Kalman filter). In addition to measurements obtained from the acquisition of signals from local transmitters, according to a particular embodiment, mobile device  100  may further apply a motion model to measurements or inferences obtained from inertial sensors (e.g., accelerometers, gyroscopes, magnetometers, etc.) and/or environment sensors (e.g., temperature sensors, microphones, barometric pressure sensors, ambient light sensors, camera imager, etc.) in estimating a location or motion state of mobile device  100 . 
     According to an embodiment, mobile device  100  may access indoor navigation assistance data through servers  140 ,  150  or  155  by, for example, requesting the indoor assistance data through selection of a universal resource locator (URL). In particular implementations, servers  140 ,  150  or  155  may be capable of providing indoor navigation assistance data to cover many different indoor areas including, for example, floors of buildings, wings of hospitals, terminals at an airport, portions of a university campus, areas of a large shopping mall, just to name a few examples. Also, memory resources at mobile device  100  and data transmission resources may make receipt of indoor navigation assistance data for all areas served by servers  140 ,  150  or  155  impractical or infeasible, a request for indoor navigation assistance data from mobile device  100  may indicate a rough or course estimate of a location of mobile device  100 . Mobile device  100  may then be provided indoor navigation assistance data covering areas including and/or proximate to the rough or course estimate of the location of mobile device  100 . 
     In one particular implementation, a request for indoor navigation assistance data from mobile device  100  may specify a location context identifier (LCI). Such an LCI may be associated with a locally defined area such as, for example, a particular floor of a building or other indoor area which is not mapped according to a global coordinate system. In one example server architecture, upon entry of an area, mobile device  100  may request a first server, such as server  140 , to provide one or more LCIs covering the area or adjacent areas. Here, the request from the mobile device  100  may include a rough location of mobile device  100  such that the requested server may associate the rough location with areas covered by known LCIs, and then transmit those LCIs to mobile device  100 . Mobile device  100  may then use the received LCIs in subsequent messages with a different server, such as server  150 , for obtaining navigation assistance data relevant to an area identifiable by one or more of the LCIs as discussed above (e.g., digital maps, locations and identifies of beacon transmitters, radio heatmaps or routeability graphs). 
     In another implementation, server  140  may provide a transmission power level of transceiver  115  to devices, other than mobile device  100 . Mobile device  100  may determine a transmission power level of transceiver  115  by measuring a travel time of a signal transmitted between mobile device  100  and transceiver  115 . Mobile device  100  may measure signal strength of signal transmitted by transceiver  115  and acquired at mobile device  100 . By combining measured travel time of signal with measured signal strength, mobile device  100 , or another device, such as server  140 , for example, may determine transmission power level. In this embodiment, measured signal strength, and measured RTT values may be transmitted to server  140 . Mobile device  100 , or server  140 , may update transceiver transmission power level at server  140 , or other location based service, for example. Other devices receiving location relevant information, such as, but not limited to RTT results, received signal strengths, or transmission power levels, from server  140 , may then receive an updated transmission power level for transceiver  115 . 
       FIG. 2  is a schematic diagram illustrating one particular implementation of an element  200  for a two-dimensional radio heatmap. A radio heatmap may comprise more than two dimensions. However, this is merely an example of implementation of a radio heatmap with two dimensions, and claimed subject matter is not limited to two dimensions. A single element  200  of a heatmap may include, but is not limited to, a node identifier (ID)  202 , expected RSSI signature values  203  and variances  204 , expected RTT signature values  205  and variances  206 , a Boolean connectivity flag  207 , or other values, for example. As shown in the particular example above, an expected RSSI signature value  203  and associated variance  204  for a given node ID  202  may be represented by one byte each while an expected RTT signature value  205  and associated variance  206  for a given node ID  202  may be represented by two bytes each, or more, for example. Additionally, a single field may indicate connectivity  207  (e.g., a feasible path) with adjoining grid points (e.g., Boolean 1 or 0 to indicate whether there is connectivity with an associated grid point). 
     In one particular implementation, a process for adjusting or updating RSSI signature values may comprise: 1) estimating a range from RTT measurements; 2) estimating a transmission power of the transceiver and a path loss exponent by comparing estimated true range and RSSI measurements; and adjusting the RSSI heatmap according to estimated transmission power of the transceiver and path loss exponent. In an alternative implementation, a pathloss exponent estimate may comprise a predetermined parameter (e.g., from assistance data received from a server). Here, it is recognized adaptive transmission power control in some scenarios transmission power may lead to frequently varying transmission power while a power loss exponent may remain relatively static. As such, a predetermined path loss exponent received as assistance data from a server may be sufficient. In one example implementation, a single or small number of RTT/RSSI measurement pairs may be collected for estimating a transmission power of a transmitter based, at least in part, on a predetermined path loss exponent received in assistance data from a server. In another implementation, a large number of RTT/RSSI measurement pairs may be collected for a transmitter and estimates of transmission power and power loss exponent may be obtained. In this context, a power loss may characterize a difference between a transmission power at a transmitter and a measured received power at a receiver arising at least in part, for example, wireless signal propagation or attenuation. In addition to a range between a transmitter and a receiver, such a power loss may be affected by other factors such as, for example, atmospheric conditions obstructions in a signal path. Here, a “power loss exponent” may comprise a single parameter that may characterize a power loss between a transmitter and a receiver base as a function of one or more factors such as, for example, a range between the transmitter and receiver. It should be understood, however, that this is merely one example of how a power loss exponent may model a path loss between a transmitter and receiver, and claimed subject matter is not limited in this respect. 
       FIG. 3  is a flowchart illustrating a method of a mobile device in accordance with an implementation. Of course, claimed subject matter is not limited in scope to the particular order or arrangement of blocks shown. Likewise, additional blocks may be included in an embodiment or blocks depicting one or more operations in place of those shown may be used in an embodiment. At block  302 , a mobile device may measure a travel time of a signal transmitted between a mobile device and a transmitter. In a particular implementation, mobile device may measure the travel time by transmitting a probe message to a transceiver, acquiring a message from the transceiver responding to the probe message, and measuring a duration from transmission of the probe message to acquisition of the response message as an RTT measurement. At block  304 , the mobile device may measure a strength of a signal transmitted by the transmitter and acquired at the mobile device as an RSSI measurement. If a location of the mobile device while measuring a travel time at block  302  is approximately the same location of the mobile device while measuring a signal strength at block  304 , at block  306  the travel time measured at block  302  and signal strength measured at block  304  may be combined to adjust one or more expected signal strength values in a radio heatmap. In one example implementation, block  306  may be performed at the mobile device to update adjust one or more expected signal strength values in an image of the radio heatmap stored locally on a memory on the mobile device. Alternatively, a mobile device may transmit one or more messages to a server containing measurements obtained at blocks  302  and  304 , while the measurements are combined according to block  306  at the server. 
     In one particular implementation, block  306  may update or adjust expected RSSI signature values for a transmitter based, at least in part, on an estimate of the transmission power and an estimated path loss. Here block  306  may recognize that a path loss comprises a reduction in the power of a signal as it propagates through a volume of space. Path loss may arise from many effects, such as, but not limited to refraction, diffraction, reflection, coupling losses, absorption, or other, for example. A path loss exponent may effectively estimate a predicted path loss for a given path that a radio frequency signal may travel between a transmitter and a receiver. For example, signals with little interference may have a very low path loss exponent, while signals with significant interference, or loss as previously discussed, may have a very high path loss exponent. As pointed out above in an example implementation, block  306  may be performed in whole or in part at a remote server. In one alternative implementation, one or more mobile devices may provide messages to a server indicating an estimated range to a transmitter computed based on a RTT measurement paired with an RSSI measurement value. Here, the server may then compute an estimated transmission power for the transmitter and estimated path loss based, at least in part, on multiple observations (e.g., ten or more) from the mobile device. In another alternative implementation, a mobile device may compute estimates of the transmitter&#39;s transmission power and the path loss over multiple observations (e.g., ten or more), and forward these estimates to the server. 
     Accumulated samples (measurements or estimates) from mobile devices may be used to update values in a heatmap. In one implementation, in addition to path loss exponent, a mobile device may report an RTT based range measurement in combination with an RSSI measurement. An updated estimate of transmission power level at a transmitter may be calculated using these two values as later discussed. Updated estimated transmission power levels may be transmitted to a server for adjusting and subsequently reporting updated RSSI signature values to other mobile devices. 
     An RTT range measurement to a transmitter from a given location of a mobile device may comprise a flight time of a probe signal transmitted by the mobile device, added to a time of flight of a response to the probe signal transmitted by a transceiver in response to the probe signal and received at the mobile device, and added to a processing delay at the transceiver may be included in the calculations. Accordingly, a range from the mobile device to the transceiver may be measured according to expression (1) as follows:
 
 R   RTT   =c *( RTT −Processing Delay)/2;  (1)
 
     where: 
     R RTT  is a measurement of range to a transmitter computed from RTT; 
     c is the speed of light; and 
     Processing Delay is a delay at the transceiver between acquisition of a probe signal and transmission of a response signal. 
     In particular implementations, a value for Processing Delay may be model or device specific, may not change over time. Additionally, a value for Processing Delay for any particular transceiver may not be subject to any dynamic control. Thus, a transceiver may store a static processing delay value for transmission for transmission to a mobile device or server for use as positioning assistance data. 
     As pointed out above, RSSI measurements and a value for R RTT  may be compared with one another to compute updated or adjusted expected RSSI signatures in a radio heatmap. In one implementation, an expected RSSI value (RSSI exp ) may be modeled according to expression (2) as follows:
 
RSSI meas =RSSI 0 −10*PathLossExp*log 10 ( R   RTT )  (2)
 
     where: 
     RSSI meas  is a measured RSSI value obtained in roughly the same location that an RTT measurement is obtained; 
     RSSI 0  is a value for RSSI computed based upon transmitter power; and 
     PathLossExp is a computed path loss exponent. 
     In particular implementations, RSSI 0  may be defined as a value for RSSI at a range of 1.0 m. A value for PathLossExp may be initially set as being between 1.5 and 2.0 in free space and approximately 2.3˜3.0 in an indoor environment. In a particular implementation, values for RSSI meas  and R RTT  may be known and/or obtained from direct measurement of acquired signals. Parameters may be estimated by applying a “best fit” over multiple paired samples of RSSI meas  and R RTT  to solve for RSSI 0  and PathLossExp over multiple data points. For example, RSSI 0  and PathLossExp may be estimated using a linear regression process where these parameters are placed in a vector “x” and measurements of RSSI are placed in a vector “y.” A matrix H may be constructed based on R RTT . Estimated values for x may then be computed as follows:
 
{circumflex over ( x )}=( H   T   H   T ) −1   H   T   y   (4)
 
     where: 
     
       
         
           
             x 
             = 
             
               [ 
               
                 
                   
                     pathLossExp 
                   
                 
                 
                   
                     
                       RSSI 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       0 
                     
                   
                 
               
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             y 
             = 
             
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                       RSSI 
                       ⁡ 
                       
                         ( 
                         1 
                         ) 
                       
                     
                   
                 
                 
                   
                     
                       RSSI 
                       ⁡ 
                       
                         ( 
                         2 
                         ) 
                       
                     
                   
                 
                 
                   
                     ⋮ 
                   
                 
                 
                   
                     
                       RSSI 
                       ⁡ 
                       
                         ( 
                         k 
                         ) 
                       
                     
                   
                 
               
               ] 
             
           
         
       
       
         
           
             H 
             = 
             
               [ 
               
                 
                   
                     
                       10 
                       * 
                       log 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       10 
                       ⁢ 
                       
                         ( 
                         
                           Rrtt 
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     As pointed out above an estimated value for a path loss exponent may be predetermined and provided by a server. With such an predetermined estimate of path loss exponent, a value for RSSI o  may be computed according to expression (5) as follows: 
     
       
         
           
             
               
                 
                   
                     
                       RSSI 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       0 
                     
                     ^ 
                   
                   = 
                   
                     
                       1 
                       k 
                     
                     ⁢ 
                     
                       
                         ∑ 
                         
                           i 
                           = 
                           1 
                         
                         k 
                       
                       ⁢ 
                       
                         [ 
                         
                           
                             RSSI 
                             ⁡ 
                             
                               ( 
                               i 
                               ) 
                             
                           
                           + 
                           
                             10 
                             × 
                             PathLossExpGiven 
                             × 
                             log 
                             ⁢ 
                             
                                 
                             
                             ⁢ 
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                               ( 
                               
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                   ( 
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                   ) 
                 
               
             
           
         
       
         
         
           
             where PathLossExpGiven is a predetermined values for a path loss exponent. 
           
         
       
    
     In implementations according to expressions (4) and (5) outlined above, outlier detection and removal may be applied to avoid measurements with large errors by checking against a deviation against measurements. For example, RSSI/RTT measurement pairs for which RSSI(i)+10×PathLossExpGiven×log 10 (R RTT (i)) deviates from RSSI 0  by more than a threshold (e.g., 1.0 sigma) may be discarded. 
     In a particular implementation, a value for RSSI 0  may be modeled according to expression (6) as follows:
 
RSSI 0  (dBm)=TX_PWR (dBm)+20·log 10 (λ/4π)  (6)
 
     Where: 
     TX_PWR (dBm) is a transmission power for a particular transmitter; and 
     λ Is the RF wavelength. 
     Values for RSSI 0  and PathLossExp may be estimated based at least in part, on multiple samples of RSSI meas  and R RTT  according a “best fit” (e.g., least square error or regression analysis) as discussed above. The estimated value for RSSI 0  may be applied to expression (6) to estimate a value for TX_PWR (dBm)=RSSI 0  (dBm)−20·log 10 (λ/4π). 
     As pointed out above, in a particular implementation in which a remote server computes updated expected RSSI signature values in a radio heatmap, a mobile device may transmit or upload particular parameters or measurements to the remote server to enable such computation. For example, mobile device may transmit or upload computed values for TX_PWR (dBm) and PathLossExp. Alternatively, the mobile device may transmit or upload computed values for RSSI0 and PathLossExp. Here, it may be observed that values for TX_PWR (dBm) and RSSI0 may be derived from one another based on a fixed relationship. A remote server may compute updated expected RSSI signature values by applying a difference between current and previously known values for PathLossExp and values for either RSSI0 or TX_PWR (dBm). 
     Alternatively, instead of transmitting or uploading computed values for TX_PWR (dBm) and RSSI0 (e.g., in combination with a computed value for PathLossExp), a mobile may send to a remote server values for deltaPwr (computed as TX_PWR_estimated−TX_PWR_given=RSSI0_estimated−RSSI0_given). The remote server may then compute updated expected RSSI signature values by applying a difference between current and previously known values for PathLossExp and a value for deltaPwr. 
     As may be observed from expression (6), a value for RSSI 0  (dBm) may vary from time to time as TX_PWR (dBm) (transmit power of a particular transmitter) drifts as discussed above. Changes in a value of RSSI 0  (dBm) may be used to compute an updated expected RSSI signature values in for signals transmitted (e.g., in a radio heatmap) by the particular transmitter according to expression (7) as follows:
 
RSSI exp ( t   n+1 )=RSSI exp ( t   n )+(RSSI 0 ( t   n+1 )−RSSI 0 ( t   n ))  (7)
 
     where: 
     RSSI exp (t n ) is an expected RSSI signature value for signals acquired from a transmitter at time t n ; 
     RSSI exp (t n+1 ) is an expected RSSI signature value updated at time t n+1  to account for drift in transmission power at the transmitter; 
     RSSI 0 (t n ) is a value for RSSI computed based upon transmitter power at time t n    
     computed according to expression (2) according to a best fit; and 
     RSSI 0 (t n+1 ) is a value for RSSI computed based upon transmitter power at time t n+1  computed according to expression (2) according to a best fit. 
     In one particular implementation, an updated expected signature value RSSI exp (t n+1 ) for a particular transmitter may be determined for one particular location identified in a radio heatmap (e.g., at a particular grid point). Here, operations according to expression (4) may be repeated for obtaining an updated expected signature value RSSI exp (t n+1 ) for multiple locations (e.g., grid points) in a radio heatmap. 
     While a mobile device may obtain an RSSI measurement from a signal transmitted by a transmitter and an acquired at the mobile device, a value of such an RSSI measurement may depend, at least in part, on a the particular receiver of the mobile device obtaining the measurement. For example, different mobile device from different manufacturers, or different models of mobile device from the same manufacturer, may have a different receiver gain to provide a different RSSI measurement value from the same transmitter while positioned at the same receiver location. 
     In a particular implementation, receiver gains of receivers of mobile devices may be calibrated at the factory so as to provide uniformity in devices obtaining measurements of RSSI. In another implementation, a receiver gain may be calibrated during the life of mobile device operation. In another implementation, even if a receiver gain is not calibrated at the factory or during the life of mobile device operation, a server combining RSSI measurements at block  306  from multiple mobile devices may have a priori knowledge of receiver gains of different makes and models of mobile devices providing the RSSI measurements. The server may then adjust RSSI measurements received from a particular make or model of mobile device according to the known receiver gain. Here, a server may track a deviation in gain per mobile device make/model (e.g., Galaxy=+5.0 dB, Nexus=−2.0 dB). Alternatively, the server may assume a single error model (e.g., Gaussian error with a mean deviation of 0.0 dB with σ=5.0 dB). While sources of variation in received power may also include motion of the receiver, user body shielding, crowdsourcing and accumulation of a sufficient number of samples may cancel much of this variation. According to an embodiment, a server may give measurements of transmission power from devices deemed to be more reliable may be given greater weight. For example, a reference receiver (e.g., a mobile device or access transceiver) may be located at a known fixed location. Accordingly, if a location of an access transceiver is known, a range or distance between the reference receiver and the access transceiver may also be known. Accordingly, any changes in RSSI of signals received at the reference receiver transmitted by the access transceiver may provide a very accurate indication of changes in transmission power at the access transceiver. In addition, measurements of RSSI obtained at the reference receiver may be smoothed or averaged over time to improve accuracy of an estimated transmission power of the access transceiver. At the server end, RSSI measurements received from a reference receiver positioned at a known location (again, presumed to be particularly accurate because of the known distance or range between the reference receiver and the access transceiver) may be given greater weight in estimating transmission power of the access transceiver than RSSI measurements obtained from other devices. 
       FIG. 4  is a flowchart illustrating a method by a server in accordance with an implementation. Of course, claimed subject matter is not limited in scope to the particular order or arrangement of blocks shown. Likewise, additional blocks may be included in an embodiment or blocks depicting one or more operations in place of those shown may be used in an embodiment. In  FIG. 4 . a server may receive one or more messages from a mobile device determined based, at least in part, on a measurement of a travel time of a signal transmitted between the mobile device and a transmitter and a measurement of a strength of a signal transmitted by the transmitter and acquired at the mobile device  402 . Therefore, a message may comprise, but is not limited to, a received signal strength, a measured round-trip time, an estimated transmission power level, a signal strength signature value, or other, for example. As pointed out above in one alternative implementation, a server may receive estimates of transmission power and estimated path loss. As pointed out in an alternative implementation, a remote server may receive RTT range measurements paired with RSSI measurement values. The server may adjust one or more signal strength signature values for application to location based services. Here, the server may apply one or more techniques described above in connection with block  306  of  FIG. 3 . Subsequent signals acquired from the transmitter may determine more accurate location based, at least in part, on updated or adjusted signal strength signature values  404 . 
       FIG. 5  is a schematic diagram of a mobile device according to an embodiment. Mobile device  100  ( FIG. 1 ) may comprise one or more features of mobile device  500  shown in  FIG. 5 . In certain embodiments, mobile device  500  may also comprise a wireless transceiver  521  which is capable of transmitting and receiving wireless signals  523  via an antenna  522  over a wireless communication network. Wireless transceiver  521  may be connected to bus  501  by a wireless transceiver bus interface  520 . Wireless transceiver bus interface  520  may, in some embodiments be at least partially integrated with wireless transceiver  521 . Some embodiments may include multiple wireless transceivers  521  and wireless antennas  522  to enable transmitting and/or receiving signals according to a corresponding multiple wireless communication standards such as, for example, WiFi, CDMA, WCDMA, LTE and Bluetooth, just to name a few examples. 
     Mobile device  500  may also comprise SPS receiver  555  capable of receiving and acquiring SPS signals  559  via SPS antenna  558 . SPS receiver  555  may also process, in whole or in part, acquired SPS signals  559  for estimating a location of mobile device  500 . In some embodiments, general-purpose processor(s)  511 , memory  540 , DSP(s)  512  and/or specialized processors (not shown) may also be utilized to process acquired SPS signals, in whole or in part, and/or calculate an estimated location of mobile device  500 , in conjunction with SPS receiver  555 . Storage of SPS or other signals for use in performing positioning operations may be performed in memory  540  or registers (not shown). 
     Also shown in  FIG. 5 , mobile device  500  may comprise digital signal processor(s) (DSP(s))  512  connected to the bus  501  by a bus interface  510 , general-purpose processor(s)  511  connected to the bus  501  by a bus interface  510  and memory  540 . Bus interface  510  may be integrated with the DSP(s)  512 , general-purpose processor(s)  511  and memory  540 . In various embodiments, functions may be performed in response execution of one or more machine-readable instructions stored in memory  540  such as on a computer-readable storage medium, such as RAM, ROM, FLASH, or disc drive, just to name a few example. The one or more instructions may be executable by general-purpose processor(s)  511 , specialized processors, or DSP(s)  512 . Memory  540  may comprise a non-transitory processor-readable memory and/or a computer-readable memory that stores software code (programming code, instructions, etc.) that are executable by processor(s)  511  and/or DSP(s)  512  to perform functions described herein. 
     Also shown in  FIG. 5 , a user interface  535  may comprise any one of several devices such as, for example, a speaker, microphone, display device, vibration device, keyboard, touch screen, just to name a few examples. In a particular implementation, user interface  535  may enable a user to interact with one or more applications hosted on mobile device  500 . For example, devices of user interface  535  may store analog or digital signals on memory  240  to be further processed by DSP(s)  512  or general purpose processor  511  in response to action from a user. Similarly, applications hosted on mobile device  500  may store analog or digital signals on memory  540  to present an output signal to a user. In another implementation, mobile device  500  may optionally include a dedicated audio input/output (I/O) device  570  comprising, for example, a dedicated speaker, microphone, digital to analog circuitry, analog to digital circuitry, amplifiers and/or gain control. It should be understood, however, that this is merely an example of how an audio I/O may be implemented in a mobile device, and that claimed subject matter is not limited in this respect. In another implementation, mobile device  500  may comprise touch sensors  562  responsive to touching or pressure on a keyboard or touch screen device. 
     Mobile device  500  may also comprise a dedicated camera device  564  for capturing still or moving imagery. Camera device  564  may comprise, for example an imaging sensor (e.g., charge coupled device or CMOS imager), lens, analog to digital circuitry, frame buffers, just to name a few examples. In one implementation, additional processing, conditioning, encoding or compression of signals representing captured images may be performed at general purpose/application processor  511  or DSP(s)  512 . Alternatively, a dedicated video processor  568  may perform conditioning, encoding, compression or manipulation of signals representing captured images. Additionally, video processor  568  may decode/decompress stored image data for presentation on a display device (not shown) on mobile device  500 . 
     Mobile device  500  may also comprise sensors  560  coupled to bus  501  which may include, for example, inertial sensors and environment sensors. Inertial sensors of sensors  560  may comprise, for example accelerometers (e.g., collectively responding to acceleration of mobile device  500  in three dimensions), one or more gyroscopes or one or more magnetometers (e.g., to support one or more compass applications). Environment sensors of mobile device  500  may comprise, for example, temperature sensors, barometric pressure sensors, ambient light sensors, camera imagers, microphones, just to name few examples. Sensors  560  may generate analog or digital signals that may be stored in memory  540  and processed by DPS(s) or general purpose processor  511  in support of one or more applications such as, for example, applications directed to positioning or navigation operations. 
     In a particular implementation, mobile device  500  may comprise a dedicated modem processor  566  capable of performing baseband processing of signals received and downconverted at wireless transceiver  521  or SPS receiver  555 . Similarly, modem processor  566  may perform baseband processing of signals to be upconverted for transmission by wireless transceiver  521 . In alternative implementations, instead of having a dedicated modem processor, baseband processing may be performed by a general purpose processor or DSP (e.g., general purpose/application processor  511  or DSP(s)  512 ). It should be understood, however, that these are merely examples of structures that may perform baseband processing, and that claimed subject matter is not limited in this respect. In particular applications, mobile device  500  may be capable of performing some or all of actions at blocks  302 ,  304  and  306  described above with reference to  FIG. 3 . 
       FIG. 6  is a schematic diagram illustrating an example system  600  that may include one or more devices configurable to implement techniques or processes described above, for example, in connection with  FIG. 1 . System  600  may include, for example, a first device  602 , a second device  604 , and a third device  606 , which may be operatively coupled together through a wireless communications network  608 . In an aspect, first device  602  may comprise a server capable of providing positioning assistance data such as, for example, a base station almanac. First device  602  may also comprise a server capable of providing an LCI to a requesting mobile device based, at least in part, on a rough estimate of a location of the requesting mobile device. First device  602  may also comprise a server capable of providing indoor positioning assistance data relevant to a location of an LCI specified in a request from a mobile device. Second and third devices  604  and  606  may comprise mobile devices, in an aspect. Also, in an aspect, wireless communications network  608  may comprise one or more wireless access points, for example. However, claimed subject matter is not limited in scope in these respects. 
     First device  602 , second device  604  and third device  606 , as shown in  FIG. 6 , may be representative of any device, appliance or machine that may be configurable to exchange data over wireless communications network  608 . By way of example but not limitation, any of first device  602 , second device  604 , or third device  606  may include: one or more computing devices or platforms, such as, e.g., a desktop computer, a laptop computer, a workstation, a server device, or the like; one or more personal computing or communication devices or appliances, such as, e.g., a personal digital assistant, mobile communication device, or the like; a computing system or associated service provider capability, such as, e.g., a database or data storage service provider/system, a network service provider/system, an Internet or intranet service provider/system, a portal or search engine service provider/system, a wireless communication service provider/system; or any combination thereof. Any of the first, second, and third devices  602 ,  604 , and  606 , respectively, may comprise one or more of a base station almanac server, a base station, or a mobile device in accordance with the examples described herein. 
     Similarly, wireless communications network  608 , as shown in  FIG. 6 , is representative of one or more communication links, processes, or resources configurable to support the exchange of data between at least two of first device  602 , second device  604 , and third device  606 . By way of example but not limitation, wireless communications network  608  may include wireless or wired communication links, telephone or telecommunications systems, data buses or channels, optical fibers, terrestrial or space vehicle resources, local area networks, wide area networks, intranets, the Internet, routers or switches, and the like, or any combination thereof. As illustrated, for example, by the dashed lined box illustrated as being partially obscured of third device  606 , there may be additional like devices operatively coupled to wireless communications network  608 . 
     It is recognized that all or part of the various devices and networks shown in system  600 , and the processes and methods as further described herein, may be implemented using or otherwise including hardware, firmware, software, or any combination thereof. 
     Thus, by way of example but not limitation, second device  604  may include at least one processing unit  620  that is operatively coupled to a memory  622  through a bus  628 . 
     Processing unit  620  is representative of one or more circuits configurable to perform at least a portion of a data computing procedure or process. By way of example but not limitation, processing unit  620  may include one or more processors, controllers, microprocessors, microcontrollers, application specific integrated circuits, digital signal processors, programmable logic devices, field programmable gate arrays, and the like, or any combination thereof. 
     Memory  622  is representative of any data storage mechanism. Memory  622  may include, for example, a primary memory  624  or a secondary memory  626 . Primary memory  624  may include, for example, a random access memory, read only memory, etc. While illustrated in this example as being separate from processing unit  620 , it should be understood that all or part of primary memory  624  may be provided within or otherwise co-located/coupled with processing unit  620 . 
     Secondary memory  626  may include, for example, the same or similar type of memory as primary memory or one or more data storage devices or systems, such as, for example, a disk drive, an optical disc drive, a tape drive, a solid state memory drive, etc. In certain implementations, secondary memory  626  may be operatively receptive of, or otherwise configurable to couple to, a computer-readable medium  640 . Computer-readable medium  640  may include, for example, any non-transitory medium that can carry or make accessible data, code or instructions for one or more of the devices in system  600 . Computer-readable medium  640  may also be referred to as a storage medium. 
     Second device  604  may include, for example, a communication interface  630  that provides for or otherwise supports the operative coupling of second device  604  to at least wireless communications network  608 . By way of example but not limitation, communication interface  630  may include a network interface device or card, a modem, a router, a switch, a transceiver, and the like. 
     Second device  604  may include, for example, an input/output device  632 . Input/output device  632  is representative of one or more devices or features that may be configurable to accept or otherwise introduce human or machine inputs, or one or more devices or features that may be configurable to deliver or otherwise provide for human or machine outputs. By way of example but not limitation, input/output device  632  may include an operatively configured display, speaker, keyboard, mouse, trackball, touch screen, data port, etc. In particular applications, second device  604  may be capable of performing actions at blocks  402  and  404  described above with reference to  FIG. 4 . 
     The methodologies described herein may be implemented by various means depending upon applications according to particular examples. For example, such methodologies may be implemented in hardware, firmware, software, or combinations thereof. In a hardware implementation, for example, a processing unit may be implemented within one or more application specific integrated circuits (“ASICs”), digital signal processors (“DSPs”), digital signal processing devices (“DSPDs”), programmable logic devices (“PLDs”), field programmable gate arrays (“FPGAs”), processors, controllers, micro-controllers, microprocessors, electronic devices, other devices units designed to perform the functions described herein, or combinations thereof. 
     Some portions of the detailed description included herein are presented in terms of algorithms or symbolic representations of operations on binary digital signals stored within a memory of a specific apparatus or special purpose computing device or platform. In the context of this particular specification, the term specific apparatus or the like includes a general purpose computer once it is programmed to perform particular operations pursuant to instructions from program software. Algorithmic descriptions or symbolic representations are examples of techniques used by those of ordinary skill in the signal processing or related arts to convey the substance of their work to others skilled in the art. An algorithm is here, and generally, is considered to be a self-consistent sequence of operations or similar signal processing leading to a desired result. In this context, operations or processing involve physical manipulation of physical quantities. Typically, although not necessarily, such quantities may take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared or otherwise manipulated. It has proven convenient at times, principally for reasons of common usage, to refer to such signals as bits, data, values, elements, symbols, characters, terms, numbers, numerals, or the like. It should be understood, however, that all of these or similar terms are to be associated with appropriate physical quantities and are merely convenient labels. Unless specifically stated otherwise, as apparent from the discussion herein, it is appreciated that throughout this specification discussions utilizing terms such as “processing,” “computing,” “calculating,” “determining” or the like refer to actions or processes of a specific apparatus, such as a special purpose computer, special purpose computing apparatus or a similar special purpose electronic computing device. In the context of this specification, therefore, a special purpose computer or a similar special purpose electronic computing device is capable of manipulating or transforming signals, typically represented as physical electronic or magnetic quantities within memories, registers, or other information storage devices, transmission devices, or display devices of the special purpose computer or similar special purpose electronic computing device. 
     Wireless communication techniques described herein may be in connection with various wireless communications networks such as a wireless wide area network (“WWAN”), a wireless local area network (“WLAN”), a wireless personal area network (WPAN), and so on. The term “network” and “system” may be used interchangeably herein. A WWAN may be a Code Division Multiple Access (“CDMA”) network, a Time Division Multiple Access (“TDMA”) network, a Frequency Division Multiple Access (“FDMA”) network, an Orthogonal Frequency Division Multiple Access (“OFDMA”) network, a Single-Carrier Frequency Division Multiple Access (“SC-FDMA”) network, or any combination of the above networks, and so on. A CDMA network may implement one or more radio access technologies (“RATs”) such as cdma2000, Wideband-CDMA (“W-CDMA”), to name just a few radio technologies. Here, cdma2000 may include technologies implemented according to IS-95, IS-2000, and IS-856 standards. A TDMA network may implement Global System for Mobile Communications (“GSM”), Digital Advanced Mobile Phone System (“D-AMPS”), or some other RAT. GSM and W-CDMA are described in documents from a consortium named “3rd Generation Partnership Project” (“3GPP”). Cdma2000 is described in documents from a consortium named “3rd Generation Partnership Project 2” (“3GPP2”). 3GPP and 3GPP2 documents are publicly available. 4G Long Term Evolution (“LTE”) communications networks may also be implemented in accordance with claimed subject matter, in an aspect. A WLAN may comprise an IEEE 802.11x network, and a WPAN may comprise a Bluetooth network, an IEEE 802.15x, for example. Wireless communication implementations described herein may also be used in connection with any combination of WWAN, WLAN or WPAN. 
     In another aspect, as previously mentioned, a wireless transmitter or access point may comprise a femto cell, utilized to extend cellular telephone service into a business or home. In such an implementation, one or more mobile devices may communicate with a femto cell via a code division multiple access (“CDMA”) cellular communication protocol, for example, and the femto cell may provide the mobile device access to a larger cellular telecommunication network by way of another broadband network such as the Internet. 
     Techniques described herein may be used with an SPS that includes any one of several GNSS and/or combinations of GNSS. Furthermore, such techniques may be used with positioning systems that utilize terrestrial transmitters acting as “pseudolites”, or a combination of SVs and such terrestrial transmitters. Terrestrial transmitters may, for example, include ground-based transmitters that broadcast a PN code or other ranging code (e.g., similar to a GPS or CDMA cellular signal). Such a transmitter may be assigned a unique PN code so as to permit identification by a remote receiver. Terrestrial transmitters may be useful, for example, to augment an SPS in situations where SPS signals from an orbiting SV might be unavailable, such as in tunnels, mines, buildings, urban canyons or other enclosed areas. Another implementation of pseudolites is known as radio-beacons. The term “SV”, as used herein, is intended to include terrestrial transmitters acting as pseudolites, equivalents of pseudolites, and possibly others. The terms “SPS signals” and/or “SV signals”, as used herein, is intended to include SPS-like signals from terrestrial transmitters, including terrestrial transmitters acting as pseudolites or equivalents of pseudolites. 
     The terms, “and,” and “or” as used herein may include a variety of meanings that will depend at least in part upon the context in which it is used. Typically, “or” if used to associate a list, such as A, B or C, is intended to mean A, B, and C, here used in the inclusive sense, as well as A, B or C, here used in the exclusive sense. Reference throughout this specification to “one example” or “an example” means that a particular feature, structure, or characteristic described in connection with the example is included in at least one example of claimed subject matter. Thus, the appearances of the phrase “in one example” or “an example” in various places throughout this specification are not necessarily all referring to the same example. Furthermore, the particular features, structures, or characteristics may be combined in one or more examples. Examples described herein may include machines, devices, engines, or apparatuses that operate using digital signals. Such signals may comprise electronic signals, optical signals, electromagnetic signals, or any form of energy that provides information between locations. 
     While there has been illustrated and described what are presently considered to be example features, it will be understood by those skilled in the art that various other modifications may be made, and equivalents may be substituted, without departing from claimed subject matter. Additionally, many modifications may be made to adapt a particular situation to the teachings of claimed subject matter without departing from the central concept described herein. Therefore, it is intended that claimed subject matter not be limited to the particular examples disclosed, but that such claimed subject matter may also include all aspects falling within the scope of the appended claims, and equivalents thereof.