PATENT DOCUMENT

Publication Number: US-9794024-B2
Application Number: US-201314075816-A
Country: US
Kind Code: B2

Title: Adaptive channel state feedback estimation

Abstract:
Aspects of the present invention provide apparatuses and methods for adaptive channel state feedback (CSF) estimation techniques. Downlink transmissions can be received at a mobile device. The downlink transmissions can be received after the mobile device has entered a power saving mode of operation. The downlink transmission received can be a discontinuous downlink subframe and can include one or more pilot symbols. A channel variation factor of the transmission channel can be determined based on the received downlink transmission. Based on the amount of variation of the transmission channel, either an earlier-received or a later-received pilot symbol can be used for CSF estimation. Further, either higher or lower weighted filter coefficients can be selected for use in CSF estimation based on the amount of variation of the transmission channel.

Claims:
We claim: 
     
       1. A method, comprising:
 receiving a first sequence of pilot symbols from a base station over a wireless transmission channel, including at least a first pilot symbol and a second pilot symbol, wherein the second pilot symbol is received after the first pilot symbol; 
 determining first channel variation information for the transmission channel; 
 selecting to sample the first pilot symbol and not the second pilot symbol based on the first channel variation not meeting a threshold; 
 determining a first channel state feedback (CSF) estimation using the selected first pilot symbol; 
 transmitting the first CSF estimation to the base station; 
 receiving a second sequence of pilot symbols from the base station over the wireless transmission channel, including at least a third pilot symbol and a fourth pilot symbol, wherein the fourth pilot symbol is received after the third pilot symbol; 
 determining second channel variation information for the transmission channel; 
 selecting to sample the fourth pilot symbol and not the third pilot symbol based on the second channel variation meeting the threshold; 
 determining a second CSF estimation using the selected fourth pilot symbol; and 
 transmitting the second CSF estimation to the base station. 
 
     
     
       2. The method of  claim 1 , further comprising:
 receiving a downlink subframe containing the first pilot symbol and the second pilot symbol. 
 
     
     
       3. The method of  claim 1 , further comprising:
 receiving a discontinuous downlink subframe containing the first pilot symbol and the second pilot symbol. 
 
     
     
       4. The method of  claim 3 , further comprising:
 receiving the discontinuous downlink subframe after entering a power saving mode of operation. 
 
     
     
       5. The method of  claim 3 , further comprising:
 receiving the discontinuous downlink subframe after entering a Connected Mode Discontinuous Reception (C-DRX) mode of operation. 
 
     
     
       6. The method of  claim 1 , wherein determining the first channel variation information includes calculating a Doppler estimate. 
     
     
       7. An apparatus, comprising:
 channel condition circuitry configured to monitor variation of a wireless channel, wherein the apparatus is configured to receive a sequence of pilot symbols from a base station over the wireless channel, including at least a first pilot symbol and a second pilot symbol, wherein the second pilot symbol is received after the first pilot symbol; 
 one or more processing elements configured to:
 select to sample the second pilot symbol and not the first pilot symbol based on the monitored variation meeting a threshold; and 
 select to sample the first pilot symbol and not the second pilot symbol based on the monitored variation not meeting the threshold; and 
 determine a channel state feedback (CSF) estimation using the selected one of the first pilot symbol and the second pilot symbol. 
 
 
     
     
       8. The apparatus of  claim 7 , further comprising one or more circuit elements configured to transmit the CSF estimation to the base station. 
     
     
       9. The apparatus of  claim 7 , wherein to monitor variation of the wireless channel, the channel condition circuitry is configured to calculate a Doppler estimate. 
     
     
       10. The apparatus of  claim 7 , wherein the first pilot symbol and the second pilot symbol are included in the same downlink subframe. 
     
     
       11. The apparatus of  claim 7 , wherein the apparatus is configured to receive the first pilot symbol and the second pilot symbol in a discontinuous downlink subframe that is received after the apparatus has entered a power saving mode of operation. 
     
     
       12. The apparatus of  claim 7 , wherein the apparatus is further configured to:
 determine one or more spectral efficiency filter coefficients based on the sampled pilot symbol; 
 filter a spectral efficiency metric based on the determined one or more spectral efficiency filter coefficients to generate a filtered spectral efficiency metric; and 
 map the filtered spectral efficiency metric to a channel quality indicator (CQI) index to form a portion of the CSF estimation. 
 
     
     
       13. A non-transitory computer-readable medium having instructions stored thereon that are executable by a computing device to perform operations comprising:
 receiving a first sequence of pilot symbols from a base station over a wireless transmission channel, including at least a first pilot symbol and a second pilot symbol, wherein the second pilot symbol is received after the first pilot symbol; 
 determining first channel variation information for the transmission channel; 
 selecting to sample the first pilot symbol and not the second pilot symbol based on the first channel variation not meeting a threshold; determining a first channel state feedback (CSF) estimation using the selected first pilot symbol; 
 transmitting the first CSF estimation to the base station; 
 receiving a second sequence of pilot symbols from the base station over the wireless transmission channel, including at least a third pilot symbol and a fourth pilot symbol, wherein the fourth pilot symbol is received after the third pilot symbol; 
 determining second channel variation information for the transmission channel; 
 selecting to sample the fourth pilot symbol and not the third pilot symbol based on the second channel variation meeting the threshold; 
 determining a second CSF estimation using the selected fourth pilot symbol; and 
 transmitting the second CSF estimation to the base station. 
 
     
     
       14. The non-transitory computer-readable medium of  claim 13 , wherein calculating the first channel variation information includes calculating a Doppler estimate. 
     
     
       15. The non-transitory computer-readable medium of  claim 13 , wherein the first pilot symbol and the second pilot symbol are included in the same downlink subframe. 
     
     
       16. The non-transitory computer-readable medium of  claim 13 , wherein first pilot symbol and the second pilot symbol are included in a discontinuous downlink subframe that is received after the computing device has entered a power saving mode of operation.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     The present application claims priority to U.S. Provisional Application No. 61/725,255, filed Nov. 12, 2012, the entirety of which is incorporated by reference herein. 
    
    
     BACKGROUND 
     Field of the Invention 
     The present invention relates to channel state feedback (CSF) estimation techniques in wireless communication systems. 
     Background Art 
     Wireless communication system transmissions can be classified as either downlink (DL) or uplink (UL) transmissions. Downlink transmissions refer to signals transmitted from a base station (e.g., an eNodeB) to a mobile device (e.g., a user equipment (UE)). Uplink transmissions refer to signals transmitted from the mobile device (e.g., the UE) to the base station (e.g., the eNodeB). To ensure reliable and consistent communication, wireless systems often track the channel state conditions and adjust communication parameters (e.g., power or modulation parameters) accordingly. As an example, in TD-LTE systems, UE&#39;s calculate channel state feedback (CSF) reports based on downlink signals. 
     In a time-division (TD) based wireless communication system, such as TD-LTE, a frame structure for transmissions can include a plurality of subframes. The subframes can be designated as either uplink or downlink subframes. The frame structure can also include at least one special subframe.  FIG. 1  illustrates an exemplary special subframe  100  for a TD wireless communication system, such as TD-LTE. The special subframe  100  can include a downlink pilot time slot or transmission  110 , a guard period  120 , and an uplink pilot time slot or transmission  130 . The uplink and downlink pilot transmissions  110  and  130  can include reference signals. The reference signals can be used for a number of purposes including channel measurements or maintaining synchronization. The guard period  120  can separate the uplink and downlink pilot transmissions  110  and  130  to account for the round trip delay experienced by transmissions between the mobile device and the base station, and to account for multipath delay. Hence, the duration of the guard period  120  can directly correlate to the cell size (i.e., the larger the cell size, the longer the guard period  120 ). 
     For many TD wireless communication systems, such as TD-LTE, the number of uplink and downlink subframes can be varied. That is, while the total number of subframes in a frame structure can be fixed, the number of individual uplink subframes and downlink frames within a particular frame can be adjusted, and can vary from frame to frame. Consequently, downlink subframes are not always transmitted consecutively. Specifically, downlink subframes can be discontinuous because downlink subframes can be separated by one or more uplink subframes and/or one or more special subframes. Transmission parameters for a downlink subframe can be set based on CSF information where the CSF information, generally, is based on prior downlink transmissions. However, CSF information for discontinuous downlink subframes may not be accurate because channel states can change during the gaps between downlink subframes, which can lead to deterioration in communication quality. 
     Existing CSF estimation techniques for handling discontinuous downlink subframes are not optimal for varying channel state conditions. One technique is to simply ignore the first downlink subframe received after a gap of uplink subframes and/or special frames. In doing so, information for determining a reliable CSF estimation can be wasted. Further, if the mobile device is operating in a power save mode, ignoring the first discontinuous downlink subframe may require the mobile to consume more power waiting and then subsequently processing a next received downlink subframe to generate a CSF estimation. 
     Accordingly, what is needed is an adaptive CSF estimation technique; in particular, an adaptive CSF estimation technique that can accommodate varying channel state conditions and discontinuous downlink subframes. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings illustrate the present invention and, together with the description, further serve to explain the principles of the invention and to enable one skilled in the pertinent art to make and use the invention. 
         FIG. 1  illustrates an exemplary special subframe for a time-division (TD) based wireless communication system. 
         FIG. 2  illustrates a wireless communication system according to an aspect of the present invention. 
         FIG. 3  illustrates an adaptive channel state feedback (CSF) estimation system that can be implemented by the mobile device depicted in  FIG. 2  in accordance with an aspect of the present invention. 
         FIG. 4  provides an exemplary flowchart illustrating a method for providing adaptive CSF estimation in accordance with an aspect of the present invention. 
         FIG. 5  provides an exemplary flowchart illustrating a method for providing adaptive CSF sampling in accordance with an aspect of the present invention. 
     
    
    
     DETAILED DESCRIPTION 
     Aspects of the present invention provide apparatuses and methods for adaptive channel state feedback (CSF) estimation techniques. Downlink transmissions can be received at a mobile device. The downlink transmissions can be received after the mobile device has entered a power saving mode of operation. The downlink transmission received can be a discontinuous downlink subframe and can include one or more pilot symbols. A channel variation factor of the transmission channel can be determined based on the received downlink transmission. Based on the amount of variation of the transmission channel, either an earlier-received or a later-received pilot symbol can be used for CSF estimation. Further, either higher or lower weighted filter coefficients can be selected for use in CSF estimation based on the amount of variation of the transmission channel. The CSF estimation can extend to multiple received downlink transmission and to multiple pilot symbols received that can be received in each downlink transmission. 
       FIG. 2  illustrates a wireless communication system  200  according to an aspect of the present invention. The wireless communication system  200  can include a base station  210 . The base station  210  can be an eNodeB. The wireless communication system  200  can further include a mobile device  220 . The mobile device  220  can be a user equipment (UE). The mobile device  220  can include an antenna element  222  and a duplexer  224 . The antenna element  222  can include one or more antennas to transmit and receive radio-frequency (RF) signals to/from the base station  210 . As an example, the antenna element  222  may be a part of a multiple-input multiple-output (MIMO) system. The duplexer  224  can provide respective transmit and receive paths. 
     The mobile device  220  can further include RF circuitry  226  and a signal processor  228 . The RF circuitry  226  that can include receive circuitry  226 . 1  and transmit circuitry  226 . 2 . The RF circuitry  126  may include mixers, amplifiers, and/or other components to up-convert baseband signals to RF and to down-covert RF signals to baseband. The signal processor  228  can process baseband signals. 
     The wireless communication system  200  may be provided as a time-division (TD) based wireless communication system, for example a TD-LTE system. Also, the wireless communication system  200  may provide discontinuous downlink and/or uplink transmission, and different uplink and downlink time slots may be configured for a given frame structure. That is, for a given frame structure, a different number and arrangement of uplink and downlink subframes can be provided. For example, the following uplink/downlink configurations shown below in Table 1 can be provided: 
                     TABLE 1                  Exemplary Subframe Uplink/Downlink Configurations.                     Uplink-Downlink   Subframe number                                                         Configuration   0   1   2   3   4   5   6   7   8   9               0   S   S   U   U   U   D   S   U   U   U       1   D   S   U   U   D   D   S   U   U   D       2   D   S   U   D   D   D   S   U   D   D       3   D   S   U   U   U   D   D   D   D   D       4   D   S   U   U   D   D   D   D   D   D       5   D   S   U   D   D   D   D   D   D   D       6   D   S   U   U   U   D   S   U   U   D                    
where “D” represents a downlink subframe, “U” represents an uplink subframe, “S” represents a special subframe and one frame includes ten subframes. The first downlink subframe in a discontinuous transmission can be considered to be a “uDL”. For example, in Table 1, for uplink-downlink configuration “0,” subframe no. 5 can be referred to as a uDL.
 
     The wireless communication system  200  can implement one or more power saving modes of operation. During a power saving mode, the mobile device  220  can reduce power consumption by processing received signals less frequently. Longer durations between required receiving and processing operations can lead to increased battery life. 
     As an example, the wireless communication system  200  can support Connected Mode Discontinuous Reception (C-DRX) mode. The C-DRX mode can be as described in 3GPP TS 36.321, “3GPP EUTRA: Medium Access Control (MAC) Protocol Specification”, v9.6.0, March 2012. With C-DRX, the mobile device  220  can conserve battery power during periods of inactivity. While operating in C-DRX, the mobile device  220  can shut down its receiver (e.g., enter a sleep mode) and can occasionally or periodically monitor a control channel (e.g., a Physical Downlink Control Channel (PDCCH) in LTE systems) at specified intervals. C-DRX may include two cycles—short and long—which can vary the length of time the mobile device  220  can shut down its receiver. In C-DRX mode, the absence of a downlink transmission for a plurality of short cycles may trigger a long cycle. 
     For many conventional wireless systems, when a mobile device monitors a communication channel and receives a first downlink transmission (i.e., a first discontinuous downlink transmission or uDL), the first downlink transmission is ignored for purposes of CSF estimation. In doing so, the mobile device may be required to stay activated for a much longer period of time to receive a subsequent discontinuous downlink transmission to be used for CSF estimation. This can drain battery life and can cancel power conservation gains intended to be realized when operating in a power saving mode, such as C-DRX. Accordingly, an aspect of the present invention is directed to improving CSF estimation during such operation. 
       FIG. 3  illustrates an adaptive CSF estimation system  300  that can be implemented by the mobile device  220  of  FIG. 2  according to an aspect of the present invention. The adaptive CSF estimation system  300  can generate a CSF report. The adaptive CSF estimation system  300  can generate a CSF report based on one or more received pilot symbols received over one or more downlink transmissions. The A CSF report may include three components: (1) a channel quality indicator (CQI); (2) a precoding matrix index (PMI); and (3) a rank indication (RI). The adaptive CSF estimation system  300  can include a multiple-input multiple-output (MIMO) channel estimator  302 , a signal-to-noise ratio (SNR) estimator  304 , an SNR-to-spectral efficiency (SE) mapping element  306 , a channel variation estimator  308 , an adaptive parameter selector  310 , an SE filter  312 , and an SE-to-CQI mapping element  314 . 
     The MIMO channel estimator  302  can monitor a MIMO channel used to receive a downlink signal and can generate a whitened channeled matrix. 
     The SNR estimator  304  can analyze the whitened channeled matrix to generate an SNR estimate of the wireless channel. The SNR estimator  304  can execute a receiver algorithm to demodulate the downlink signal to generate the SNR estimate. The receiver algorithm can be, for example, a linear minimum mean square error (LMMSE), a maximum likelihood method (MLM), or a LMMSE with serial interference cancellation (LMMSE-SIC) algorithm. Further, the SNR estimation can be based on PMI (precoding matrix index) and RI (rank index). 
     The SNR-to-SE mapping element  306  can map the SNR estimate to an estimated SE metric considering the channel capacity and possible loss due to practical receiver implementations, thereby generating a raw SE metric. As an example, the SE estimation may be performed in a finer granularity with a smaller number of resource blocks (RBs) (e.g., 2 RBs). 
     The channel variation estimator  308  can monitor channel conditions. The channel estimator  308  can monitor channel conditions between discontinuous downlink subframes. The channel estimator  308  can generate a channel variation estimate, CH V . 
     As an example, the channel variation estimator  308  can be implemented as a Doppler estimator that can generate a Doppler estimate, Φ est . In a dynamic propagation environment, for example, Doppler estimation can be used to estimate the Doppler spread experienced by the mobile device  220  as it moves with non-zero speed. Doppler spread may be directly proportional to the channel time correlation. In other words, the faster the mobile device  220  moves, the larger the Doppler spread and the smaller the channel correlation time. 
     Doppler spread can be estimated in a variety of ways. One way to estimate Doppler spread is by calculating channel time auto-correlation estimates to perform Doppler spread classification into various Doppler spread regimes. This technique exploits the direct relationship between the channel time auto-correlation and Doppler spread. 
     Another way to estimate Doppler spread is by maximum likelihood estimation based on Doppler power spectral density. For example, the mobile device  220  can estimate Doppler power spectral density (PSD) using channel estimation from one or more pilot signals. Doppler shift can then be estimated based on maximum likelihood estimation of the expected Doppler PSD because Doppler PSD of a fading channel is indicative of its effect on spectral broadening. A technique for determining Doppler PSD in Rayleigh fading channels is described in “A Statistical Theory of Mobile Radio Reception,” by R. H. Clarke, Bell Systems Technical Journal 47 (6): 957-1000, 1968. 
     Alternatively or in addition to the these techniques, the channel variation estimator  308  can estimate other channel variation factors such as downlink block error rate (DL BLER)/cyclic redundancy check (CRC), frequency error, timing error, and/or any other suitable channel variation factors. 
     The adaptive parameter selector  310  can receive the channel variation estimate CH V  from the channel estimator  308 . The adaptive parameter selector  310  can compare the channel variation estimate CH V  to a threshold value, CH TH   _   V . Based on the comparison result, the adaptive parameter selector  310  can select adaptive parameters to be applied to the CSF generation to account for the channel variation. For example, the adaptive parameter selector  310  can select values for α that correspond to filtering coefficients for adaptive SE filtering and may select values for β that corresponds to pilot symbol positions for adaptive sampling. 
     The SE filter  312  can include one or more FIR (finite impulse response) filters or one or more IIR (infinite impulse response) filters or a combination thereof to filter the raw SE metric to generate a filtered SE estimate or metric. FIR filtering can have a fixed length of memory and can be a weighted sum of previous SE estimation. IIR filtering, on the other hand, can have a memory of infinite length with the impact of each sample exponentially decreasing, which generally provides a smooth weighted average across the time. As an example, a single-pole IIR filter may be implemented, and the time constant can be approximated as the inverse of the IIR filter coefficient. Filter coefficients used by the SE filter  312  can be based on α values received from the adaptive parameter selector  310 . The received β values can be used for adaptively sampling the received pilot symbol positions. The SE filter  312  may be implemented with optimal PMI/RI selection. 
     The SE-to-CQI mapping  314  may map the filtered SE estimation to a CQI value, which will can be reported back to the base station, for example, in an uplink transmission. A range of CQI values may be pre-set. For example, the following table lists CQI value ranges that may be used (which can be based on 3GPP TS 36.213, “3GPP Technical Specification Group Radio Access Network, Evolved Universal Terrestrial Radio Access (E-UTRA); Physical layer procedures”, V9.3.0, Sep. 2010): 
     
       
         
           
               
             
               
                 TABLE 2 
               
             
            
               
                   
               
               
                 Exemplary CQI Values 
               
            
           
           
               
               
               
               
            
               
                 CQI Index 
                 Modulation 
                 Code Rate × 1024 
                 Efficiency 
               
               
                   
               
            
           
           
               
               
            
               
                 0 
                 &lt;out of range&gt; 
               
            
           
           
               
               
               
               
            
               
                 1 
                 QPSK 
                 78 
                 0.1523 
               
               
                 2 
                 QPSK 
                 120 
                 0.2344 
               
               
                 3 
                 QPSK 
                 193 
                 0.3770 
               
               
                 4 
                 QPSK 
                 308 
                 0.6016 
               
               
                 5 
                 QPSK 
                 449 
                 0.8770 
               
               
                 6 
                 QPSK 
                 602 
                 1.1758 
               
               
                 7 
                 16-QAM 
                 378 
                 1.4766 
               
               
                 8 
                 16-QAM 
                 490 
                 1.9141 
               
               
                 9 
                 16-QAM 
                 616 
                 2.4063 
               
               
                 10 
                 64-QAM 
                 466 
                 2.7305 
               
               
                 11 
                 64-QAM 
                 567 
                 3.3223 
               
               
                 12 
                 64-QAM 
                 666 
                 3.9023 
               
               
                 13 
                 64-QAM 
                 772 
                 4.5234 
               
               
                 14 
                 64-QAM 
                 873 
                 5.1152 
               
               
                 15 
                 64-QAM 
                 948 
                 5.5547 
               
               
                   
               
            
           
         
       
     
     
       
         
           
               
             
               
                 TABLE 3 
               
             
            
               
                   
               
               
                 Exemplary Modulation and TBS Index Table for Physical 
               
               
                 Downlink Shared Channel (PDSCH) 
               
            
           
           
               
               
               
            
               
                 MCS Index 
                 Modulation Order 
                 TBS Index 
               
               
                 I MCS   
                 Q m   
                 I TBS   
               
               
                   
               
            
           
           
               
               
               
            
               
                 0 
                 2 
                 0 
               
               
                 1 
                 2 
                 1 
               
               
                 2 
                 2 
                 2 
               
               
                 3 
                 2 
                 3 
               
               
                 4 
                 2 
                 4 
               
               
                 5 
                 2 
                 5 
               
               
                 6 
                 2 
                 6 
               
               
                 7 
                 2 
                 7 
               
               
                 8 
                 2 
                 8 
               
               
                 9 
                 2 
                 9 
               
               
                 10 
                 4 
                 9 
               
               
                 11 
                 4 
                 10 
               
               
                 12 
                 4 
                 11 
               
               
                 13 
                 4 
                 12 
               
               
                 14 
                 4 
                 13 
               
               
                 15 
                 4 
                 14 
               
               
                 16 
                 4 
                 15 
               
               
                 17 
                 6 
                 15 
               
               
                 18 
                 6 
                 16 
               
               
                 19 
                 6 
                 17 
               
               
                 20 
                 6 
                 18 
               
               
                 21 
                 6 
                 19 
               
               
                 22 
                 6 
                 20 
               
               
                 23 
                 6 
                 21 
               
               
                 24 
                 6 
                 22 
               
               
                 25 
                 6 
                 23 
               
               
                 26 
                 6 
                 24 
               
               
                 27 
                 6 
                 25 
               
               
                 28 
                 6 
                 26 
               
               
                 29 
                 2 
                 reserved 
               
               
                 30 
                 4 
               
               
                 31 
                 6 
               
               
                   
               
            
           
         
       
     
     Adaptive CSF estimation techniques described herein in accordance with an aspect of the present invention can be used in all communication modes of mobile device  202 . For example, adaptive CSF estimation techniques can be used when the mobile device  220  operates in a connected continuous mode where adaptive CSF estimation may improve time budgets. Adaptive CSF estimation can be especially beneficial in C-DRX mode, however, because of power consumption considerations and because of the ability to provide accurate estimations with a small amount of data and little time. 
       FIG. 4  provides an exemplary flowchart illustrating a method  400  for providing adaptive CSF estimation in accordance with an aspect of the present invention. The method  400  can be implemented by the mobile device  220 , including mobile device  220  having adaptive CSF estimation system  300  described above in relation to  FIGS. 2 and 3 , respectively. The method  400  is exemplary and an aspect of the present invention provides for the steps of the method  400  to be performed in different sequences or with multiple steps being performed at substantially the same time. 
     At step  402 , a power saving mode of operation can be entered. As an example, C-DRX mode of operation can be entered. As described above, C-DRX mode is a connected discontinuous reception mode that allows mobile device to conserve battery power during periods of inactivity. 
     At step  404 , a downlink transmission is received. The downlink transmission can be a discontinuous downlink transmission including one or more subframes. The downlink transmission can be a uDL. 
     At step  406 , a channel variation factor, CH V , can be calculated. As an example, the channel variation factor CH V  can be a Doppler estimate Φ est . Calculating the channel variation factor can be considered to be monitoring the transmission channel conditions or determining a condition of the transmission channel. 
     At step  408 , the channel variation factor CH V  can be compared to a threshold value, CH TH   _   V . As an example, for a Doppler estimate (Φ est , it can be compared to a Doppler threshold value, Φ thres . 
     At step  410 , if the channel variation factor CH V  is less than or equal to the threshold value CH TH   _   V , then a higher weighted filtering coefficient, α H , can be applied. As an example, for a Doppler estimate Φ est , if it is less than or equal to Φ thres , then a higher weighted filtering coefficient α H  can be applied. If the channel variation factor CH V  is greater than the threshold value CH TH   _   V , then a lower weighted filtering coefficient, α L , can be applied. As an example, for a Doppler estimate Φ est , if it greater than Φ thres , then the lower weighted filtering coefficient α L  can be applied. Further, α H  can be larger (e.g., its magnitude) than α L  (α H &gt;α L ). 
     The selected filter coefficient, either α H  or α L , can be used to perform SE filtering. For example, as shown in  FIG. 3 , the filter coefficient selected by the adaptive parameter selector  310  can be provided to the SE filter  312  to filter a raw SE metric provided by the SNR-to-SE mapping elements  306 . The resulting filtered SE metric can then be used by the SE-to-CQI mapping element  314  to generate a portion of the CSF estimation. In this way, the CSF estimation is based on channel conditions and weighted accordingly. For example, the CSF estimation can be provided for a uDL and weighted based on channel conditions and specifically how quickly the channel conditions are varying. 
     Based on the adaptive CSF estimate method  400 , if the channel conditions tend to vary (i.e., exceed a threshold), a lower weight may be applied to the CSF estimation. Conversely, if the channel conditions tend to be stable (i.e., below a threshold), a higher weight may be applied to the CSF estimation. The adaptive CSF estimation illustrated in  FIG. 4  can extend to multiple pilot symbols received over multiple downlink transmissions. 
       FIG. 5  provides an exemplary flowchart illustrating a method  500  for providing adaptive CSF sampling in accordance with an aspect of the present invention. The method  500  can be implemented by the mobile device  220 , including mobile device  220  having adaptive CSF estimation system  300  described above in relation to  FIGS. 2 and 3 , respectively. The method  500  is exemplary and an aspect of the present invention provides for the steps of the method  500  to be performed in different sequences or with multiple steps being performed at substantially the same time. 
     At step  502 , a channel variation factor, CH V , can be calculated. As an example, the channel variation factor CH V  can be a Doppler estimate Φ est . Calculating the channel variation factor can be considered to be monitoring the transmission channel conditions or determining a condition of the transmission channel. 
     At step  504 , the channel variation factor CH V  can be compared to a threshold value, CH TH   _   V . As an example, for a Doppler estimate Φ est , it can be compared to a Doppler threshold value, Φ thres . 
     At step  506 , if the channel variation factor CH V  is less than or equal to the threshold value CH TH   _   V , then an earlier pilot symbol β E  can be used for sampling. 
     At step  508 , if the channel variation factor CH V  is greater than the threshold value CH TH   _   V , then a later pilot symbol β L  can be used for sampling. 
     The earlier pilot symbol β E  is received prior to the later pilot symbol β L . As an example, for a Doppler estimate Φ est , if it is less than or equal to Φ thres , then β E  can be used. Otherwise, β L  can be used. Based on the adaptive CSF sampling method  500 , if the channel conditions tend to vary (i.e., exceed threshold), a later pilot symbol may be used for sampling that will better approximate channel conditions at the current CSF estimation time. However, if the channel conditions tend to be stable (i.e., below threshold), an earlier pilot symbol may be used for sampling. 
     The adaptive CSF sampling method  500  can be applied to a given received subframe. For example, a received subframe can include four pilot symbols (e.g., at symbol positions 0, 4, 7, 11). If the channel conditions over which received downlink frames tend to vary (i.e., exceed threshold), a later pilot symbol can be used for sampling. For example, the pilot symbol at symbol position 11 (rather than an earlier pilot symbol at symbol positions 0, 4, or 7) can be used. By using a later pilot symbol, the CSF estimation may resemble current channel conditions more accurately than using an earlier pilot symbol. 
     However, if the channel conditions tend to be stable (i.e., below threshold), an earlier pilot symbol can be used for sampling. For example, the pilot symbol at symbol position 0 (rather than a later received pilot symbol at symbol positions 4, 7, or 11) can be used. By using an earlier pilot symbol, the mobile device (e.g., mobile device  220 ) can have more time to perform the CSF estimation without compromising accuracy while using power more efficiently since the channel conditions at the time of sampling may resemble current conditions. The adaptive CSF sampling illustrated in  FIG. 5  can extend to multiple pilot symbols received over multiple downlink transmissions. 
     The selected pilot symbol, either β L  or β E , can be used to perform SE filtering. For example, as shown in  FIG. 3 , the selected pilot symbol can be used by the adaptive parameter selector  310  and the SE filter  312  to determine filter coefficient α. The filter coefficient used by the SE filter  312  can be based on the selected pilot symbol used for sampling. The filter coefficient can be used to filter a raw SE metric provided by the SNR-to-SE mapping element  306 . The resulting filtered SE metric can then be used by the SE-to-CQI mapping element  314  to generate a portion of the CSF estimation. In this way, the CSF estimation is based on channel conditions and weighted accordingly. For example, the CSF estimation can be provided for a uDL and weighted based on channel conditions and specifically how quickly the channel conditions are varying. 
     While various aspects of the present invention have been described above, it should be understood that they have been presented by way of example and not limitation. It will be apparent to one skilled in the pertinent art that various changes in form and detail can be made therein without departing from the spirit and scope of the invention. Therefore, the present invention should only be defined in accordance with the following claims and their equivalents.

Metadata:
Filing Date: 20131108
Publication Date: 20171017
Grant Date: 20171017
Priority Date: 20121112
Inventors: JI ZHU
DAMJI NAVID
SEBENI JOHNSON
Assignee: APPLE INC
CPC Classifications: [{"code": "H04L25/0204", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04W24/10", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04L25/0224", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04L25/0222", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04B7/065", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04L1/0023", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04L1/0026", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04L25/0222", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04L25/0224", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04B7/065", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04L1/0023", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04W24/10", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04L25/0204", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04L1/0026", "inventive": true, "first": false, "tree": "[]"}]
Family ID: 49679622