Abstract:
An apparatus and method estimates the adaptive wireless channel for a moving vehicle. Once a packet is received, this invention analyzes a channel interference index for the moving vehicle, and computes a first recursive parameter, a second recursive parameter and an interpolation number. Based on the first recursive parameter and the interpolation number, partial channel information is calculated for further channel estimation by using an interpolation. The parameter of an equalizer is also immediately updated. Cooperating with a decision feedback scheme and based on the second recursive parameter, channel tracking is performed. In order to achieve the adaptive channel estimation for wireless access on the time-variant vehicle environment, the parameter for the algorithm for performing the channel estimation is adjusted.

Description:
FIELD OF THE INVENTION 
   The present invention generally relates to an apparatus and method for adaptive wireless channel estimation, applicable to the wireless access on vehicle environment. 
   BACKGROUND OF THE INVENTION 
   The recent rapid growth in wireless communication adds the mobility to information services. However, for the vehicles traveling at high speed, such as cars and rapid railway, the service similar to wireless local area network (WLAN) is still not available. The transportation safety mechanism is one of the major issues in the car market. As more and more electronic technologies, such as global positioning system (GPS) and reverse radar, become the standard options for most vehicles, the safer and inexpensive collision prevention mechanism is becoming the next wave for market competition. 
   The general communication environment is moving from the pedestrian towards the vehicles in three directions. The first is the telematics service, such as remote diagnostics, which requires the cart to be connected to the back-end server for transmitting and receiving information to access network resources. The second is the communication for connecting one car to another for exchanging the sensed data and information, and exchanging the information between a car and an infrastructure, such as electronic toll, and inter-vehicle warning communication. The third is to provide connection of portable devices with the vehicle so that the vehicle information can be easily transmitted to the portable devices. 
   The global vehicle telematics service can be provided with the help of the wide-coverage 3G wireless communication or GPS. The stationary or low speed connection of portable devices to the network can be accomplished by the hotspot or the fixed WLAN access. 
   U.S. Pat. No. 6,954,421 disclosed an orthogonal frequency division multiplexing (OFDM) receiver device.  FIG. 1  shows a schematic view of a channel estimation method of the receiver device. As shown in  FIG. 1 , the receiver device uses four pilot signals for four-point channel estimation values. The linear interpolation is performed on the channel estimation values at these four points H( 0 , 0 )-H( 0 , 3 ) to obtain the channel estimation values H′( 1 , 0 )-H′( 47 , 0 ) of a full transmission path, and the equalizer parameter is updated in real time to improve the channel estimation performance. 
   In the multi-path time-variant channel, the linear interpolation on four-point channel estimation can cause the resolution to drop as the interpolation range is large, which further results in the large estimation error, and the time-variant compensation effect deteriorates. The stability of wireless network access for high speed vehicles is poor when applying this method. 
   The major obstacle of the current wireless communication technology to overcome is how to apply the WLAN concept to the inter-vehicle communication and the communication for access points between vehicle and roadside, so that the vehicle has the inexpensive data communication functionality and can form a moving short-distance LAN for promoting driving safety and providing warning messages. The technology barrier is the signal detection and decoding at high speed because the estimation and decoding difficulties increase due to the time-variant channel effect caused by high Doppler frequency. The solution will require the synchronization, channel equalization and estimation, decoding mechanism to form an efficient combination to reduce the cost. 
   SUMMARY OF THE INVENTION 
   The examples of the present invention may provide an apparatus and method for adaptive wireless channel estimation, applicable to a moving vehicle in a time-variant environment. The apparatus utilizes the existing basic structure and specification to provide a new adaptive channel tracking mechanism to estimate and compensate the time-variant channel. 
   The adaptive wireless channel estimation apparatus comprises a decision feedback channel tracking unit, a pilot-aided channel tracking module, and an adaptive controller. 
   The present invention performs the interpolation on the channel estimation information of the pilot signal and the channel estimation information of the feedback signal. Then, a recursive computation is performed and the equalizer parameter is updated. The decision feedback is further used for tracking time-variant channel, and the algorithm parameter can be adaptively adjusted for moving vehicle time-variant environment so as to achieve the adaptive wireless channel estimation. 
   The foregoing and other objects, features, aspects and advantages of the present invention will become better understood from a careful reading of a detailed description provided herein below with appropriate reference to the accompanying drawings. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
       FIG. 1  shows a schematic view of a conventional channel estimation method of the receiver device. 
       FIG. 2  shows a schematic view of an apparatus for adaptive wireless channel estimation according to the present invention. 
       FIG. 3  shows a flowchart illustrating the operation of the apparatus for adaptive wireless channel estimation of  FIG. 2 . 
       FIG. 4  shows the detailed structure of each element of the pilot-aided channel tracking module and the operation process thereof. 
       FIG. 5  shows an example illustrating the channel estimation method used by the apparatus of the present invention. 
       FIG. 6  shows the operating for the adaptive channel estimation of the present invention cooperating with an equalizer after receiving a packet. 
   

   DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     FIG. 2  shows a schematic view of an apparatus for adaptive wireless channel estimation according to the present invention. As shown in  FIG. 2 , an apparatus  200  for adaptive wireless channel estimation comprises a pilot-aided channel tracking module  201 , a decision feedback channel tracking unit  203  and an adaptive controller  205 . The outputs of the pilot-aided channel tracking module  201  and the decision feedback channel tracking unit  203  are combined and then sent to an equalizer  207 .  FIG. 3  shows a flowchart illustrating the operation of the apparatus for adaptive wireless channel estimation of  FIG. 2 . 
   The apparatus for wireless channel estimation is applicable to a moving vehicle in a time-variant environment, such as wireless access on a vehicle environment. In other time-variant wireless access environment, an OFDM-based system can also use the adaptive channel estimate apparatus to improve the reliability of channel information. 
   The following describes the operating flow of  FIG. 3  in conjunction with  FIG. 2 . When a packet is received, the first step is to initialize the channel estimation. Then, the adaptive controller  205  performs an adaptive analysis and calculates a first recursive parameter G 1 , a second recursive parameter G 2 , and an interpolation number interp_no, as shown in step  301 . The adaptive controller  205  targets the channel interference index, such as the environmental signal-to-noise ratio (SNR) and the speed of the moving vehicle, to perform adaptive analysis. Based on the first recursive parameter G 1  and interpolation number interp_no, the pilot-aided channel tracking module  201  performs the channel tracking on an information symbol of the packet, and determines an optimal channel information, as shown in step  302 . 
   In step  302 , an interpolation is performed on a plurality of pilot-aided channel estimations and a plurality of feedback channel estimations at previous time to obtain a plurality of partially updated channel information, to adjust the optimal channel information through the first recursive parameter G 1 , and to update the parameter of the equalizer  207  in real time. 
   The updated equalizer  207  performs channel compensation on the information symbol, as shown in step  303 . In step  303 , the updated equalizer  207  refers to a plurality of partially updated channel information and a signal in frequency axis f obtained from the pilot-aided channel tracking to perform channel compensation. The signal in frequency axis f(n) can be signals transformed by a Fast Fourier Transform (FFT) processing unit. 
   The decision feedback tracking unit  203  performs decision feedback on the compensated information symbol, performs channel tracking according to the recursive parameter G 2 , and performs iterative update on the feedback channel estimation of previous time to provide for the next information symbol, as shown in step  304 . 
   The above steps are repeated until all the information symbols in the packet are processed, as shown in step  305 , and the process proceeds to the next received packet. 
   When the interpolation is performed in step  302 , if the information symbol in the packet is the first information symbol, the estimated channel information and pilot information obtained from the long preamble are used in the interpolation. The subsequent symbols use the channel estimation values of decision feedback and the pilot information for interpolation. 
   It is worth noting that the pilot channel estimation values obtained by the symbols can be estimated in several ways, such as least mean square (LMS). Then, the adjustment of the optimal channel information can be performed according to the recursive parameter determined by the environmental quality. 
   In transmitting the packet, the speed of moving vehicle and the environmental SNR are the indicators regarding whether the transmitted signals are prone to channel interference. For example, when the moving vehicle moves at a higher speed, and the environmental SNR is lower, the channel changes more drastically. Therefore, the channel estimation error will increase. Hence, recursive parameters G 1 , G 2  should be tuned down and the interpolation number should be reduced. 
     FIG. 4  shows the detailed structure of each element of the pilot-aided channel tracking module and the operation process thereof. As shown in  FIG. 4 , the pilot-aided channel tracking module  201  includes a pilot signal generator  401   a,  a pilot-aided channel estimation unit  401   b,  a channel interpolation module  401   c,  and a recursive computing unit  401   d.  The operation of pilot-aided channel tracking module  201  is as follows. The pilot signal generator  401   a  extracts a plurality of pilot signals from each information symbol to provide to pilot-aided channel estimation unit  401   b.  Based on the pilot signals, the pilot-aided channel estimation unit  401   b  performs a plurality of channel estimations. Then, based on interpolation number interp_no, the channel estimations by pilot-aided channel estimation unit  401   b,  and the channel information of previous time estimated by the decision feedback channel tracking unit  203 , the channel interpolation module  401   c  performs an interpolation to obtain a plurality of partially update channel information. Finally, the recursive computing unit  401   d  uses LMS to adjust the optimal channel information by using the pilot-aided channel estimation values from two successive information symbols and the recursive parameter G 1  determined by the environmental quality. 
   The adjusted optimal channel information is provided to the equalizer  207  for updating parameter in real time. The interpolation number interp_no can also be adjusted according to the environment. The updated equalizer  207  performs channel compensation on the information symbol. 
     FIG. 5  shows an example illustrating the channel estimation method used by the apparatus of the present invention. As shown in  FIG. 5 , the present invention uses a plurality of pilot signals for multi-point channel estimation, and uses the pilot-aided channel estimation values H PA ( 0 , 0 )−H PA ( 0 ,n) and the feedback signal channel estimation values I( 0 , 0 )−I( 0 ,m) for interpolation to obtain the channel estimation values of a full transmission path, including using an algorithm in channel estimation, adjusting algorithm parameter, updating equalizer parameter, channel compensation, and combining the channel estimation information from decision feedback. 
   Because the present invention uses pilot-aided channel estimation values and feedback signal channel estimation values for interpolation, the interpolation range shrinks and resolution increases. Combining decision feedback channel estimation also increases the channel estimation precision. Furthermore, for the time-variant vehicle environment, the present invention adaptively adjusts the algorithm parameter to improve the time-variant channel tracking. The present invention is also stable when applied to the wireless network access in a high speed vehicle environment. 
   In comparison with the conventional channel estimation method of  FIG. 1 , the present invention has a smaller estimation error in multi-path time-variant channel estimation, the better frequency selection, and better adaptation to vehicle environment. 
   In summary,  FIG. 6  shows the adaptive channel estimation operation of the present invention cooperating with an equalizer after receiving a packet. As shown in  FIG. 6 , step  601  is to perform channel estimation initialization after receiving a packet. As aforementioned, when the information symbol of the packet is the first information symbol, the channel information and pilot-aided information obtained by long preamble are used for interpolation. This detail is omitted from  FIG. 6 . 
   The subsequent information symbols use decision feedback channel estimation and pilot-aided information for interpolation. The subsequent information symbols also cooperate with the equalizer in adaptive channel estimation. 
   The adaptive controller  205  performs an adaptive analysis  602  for the speed of moving vehicle and the environmental SNR. The adaptive analysis  602  calculates the first recursive parameter G 1 , the second recursive parameter G 2 , and the interpolation number interp_no. The first recursive parameter G 1  and the interpolation number interp_no are provided to the pilot-aided channel tracking module  201  for pilot-aided channel tracking  603 , and the second recursive parameter G 2  is provided to the decision feedback channel tracking unit  203  for decision feedback channel tracking  606 . 
   In the pilot-aided channel tracking  603 , the pilot signal generator  401   a  extracts pilot-signals from each information symbol, and the pilot signals are used for detailed channel estimation. Because pilot signals have certain characteristics, the channel estimation is accomplished with certain precision. Based on the pilot signals, the pilot-aided channel estimation unit  401   b  performs channel estimations. Based on interpolation number interp_no, the pilot-aided channel estimations of the current information symbol from the pilot-aided channel estimation unit  401   b,  and the channel information of previous time from the decision feedback channel tracking unit  203 , the channel interpolation module  401   c  performs an interpolation to obtain a plurality of partial update channel information H pA1 (n). As aforementioned, the recursive computing unit  401   d  uses LMS to adjust the optimal channel information H LMS1 (n) by using the pilot-aided channel estimation from two successive information symbols and the recursive parameter G 1  determined by the environmental quality. That is, H LMS1 (n)=H pA1 (n)*G 1 +H pA1 (n−1)*(1−G 1 ). 
   In the decision feedback channel tracking  606 , the decision feedback tracking unit  203  uses decision feedback symbol as the training symbol to perform frequency domain response on channel, and uses LMS to iteratively update channel estimation values H new (n) and H new (n−1). Each information symbol is executed once. In LMS algorithm, the recursive parameter G 2  is generated by the adaptive controller  205 . In other words, after using LMS for iterative update of channel estimation values, the adjusted channel estimation value is H LMS2(n) , where H LMS2 (n)=H new (n)*G 2 +H new (n−1)*(1−G 2 ). 
   The present invention uses channel estimation H LMS2 (n) that is iteratively updated by the decision feedback channel tracking unit  203  and the optimal channel information H LMS1 (n) that is adjusted by the pilot-aided channel tracking module  201  to perform the equalizer update  604 . That is, the parameter of equalizer  207  is updated in real time. The updated equalizer  207  performs channel compensation on information symbols. 
   The decision feedback channel tracking unit  203  performs decision feedback on the compensated information symbol, and performs channel tracking based on the recursive parameter G 2 . The updated channel estimation H LMS2 (n) is provided to the next information symbol. 
   Although the present invention has been described with reference to the preferred embodiments, it will be understood that the invention is not limited to the details described thereof. Various substitutions and modifications have been suggested in the foregoing description, and others will occur to those of ordinary skill in the art. Therefore, all such substitutions and modifications are intended to be embraced within the scope of the invention as defined in the appended claims.