Abstract:
A generator ( 304 ) generates first and second training signals ( 320, 318 ) that originate within a wireless communication device (FIG.  3 ) instead of being received from a source outside the device. A receive portion ( 212, 214, 216 ) of the device processes the first training signal to derive a processed training signal. An adaptive equalizer ( 310 ) equalizes the processed training signal to derive an equalized training signal. A processor ( 312 ) compares the equalized training signal and the second training signal using an adaptive algorithm to derive coefficients for the adaptive equalizer to compensate for variations in the receive portion, and adjusts the adaptive equalizer in accordance with the coefficients to derive a compensated output signal.

Description:
FIELD OF THE INVENTION 
     This invention relates in general to wireless communication systems, and more specifically to a method and apparatus for compensating for variations in a receive portion of a wireless communication device. 
     BACKGROUND OF THE INVENTION 
     Optimal demodulation of signals in additive white Gaussian noise channels requires that the receive filter be matched to the transmit filter. A wireless communication device, however, generally uses analog filters in its receive portion for anti-aliasing and selectivity purposes. Unfortunately, the frequency and time domain responses of analog filters can vary over process, temperature, and supply voltage. Thus, in the prior art it has not been possible to maintain a fixed composite response in the receiver that is matched to the transmit filter in the base station throughout the operational life and environmental range of the wireless device without using a training sequence originating from the base transmitter. Such non-optimal, unmatched filtering can degrade the receiver sensitivity by more than 1 dB. Further, for high data rate systems such as those commonly referred to as 2.5G and 3G systems, a 1 dB sensitivity loss can lead to significant loss in system throughput and capacity. 
     Thus, what is needed is a method and apparatus for compensating for variations in the receive portion of a wireless communication device. Preferably, the method and apparatus will provide near-optimal matched filtering and, hence, greatly improved receiver performance over the operating life of the wireless communication device. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an electrical block diagram depicting channel filters in a prior-art wireless communication system. 
         FIG. 2  is an electrical block diagram of an exemplary prior-art wireless communication device. 
         FIG. 3  is an electrical block diagram of an exemplary wireless communication device in accordance with a first embodiment of the present invention. 
         FIG. 4  is a simplified operational block diagram in accordance with the present invention. 
         FIG. 5  is an electrical block diagram of an exemplary wireless communication device in accordance with a second embodiment of the present invention. 
         FIG. 6  is a flow diagram depicting a receiver warm-up sequence in accordance with the present invention. 
         FIG. 7  is a diagram depicting magnitude response in accordance with the present invention. 
         FIG. 8  is a diagram depicting group delay response in accordance with the present invention. 
     
    
    
     DETAILED DESCRIPTION 
     Referring to  FIG. 1 , an electrical block diagram depicts channel filters in a prior-art wireless communication system. The filters include an ideal transmit filter  104  in a base station  102 . The transmit filter  104  comprises relatively expensive components to achieve a filter response, g(n), that is close to ideal and is maintained to a high degree over, for example, temperature and supply voltage variations. Next, there is a response, c(n,t) of the communications channel  106 , which varies over time. 
     Finally, in a mobile device  108 , a receiver&#39;s composite channel filter response is primarily dictated by an analog baseband filter  110  prior to the A/D, and a digital baseband selectivity filter  112  located thereafter. This is because other filters within the receiver such as high frequency SAW type filters used for the RF/IF frequencies typically exhibit a rather flat in-band group delay response and a much wider cutoff frequency than the baseband filters. This results in the RF/IF filters having a negligible impact on the in-band magnitude/phase response of the composite channel filter in the receiver of the mobile device. For this reason, the effects of the RF/IF filters are largely ignored in this disclosure. In  FIG. 1 , the analog filter response, h(n,t), primarily denotes the response of the analog baseband filter  110 , which serves the purposes of anti-aliasing as well as protection against nearby blockers and higher order modulation products. Notice that the response of this analog filter has a time variable, t, associated with it, since its response varies with asundry process, temperature, and supply voltage variations. Ultimately, after the A/D device, there is typically the need for the digital baseband selectivity filter  112  with response, f(n), to provide the final mobile device selectivity against adjacent channel and blocker type interferers. Another purpose of this digital filter is to provide a composite magnitude/phase response in the receiver which matches that in the base station transmitter in an attempt to maximize SNR (Signal-to-Noise ratio) and thus receiver sensitivity. Note that the digital filter response, f(n), does not have any time variable associated with it since its magnitude/phase response does not significantly change over or with process, temperature, and supply voltage variations. 
     There are many methods in designing, f(n), with varying complexity and sensitivity, which are inversely proportional. The most common method for designing f(n), which is the least complex and hence provides the worst average SNR, uses a single fixed filter designed for the mean value of the analog circuit, h(n,t). However, any deviation in the channel, c(n,t), or the analog circuit, h(n,t), will result in a degradation of the SNR. Hence, the most complex method for f(n), which provides the best SNR, is an adaptive filter to model both the channel, c(n,t), and receiver front end analog circuits, h(n,t). This method requires that the base station transmitter periodically send training sequences. This will result in the optimal receiver SNR, assuming that c(n,t) and h(n,t) change very slowly during the period of time between training sequences. The main drawback is that the system&#39;s throughput is decreased because the base transmitter must periodically transmit such training sequences. 
     An aspect of the present invention described herein below is that it can improve the receiver sensitivity when employing communication standards which do not have provisions for periodic training sequences in the protocol definition. For protocols that do support periodic training sequences, the present invention is still applicable in situations when the training sequence is NOT received with sufficient signal strength. 
     Referring to  FIG. 2 , an electrical block diagram depicts an exemplary prior-art wireless communication device  200  with quadrature inputs to the transmit signal path and quadrature outputs from the receive signal path. The transmit path consists of ideal I/Q digital transmit filters  206  at baseband whose outputs are converted to the analog domain by digital to analog convertors before being modulated up to RF frequency levels in the transmit lineup  202 . In the receive path, the RF signal is first demodulated to a baseband signal and then passed through an analog anti-aliasing/blocker protection filter (AAF)  212  before being converted to digital I/Q signals using the A/D converters  214 . Following the A/D converters, digital A/D filters  216  as shown are required when commonly used oversampled A/D type converters are employed. (Other types of A/D converters may not require the A/D filters  216 ) Such oversampled A/D converters are frequently used to minimize the selectivity (and also cost) requirements of the anti-aliasing filter. Popular sigma-delta type A/D converters also fall into this oversampled A/D converter category. The A/D filters  216  shown in this diagram are essentially decimation filters which preserve the in-band frequency response and sufficiently attenuate out-of-band noise. With this baseband line-up, the response of the receiver portion comprising the AAF  212  and the A/D converter  214  can vary over process, temperature, and supply voltage. 
     In addition, encompassing the analog baseband filter and the A/D unit there typically is the need for a mixed-mode DC offset correction (DCOC) loop  218 ,  220 . The purpose of this loop is to eliminate static and dynamic DC offsets that can leak to the baseband signal path and can adversely affect the dynamic range of both the analog baseband filter  212  and the A/D  214 . In addition, DC offsets can also degrade the detectability of the received signal. The DCOC loop is typically comprised of digital DC offset detection  218 , conversion of the DC offset error signal to analog format in a D/A  220 , and subtraction of the error from the input signal at the baseband filter input  224 . After this DC correction loop, there resides a fixed digital filter  222  which provides additional selectivity against adjacent channel and blocker type interferers. Another purpose of this filter  222  is to provide a matched filter response to achieve improved SNR. Unfortunately, since this digital filter is typically a fixed filter, greater than 1 dB sensitivity loss can result due to variations in the analog baseband filter pole/zero locations with or over process, temperature, and supply voltage variations. This is because these changes in the pole and zero locations result in undesirable distortions in the cutoff frequency, high frequency amplitude peaking, and group delay responses. The result of all this is degraded SNR at the detection unit and reduced receiver sensitivity performance. 
     Referring to  FIG. 3 , an electrical block diagram  300  depicts an exemplary wireless communication device in accordance with a first embodiment of the present invention. The diagram  300  is similar to the diagram  200 , the essential difference being the replacement of the fixed selectivity filter  222  by the adaptive equalizer  310  and control circuitry therefor, in accordance with the present invention, as described further herein below. As mentioned earlier, the RF/IF high frequency SAW type filters  322 ,  324  are typically much wider bandwidths with a rather flat group delay response in-band, thus, they have a negligible impact on the in-band response. Therefore, we do not compensate for these high frequency filters in the adaptive equalizer  310 . This equalizer can adaptively compensate for the frequency and time domain distortions in both the analog baseband filter (AAF)  212  and the A/D converter  214 . The adaptive architecture depicted in  FIG. 3  advantageously makes use of pre-existing hardware with minimal additional circuitry to achieve the desired adaptation while achieving the desired channel selectivity at the same time. The adaptive equalizer works as follows. During periodic warm-up sequences, after the DC offset correction loop has settled, a conventional pseudo-random PN sequence generator  304  preferably is used to supply a first training signal  320  to an input  308  of the feedback path in the DC offset correction loop in both the I and Q portions of the receive path. It is also preferably applied (through a multiplexer  302 ) to the input of the ideal transmit filter  206  of the I transmit path to derive a second training signal  318 . As shown, the first training signal  320  preferably is added to the DC offset acquired previously and then the result is fed into the input of the analog baseband filter  212 . This ensures that the training signal does not have any undesirable DC offset bias. The first training signal is then processed by the analog baseband filter  212  and the A/D section  214 ,  216  to derive a processed training signal at the input of the adaptive equalizer  310 . The signal path through the analog baseband filters and the A/Ds represents the non-ideal signal path while the signal path through the transmit filter to the inputs of the equalizers represents the ideal signal path. It will be appreciated that, alternatively, other types of training signals, e.g., a step input, a ramp input, an impulse, can be used as well for training the adaptive equalizer  310 . It will be further appreciated that, alternatively, the training signal can be inserted into a different point of the analog section of the receive path, e.g., directly into the analog baseband filter  212 . In addition, it will be appreciated that, alternatively, another filter, e.g., a desired target receive filter that achieves an optimal link performance in the presence of expected interferers, can be used instead of the ideal transmit filter  206  for deriving the second training signal  318 . 
     The adaptive equalizer  310  equalizes the processed training signal to derive an equalized training signal at its output. The adaptive equalizer  310  and adaptive algorithm processor  312  then cooperate to compare the equalized training signal with the second training signal  318  to modify the equalizer coefficients with the objective of matching the equalized training signal to the second training signal. Note that the delay element, z −N    306 , which is used in the ideal signal path is used to compensate for any additional delays in the non-ideal signal path through the baseband filter  212  and A/D section  214 ,  216 . After the adaptive equalization has been completed, the adaptive equalizer coefficients are held until the next warm-up sequence when the first and second training signals are again applied for adaptation purposes. It will be appreciated that the digital portions of the diagram  300  can be realized in a conventional digital signal processor (DSP) through software written by one of ordinary skill in the art, given the teachings of this disclosure. It will be further appreciated that some or all portions of the diagram  300  can be realized in one or more custom integrated circuits. 
     Referring to  FIG. 4 , a simplified block diagram in accordance with the present invention helps explain the operation of the diagram  300 . Here, the filter, h(n,t)  408  represents the composit response of the analog baseband filter  212  and the A/D section  214 ,  216 , which can vary over or with process, temperature, and supply voltage variations. Thus, it represents the non-ideal signal path. The output of filter  408  is x(n)  416  and this is applied to the adaptive equalizer  310  having respnse f(n) to provide the output y(n)  414  which is also coupled to the adaptive algorithm processor  312 . The ideal signal path is represented by the path through the transmit filter  206  and delay element  306  that provides the ideal or reference signal d(n)  418  to the adaptive algorithm processor  312 . The objective of the adaptive algorithm processor  312  is to modify the response ƒ(n), of the adaptive equalizer  310  such that the response of the non-ideal path is corrected to match that of the ideal path. 
     The equalizer training process preferably uses known optimal filtering methods to determine the coefficients for the matched filter. The adaptive algorithm can be any one of the following known adaptation methods: 
     Least Mean Squares (LMS) (This is the preferred method when a PN training sequence is used): 
                 f     n   +   1       _     =         f   n     _     +     α   ⁢           ⁢     e   ⁡     (   n   )       ⁢       x   n     _               
where e(n)=d(n)−y(n).
 
     Recursive Least Squares (RLS) (Alternative method): 
                 f     n   +   1       _     =         f   n     _     +     α   ⁢           ⁢     R     -   1       ⁢           ⁢     e   ⁡     (   n   )       ⁢       x   n     _               
where:
 
     
       
         
           
             R 
             = 
             
               E 
               ⁢ 
               
                 
                   { 
                   
                     
                       
                         x 
                         n 
                       
                       ⁢ 
                       
                         x 
                         n 
                         T 
                       
                     
                     _ 
                   
                   } 
                 
                 . 
               
             
           
         
       
     
     It will be further appreciated that, as a further alternative, a more complex method such as the decision feed back equalizer, DFE, which will completely remove all intersymbol interference, can be utilized as well to establish the equalizer coefficients. 
       FIG. 3  showed how a transceiver can use its own transmit filter to create the ideal path for the adaptive algorithm, but this is not necessary. A second embodiment for achieving the same equalization goals is illustrated in  FIG. 5 . Here, the transmit filter  206  is not included in the ideal path. In this case, the adaptive algorithm processor  510  will cooperate with the adaptive equalizer  502  to create an equalizer response which is the inverse response of the analog baseband functions. Their goal is to create an inverse response filter given the ideal unfiltered PN sequence and the non-ideally filtered PN sequence (by the analog baseband functions) as inputs. 
     The  FIG. 5  electrical block diagram  500  of an exemplary wireless communication device in accordance with a second embodiment of the present invention is similar to the diagram  300 , the essential difference being that the ideal transmitter filter  206  is not used to derive the second training signal. Instead, the first and second training signals  508 ,  506  are identical to one another. Also, following the adaptive equalizer  502  resides an ideal matched filter  504 . Its purpose is to provide a matched filter response to the base station transmit filter  104  while at the same time meeting the out-of-band selectivity requirements. The architecture depicted in  FIG. 5  advantageously is more cost effective than the architecture depicted in  FIG. 3  for the following reasons. First, by not requiring the adaptive equalizer  502  to perform the matched filtering function, the number of taps needed in the equalizer  502  is minimized. Second, since the matched filter  504  is fixed (i.e. not adaptive), its coefficients can also be fixed (or hard-wired) in the digital logic implementation. This eliminates the need for using actual multipliers in the matched filter since multiplication by the fixed coefficients can be implemented in a simple look-up table fashion. The implementation of this look-up table can be done cost-efficiently using a conventional ROM-based approach or using a conventional optimized PLA type of digital logic. 
     Referring to  FIG. 6 , a flow diagram depicts a receiver warm-up sequence in accordance with the present invention. As mentioned previously, it is desired that the adaptive equalization be performed during periodic warm-up sequences to compensate for the frequency and time domain variations in the analog baseband filter and A/D section, which as above noted may vary with or over process, temperature, and supply voltage. 
     The warm-up sequence in accordance with the present invention preferably begins with the RF and IF sections of the receiver set  602  to minimum gain and the DC offset correction loop (DCOC) enabled. Setting the RF and IF sections to minimum gain allows for fast acquisition of DC offsets. Removing the DC offset at the baseband filter inputs improves the operating range of the baseband filter and the A/D section while improving the detection capability of the received signal. It also improves the training capability and settling time of the adaptive equalizer. After the DC correction loop has settled, its correction values are held  604  while the RF and IF sections are maintained at minimum gain. With the DC offset removed, the PN sequence generator and the adaptive equalizer are enabled for the training duration of the adaptive equalizer. After the adaptive equalizer has settled, its coefficients remain fixed during normal data reception mode  606 , since the PN generator training signal is disabled during that operational mode. The PN generator is disabled during normal data reception mode so that the detectability of the desired received signal is unaffected. In addition, during normal data reception, the RF gain is preferably controlled by an automatic gain control unit (AGC) (not shown), while the DC correction loop is placed in a low bandwidth mode. As can be seen in the indicated warm-up sequence, including an adaptive filter in the receiver incurs only the one additional intermediate step  604 . It is important to note that although the poles and zeros of the analog circuitry, h(n,t), will vary over temperature and supply voltage, it is likely that they will be very slowly time varying. Thus, updating the filter coefficients once during each warm-up sequence should be sufficient to maintain an excellent SNR. 
       FIGS. 7 and 8  graphically show the performance of the adaptive equalizer in accordance with the present invention. The ideal matched filter response, a root raised cosine, is depicted in curves  708 ,  808 . An exemplary magnitude response of the anti-aliasing filter and the A/D section is plotted in curves  704 ,  804 . As can be seen from curve  704 , the AAF, in its atempts to improve the selectivity and hence reduce the effects of the aliasing components, creates in-band droop. Also, the roll-off response (i.e. 3 dB bandwidth) of this filter varies over temperature and supply voltage. Since the AAF filter is time varying, the magnitude and group delay response curves  704 ,  804  are also time varying. The adaptive equalizer responses are shown in curves  702 ,  802 , and the composite response of the anti-aliasing filter, the A/D section, and the equalizer is depicted in curves  706 ,  806 . (Note that the curves  806 ,  808  lie atop one another.) The adaptive equalizer response, depicted in curves  702  and  802 , will be updated by the periodic PN training sequence, thus tracking the changes in the AAF and A/D response over the operating life of the wireless communication device. 
     Thus, it should be clear from the preceding disclosure that the present invention provides a method and apparatus for compensating for variations in the receive portion of a wireless communication device. Advantageously, the method and apparatus provides near-optimal matched filtering and, hence, greatly improved receiver performance over the operating life of the wireless communication device. In addition, the present invention is applicable to communication protocols that do and do not support periodic training sequences. 
     Many modifications and variations of the present invention are possible in light of the above teachings. Thus, it is to be understood that, within the scope of the appended claims, the invention can be practiced other than as described herein above.