Abstract:
A wireless receiver for receiving an incoming signal having spatial and temporal diversity. The receiver uses noise-based prescaling of multiple receiver chain signals for optimally combining the receiver chain signals in a composite equalized signal and uses noise-based time-varying postscaling the equalized signal. The receiver determines noise-based scale factors by comparing signal symbols to dispersed replica symbols of a training sequence for the incoming signal.

Description:
BACKGROUND OF THE INVENTION 
   1. Field of the Invention 
   The invention relates generally to diversity and more particularly to wireless receivers using noise levels for combining multiple signals, using noise levels for dynamic scaling of an equalized signal, and having a method for determining noise levels. 
   2. Description of the Prior Art 
   There is an escalating demand for wireless systems such as cellular telephones and wireless local area networks (LAN)s. This demand and economic factors are driving requirements for ever higher data throughput and greater range for these systems. However, as data rate and range is increased the wireless signals in these systems are increasingly degraded by burst noise and by time-varying frequency selective attenuation (fading) and delay distortion. This fading and distortion, generally caused by having multiple signal paths or channels between a transmitter and receiver, is known as multipath fading or multipath distortion or simply multipath. 
   A technique called equalization is commonly used for compensating for the effects of the multipath in order to estimate the bits that were actually transmitted. Most modem systems also use error detection and correction encoding where the transmitter encodes the bits that are transmitted with extra information that enables the receiver to use a decoding algorithm to detect and correct errors in the received bits after equalization. 
   Recent systems have improved upon standard or hard bit decision equalization with soft equalization where probabilities of transmitted bits are estimated. Where soft equalization is used, the receiver decoding algorithm operates on the probabilities of the equalized transmitted bits for error detection and correction. 
   In addition to equalization and encoding, wireless systems sometimes use other techniques, such as temporal diversity and spatial diversity, for combating burst noise and multipath. For temporal diversity, transmitted bits are interleaved into time-separated packets at a transmitter, spreading and thereby reducing the effect of burst noise or multipath fading in particular packets. The interleaved bits are then deinterleaved at the receiver to recreate their original order. However, in known systems where soft equalization is used, the reliability of the error detection and correction decoding process in the receiver is limited by changes in noise and multipath during the time separation. 
   Multiple antennas are used for spatial diversity for transmitting or receiving the wireless signals. Because the multiple antennas have different spatial locations, the signal paths are different and therefore the multipath is different. The multiple signals are combined at the receiver. A wireless receiver can use the idea that the multipath is different in the different signal paths in order to reduce the degradation that the multipath causes. Several combining methods, such as maximal ratio combining and equal gain combining are known in the prior art. However, none of the known methods combine the signals in an optimum way in the presence of equalization. 
   There remains a need for improved methods using spatial diversity and temporal diversity with equalization for reducing multipath effects. 
   SUMMARY OF THE INVENTION 
   It is therefore an object of the present invention to provide a spatial diversity receiver and method where multiple signals are weighted and combined according to their noise levels for providing an optimal composite equalized signal. 
   Another object of the present invention is to provide a temporal diversity receiver and method using noise scaling of a soft equalized signal before the signal is deinterleaved. 
   Another object of the present invention is to provide a simple apparatus and convenient method for determining a representation of signal noise level. 
   Briefly, a method and a receiver of the present invention determines ratios of noise levels of received signals and then uses the noise level ratios for determining noise-based scale factors. For spatial diversity, the noise-based scale factors are used for weighting multiple received signals inversely according to their respective noise levels for providing a composite equalized signal. For temporal diversity, the noise-based scale factors are used for dynamically scaling an equalized signal in order to compensate for time variations in noise and multipath. For temporal diversity and spatial diversity used together, the equalized signal that is scaled is the composite equalized signal. 
   In a preferred embodiment, for spatial diversity a receiver of the present invention includes multiple receiver chains and a noise-based spatial diversity combiner. For temporal diversity a receiver of the present invention includes a noise postscaler. For combined spatial and temporal diversity, the receiver includes the multiple receiver chains, the spatial diversity combiner, and the noise postscaler. 
   For spatial diversity, the receiver chains receive an incoming signal and provide sampled receiver chain signals to the spatial diversity combiner. The spatial diversity combiner scales and equalizes the sampled receiver chain signals by computing a set of composite equalizer branch metrics t n (s→s′) as shown in an equation 1 and then uses the composite equalizer branch metrics t n (s→s′) for providing a composite equalized signal u i  as shown in an equation 2. 
                     t   n     ⁡     (     s   →     s   ′       )       =         1     p   a   2       ⁢              r     n   ,   a       -       h     o   ,   a       ⁢       x   n     ⁡     (     s   →     s   ′       )         -       ∑     k   =   1     K     ⁢       h     k   ,   a       ⁢       x     n   -   k       ⁡     (   s   )                  2       +       1     p   b   2       ⁢              r     n   ,   b       -       h     o   ,   b       ⁢       x   n     ⁡     (     s   →     s   ′       )         -       ∑     k   =   1     K     ⁢       h     k   ,   b       ⁢       x     n   -   k       ⁡     (   s   )                  2     ⁢   ⋯     ⁢           +       1     p   m   2       ⁢              r     n   ,   m       -       h     o   ,   m       ⁢       x   n     ⁡     (     s   →     s   ′       )         -       ∑     k   =   1     K     ⁢       h     k   ,   m       ⁢       x     n   -   k       ⁡     (   s   )                  2                 (   1   )                 u   i   =F ({{ t   n ( s→s ′)}, s,s′}   n=0   N−1 )  (2) 
   In the equation 1, the n is the time index of the received symbols, the r n,a , r n,b  through r n,m  represent nth symbols received in receiver chains denoted “a”, “b” through “m”, respectively; the h k,a , h k,b  through h k,m  represent kth of 0 to K coefficients of channel impulse response sets for the “a”, “b” through “m” receiver chains, respectively; the x n (s→s′) represents a symbol uniquely determined by an equalizer transition from an originating state s to a new state s′ for the nth symbol; the x n−k (s) represents symbols uniquely determined by the state s for the nth symbol and the kth of said of 1 to K coefficients; the p a   2 , p b   2  through p m   2  are quantities that represent the noise variances in the “a”, “b” through “m” receiver chains, respectively; and the t n (s→s′) represents composite equalizer branch metrics corresponding to the equalizer transitions for the nth received symbols. The K most recent symbols {x n−k (s)} k=1   K  are uniquely determined by the originating state s. The 1/p a , 1/p b  through 1/p m  or their squares are noise-based scale factors. 
   There are S=P K+1  state s to state s′ equalizer transitions for each index n where “P” is the number of modulation states in the transmitted signal and “K+1” is the length or number of coefficients in the channel impulse response. For example for BPSK, “P” is two. For a P of two and a K of five, the number S of equalizer branch metrics t n (s→s′) is 64 for each index n. 
   In the equation 2, the composite equalized signal u i  is the ith index for a function of all equalizer branch metrics. The composite equalized signal u i  has the form of a sample stream of bit probabilities for the i=0 . . . (N−1)th received symbol where N is the total number of received symbols over which the equalizer operates. This is the “soft” information that feeds an error correcting decoder. 
   The present invention can be implemented by noise scaling each of the composite equalizer branch metrics t n (s→s′) as shown in equation 1, as it is being computed within an equalizer. However, this would require several multiplications per index n, the number of multiplications dependent on the total number of state transitions within the equalizer trellis (64 in the example above). In a preferred embodiment, the spatial diversity combiner therefore includes noise prescalers for prescaling the receiver chain signals r n,a , r n,b  through r n,m  and channel impulse response sets h k,a , h k,b  through h k,m  according to equations 3A–C and 4A–C.
 
 {tilde over (r)}   n,a =( p   min   /p   a ) r   n,a    (3A)
 
 {tilde over (r)}   n,b =( p   min   /p   b ) r   n,b    (3B)
 
 {tilde over (r)}   n,m =( p   min   /p   m ) r   n,m    (3C)
 
 {tilde over (h)}   k,a =( p   min   /p   a ) h   k,a    (4A)
 
 {tilde over (h)}   k,b =( p   min   /p   b ) h   k,b    (4B)
 
 {tilde over (h)}   k,m =( p   min   /p   m ) h   k,m    (4C)
 
   In the equations 3A–C and 4A–C, the p min =min(p a ,p b  . . . p m ) where p min  is the smallest of the p a  and p b  through p m ; the {tilde over (r)} n,a , {tilde over (r)} n,b  through {tilde over (r)} n,m  represent prescaled receiver chain signals; and the {tilde over (h)} k,a , {tilde over (h)} k,b  through {tilde over (h)} k,m  represent the prescaled channel impulse response sets. The p min /p a , p min /p b  through p min /p m  are noise-based scale factors. An equation 5 shows composite equalizer branch metrics {tilde over (t)} n (s→s′) determined from the prescaled receiver chain signals {tilde over (r)} n,a , {tilde over (r)} n,b  through {tilde over (r)} n,m  and the prescaled channel impulse response sets {tilde over (h)} k,a , {tilde over (h)} k,b  through {tilde over (h)} k,m . 
   
     
       
         
           
             
               
                 
                   
                     
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   Because it is the ratio of the scale factors and not their actual values that is necessary for the optimal combining of the receiver chain signals, the p min  in the numerator of the scale factors can be replaced by an arbitrary constant. However, an advantage of the use of the p min  is that the signal level after automatic gain control (AGC) of the dominant receiver chain signal is retained while the signal levels of the other receiver chains are lowered, thereby retaining the use of the dynamic range of the equalizer. An equation 6 shows a composite equalized signal ũ i  of a sample stream of bit probabilities that is analogous to the composite equalized signal u i  of the equation 2.
 
 ũ   i   =F ({{ {tilde over (t)}   n ( s→s ′)}, s,s′}   n=0   N−1 )  (6)
 
   In a system using temporal diversity, the noise postscaler dynamically scales packets of the composite equalized signal ũ i  by 1/p min   2  in order to eliminate the effect of packet-to-packet changes in noise level. 
   It should be noted that the composite equalizer branch metrics {tilde over (t)} n (s→s′) scaled by 1/p min   2  are equal to the composite equalizer branch metrics t n (s→s′) shown in the equation 1 and that the composite equalized signal ũ i  times 1/p min   2  is the composite equalized signal u i . However, the prescaling and postscaling of the present invention have substantially reduced the number of multiplications that are required. 
   For an alternative embodiment the equation 1 may be reformatted as shown in an equation 7. 
   
     
       
         
           
             
               
                 
                   
                     
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   In the equation 7 the product(p ā   2 ) is the product of all the noise representations p a   2 , p b   2  through p m   2  except the noise representation p a   2 ; the product(p {overscore (b)}   2 ) is the product of all the noise representations p a   2 , p b   2  through p m   2  except the noise representation p b   2 ; the product(p {overscore (m)}   2 ) is the product of all the noise representations p a   2 , p b   2  through p m   2 , except the noise representation p m   2 ; and the {tilde over (t)} n ″(s→s′) represents the equalizer branch metrics corresponding to the trellis transition from state s to state s′, for the nth index. The product(p ā )/p a p b  . . . p m , product(p {overscore (b)} )/p a p b  . . . p m  through product(p {overscore (m)} )/p a p b  . . . p m  or their squares are noise-based scale factors. For only two receiver chains “a” and “b”, the product(p ā   2 ) is p b   2  and the product(p {overscore (b)}   2 ) is p a   2 . For this alternative embodiment, the spatial diversity combiner includes noise prescalers for implementing equations 8A–C, 9A–C and 10 for determining composite equalizer branch metrics {tilde over (t)} n ″(s→s′) for the spatial diversity combiner with the prescaling for the receiver chains “a”, “b” through “m”.
 
 {tilde over (r)}″   n,a =product( p   ā   /p   max ) r   n,a    (8A)
 
 {tilde over (r)}″   n,b =product( p   {overscore (b)}   /p   max ) r   n,b    (8B)
 
 {tilde over (r)}″   n,m =product( p   {overscore (m)}   /p   max ) r   n,m    (8C)
 
 {tilde over (h)}″   k,a =product( p   ā   /p   max ) h   k,a    (9A)
 
 {tilde over (h)}″   k,b =product( p   {overscore (b)}   /p   max ) h   k,b    (9B)
 
 {tilde over (h)}″   k,m =product( p   {overscore (m)}   /p   max ) h   k,m    (9C)
 
   
     
       
         
           
             
               
                 
                   
                     
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   In the equations 8A–C and 9A–C, the p max =max(p a ,p b  . . . p m ) where p max  is the largest of the noise representations p a  and p b  through p m ; the {tilde over (r)}− n,a , {tilde over (r)}″ n,b  through {tilde over (r)}″ n,m  represent prescaled receiver chain signals; the {tilde over (h)}″ k,a , {tilde over (h)}″ k,b  through {tilde over (h)} k,m  represent the prescaled channel impulse response sets; and the {tilde over (t)} n ″(s→s′) represents composite equalizer branch metrics for the receiver chain signals {tilde over (r)}″ n,a , {tilde over (r)}″ n,b  through {tilde over (r)}″ n,m  and the channel impulse response sets {tilde over (h)}″ k,a , {tilde over (h)}″ k,b  through {tilde over (h)}″ k,m . The product(p ā /p max ) is the product of the noise representations for all the receiver chains except the receiver chain “a” divided by the largest noise representation, the product(p {overscore (b)} /p max ) is the product of the noise representations for all the receiver chains except for the receiver chain “b” divided by the largest noise representation, product(p {overscore (m)} /p max ) is the product of the noise representations for all the receiver chains except for the receiver chain “m” divided by the largest noise representation. The product(p ā /p max ), product(p {overscore (b)} /p max ) through product(p {overscore (m)} /p max ) are noise-based the scale factors. For only two receiver chains “a” and “b”, the product(p ā /p max ) is p b /p max  and the product(p {overscore (b)} /p max ) is p a /p max . For three receiver chains “a”, “b” and “c”, the product(p ā /p max ) is p b p c /p max  the product(p {overscore (b)} /p max ) is p a p c /p max   2  and the product(p {overscore (c)} /p max ) is p a p b /p max   2 . Because it is the ratio of the scale factors and not their actual values that is necessary for the optimal combining the receiver chains, the p max  in the denominator of the scale factors may be replaced by an arbitrary constant. However, an advantage of the use of the p max  is that the signal level after automatic gain control (AGC) of the dominant receiver chain signal is retained while the signal levels of the other receiver chains are lowered, thereby retaining the use of the dynamic range of the equalizer. 
   In a system using temporal diversity, the noise postscaler in the alternative embodiment scales the composite equalizer branch metrics {tilde over (t)} n ″(s→s′) by a postscale factor of p max   2(M−1) /p a   2 p b   2  . . . p m   2  in order to eliminate packet to packet changes in noise level where the M is the total number of receiver chains and the p a   2 p b   2  . . . p m   2  is the product of the quantities that represent the noise variances of all the receiver chains “a”, “b” through “m”. For only two receiver chains “a” and “b” the postscale factor is p max   2 /p a   2 p b   2 . It should be noted that the composite equalizer branch metrics {tilde over (t)} n ″(s→s′) scaled by p max   2 /p a   2 p b   2  are equal to the composite equalizer branch metrics t n (s→s′) shown in the equation 1. Hence the two systems provide the same results. 
   In a system using spatial diversity but not temporal diversity, the postscaler is not required. In a system using temporal diversity but not spatial diversity, only one receiver chain, denoted by “a”, is needed and the spatial diversity combiner is an equalizer for equalizing the receiver chain signal r n,a  with the channel impulse response set h k,a  without the need for noise-based prescaling. For a receiver with only the single receiver chain “a”, the postscaler uses a scale factor of 1/p a   2  for scaling the equalized signal in each data packet. 
   The true noise variances for the receiver chain signals r n,a , r n,b  through r n,m  can be computed and used for the quantities p a   2 , p b   2  through p m   2 , respectively. However, the calculation of such noise variances requires the computationally intensive operations of squaring real and imaginary noise components and then taking a square root of the squared real and imaginary components to compute the prescale factors required for the equations in 3A–C and 4A–C or 8A–C and 9A–C. The noise estimators of the present invention avoid the squaring and square root operations by using real and imaginary cyclic finite impulse response (FIR) filters for determining real and imaginary noises by comparing the symbols of the receiver chain signals r n,a , r n,b  through r n,m  to a known preamble as dispersed according to the calculated channel impulse response coefficients. The noise estimators then simply add the real and imaginary noises for determining the noise representations p a , p b  through p m . An equation 11 shows the determination of the noise representation p a  for the receiver chain “a”. The noise representations p b  through p m  are calculated in an identical manner for a receiver having multiple receiver chains “b” through “m”. 
   
     
       
         
           
             
               
                 
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   In the equation 11, the w n−k  represents the symbols corresponding to a known training sequence in the incoming signal, the ξ is the time index offset of the first received symbol corresponding to the training sequence received in the receiver chain “a”, and the outer brackets “&lt; &gt;” denote averaging. It should be noted that the method of the present invention takes advantage of the fact that the noise on the incoming signal is approximately uncorrelated between real and imaginary and both the real and imaginary noises have approximately a Gaussian distribution. 
   In a preferred embodiment for a Global System for Mobile Communication (GSM) system, the cyclic FIR filters take advantage of the fact that a 26 bit preamble includes a pre-pended 5 bits that duplicate the last 5 bits of a 16 bit mid-section and a post-pended 5 bits that duplicate the first 5 bits of the 16 bits of the mid-section for operating in a circular manner. 
   These and other objects and advantages of the present invention will no doubt become obvious to those of ordinary skill in the art after having read this summary and the following detailed description of the preferred embodiments which are illustrated in the various figures. 

   
     IN THE DRAWINGS 
       FIG. 1  is a block diagram of a receiver of the present invention for determining a noise representation and then using the noise representation for combining signals having temporal and spatial diversity; 
       FIG. 2  is a diagram of a system showing multiple signals channels with multiple antennas in the receiver of the present invention; 
       FIG. 3  is another block diagram of the receiver of  FIG. 1 ; 
       FIG. 4  is a block diagram of a noise estimator of the receiver of  FIG. 1 ; 
       FIG. 5  is a flow chart of a method for determining a noise representation and then using the noise representation for combining signals having temporal and spatial diversity of the receiver of  FIG. 1 ; 
       FIG. 6  is a flow chart for combining signals in the method of  FIG. 5 ; and 
       FIG. 7  is a flow chart for determining the noise representation in the method of  FIG. 5 . 
   

   DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     FIG. 1  is a block diagram of a preferred embodiment of a receiver of the present invention referred to by a general reference number  10 . The receiver  10  includes a receiver chain  12 A for processing signals received in an antenna A a , denoted by  14 A, and a receiver chain  12 B for processing signals received by an antenna A b , denoted by  14 B. Although the receiver  10  is illustrated and described for two channels, the idea may extended to any number of channels. 
   The receiver chain  12 A includes analog circuits G a , denoted by  24 A; an analog-to-digital converter A/D a , denoted by  26 A; and digital circuits g a ; denoted by  28 A. Similarly, the receiver chain  12 B includes analog circuits G b , denoted by  24 B; an analog-to-digital converter A/D b , denoted by  26 B; and digital circuits g b , denoted by  28 B. The antennas A a    14 A and A b    14 B convert incoming radio frequency (RF) signals from an airwave to a conducted form. The analog circuits G a    24 A and G b    24 B filter, amplify, and downconvert the conducted RF signals to a lower frequency. The analog circuits G a    24 A and G b    24 B also provide automatic gain control (AGC) for the signals. The A/D a    26 A and A/D b    26 B convert the lower frequency signals from an analog form to a digital form. The digital circuits g a    28 A and g b    28 B apply further filtering, amplification, frequency conversion, and AGC to the digitized signals and issue sampled receiver chain signals r n,a  and r n,b  where n is the index of the nth signal symbols received in the receiver chains  12 A and  12 B, respectively. The antenna A a    14 A has a different spatial location than the antenna A b    14 B, thereby providing spatial diversity. 
   Referring to  FIG. 2 , the receiver  10  receives a signal  30  from a transmitter  31  through a signal transmission channel A, denoted by  32 A; and a signal transmission channel B, denoted by  32 B, to antennas A a    14 A and A b    14 B, respectively. Because antennas A a    14 A and A b    14 B are physically separated, the signal transmission channels A  32 A and B  32 B are different and in general have different multipath. For temporal diversity, the transmitter  31  interleaves information bits into time-separated packets according to a system specification. The transmitter  31  also encodes and frames the information bits with an error detection/correction algorithm into packets. The encoded interleaved framed packets of transmitted bits are carried on the signal  30 . 
   Returning to  FIG. 1 , the receiver  10  also includes a summer  34 , a timing recovery circuit  36 , a noise comparator  37 , a diversity processor  38 , and a postprocessor  39 . The diversity processor  38  weights, combines and equalizes the receiver chain signals r n,a  and r n,b  by determining effective equalizer branch metrics according to the equation 1 or the equation 10. 
   The diversity processor  38  preferably includes a noise-based spatial diversity combiner  40  and a noise postscaler  41 . The spatial diversity combiner  40  includes a noise prescaler  42 A, a noise prescaler  42 B, and an equalizer  43 . The noise prescaler  42 A can also be considered a part of the receiver chain  12 A and similarly the noise prescaler  42 B can be considered a part of the receiver chain  12 B. 
   The receiver chain  12 A also includes a channel estimator  44 A, a squarer  45 A, a noise estimator  46 A, and buffers  48 A and  49 A. Similarly, the receiver chain  12 B includes a channel estimator  44 B, a squarer  45 B, a noise estimator  46 B, and buffers  48 B and  49 B. For the purpose of the present invention, there is no significant difference whether the analog circuits G a ,G b    24 A,B, the analog-to-digital converters A/D a ,A/D b    26 A,B, the digital circuits g a ,g b    28 A,B, and the channel estimators  44 A,B, the squarers  45 A,B, and the noise estimators  46 A,B are constructed separately for the receiver chains  12 A, 12 B; or are constructed so as to span the receiver chains A,B  12 A, 12 B. 
   The noise estimator  46 A determines a representation p a  of the noise variance for the noise, including signal interference, for the receiver chain signal from the digital circuit g a    28 A and passes the noise representation p a  to the noise comparator  37 . Similarly, the noise estimator  46 B determines a representation p b  of the noise variance for the noise, including signal interference, for the receiver chain signal from the digital circuit g b    28 B and passes the noise representation p b  to the noise comparator  37 . It is not necessary that the noise representations p a  and p b  be actual noise variances but only that they each have a relationship or ratio that can be directly to the actual noise variance ratio. The noise comparator  37  determines the smallest of the noise representations p a  and p b  as a minimum noise representation p min , and then computes a noise-based scale factor p min /p a  for the receiver chain  12 A and a noise-based scale factor p min /p b  for the receiver chain  12 B. 
   The channel estimators  44 A and  44 B use a training sequence embedded in the frames of the receiver chain signals from the digital circuits g a    28 A and g b    28 B, respectively, for estimating channel impulse response sets h k,a  and h k,b , respectively. The squarers  45 A and  45 B square absolute values of the channel impulse responses h k,a  and h k,b  and issue squared outputs H a  and H b  to the summer  34 . The summer  34  adds the squared channel impulse responses H a  and H b  and then issues summed squared channel impulse responses to the timing recovery circuit  36 . The timing recovery circuit  36  uses the summed squared channel impulse responses for providing a symbol synchronization index. The buffers  48 A and  48 B use the symbol synchronization index for buffering the receiver chain signals r n,a  and r n,b , respectively. The buffers  49 A and  49 B synchronize the channel impulse response sets h k,a  and h k,b , respectively. 
   The noise comparator  37  passes the scale factors p min /p a  and p min /p b  to the noise prescalers  42 A and  42 B, respectively. The noise prescaler  42 A includes a signal prescaler  52 A and a transmission channel prescaler  54 A. The signal prescaler  52 A multiplies the buffered received signal samples r n,a  by p min /p a  for providing a prescaled receiver chain signal {tilde over (r)} n,a  as shown in the equation 3A. The transmission channel prescaler  54 A multiplies the buffered channel impulse response set h k,a  by p min /p a  for providing a prescaled channel impulse response set {tilde over (h)} k,a  as shown in the equation 4A. Similarly, the noise prescaler  42 B includes a signal prescaler  52 B and a transmission channel prescaler  54 B. The signal prescaler  52 B multiplies the buffered receiver chain signal r n,b  by p min /p b  for providing a prescaled receiver chain signal {tilde over (r)} n,b  as shown in the equation 3B. The transmission channel prescaler  54 B multiplies the buffered channel impulse response set h k,b  by p min /p b  for providing a prescaled channel impulse response set {tilde over (h)} k,b  as shown in the equation 4B. The noise postscaler  41  uses a scale factor of 1/p 2   min  received from the noise comparator  37  for dynamically scaling the composite equalized signal ũ i . 
     FIG. 3  is a block diagram of the receiver  10  showing the receiver chains  12 A and  12 B through to a receiver chain  12 M for providing signals to the noise prescalers  42 A and  42 B through to a noise prescaler  42 M. The noise prescalers  42 A–M pass signals to the equalizer  43  as described above. The receiver chain  12 M is similar in all respects to the receiver chains  12 A and  12 B, and the noise prescaler  42 M is similar in all respects to the noise prescalers  42 A and  42 B, described above. The receiver  10  may have many receiver chains  12 A–M for spatial diversity or spatial and temporal diversity, or only one receiver chain  12 A for temporal diversity but not spatial diversity. The receiver chains  12 A,  12 B through  12 M provide squared channel impulse responses H a , H b  through H m  to the summer  34  and receive the index from the timing recovery circuit  36 . The noise prescalers  42 A–M receiver prescale scale factors from the noise comparator  37 . The equalizer  43  is preferably a soft equalizer for providing bit probabilities as opposed to a hard equalizer where the actual bits are estimated. 
   The equalizer  43  includes functional blocks for a branch metric calculator  62 , a combiner  64 , and a probability calculator  66  preferably implemented together in a digital signal processor (DSP) integrated circuit where the DSP circuit is constructed as a single physical block. Because the DSP circuit is constructed as a single block it may not be possible to separate the functional blocks physically. 
   The branch metric calculator  62  uses prescaled channel impulse response sets {tilde over (h)} k,a , {tilde over (h)} k,b  through {tilde over (h)} k,m  for equalizing prescaled receiver chain signals {tilde over (r)} n,a , {tilde over (r)} n,b  through {tilde over (r)} n,m  for providing respective noise weighted terms of equalizer branch metrics for the receiver chains  12 A,  12 B through  12 M, respectively. The combiner  64  adds the noise weighted terms for providing the composite equalizer branch metrics {tilde over (t)} n (s→s′) as shown in the equation 5. The probability calculator  66  uses the composite equalizer branch metrics {tilde over (t)} n (s→s′) for providing the composite equalized probability signal ũ i  as shown in the equation 6. Technical information for determining an equalized probability signal from equalizer branch metrics is shown by Gordon L. Stüber in “Principles of Mobile Communication, Second Edition” published 2001 by Kluwer Academic Publishers on pages 329–335, and by Gerhard Branch and Volker Franz in “A Comparison of Soft-In/Soft-Out Algorithms for “Turbo-Detection” published in the Proceedings of the International Conference on Telecommunications, ICT-98, on pages 259–263 in June, 1998. In a preferred implementation using a DSP integrated circuit the composite branch metrics {tilde over (t)} n (s→s′) are intermediate results that are used in the equalizer  43  but are not necessarily available outside the equalizer  43 . 
   The post processor  39  includes a deinterleaver  74  and a decoder  76 . The noise postscaler  41  issues the postscaled composite equalized probability signal to the deinterleaver  74 . The deinterleaver  74  reverses the interleaving of the system specification for placing the samples back into the order that they would have had without the interleaving performed by the transmitter  31  and passes a deinterleaved signal to the decoder  76 . The decoder  76  uses a decoding algorithm according to a system specification for detecting and correcting errors in the deinterleaved signal in order to recover information bits. The information bits may receive further higher level processing in order to pass information for an application to its intended user. 
   The receiver  10  has been described in a detailed embodiment using prescale noise-based scale factors of p min /p a , p min /p b  through p min /p m , and a postscale noise-based scale factor of 1/p 2   min  as shown in the equations 3A–C, 4A–C, 5, and 6. In an alternative embodiment, a receiver  110  of the present invention uses prescale noise-based scale factors of product(p ā /p max ), product(p {overscore (b)} /p max ) through product(p {overscore (m)} )/p max , and a postscale noise-based scale factor of p max   2(M−1) /p a   2 p b   2  . . . p m   2  as shown in the equations 8A–C, 9A–C and 10. 
   In the receiver  110  a noise comparator  137  receives the noise representation p a  from the noise estimator  46 A, the noise representation p b  from the noise estimator  46 B, and determines the largest of the noise representations p a , p b  as a maximum noise p max  and then computes the scale factor p b /p max  for the receiver chain  12 A and the scale factor as p a /p max  for the receiver chain  12 B. The noise comparator  137  passes the scale factor p b /p max  to the noise prescaler  42 A, passes the p a /p max  to the noise prescaler  42 B, and passes the scale factor p max   2(M−1) /p a   2 p b   2  . . . p m   2  to the noise postscaler  41 . 
   For two receiver chains  12 A and  12 B the noise prescaler  42 A uses the scale factor p b /p max  for prescaling the buffered receiver chain signal r n,a  for providing a prescaled receiver chain signal {tilde over (r)}″ n,a  as shown in the equation 8A and prescaling the buffered channel impulse response set h k,a  for providing a prescaled channel impulse response set {tilde over (h)}″ k,a  as shown in the equation 9A; similarly, the noise prescaler  42 B uses the scale factor p a /p max  for prescaling the buffered receiver chain signal r n,b  for providing a prescaled receiver chain signal {tilde over (r)}″ n,b  as shown in the equation 8B and prescaling the buffered channel impulse response set h k,b  for providing a prescaled channel impulse response set {tilde over (h)}″ k,b  as shown in the equation 9B. The branch metric calculator  62  of the equalizer  43  uses the prescaled channel impulse response set {tilde over (h)}″ k,a , {tilde over (h)}″ k,b  through {tilde over (h)}″ k,m  for equalizing the prescaled receiver chain signals {tilde over (r)}″ n,a , {tilde over (r)}″ n,b  through {tilde over (r)}″ n,m  and the combiner  64  adds the terms for issuing values of composite branch metrics as shown in the equation 10. The probability calculator  66  uses the composite equalizer branch metrics {tilde over (t)} n ″(s→s′) for providing the composite equalized probability signal ũ″ i  analogous to the composite equalized signal ũ i  shown in the equation 6. 
     FIG. 4  is a block diagram of the noise estimator  46 A of the present invention for the receiver chain  12 A where the receiver  10 , 110  is a Global Systems for Mobile Communications (GSM) cellphone receiver. The GSM system specifies a 26-symbol training sequence of the form w 11 , w 12 , w 13 , w 14 , w 15 , w 0 , w 1 , w 2 , w 3 , w 4 , w 5 , w 6 , w 7 , w 8 , w 9 , w 10 , w 11 , w 12 , w 13 , w 14 , w 15 , w 0 , w 1 , w 2 , w 3 , w 4 . The noise estimator  46 A uses the GSM training sequence in real and imaginary cyclic finite impulse response (FIR) filters for providing the noise representation p a  as shown in the equation 11. Block diagrams for the noise estimator  46 B for the receiver chain  12 B or for additional noise estimators for additional receiver chains  12 B through  12 M are the same. 
   The noise estimator  46 A includes a cyclic inter-symbol interference (ISI) sequence generator  102  implemented with shift registers, a convolver implemented with real and imaginary convolvers  104 I and  104 Q, a comparator implemented with real and imaginary signal comparators  106 I and  106 Q, and a linear noise combiner  108 . The ISI sequence generator  102  shifts and recycles the sixteen central symbols w 0  through w 15  of the 26-symbol GSM training sequence that are known according to the GSM system specification. 
   The 26-symbol GSM training sequence includes a pre-pended section of five symbols w 11  through w 15  followed by a center section of sixteen symbols w 0  through W 15  followed by five post-pended section of five symbols w 0  to w 4 . The pre-pended five symbol section is a duplicate of the last five symbols (w 11  to w 15 ) of the center sixteen symbol section and the post-pended five symbol section is a duplicate of the first five symbols (w 0  to w 4 ) of the center sixteen symbol section. The convolver  104 I is shown for an impulse response set of six coefficients h 0,a  to h 5,a . Other numbers of coefficients may be used. At the start, the receiver chain signal r n+ξ,a =r ξ,a  for the index n=0 is synchronized with the w 0  as shown at the start of the ISI sequence generator  102 . 
   The convolver  104 I includes multipliers  112 I and a convolution summer  114 I. For the index n=0, the multipliers  112 I multiply the first six symbols w 0 , w 15  through w 11  in the generator  102  by the six impulse response coefficients h 0,a , h 1,a  through h 5,a , respectively, for providing six products. The six products are added in the convolution summer  114 I and the convolution result of the real n=0 channel dispersed training symbol is passed to the signal comparator  106 I. The signal comparator  106 I determines a difference between the n=0 channel dispersed training symbol and the receiver chain symbol r ξ,a  and determines the absolute value of the difference as a real symbol noise amplitude for the first training symbol. The real first symbol noise amplitude is passed to the linear noise combiner  108 . It should be noted that the real symbol noise amplitude is an absolute value. 
   This is repeated for the indexes n equal to 1 through 15 while the ISI sequence generator  102  cycles at the same rate, and the results are passed to the linear noise combiner  108 . For example, for the next index (n=1) the generator  102  is cycled so that its first symbol is w 1 , its second symbol is w 0 , and so on so that its fifteenth symbol is w 2 . The multipliers  112 I multiply the first six symbols w 1 , w 0  through w 12  in the generator  102  by the six impulse response coefficients h 0,a , h 1,a  through h 5,a , respectively, for providing six new products. The six new products are added in convolution summer  114 I and the real n=1 channel dispersed training symbol is passed to the signal comparator  106 I. The signal comparator  106 I subtracts the n=1 channel dispersed training symbol from the receiver chain symbol r ξ+1,a  and passes the absolute value of the difference as a real second symbol noise amplitude to the linear noise combiner  108 . 
   The linear noise combiner  108  includes real and imaginary accumulators  122 I and  122 Q and a real imaginary adder  124 . The accumulator  122 I receives the real symbol noise amplitudes. When the accumulator  122 I has accumulated the real symbol noise amplitudes for n from 0 to 15, it passes the accumulated result to the adder  124 . The imaginary convolver  104 Q, the imaginary signal comparator  106 Q, and the imaginary accumulator  122 Q operate in an identical manner. 
   The adder  124  adds the accumulated results from the real and imaginary accumulators  122 I and  122 Q for providing the noise representation p a  as shown in the equation 11. In an equivalent alternative block diagram, the real and imaginary symbol noise amplitudes are added and then the sum is accumulated for providing the noise representation p a . It should be noted that the averaging shown in the equation 11 is equivalent to adding all the real and imaginary symbol noise absolute amplitudes divided by the number of symbols, sixteen in the above description, that were used in the addition. It should also be noted that the noise representation p a  is determined without any requirement for squaring the real and imaginary noise components or for taking a square root of any combination of real and imaginary noise components. 
     FIG. 5  is a flow chart of a method in the receiver  10 , 110  for diversity processing of the incoming signal  30 . In a step  202  the receiver  10 , 110  receives the signal  30  and provides receiver chain signals. In a step  210  noise representations for noise levels of the receiver chain signals are determined. There is a noise representation for the receiver chain signal for each receiver chain, respectively. In a step  212  the noise-based scale factors for each of the receiver chain signals are calculated from the noise representations. Then, in a step  220  the scale factors are used for effectively weighting equalizer branch metrics that represent the receiver chain signals in order to determine the composite equalized signal. In a step  224 , for temporal diversity, the composite equalized signal is deinterleaved. Then, in a step  226  the deinterleaved composite equalized signal is decoded for providing a best estimate of the information bits that were transmitted by the transmitter  31  and carried in the form of coded, interleaved symbols modulated onto the signal  30 . 
     FIG. 6  is a flow chart of a preferred embodiment for the step  220  for determining the composite equalized signal. In a step  232  the channel impulse response coefficients are determined for the receiver chain signal for the receiver chains  12 A–M, respectively. There is a set of channel impulse response coefficients for each receiver chain signal, respectively. In a step  234  the channel impulse response coefficients for each of the receiver chain signals are prescaled with the prescale factor for that receiver chain signal. In a step  242  the receiver chain signals are prescaled with the respective prescale factors. In a step  250  the prescaled receiver chain signals are equalized with the prescaled channel impulse response coefficients for determining a composite equalized signal. Where temporal diversity is used, the composite equalized signal is a preliminary composite equalized signal. In a step  260 , for temporal diversity the preliminary composite equalizer signal is postscaled with the postscale factor for providing the composite equalizer signal. 
   The step  250  for equalizing the receiver chain signals functionally includes steps  262 ,  264 , and  266 . In the step  262  prescaled equalizer branch metrics are determined from the prescaled receiver chain signals and the prescaled channel impulse response coefficients. In the step  262 , for spatial diversity, the prescaled equalizer branch metrics for the receiver chains  12 A–M are combined for providing the composite equalizer branch metrics. In the step  266  the composite equalizer branch metrics are processed for determining the composite equalized signal. It should be emphasized that the steps  262 – 266  are functional operations that may be performed in various ways by digital signal processing techniques where the functions may or may not be physically separable. 
     FIG. 7  is a flow chart of a preferred embodiment for the step  210  for determining the noise representations. In the step  232  the channel impulse response coefficients are determined for the receiver chain signals for the receiver chains  12 A–M, respectively. In a step  272  a stored replica sequence of predetermined training symbols are continuously shifted and the replica symbols of the shifting sequence are issued in parallel. For the example of GSM the training symbols are shifted in as a circulating cycle. However, the symbols could be shifted in different ways for different system specifications. Real shifting replica symbols are convolved with real channel impulse response coefficients in a step  274 ; and imaginary shifting replica symbols are convolved with imaginary channel impulse response coefficients in a step  275  for providing real and imaginary channel dispersed replica symbols. In a step  276  real symbols noise amplitudes are determined from the absolute values of the differences between the real dispersed replica symbols and the real symbols in the corresponding receiver chain signals. In a step  277  imaginary symbols noise amplitudes are determined from the absolute values of the differences between the imaginary channel dispersed replica symbols and the imaginary symbols in the corresponding receiver chain signals. Each symbol in a receiver chain signal has an unsigned real noise value and an unsigned imaginary noise. In a step  280  the real and imaginary symbol noise values for a receiver chain signal are accumulated over a certain number of symbols for determining the noise representations for that receiver chain signal. 
   Although the present invention has been described in terms of the presently preferred embodiments, it is to be understood that such disclosure is not to be interpreted as limiting. Various alterations and modifications will no doubt become apparent to those skilled in the art after having read the above disclosure. Accordingly, it is intended that the appended claims be interpreted as covering all alterations and modifications as fall within the true spirit and scope of the invention.