Abstract:
Aspects of the present invention include methods, systems, and computer-readable medium for canceling interference in wireless communication. The method includes receiving wireless CDMA communication signals using one or more antennas at least from a first entity via a first communication channel and a second entity via a second communication channel, determining a set of known characteristics associated with the first entity, the first set of characteristics comprising a first signal strength, a first synchronization information, and an first channel identification information, and determining an aggregate signal matrix based on signals received from at least the first entity and the second entity. The method further includes determining a covariance matrix associated with the aggregate signal value, determining a reference signal matrix based on the set of known characteristics, calculating an interference matrix by subtracting the reference signal matrix from the covariance matrix, and removing the interference estimation from the communication signals.

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
       [0001]    The present application claims priority to PCT application No. PCT/CN2012/084511, filed on Nov. 13, 2012, and entitled “Method and System for Blind Interference Cancellation in a wireless communication systems”, the entire disclosure of which is incorporated herein by reference. 
     
    
     BACKGROUND 
       [0002]    Currently, there are two main types of interference cancellation receivers. Namely, linear minimal mean square error (LMMSE) based interference cancellation receivers and non-linear interference cancellation (NLIC) receivers. LMMSE based interference cancellation receivers estimate the covariance matrix and find the coefficient which is used to achieve the MMSE by solving the large matrix inversion. The minimal required pre-knowledge to use this algorithm in CDMA based communication systems is the desired signal&#39;s scrambling and spread code. The NIX based interference cancellation receivers estimate interference items and subtract such items from the received signal in parallel or successively. 
         [0003]    These techniques reconstruct the interference items by estimating each interference&#39;s amplitude, timing, channel response, and information bit and then remove them from the received signal, based on the pre-knowledge of the desired signal and interference&#39;s scrambling and spread codes. Specifically, in wide-band code division multiple access (CDMA) (WCDMA) downlink, the knowledge of variable spreading factors and spread codes of intra-channel and inter-channel interferences is very limited, and an additional algorithm is needed to detect the presence of the interferences. 
         [0004]    A significant drawback of these existing interference cancellation techniques is that they require computational complexity and have high requirement for the accuracy of the estimated interference signal in the NLIC receivers. Hence, for these and other reasons, improvements are needed in the art. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0005]    A further understanding of the nature and advantages of the present invention may be realized by reference to the remaining portions of the specification and the drawings wherein like reference numerals are used throughout the several drawings to refer to similar components. In some instances, a sub-label is associated with a reference numeral to denote one of multiple similar components. When reference is made to a reference numeral without specification to an existing sub-label, it is intended to refer to all such multiple similar components. 
           [0006]      FIG. 1  illustrates a block diagram of a receiver with blind interference cancellation, according to one embodiment of the present invention. 
           [0007]      FIG. 2  illustrates a block diagram of intra-interference and inter-interference cancellation and channel equalization, according to one embodiment of the present invention. 
           [0008]      FIG. 3  illustrates a block diagram of blind interference cancellation on each channel, according to one embodiment of the present invention. 
           [0009]      FIG. 4  illustrates a block diagram of multi-channel/multi-stage blind interference cancellation, according to one embodiment of the present invention. 
           [0010]      FIGS. 5A and 5B  illustrates flow diagrams for implementing blind interference cancellation, according to one embodiment of the present invention. 
           [0011]      FIG. 6  illustrates a block diagram of a receiver with an interference cancellation and equalizer according to one embodiment of the present invention. 
           [0012]      FIG. 7  illustrates a block diagram of multi-channel interference cancellation and equalizer, according to one embodiment of the present invention. 
           [0013]      FIG. 8  illustrates a block diagram of self-tracking multi channel equalizer based on a pilot channel, according to one embodiment of the present invention. 
           [0014]      FIG. 9  illustrates a flow diagram for combining symbol level interference cancellation and chip level channel equalizer, according to one embodiment of the present invention. 
           [0015]      FIG. 10  illustrates a flow diagram for dynamically selecting the interference cancellation and channel equalizer, according to one embodiment of the present invention. 
           [0016]      FIG. 11  is a generalized schematic diagram illustrating a computer system, in accordance with various embodiments of the invention. 
           [0017]      FIG. 12  is a block diagram illustrating a networked system of computers, which can be used in accordance with various embodiments of the invention. 
         SUMMARY OF THE INVENTION 
         [0018]    The present invention is related to a method for canceling interference in wireless communication. The method includes receiving wireless code division multiple access (CDMA) communication signals using one or more antennas at least from a first entity via a first communication channel and a second entity via a second communication channel, determining a set of known characteristics associated with the first entity, the first set of characteristics comprising a first signal strength, a first synchronization information, and an first channel identification information, and determining aggregate signal matrix based on signals received from at least the first entity and the second entity. The method further includes determining a covariance matrix associated with the aggregate signal value, determining a reference signal matrix based on the set of known characteristics, and calculating an interference matrix by subtracting the reference signal matrix from the covariance matrix. Furthermore, the method includes determining a maximum eigenvalue and an eigenvector corresponding to the maximum eigenvalue for with the interference matrix, generating an interference estimation using the maximum eigenvalue and the eigenvector, and removing the interference estimation from the communication signals. 
           [0019]    The method also includes performing recursive calculations with a threshold condition to determine the maximum eigenvalue. The threshold is determined based on a desired signal-to-noise ratio and the correlation feature of the designed signature code. Also, the channel identification information comprises a signature (spreading) code, scrambling code, in orthogonal code, or non-orthogonal. The reference signal matrix is associated with covariance values of the set of known characteristics, and the wireless communication CDMA signals includes interference signals. 
           [0020]    In a further embodiment, a system for canceling interference in wireless communication, is described. The system includes a storage device, a common reference timing, and a processor in communication with the storage device. There are two types of storage devices: instruction memory block and data memory block. The former storage device has sets of instructions stored thereon which, when executed by the processor, cause the processor to: receive wireless code division multiple access (CDMA) communication signals using one or more antennas at least from a first entity via a first communication channel and a second entity via a second communication channel, called reference channel,and other entities via all other available communication channels and save to the data storage device at a preset time. The processor will process these saved data offline to: determine a set of known characteristics associated with the first entity, the first set of characteristics comprising a first signal strength, a first synchronization information, and an first channel identification information, and determine an aggregate signal matrix based on signals received from at least the first entity and the other related entities. 
           [0021]    The sets of instructions further cause the processor to determine a covariance matrix associated with the aggregate signal value, determine a reference signal matrix based on the set of known characteristics, calculate an interference matrix by subtracting the reference signal matrix from the covariance matrix, determine a maximum eigenvalue and an eigenvector corresponding to the maximum eigenvalue for with the interference matrix, generate an interference estimation using the maximum eigenvalue and the eigenvector, and remove the interference estimation from the communication signals. 
           [0022]    Further, another embodiment describes a hardware processing accelerator to complete all the above interference estimation and cancellation process. Further, another embodiment describes a computer-readable medium for updating user assistance content. The computer-readable medium has sets of instructions stored thereon which, when executed by a computer, cause the computer to: receive wireless code division multiple access (CDMA) communication signals using one or more antennas at least from a first entity via a first communication channel, a second entity via a second communication channel and so on, determine a set of known characteristics associated with the first entity, the first set of characteristics comprising a first signal strength, a first synchronization information, and an first channel identification information, determine an aggregate signal matrix based on signals received from at least the first entity and the second entity, determine a covariance matrix associated with the aggregate signal value, determine a reference signal matrix based on the set of known characteristics, calculate an interference matrix by subtracting the reference signal matrix from the covariance matrix, determine a maximum eigenvalue and an eigenvector corresponding to the maximum eigenvalue for with the interference matrix, generate an interference estimation using the maximum eigenvalue and the eigenvector, and remove the interference estimation from the communication signals. 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       [0023]    While various aspects of embodiments of the invention have been summarized above, the following detailed description illustrates exemplary embodiments in further detail to enable one of skill in the art to practice the invention. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced without some of these specific details. In other instances, well-known structures and devices are shown in block diagram form. Several embodiments of the invention are described below and, while various features are ascribed to different embodiments, it should be appreciated that the features described respect to one embodiment may be incorporated with another embodiment as well. By the same token, however, no single feature or features of any described embodiment should be considered essential to the invention, as other embodiments of the invention may omit such features. 
         [0024]    Aspects of the present invention relate to inter symbol interference cancellation and channel equalizer. Removing interferences includes symbol level inter-interference and intra-interference cancellation (e.g., blind interference cancellation). Aspects of the invention further includes chip level inter symbol interference cancellation and channel equalization, time tracking on the reference channel by analyzing the equalizer channel profile, estimate the equalizer coefficient on the reference channel, applying the equalizer coefficient on all channels associated with the desired user, and dynamically selecting the combination of the symbol level inter-interference and intra-interference cancellation and chip level equalizer based on the interference detection and the output signal-to-noise ratio. 
         [0025]    Further aspects of the present invention relate to interference cancellation of wireless communication systems, and specifically to CDMA based mobile communication systems (i.e., WCDMA) which are particularly applied in a universal mobile telecommunications system (UMTS) terrestrial radio access-frequency division duplexing (UTRA-FDD) downlink receiver to cancel the intra-cell interference, and inter-cell interference, and mitigate inter symbol interference (ISI) interference. 
         [0026]    Instead of estimating an interference signal, the present invention blindly cancels interferences in succession based on second order statistics to avoid the computational complexity. The most dominant interference contribution to the received covariance matrix is first estimated and then removed from the receiving vector. Then, the weaker interferences are removed in succession by repeating this process. The desired signal will be detected after each of the significant interference items are removed. The estimation of the interference contribution to the received covariance matrix can be implemented by using subspace technique to project the interference on the maximum eigenvalue and its corresponding maximum eigenvector. 
         [0027]    Furthermore, the present invention provides improved performance by adding the interference cancellation and thus increasing the data rate. Further, the effect of signal covariance matrix estimation errors are mitigated. The computational complexity is decreased by removing the block to detect unknown interferences. Processing delay is reduced by removing the interference reconstruction from the decision feedback. As such, the present invention increases calculation speed without sacrificing accuracy in order to solve inter-cellular and intra-cellular interferences. 
         [0028]    Referring now to  FIG. 1  which a system  100  of a receiver with blind interference cancellation, according to one embodiment of the present invention. In one embodiment, the system  100  includes a radio frequency block  101  in communication with a digital front end block  102 . Radio frequency block  101  includes an RF block A  103  and RF block B  104 , which receive radio frequencies Rx 1  and Rxi, respectively. 
         [0029]    Digital front end block  102  includes a digital sampling block A  105  which receives input from RF block A  103  and a digital sampling block B  106  which receives input from RF block B  104 . Further, digital front end block  102  includes a storage block A  107 , a channel estimation block A  109 , a storage block B  108 , and a channel estimation block B  110 . Storage block A  107 , channel estimation block A  109  receive inputs from digital sampling block A  105 , and storage block B  108 , channel estimation block B  110  receive inputs from digital sampling block B  106 . Accordingly, storage block A  107  and storage block B  108  store the received signals, and channel estimation block A  109  and channel estimation block B  110  perform channel estimation based on the received signals. 
         [0030]    A scrambling spreading code generator  111  is in communication with channel estimation block A  109  and channel estimation block B  110 . Then, a blind interference cancellation block A  112  receives {r 1 } from storage block A  107 , {h 1 } from channel estimation block A  109 , and an input from scrambling spreading code generator  111 . Further, a blind interference cancellation block B  113  receives {ri} from storage block B  108 , {hi} from channel estimation block B  110 , and an input from scrambling spreading code generator  111 . Furthermore, a RF block  114  receives input from blind interference cancellation block A  112 , blind interference cancellation block B  113 , and {sci} from scrambling spreading code generator  111 . 
         [0031]    Turning now to  FIG. 2 , which is block diagram illustrating a system  200  for implementing intra-interference and inter-interference cancellation and channel equalization, according to one embodiment of the present invention. In one embodiment, system  200  includes a m-stage intra-CHk blind interference cancellation (BIC) 1   201 , an m-stage intra-CH 1  BIC 1   202 , and a m-stage CPICH BIC 1   203 , each of which receive input from r (1) . Furthermore, m-stage intra-CHk BIC 2   206 , an m-stage intra-CH 1  BIC 2   205 , and a m-stage CPICH BIC 2   204 , each of which receive input from r (2) . 
         [0032]    In a further embodiment, system  200  includes an equalizer  211  which includes a channel equalizer (CE) 1   207  in communication with an equation (EQU) 1  coefficient (COEFF)  209 , and a CE 2   208  in communication with an EQU 2  COEFF  210 . Further, CE 1   207  receives input r m,pi   (1)  from m-stage CPICH BIC 1   203 , and CE 2   208  receives input r m,pi   (2)  from m-stage CPICH BIC 1   204 . 
         [0033]    System  200  further includes an apply EQU coefficients and combiner  212  which receives input r m,chk   (1)  from m-stage intra-CHk BIC 1   201 , input r m,ch1   (1)  from m-stage intra-CH 1  BIC 1   202 , input r m,ch1   (2)  from m-stage intra-CH 1  BIC 2   205 , and input r m,chk   (2)  from m-stage intra-CHk BIC 2   206 . apply EQU coefficients and combiner  212  also received input from EQU 1  COEFF  209  and EQU 2  COEFF  210 . apply EQU coefficients and combiner  212  then processes the inputs and outputs r pi , r ch1 , and r chk  to CPICH demod  213 , intra-CH 1  demod  214 , and inta-CHk demod  215 , respectively. 
         [0034]    In one embodiment, in system  200  the received high-speed downlink packet access (HSDAP) signal of the serving cell includes the synchronous intra-cell channels and the asynchronous inter-cell interferences. The HSDAP received signal on the p th  branch on symbol level is simplified as: 
         [0000]    
       
         
           
             
               
                 
                   
                     r 
                     
                       ( 
                       p 
                       ) 
                     
                   
                   = 
                   
                     
                       ∑ 
                       
                         k 
                         = 
                         0 
                       
                       
                         K 
                         - 
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                      
                     
                       
                         ∑ 
                         
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                                   N 
                                   
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                   Equation 
                    
                   
                       
                   
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                   1 
                 
               
             
           
         
       
     
         [0000]    where SC is the equivalent spreading code combined by the scrambling code and the orthogonal spreading code. The scrambling codes are used to identify cells, indexed by k, and in each cell the intra-cell channels are identified by orthogonal spreading code, indexed by ch.  FIG. 2  demonstrates a single input, multiple outputs (SIMO) system where there are two receiving branches. The received signal on each branch is modeled first as passing to a multi-path channel and the channel h is assumed not changing for the duration of a symbol l is used to index the multi-path. Then ISI will be removed by the equalizer after the multi-stage blind interference cancellation. The equalizer coefficients will be obtained from common pilot channel (CPICH) and applied on all intra-channels. 
         [0035]    Turning next to  FIG. 3  which illustrates a block diagram of a system  300  for implementing blind interference cancellation on each channel, according to one embodiment of the present invention. In one embodiment, system  300  includes a BIC state  1   301 , which includes a covariance matrix estimator R r    302 , a desired multipath signal matrix estimator R ch    303 , a max interference vector and matrix on subspace estimator  304 , an interference on signal space reconstructor  305 , and an excessive cancellation detector  306 . 
         [0036]    The outputs R r,1  and r 1  from BIC state  1   301  are received by a BIC stage  2   308  and then outputs R r,2  to R r,m-1  and r 2  to r m-1  are received by BIC stage m  309 . Then, BIC stage m  309  outputs r m . 
         [0037]    In one embodiment, the following the multi stage blind interference cancellation block may be implemented using system  300  in  FIG. 3 . The received signal vector with a length of N ch  chips at symbol i is noted as r(i), where N ch  usually is the spreading factor of the channel. Note that the maximum number of interference components may be detected and cancelled usually meets the following relations: N ch ≧2K a +K s +1, where K a  is the total number of asynchronous interference items and K s  is the total number of synchronous interference items. The receiving signal covariance matrix can be estimated directly from the received signal sample or channel estimation. Equation 2 is a typical sample estimation with the estimation window size of N: 
         [0000]    
       
         
           
             
               
                 
                   
                     
                       R 
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                   Equation 
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         [0000]    The desired multipath signal matrix is estimated as: 
         [0000]    
       
         
           
             
               
                 
                   
                     
                       
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         [0000]    where H is Hermitian conjugation operation, the channel estimation on symbol level ĥ can simply use the finger output of RAKE receiver and is not the key focus of this invention. Dropping the symbol index i for simplification, the interference covariance matrix can be obtained by removing the desired signal as: 
         [0000]        {circumflex over (R)}   r,0   ={circumflex over (R)}   r   −{circumflex over (R)}   ch    Equation 4
 
         [0038]    The mean energy (ME) of the received signal r on the N ch -dimensional vector space u is defined as ME(u)=E{(r H u) 2 }, where u H u=1. According to linear algebra theory, the eigenvalue λ and the corresponding eigenvector v is the necessary condition to maximize ME(v) as R r v=λv. For a set of eigenvalue and the corresponding eigenvector of R r , ME(V)=V H R r V=D , where D=diag{λ n }, n=0 . . . N ch −1 and V is the Eigen-matrix consist of N ch  orthogonal Eigenvectors. Therefore the eigenvector corresponding to the maximum eigenvalue is the vector that maximizes the mean energy on it. The next step is to remove the maximum interference contribution in the interference covariance matrix in stage m by applying this subspace theory as: 
         [0000]        {circumflex over (R)}   r,m   ={circumflex over (R)}   r,m-1 −λ max   (m)   v   max   (m)   v   H     (m)       max      Equation 5
 
         [0039]    To find the maximum eigenvalue λ max  and the corresponding Eigenvector v max . The Eigen-decomposition in full is not needed. Instead an iterative solution like power method (PM) can be used. The iteration algorithm to obtain the maximum eigenvalue λ max  and the corresponding Eigenvector v max  is not the key topic in this invention. The excessive cancellation detector in stage m can be implemented by a threshold, which is associated with the signal-to-noise ratio and the correlation feature of the combined spreading code, check as: 
         [0000]        w   m =(SC ch   H   v   max   (m) &gt;Threshold)?0:1   Equation 6
 
         [0000]    The cleaner signal will feed to the next stage when w m =1 else stop. 
         [0000]        {circumflex over (r)}   m   =r   m-1   −w ·( r   m-1   H   v   max   (m) )v max   (m)    Equation 7
 
         [0000]    where r 0 =r. 
         [0040]    In UTRA-FDD downlink, the CPICH can be used to calculate the channel equalizer coefficients and the coefficients will apply on each channel after performing multi-stage blind interference cancellation on each channel to remove ISI. The equalizer can be implemented in time domain or frequency domain based on the signal covariance matrix estimation and is not the main focus in this invention. 
         [0041]    Referring next to  FIG. 4  which illustrates a system  400  for implementing multi-channel/multi-stage blind interference cancellation, according to one embodiment of the present invention. In one embodiment, system  400  includes a J th  Channel Multi-Stage Blind Interference Cancellation A  401 , a 1 st  Channel Multi-Stage Blind Interference Cancellation A  402 , and a channel estimation block A  405 , which each receive input {r 1 }. Further, a J th  Channel Multi-Stage Blind Interference Cancellation B  404 , a 1 st  Channel Multi-Stage Blind Interference Cancellation B  403 , and a channel estimation block B  406 , each receive input {ri}, 
         [0042]    Channel estimation block A  405  provides input {h 11 } to 1 st  Channel Multi-Stage Blind Interference Cancellation A  402  and input {h 1 } to J th  Channel Multi-Stage Blind Interference Cancellation A  401 . Further, channel estimation block B  406  provides input {hi 1 } to 1 st  Channel Multi-Stage Blind Interference Cancellation B  403  and input {hij} to J th  Channel Multi-Stage Blind Interference Cancellation B  404 . 
         [0043]    System  400  further includes a scrambling spreading code generator  407  which provides input {sc 11 } to 1 st  Channel Multi-Stage Blind Interference Cancellation A  402  and input {sc 1   j } to J th  Channel Multi-Stage Blind Interference Cancellation A  401 , as well as input {sci 1 } to 1 st  Channel Multi-Stage Blind Interference Cancellation B  403  and input {scij} to J th  Channel Multi-Stage Blind Interference Cancellation B  404 , scrambling spreading code generator  407  also provides input to a demod block  408 , and demod block  408  outputs {d 1  to dj}. 
         [0044]    Furthermore, J th  Channel Multi-Stage Blind Interference Cancellation A  401  outputs {r 1   j } to a J th  Channel Combiner  410  and J th  Channel Multi-Stage Blind Interference Cancellation B  404  also outputs {rij} to J th  Channel Combiner  410 . 1 st  Channel Multi-Stage Blind Interference Cancellation A  402  outputs {r 11 } to 1 st  Channel Combiner  409  and 1 st  Channel Multi-Stage Blind Interference Cancellation B  403  outputs {ri 1 } to 1 st  Channel Combiner  409 . Further, 1 st  Channel Combiner  409  and J th  Channel Combiner  410  provide output to demod block  408 . 
         [0045]      FIGS. 5A and 5B  illustrates a method  500  for implementing blind interference cancellation, according to one embodiment of the present invention. In one embodiment, method  500  may be implemented using any one of systems  100 ,  200 ,  300 , or  400 . At process block  501 , a signal vector is received and saved. The signal vector is then input into a 1st stage blind interference cancellation module. At process block  502 , a covariance matrix is received and processed. 
         [0046]    At process block  503 , a channel estimation for a desired signal is performed and a covariance matrix for the desired signal is processed (process block  504 ). At process block  505 , an interference matrix is processed by subtracting the output of the processing of the covariance matrix for the desired signal. Then, the maximum eigenvalue and its eigenvector of the interference matrix is determined (process block  506 ). 
         [0047]    At process block  507 , the strongest interference based on the determined eigenvector is generated to rebuild the 2 nd  item in Equation 7. The strongest interference covariance matrix is determined based on the eigenvalue and its eigenvector for the 2 nd  item in Equation 5 (process block  508 ). Then, at process block  509 , a threshold is checked against the correlation between the desired signal and the eigenvector results. 
         [0048]    If the threshold is not exceeded, then the process moves to point ‘A’, otherwise the process moves to point ‘B’ and on to process block  515 . Turning now to  FIG. 5B  from point ‘A’, at process block  511 , a cleaner signal vector is obtained by subtracting the results of process block  507  from the input to the stage vector. 
         [0049]    A determination is made whether the number of stages has reached the number of the covariance matrix dimension (decision block  512 ). If the number of stages has not reached the number of the covariance matrix dimensions, then at process block  513 , the remaining interference covariance matrix is processed by removing the results from process block  508 . At process block  514 , the next stage BIC is stared with two inputs from process blocks  511  and  513 . Then, the process returns to process block  506  via point ‘C’. Otherwise, the process proceeds to point ‘B’ and process block  515 . At process block  515 , the outputs from process block 511 from each antenna for each channel are combined. At process block  516 , the outputs of process block  515  for each channel are dispread. 
         [0050]    One implementation of the method  500  includes calculating (2×2) covariance matrix (it should be noted that the larger the dimension of the covariance matrix, the more interference items can be detected and further cancelled, and usually the size of the covariance matrix is equivalent to the length of each CDMA channel&#39;s spreading code). 
         [0051]    In one embodiment, the desired signal&#39;s signature code in one symbol for the desired user is: 
         [0000]      s 0 =[1 1] T ,       the interference&#39;s item is:         
         [0000]      s 1 =[1 −1] T  
       the covariance matrix for the received signal is:       
 
         [0000]    
       
         
           
             
               R 
               = 
               
                 [ 
                 
                   
                     
                       2.1 
                     
                     
                       0 
                     
                   
                   
                     
                       0 
                     
                     
                       0.1 
                     
                   
                 
                 ] 
               
             
             , 
           
         
       
       
         
           
             with a variance of normal additive noise is estimated at 0.1. 
             the covariance matrix for the desired user is estimated perfectly as: 
           
         
       
     
         [0000]    
       
         
           
             
               R 
               0 
             
             = 
             
               [ 
               
                 
                   
                     0.5 
                   
                   
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             the covariance matrix after being removed, the desired user&#39;s contribution (interference and noise) will be: 
           
         
       
     
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                 r 
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               . 
             
           
         
       
       
         
           
             the max Eigenvalue and corresponding Eigenvector will be: 
           
         
       
     
         [0000]      λ max =1.718 and ν max =[−0.9732 0.2298] T .
 
         [0058]    The rebuild interference ŝ 1 =[1.9337 0.4565] and the cleaner signal after interference remove will be ŝ 0 =[0.0915 0.3875] T  and the estimated symbol will be detected as 1 as expected, 
         [0059]    Turning now to  FIG. 6  which illustrates a system  600  of a receiver with an interference cancellation and equalizer, according to one embodiment of the present invention. In one embodiment, system  600  includes similar elements of  FIG. 1  with the Interference and Cancellation Equalizer Block A  601 , Interference and Cancellation Equalizer Block B  602 , and Combine and Demod Block  603 , which replace Blind Interference Cancellation Block A  112 , Blind Interference Cancellation Block B  113 , and RF block  114 , 
         [0060]    Turning next to  FIG. 7  which illustrates a system  700  for implementing multi-channel interference cancellation and equalizer, according to one embodiment of the present invention. In one embodiment, system  700  includes the elements of  FIG. 4  with a Reference Channel Equalizer Coefficient Estimation  701 , a finite impulse response (FIR) Filter Bank  702 , and Demod Block  703 , which replace Demod Block  408 , 1st Channel Combiner  409 , and J th  Channel Combiner  410 . 
         [0061]      FIG. 8  illustrates a system  800  for implementing a self-tracking multi-channel equalizer based on a pilot channel, according to one embodiment of the present invention. In one embodiment, system  800  includes a storage block A  801  which receives input {r 1 } or {r 11 }. System  800  further includes a storage block B  802  which receives input or {ri} or {ri 1 }. System  800  further includes a Channel Estimation with Fraction Chip Level Resolution A  803  and Channel Estimation with Fraction Chip Level Resolution B  804 , which receives input from storage block A  801  and storage block B  802 , respectively. 
         [0062]    System  800  further includes a Scrambling Spreading Code Generator  805  which sends output {sc 1 } to Channel Estimation with Fraction Chip Level Resolution A  803  and output {cs 1 } to Channel Estimation with Fraction Chip Level Resolution B  804 . Furthermore, Channel Estimation with Fraction Chip Level Resolution A  803  receives input {t 11 } from an Equalizer Control Engine  806  and Channel Estimation with Fraction Chip Level Resolution B  804  receives an input {ti 1 } from Equalizer Control Engine  806 . 
         [0063]    System  800  further includes an Equalizer Coefficient Estimator  807  which receives input {hlk} from Channel Estimation with Fraction Chip Level Resolution A  803  and input {hik} from Channel Estimation with Fraction Chip Level Resolution B  804 . Further, Equalizer Coefficient Estimator  807  outputs c 1  to cn. 
         [0064]    Referring now to  FIG. 9  which illustrates a method  900  for combining symbol level interference cancellation and chip level channel equalizer, according to one embodiment of the present invention. At process block  901 , the signal vectors are saved on the reference channel after interference cancellation or with the resolution of the fraction chip. A covariance matrix is then received and processed (process block  902 ). 
         [0065]    At process block  903 , the received and processed Covariance matrix is used, and the equalizer tap coefficient and tap energy are calculated and saved (process block  904 ). At decision block  905 , a determination is made whether additional start time positions are in start window. If there are additional start time positions in the start window, then the process returns to process block  902 . Otherwise the process continues to process block  906 , which analyzes the channel characters and the output signal-to-noise ratio (SNR) in the control engine to decide the time position in the fraction chip. 
         [0066]    At process block  907 , the input signal vector window time position may be changed based on results of process block  906 . Then, the channel estimation start time position is changed based on results of process block  906  (process block  908 ). At process block  909 , the demodulation time position is determined based on process block  906 . Then, a determination for a set of time positions the equalizer tap coefficients is made (process block  910 ). At process block  911 , the equalizer tap coefficients are applied on each channel signal vector for a desired user. 
         [0067]    Referring next to  FIG. 10  which illustrates a method  1000  for dynamically selecting the interference cancellation and channel equalizer, according to one embodiment of the present invention. At decision block  1001 , a determination is made whether valid interference components are detected on the reference channel. If valid interference components are detected on the reference channel, then the process moves to process block  1004 , otherwise the process continues to process block  1002 . 
         [0068]    At process block  1002 , blind interference cancellation on each channel is processed. At process block  1003 , the output SNR of the BIC on each channel are estimated. Then, the channel equalizer coefficients on the reference channel are estimated. At process block  1005 , the timing position in response to the output of process block  1003  is adjusted. 
         [0069]    At process block  1006 , the equalizer coefficients on all channels are applied and the output SNR of equalizer on each channel are estimated (process block  1007 ). At decision block  1008 , a determination of whether the SNR equalization output is improved. If the SNR equalization output is improved, then the output of equalizer to the demodulation is connected. Otherwise, the output of interference to the demodulation is connected. 
         [0070]      FIG. 11  is a block diagram illustrating an exemplary system  1100  in which embodiments of the present invention may be implemented. For example, the system  1100  can be a wireless communication device, a portable computer with wireless communication interface, abase station, and/or others. The system  1100  is shown comprising hardware elements that may be electrically coupled via a bus  1190 . The hardware elements may include one or more central processing units  1110 , one or more input device(s)  1120  (e.g., keypad, etc.), and one or more output device(s)  1130  (e.g., a display device, a printer, etc.). The system  1100  may also include one or more storage device(s)  1140 . By way of example, storage device(s)  1140  may be disk drives, optical storage devices, a solid-state storage device such as a random access memory (“RAM”) and/or a read-only memory (“ROM”), which can be programmable, flash-updateable, and/or the like. The system  1100  is adapted to performed interference cancellation in real time. For example, the interference cancellation is performed with a latency of less than 2 ms. 
         [0071]    The system  1100  may additionally include a computer-readable storage media reader  1150 . The system  1100  includes a communication system  1160  (e.g., a modem, a network card (wireless or wired), an infra-red communication device, Bluetooth™ device, cellular communication device, etc.), and working memory  1180 , which may include RAM and ROM devices as described above. For example, the communication system  1160  comprises a wireless communication interface compatible with CDMA standard. In some embodiments, the computer system  1100  may also include a processing acceleration unit  1170 , which can include a digital signal processor, a special-purpose processor, and/or the like. 
         [0072]    The computer-readable storage media reader  1150  can further be connected to a computer-readable storage medium, together (and, optionally, in combination with storage device(s)  1140 ) comprehensively representing remote, local, fixed, and/or removable storage devices plus storage media for temporarily and/or more permanently containing computer-readable information. The communication system  1160  may permit data to be exchanged with a wireless network, system, computer, and/or other component described above. 
         [0073]    The system  1100  may also comprise software elements, shown as being currently located within a working memory  1180 , including an operating system  1188  and/or other code  1184 . It should be appreciated that alternate embodiments of a computer system  1100  may have numerous variations from that described above. For example, customized hardware might also be used and/or particular elements might be implemented in hardware, software (including portable software, such as applets), or both. Furthermore, connection to other computing devices such as network input/output and data acquisition devices may also occur. 
         [0074]    Software of system  1100  may include code  1184  for implementing any or all of the functions of the various elements of the architecture as described herein. For example, software, stored on and/or executed by a computer system such as system  1100 , can provide the functionality and/or other components of the invention such as those discussed above. Methods implementable by software on some of these components have been discussed above in more detail. 
         [0075]    Merely by way of example,  FIG. 12  illustrates a schematic diagram of a system  1200  that can be used in accordance with one set of embodiments. The system  1200  can include one or more user devices  1205 . The user devices  1205  can be general purpose personal computers (including, merely by way of example, laptop computers running any appropriate flavor of Microsoft Corp.&#39;s Windows™ and/or Apple Corp.&#39;s Macintosh™ operating systems) and/or workstation computers running any of a variety of commercially available UNIX™ or UNIX-like operating systems. These user computers  1205  can also have any of a variety of applications, including one or more applications configured to perform methods of the invention, as well as one or more office applications, database client and/or server applications, and web browser applications. Alternatively, the user computers  1205  can be any other electronic device, such as a thin-client computer, Internet-enabled mobile telephone, and/or personal digital assistant (PDA), capable of communicating via a wireless network (e.g., the network  1210  described below) and/or displaying and navigating web pages or other types of electronic documents. Although the exemplary system  1200  is shown with three user devices  1205 , any number of user computers can be supported. For example, the user device  1205   a  is a wireless phone, which can be configured to performed interference cancellation described above. 
         [0076]    Certain embodiments of the invention operate in a networked environment, which can include a network  1210 . The network  1210  can be any type of network familiar to those skilled in the art that can support data communications using any of a variety of commercially available protocols, including without limitation TCP/IP, SNA, IPX, AppleTalk, and the like. Merely by way of example, the network  1210  can be a local area network (“LAN”), including without limitation an Ethernet network, a Token-Ring network, and/or the like; a wide-area network (WAN); a virtual network, including without limitation a virtual private network (“VPN”); the Internet; an intranet; an extranet; a public switched telephone network (“PSTN”); an infrared network; a wireless network, including without limitation a network operating under any of the IEEE 802.11 suite of protocols, the Bluetooth™ protocol known in the art, and/or any other wireless protocol; and/or any combination of these and/or other networks. In various embodiments, the network  1210  is a wireless communication network. For example, the network  1210  is configured to communicate using wireless communication protocols such as CDMA, GSM, and/or others. 
         [0077]    Embodiments of the invention can include one or more server computers  1215 . Each of the server computers  1215  may be configured with an operating system, including without limitation any of those discussed above, as well as any commercially (or freely) available server operating systems. Each of the servers  1215  may also be running one or more applications, which can be configured to provide services to one or more user devices  1205  and/or other server computers  1215 . 
         [0078]    Merely by way of example, one of the server computers  1215  may be a web server, which can be used, merely by way of example, to process requests for web pages or other electronic documents from user computers  1205 . The web server can also run a variety of server applications, including HTTP servers, FTP servers, CGI servers, database servers, Java™ servers, and the like. In some embodiments of the invention, the web server may be configured to serve web pages that can be operated within a web browser on one or more of the user computers  1205  to perform methods of the invention. 
         [0079]    The server computers  1215 , in some embodiments, might include one or more application servers, which can include one or more applications accessible by a client running on one or more of the user computers  1205  and/or other server computers  1215 . Merely by way of example, the server computers  1215  can be one or more general purpose computers capable of executing programs or scripts in response to the user computers  1205  and/or other server computers  1215 , including without limitation web applications (which might, in some cases, be configured to perform methods of the invention). Merely by way of example, a web application can be implemented as one or more scripts or programs written in any suitable programming language, such as Java™, C, C#™ or C++, and/or any scripting language, such as Perl, Python, or TCL, as well as combinations of any programming/scripting languages. The application server(s) can also include database servers, including without limitation those commercially available from Oracle™, Microsoft™. Sybase™, IBM™ and the like, which can process requests from clients (including, depending on the configuration, database clients, API clients, web browsers, etc.) running on a user computer  1205  and/or another server computer  1215 . In some embodiments, an application server can create web pages dynamically for displaying the information in accordance with embodiments of the invention. Data provided by an application server may be formatted as web pages (comprising HTML, Javascript, etc., for example) and/or may be forwarded to a user computer  1205  via a web server (as described above, for example). Similarly, a web server might receive web page requests and/or input data from a user computer  1205  and/or forward the web page requests and/or input data to an application server. In some cases, a web server may be integrated with an application server. 
         [0080]    In accordance with further embodiments, one or more server computers  1215  can function as a file server and/or can include one or more of the files (e.g., application code, data files, etc.) necessary to implement methods of the invention incorporated by an application running on a user computer  1205  and/or another server computer  1215 . Alternatively, as those skilled in the art will appreciate, a file server can include all necessary files, allowing such an application to be invoked remotely by a user computer  1205  and/or server computer  1215 . It should be noted that the functions described with respect to various servers herein (e.g., application server, database server, web server, file server, etc.) can be performed by a single server and/or a plurality of specialized servers, depending on implementation-specific needs and parameters. 
         [0081]    In certain embodiments, the system can include one or more database(s)  1220 . The location of the database(s)  1220  is discretionary. Merely by way of example, a database  1220   a  might reside on a storage medium local to (and/or resident in) a server computer  1215   a  (and/or a user computer  1205 ). Alternatively, a database  1220   b  can be remote from any or all of the computers  1205 ,  1215 , so long as the database can be in communication via the network  1210 ) with one or more of these. In a particular set of embodiments, a database  1220  can reside in a storage-area network (“SAN”) familiar to those skilled in the art. (Likewise, any necessary files for performing the functions attributed to the computers  1205 ,  1215  can be stored locally on the respective computer and/or remotely, as appropriate.) In one set of embodiments, the database  1220  can be a relational database, such as an Oracle™ database, that is adapted to store, update, and retrieve data in response to SQL-formatted commands. The database might be controlled and/or maintained by a database server, as described above, for example. 
         [0082]    The invention has now been described in detail for the purposes of clarity and understanding. However, it will be appreciated that certain changes and modifications may be practiced within the scope of the appended claims.