Patent Publication Number: US-8971384-B2

Title: Method and apparatus for modulation and coding scheme adaption in a MIMO system

Description:
PRIORITY CLAIM AND CROSS-REFERENCE 
     This application is a divisional of, and claims priority to, U.S. patent application Ser. No. 13/310,627, filed on Dec. 2, 2011 and entitled “Method and Apparatus for Modulation and Coding Scheme Adaption in a MIMO System” which application is incorporated herein by reference. 
    
    
     TECHNICAL FIELD 
     Embodiments of the present invention relate in general to modulation and coding scheme adaption as well as decoding for communication systems with correlated signals and interferences. 
     BACKGROUND 
     Multiple input, multiple output (MIMO) systems refer to communication systems that have multiple transmission and multiple reception antennas at both enhanced Node B (eNB) (or base station (BS), Node B (NB), communications controller, and so forth) and User Equipment (UE) (or mobile station (MS), terminal, user, relay, subscriber, subscriber equipment, and so on). Such MIMO systems can achieve better channel utilization and better overall performance. The Third Generation Partnership Project (3GPP) E-UTRA standards specify MIMO schemes for use by E-UTRA UEs and eNBs. Single-cell enhanced Multi-User MIMO (MU-MIMO) has been identified as an important technique for LTE Advanced (LTE-A) to improve system performance. In LTE Rel-8, Single-User MIMO (SU-MIMO) and MU-MIMO are supported by different transmission modes which are configured semi-statically by higher layer. In LTE Rel-9 and LTE Rel-10, transparent MU-MIMO can be supported. 
     In a typical Multi-User Multiple-Input Multiple-Output (MU-MIMO) system, a transmitter transmits a MU-MIMO signal, which comprises multiple signals that are addressed to multiple respective receivers. Each of the signals is precoded with a respective precoding scheme, and the signals are spatially-multiplexed and transmitted in the same time-frequency slot, therefore a signal to one receiver can cause more interference to another. 
     SUMMARY OF THE INVENTION 
     These and other problems are generally solved or circumvented, and technical advantages are generally achieved, by embodiments of a system and method for modulation and coding scheme adaption as well as decoding for communication systems with correlated signal and interference. 
     In accordance with an example embodiment, a method for signal processing in a communication system is provided. A base station eNB generates a transmitted signal from a set of signals through a coding process, and the set of signals x=[x 1  x 2  . . . x K ] T  comprises a first signal x j  and a plurality of other signals. The coding process defines a correlation relationship amongst the first signal and the plurality of other signals in the set. The coding process used in generating the transmitted signal from the set of signals may comprise a linear or non-linear precoding performed by a precoder within the transmitter or the eNB, such as a dirty-paper non-liner precoding, a linear zero-forcing precoding, or a linear regularized zero-forcing precoding. 
     In accordance with an example embodiment, the transmitted signals may be targeted to multiple users or receivers in a MIMO system. A receiver receives the transmitted signal sent by the eNB or the transmitter through a channel. The receiver decodes the transmitted signal into a first estimate component for estimating the first signal, a first interference component caused by the correlation relationship among the set of signals, and a first noise component, wherein the decoding is performed in accordance with correlation information about the correlation relationship among the set of signals. The receiver may decode a second signal in addition to the first signal, by similarly decoding the received signal into a second estimate component for estimating a second signal of the set of signals, a second interference component caused by the correlation relationship among the set of signals, and a second noise component. 
     In accordance with an example embodiment, the correlation information about the correlation relationship among the set of signals used in decoding by the receiver may be sent directly by the transmitter using a pilot signal or a control signal. Alternatively, the correlation information may be sent by the transmitter using a dedicated reference symbol (DRS). The correlation information may be a correlation matrix R x =E[xx H ] or D=diag(R x ) −1 , wherein x=[x 1  x 2  . . . x K ] T  is the set of signals. 
     In accordance with an example embodiment, the decoder within the receiver may perform decoding by determining a linear receiver filter for the first signal in accordance with the received correlation information, and de-correlating the first signal and interferences to generate the first estimate component of the first signal, the first interference component, and the first noise component. The de-correlation of the first signal and the interferences may be derived through usage of a Cholesky factorization process. 
     In accordance with an example embodiment, the linear receiver filter for the first signal x j  may be as r 1×N , where r 1×N =[R x ] jth row  H H  (HR x H H +R n ) −1  wherein x=[x 1  x 2  . . . x K ] T  is the set of signals, R x =E[xx H ] is a correlation matrix of x=[x 1  x 2  . . . x K ] T , H represents a combined impact of the channel and the coding process, and the channel H has a noise vector n with a correlation matrix R n =E[nn H ]. The linear receiver filter for the first signal x j  may be of other forms such as s*r 1×N =s*[R x ] jth row H H  (HR x H H +R n ) −1 , wherein a scalar number is denoted as s. 
     In accordance with an example embodiment, the receiver decodes the first estimate component for the first signal x j  to be 
                 1       [     R   x     ]     jj       ⁢       rH   ⁡     [     R   x     ]         jth   ⁢           ⁢   column       ⁢     x   j       ,         
the first interference component to be
 
             rHx   -       1       [     R   x     ]     jj       ⁢       rH   ⁡     [     R   x     ]         jth   ⁢           ⁢   column       ⁢     x   j             
and a signal to interference and noise ratio (SINR) for the first signal to be
 
     
       
         
           
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     In accordance with an example embodiment, an apparatus for signal processing in a communication system is provided. The apparatus comprises a receiver configured to receive a transmitted signal sent by a transmitter through a channel, wherein the transmitted signal is generated from a set of signals through a coding process, and wherein the set of signals comprises a first signal and a plurality of other signals with a correlation relationship after the coding process. The apparatus further comprises a processor configured to decode, in accordance with a correlation information about the correlation relationship among the set of signals, the received signal into a first estimate component for estimating the first signal, a first interference component caused by the correlation relationship among the set of signals, and a first noise component. The receiver is configured to receive the correlation information about the correlation relationship among the set of signals from the transmitter; and the processor is configured to generate a linear receiver filter for the first signal; and to de-correlate the first signal and interferences to generate the first estimate component of the first signal, the first interference component, and the first noise component. 
     In accordance with an example embodiment, an apparatus for signal processing in a communication system is provided. The apparatus comprises a processor configured to generate a transmitted signal from a set of signals through a coding process, wherein the set of signals comprises a first signal and a plurality of other signals with a correlation relationship after the coding process. The apparatus further comprises a transmitter to send the transmitted signal through a channel, and to send a correlation information about the correlation relationship among the set of signals through the channel, wherein the correlation information is related to a first interference component of the transmitted signal caused by the correlation relationship among the set of signals. The apparatus may send the correlation information using a pilot signal, a control signal, or a dedicated reference symbol (DRS). 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       For a more complete understanding of the present invention, and the advantages thereof, reference is now made to the following descriptions taken in conjunction with the accompanying drawing, in which: 
         FIG. 1  illustrates an example of a MIMO system with an eNB and a plurality of receivers; 
         FIGS. 2(   a )- 4  illustrate examples of operations performed by a receiver; and 
         FIG. 5  illustrates an example of a controller implementing the operations performed by the eNB and the receiver. 
     
    
    
     DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS 
     The making and using of the presently preferred embodiments are discussed in detail below. It should be appreciated, however, that the present invention provides many applicable inventive concepts that can be embodied in a wide variety of specific contexts. The specific embodiments discussed are merely illustrative of specific ways to make and use the invention, and do not limit the scope of the invention. 
     In a multi-user multiple input multiple output (MU-MIMO) system, a base station (eNB) serves one or more user equipments (UEs) simultaneously by transmitting communication signals to one or more UEs.  FIG. 1  illustrates an example MU-MIMO system  100 . MU-MIMO system  100  may be a downlink MU-MIMO system, but it is not limited to such a system. MU-MIMO system  100  comprises an eNB  102  which has one or more transmission antennas  104 - 1 ,  104 - 2 , . . . ,  104 -K to transmit a signal vector x=[x 1  x 2  . . . x K ] T . A signal vector x=[x 1  x 2  . . . x K ] T  a plurality of signals x=[x 1  x 2  . . . x K ] T  a set of signals, or signals x=[x 1  x 2  . . . x K ] T  may be used to mean the same x=[x 1  x 2  . . . x K ] T , which comprises a plurality of signals x j . eNB  102  may transmit the signal vector via transmission antennas  104 - 1  to  104 -K to one or more receivers UE 1 , UE 2 , . . . UEM, which may each have one or more reception antennas  106 - 1 ,  106 - 2 , . . . ,  106 -N. The number of antennas may not be the same as the number of signals to be transmitted. Each of the receivers UE 1  to UEM may be capable of transmitting signals to the base station. Different UEs may have different number of antennas. The number of UEs, the number of antennas for the eNB and the UEs, are only shown for illustrative purposes and are not limiting. There may be other number of UEs with other number of antennas can be used in the system. 
     The base station eNB  102  may be a wireless transmitter (e.g., cellular site, satellite, etc.) connected to a network (not shown). The eNB  102  may include a precoder  112  for precoding signals transmitted by transmission antennas  104 - 1  to  104 -K, a scheduler  114  for scheduling one or more transmissions, and a correlation transmitter  116  for transmitting signal correlation information. The functions of the precoder  112 , the scheduler  114 , and the transmitter  116  may be implemented by an example controller  500  illustrated in  FIG. 5 . The group of users UE 1  to UEM is selected by the scheduler  114  for the transmission. There may be a different number of UEs connected to eNB  102  but some of them may not be selected for transmission. In some embodiments, eNB  102  may comprise multiple transmitters, each with multiple precoders  112  and transmission antennas. Further, eNB  102  may comprise one or more reception antennas and inputs (not shown) for receiving input data and feedback signals, etc. and one or more controllers and/or or appropriate control circuitry, symbol generators, multiplexers, etc. 
     Precoder  112  may be capable of performing precoding functions on each of signals x=[x 1  x 2  . . . x K ] T , x j . That is, the precoder  112  may design, determine, and implement a precoder or a codebook for use in signal transmission by eNB  102 . The precoder  112  may precode each signal x j  sequentially or in parallel. Precoding algorithms used in MU-MIMO may be divided into non-linear and linear precoding types. A non-linear precoding technique may be the so-called Dirty-Paper Coding (DPC) which pre-cancels the interference of the signal transmitted by the transmitter without any power penalties. Linear precoding includes zero-forcing (ZF) and Regularized Zero-Forcing (R-ZF) precoding. Zero-forcing (ZF) technique requires that the transmitter know the downlink channel state information. Accordingly, in the case of limited or inaccurate channel state information, Regularized Zero-Forcing (R-ZF) precoding may be used to compensate unfavorable channel conditions. 
     Each of signals x=[x 1  x 2  . . . x K ] T , x j , comprises a sequence of modulated symbols, which carry data addressed to respective UE. Any suitable modulation scheme, such as Quadrature Phase Shift Keying (QPSK) or Quadrature Amplitude Modulation (QAM), can be used. The data conveyed by each signal is typically encoded with an Error Correction Code (ECC). The choice of modulation and ECC used in a given signal is referred to as a Modulation and Coding Scheme (MCS). The set of signals x=[x 1  x 2  . . . x K ] T  may be each precoded, encoded with ECC schemes, and modulated, and finally multiplexed together to form a transmitted signal, which is to be transmitted by eNB  102  to the UEs. For a first signal x j , the transmitted signal comprises a first estimate component of x j , and a first interference component to indicate the amount of interference caused by the correlation relationship among the signals x=[x 1  x 2  . . . x K ] T  after the coding process. When the transmitted signal is received by a UE through a channel, the received transmitted signal has a third component which is a noise component to indicate the impact of the noise of the channel. 
     The eNB  102  may further comprise a correlation transmitter  116 . The signal vector x=[x 1  x 2  . . . x K ] T  precoded by the precoder  112  may have a correlation relationship. Such a correlation relationship may be represented by a correlation matrix R x =E[xx H ], which may be transmitted by the pilot or control signals to the UEs through one or more of the plurality of transmit antennas. Other forms of correlation information can be represented as well. For example, a matrix may be defined as D=diag(R x ) −1 , i.e., 
                   [   D   ]     kk     =     1       [     R   x     ]     kk         ,         
k=1, . . . , K. The correlation information, being it as the correlation matrix R x =E[xx H ] or D=diag(R x ) −1 , i.e.,
 
                   [   D   ]     kk     =     1       [     R   x     ]     kk         ,         
k=1, . . . , K, provides information about the first interference component of the transmitted signal to indicate the amount of interference caused by the correlation relationship among the signals x=[x 1  x 2  . . . x K ] T  after the coding process. The first interference component of the transmitted signal may be identified at the receiver by decoding the received signals. At the transmitter, the dedicated reference symbols (DRS) may be precoded by R x D and transferred to UEs. The detailed functions of those units scheduler  114 , precoder  112 , and a correlation transmitter  116  may be implemented by a controller  500  shown in  FIG. 5 , wherein a processor  502  may be configured to perform each of the functions. The processor  502  may be an ASIC, a general purpose processor, a Digital Signal Processor, a combination of processors, a processor with dedicated circuitry, dedicated circuitry functioning as a processor, and a combination thereof.
 
     Prior to transmitting data signals, eNB  102  usually transmits pilot or control signals to the UEs through one or more of the plurality of transmit antennas. Based at least in part on signals (e.g., pilot signals) received from the eNB  102 , each individual UE estimates a condition of the wireless channels between the eNB  102  and the UE. For example, UE 1  estimates a channel matrix H 1 , which is representative of quality of a wireless communication channel between the eNB  102  and the UE 1 . Similarly, UE 2 , . . . , UEM estimate respective channel matrices H 2 , . . . , H M  that are representative of quality of respective wireless communication channels. 
     The eNB  102  transmits the transmitted signal generated from the precoded, which may include modulation and ECC, signal vector x=[x 1  x 2  . . . x K ] T  through the antennas  104 - 1 ,  104 - 2 , . . . , and  104 - k . The transmitted signal is received by the N receiving antennas  106 - 1 , . . . ,  106 -N of M receivers, which will be decoded. 
     Receivers UE 1  to UEM may be wireless reception devices (e.g. mobile telephone, ground station, etc.) as are known and may be capable of receiving and decoding (e.g., demultiplexing) signals y=[y 1  y 2  . . . y N ] T  received at reception antennas  106 - 1  to  106 -N as well as transmitting feedback (e.g., quantized feedback) to eNB  102 . It is understood that this feedback transmission may be wired and wireless over feedback links and may be transmitted using a combination of reception antennas  106 - 1  to  106 -N. 
     Combined together for all users UE 1  to UEM, the MIMO system  100  may be described by
 
 y   N×1   =H   N×K   x   K×1   +n   N×1,   (1)
 
where x=[x 1  x 2  . . . x K ] T  is the set of signals which are precoded and processed to generate the transmitted signal, a first signal may be any of the signals x j , y=[y 1  y 2  . . . y N ] T  is the received signal after decoded by the UEs, H represents combined channel and precoder, and n=[n, n 2  . . . n N ] T  is the noise for the channel H. The set of signals x has correlation matrix R x =E[xx H ]. The noise vector n has correlation matrix R n =E[nn H ].
 
     A receiver may be only interested in decoding a subset of the elements of x. For simplicity in presentation, a receiver is assumed to be only interested in decoding x. Then all other elements of x will be considered as interference for the receiver. If the receiver is interested in decoding more than one element, the same approach presented below can be used repeatedly to decode the other desired elements. 
     The system model described above covers the downlink MU-MIMO scenario where the transmitted signal contains signal for all receivers and each receiver is only interested in decoding its own signal. In many MU-MIMO systems, the transmitted signal generated from the set of signals x will be correlated due to precoding or other reasons. It is assumed that the correlation matrix R x  or some other form of correlation information is known at the receiver. Methods for conveying the correlation information from the transmitter to the receiver will be described below. 
       FIGS. 2(   a )- 2 ( b ) illustrate an example structure of a receiver UE 1 . It may be other receivers instead of UE 1 . The receiver UE 1  comprises an antenna  106 - 1 . The receiver UE 1  may comprise other numbers of antennas. The receiver UE 1  shown in  FIG. 2(   a ) illustrates the steps performed within the receiver. The first step is to receive at step  201  signal correlation information generated by the eNB by the unit  116 . The second step is to determine at step  203  a linear receiver filter for the first signal to be estimated. The third step is to de-correlate the first signal and interferences at step  205 . On the other hand, the receiver UE 1  may comprises a receiver  2011  to receive the transmitted signal sent by the transmitter, a receiver  201  to receive the correlation information, a liner receiver filter  203 , and a de-correlator  205  to de-correlate the first signal and interferences, as shown in  FIG. 2(   b ), where the receiver  201 , the linear receiver filter  203 , and a de-correlator  205  form a decoder  207 . The detailed functions of those units  2011 ,  201 ,  203 , and  205  may be implemented by a controller  500  shown in  FIG. 5 , wherein a processor  502  may be configured to perform each of the functions shown in  FIG. 2(   b ). The processor  502  may be an ASIC, a general purpose processor, a Digital Signal Processor, a combination of processors, a processor with dedicated circuitry, dedicated circuitry functioning as a processor, and a combination thereof. 
     According to the embodiments shown in  FIGS. 2(   a ) and  2 ( b ), after the de-correlation, the signal received by UE 1  is decomposed into three parts, a first estimate component of x 1 , the intended or desired signal, or the first signal for UE 1 , a second interference component to indicate the amount of interference caused by the correlation relationship among the signals x=[x 1  x 2  . . . x K ] T  after the coding process, and a third component which is a noise component to indicate the impact of the noise. The second interference component to indicate the amount of interference caused by the correlation relationship among the signals x=[x 1  x 2  . . . x K ] T  is related to the first interference component of the transmitted signal. 
     In one embodiment, the receiver  201  may receive the correlation matrix R x =E[xx H ] at step  201 . Afterwards linear receiver filters  203  may be determined at step  203 . Examples of linear receiver filters are zero forcing (ZF) and minimum mean square error (MMSE). There may be other receiver filters used at the receiver. A MMSE receiver filter for the first signal which takes into account the correlation of the transmitted signal is given by
 
 r   1×N   =[R   x ] jth row   H   H ( HR   x   H   H   +R   n ) −1   (2)
 
     Subsequently, the de-correlator  205  performs de-correlation of the first signal and interferences at step  205 . The following illustrates such an example of performing de-correlation of the first signal and interferences. 
     Suppose a receiver filter r 1×N , has been used by the receiver to decode x j . The correlation of data vector x can be used in order to enhance the signal power at receivers. Let R x  be decomposed as
 
 R   x   =G   j   G   j   H .  (4)
 
For j=1, G j  is simply a lower triangular matrix with real elements on the diagonals obtained from Cholesky decomposition of R x . For j&gt;1, the form of G, is as follows: starting with a lower triangular matrix form, switch j-th row with first row and then switch j-th column with first column. For example, for K=3, G j s will have the forms
 
                 G   1     =     [           j   1         0       0             j   2           j   3         0             j   4           j   5           j   6           ]       ,       G   2     =     [           h   1           h   2         0           0         h   3         0             h   4           h   5           h   6           ]       ,       G   3     =       [           i   1           i   2           i   3               i   4           i   5         0           0       0         i   6           ]     .             
In any of the above forms, the diagonal elements have real values.
 
From (4) and given the form of G j , it can easily be verified that
 
                       [     G   j     ]       jth   ⁢           ⁢   column       =         1         [     R   x     ]     jj         ⁡     [     R   x     ]         jth   ⁢           ⁢   column               (   5   )               
Making the following whitening transformation
 
 v=G   j   −1   x,   (6)
 
which makes v white:
 
 R   vv   =E[vv   H   ]=I   K (7)
 
Furthermore, from the form of G, it has
 
 x   j =√{square root over ([R x ] jj )}v j   (8)
 
Using the transformation (6), the processed received signal can be written as
 
                           y   ~     =       ⁢         rHG   j     ⁢   v     +     n   ~                   =       ⁢           [     rHG   j     ]       1   ⁢           ⁢   j       ⁢     v   j       +         ∑     k   ≠   j       ⁢         [     rHG   j     ]       1   ⁢   k       ⁢     v   k           ︸   interference       +     n   ~                   =       ⁢               1         [     R   x     ]     jj         ⁡     [     rHG   j     ]         1   ⁢   j       ⁢     x   j         ︸   signal       +         ∑     k   ≠   j       ⁢         [     rHG   j     ]       1   ⁢   k       ⁢     v   k           ︸   interference       +     n   ~                     (   9   )               
From (9), it can be seen that signal and interference has become uncorrelated and SINR adaptation and decoding can be done properly. In the following, Equation (9) is rewritten in term of R x . Using (5), the first signal estimate term in (9) can be written as
 
                           first   ⁢           ⁢   signal   ⁢           ⁢   estimate   ⁢           ⁢   component     =       ⁢           1         [     R   x     ]     jj         ⁡     [     rHG   j     ]         1   ⁢   j       ⁢     x   j                   =       ⁢       1         [     R   x     ]     jj         ⁢       rH   ⁡     [     G   j     ]         jth   ⁢           ⁢   column       ⁢     x   j                   =       ⁢       1       [     R   x     ]     jj       ⁢       rH   ⁡     [     R   x     ]         jth   ⁢           ⁢   column       ⁢     x   j                     (   10   )               
The first interference component is simply given by
 
                           first   ⁢           ⁢   interference   ⁢           ⁢   component     =       ⁢     rHx   -     desired   ⁢           ⁢   signal                   =       ⁢     rHx   -       1       [     R   x     ]     jj       ⁢       rH   ⁡     [     R   x     ]         jth   ⁢           ⁢   column       ⁢     x   j                       (   11   )               
For MCS adaptation, we need to calculate the signal to interference and noise ratio (SINR). The desired signal power is given by
 
                     desired   ⁢           ⁢   signal   ⁢           ⁢   power     =       1       [     R   x     ]     jj       ⁢              rH   ⁡     [     R   x     ]         jth   ⁢           ⁢   column            2               (   12   )               
The interference power is given by
 
                     interference   ⁢           ⁢   power     =         rHR   x     ⁢     H   H     ⁢     r   H       -       1       [     R   x     ]     jj       ⁢              rH   ⁡     [     R   x     ]         jth   ⁢           ⁢   column            2                 (   13   )               
Finally, the SINR of the first signal is given by
 
                   SINR   =         1       [     R   x     ]     jj       ⁢            r   ⁢           ⁢       H   ⁡     [     R   x     ]         jth   ⁢           ⁢   column              2             rHR   x     ⁢     H   H     ⁢     r   H       -       1       [     R   x     ]     jj       ⁢              rH   ⁡     [     R   x     ]         jth   ⁢           ⁢   column            2       +       rR   n     ⁢     r   H                   (   14   )               
As it can be seen from Equations (10)-(14), the desired signal, interference, and SINR are represented in terms of R x .
 
     It should be noted that the Cholesky factorization introduced in Eqn. (4) is only a tool to show how to de-correlate the first signal and interferences and it is not required to be done as part of signal processing at the receiver or the base station for either decoding or MCS adaptation. 
       FIG. 3  illustrates the function of the receivers when the correlation information is sent in a different way, e.g., in terms of the matrix D=diag(R x ) −1 . Let D=diag(R x ) −1 , i.e., 
                   [   D   ]     kk     =     1       [     R   x     ]     kk         ,         
k=1, . . . , K. At the transmitter, the dedicated reference symbols (DRS) are precoded by R x D.
 
     In  FIG. 3 , in step  201 , the receiver receives and estimates HR x D from received DRS. Then the receiver proceeds to step  203  to determine the linear receiver filter which is done in two steps. 
     In Step  2031 , the receiver calculates long-term covariance matrix of the received signal from data channel: 
                           E   ⁡     [     yy   H     ]       =       ⁢     =     E   ⁡     [       (     Hx   +   n     )     ⁢     (         x   H     ⁢     H   H       +     n   H       )       ]                     =       ⁢         HR   x     ⁢     H   H       +     R   n                     (   15   )               
Then in step  2033 , the optimal MMSE filter for the first signal at the receiver is calculated as
 
                           r   ^     =       ⁢         [       (       HR   x     ⁢   D     )     H     ]       jth   ⁢           ⁢   row       ⁢       E   ⁡     [     yy   H     ]         -   1                     =       ⁢         [       DR   x     ⁢     H   H       ]       jth   ⁢           ⁢   row       ⁢       (         HR   x     ⁢     H   H       +     R   n       )       -   1                     =       ⁢         [     DR   x     ]       jth   ⁢           ⁢   row       ⁢         H   H     ⁡     (         HR   x     ⁢     H   H       +     R   n       )         -   1                     =       ⁢           1       [     R   x     ]     jj       ⁡     [     R   x     ]         jth   ⁢           ⁢   row       ⁢         H   H     ⁡     (         HR   x     ⁢     H   H       +     R   n       )         -   1                       (   16   )               
which is the same as Eqn. (2) except for a scaling factor which does not matter.
 
     Subsequently in step  205  shown in  FIG. 4 , in order to calculate the desired first signal, the receiver multiplies its receiver filter as in Equation (16) by the j-th column of its channel estimate from receive DRS, i.e., HR x D to obtain the first signal estimate as follows: 
                           first   ⁢           ⁢   signal   ⁢           ⁢   estimate   ⁢           ⁢   component     =       ⁢           r   ^     ⁡     [       HR   x     ⁢   D     ]         jth   ⁢           ⁢   column       ⁢     x   j                   =       ⁢       1       [     R   x     ]     jj       ⁢         r   ^     ⁡     [     HR   x     ]         jth   ⁢           ⁢   column       ⁢     x   j                   =       ⁢       1       [     R   x     ]     jj       ⁢     r   ^     ⁢       H   ⁡     [     R   x     ]         jth   ⁢           ⁢   column       ⁢     x   j                     (   17   )               
which is in line with Eqn. (10).
 
     The above various processes may be collectively shown in  FIG. 4  demonstrating the operation of the UE 1  as illustrated in  FIG. 2 . In Step  201  of  FIG. 2 , there may be different forms of correlation information of the signals sent from the eNB  102  to the UE. In step  203 , linear receiver filter may be decided as shown in  FIG. 4 . The difference between the two filters shown in step  203  in  FIG. 4  is a scale factor. There may be other scale factors derived from different approaches, which do not change the substance of the process demonstrated in  FIG. 2 . Furthermore, the Step  205  in  FIG. 4  shows the result of the desired signal, the interference, and the SINR are the same for different forms of the correlation information. 
       FIG. 5  illustrates an example controller  500  according to an embodiment of the disclosure. Controller  500  may be used in conjunction with and may perform the functions of the eNB  102 , the precoder  112 , the scheduler  114 , and the transmitter  116 . In the same or alternative embodiments, controller  500  may reside at, be component of, or may be used by one or more UEs UE 1  to UEM, to perform operations in step  201 ,  203 , and  205  as shown in  FIG. 2(   a ). 
     Controller  500  may contain a processor  502  which controls the overall operation of the controller  500  by executing computer program instructions which define such operation. The computer program instructions may be stored in a storage device  504  (e.g., magnetic disk, database, etc.) and loaded into memory  506  when execution of the computer program instructions is desired. Thus, applications for performing the herein-described method steps, such as precoding, scheduling, transmitting and receiving data are defined by the computer program instructions stored in the memory  506  or storage  504  and controlled by the processor  502  executing the computer program instructions. The controller  500  may also include one or more network interfaces  508  for communicating with other devices via a network (e.g., a peer to peer network, etc.). The controller  500  also includes input/output devices  510  (e.g., display, keyboard, mouse, speakers, buttons, etc.) that enable user interaction with the controller  500 . Controller  500  and processor  502  may include one or more central processing units, read only memory (ROM) devices and/or random access memory (RAM) devices. The processor  502  may be an ASIC, a general purpose processor, a Digital Signal Processor, a combination of processors, a processor with dedicated circuitry, dedicated circuitry functioning as a processor, and a combination thereof. An implementation of an actual controller could contain other components as well, and that the controller of  FIG. 5  is a high level representation of some of the components of such a controller for illustrative purposes. 
     In alternative embodiments, hard-wired circuitry or integrated circuits may be used in place of, or in combination with, software instructions for implementation of the processes of the present invention. Thus, embodiments of the present invention are not limited to any specific combination of hardware, firmware, or software. The memory  506  may store the software for the controller  500 , which may be adapted to execute the software program and thereby operate in accordance with the present invention and particularly in accordance with the methods described in detail above. However, the invention as described herein could be implemented in many different ways using a wide range of programming techniques as well as general purpose hardware sub-systems or dedicated controllers. 
     Although the present embodiments and their advantages have been described in detail, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the embodiments as defined by the appended claims. For example, many of the features and functions discussed above can be implemented in software, hardware, or firmware, or a combination thereof. 
     Moreover, the scope of the present application is not intended to be limited to the particular embodiments of the process, machine, manufacture, composition of matter, means, methods and steps described in the specification. The disclosure of the present invention, processes, machines, manufacture, compositions of matter, means, methods, or steps, presently existing or later to be developed, that perform substantially the same function or achieve substantially the same result as the corresponding embodiments described herein may be utilized according to the present invention. Accordingly, the appended claims are intended to include within their scope such processes, machines, manufacture, compositions of matter, means, methods, or steps.