Abstract:
A receiver for a multi-carrier CDMA system receives a signal transmitted having a known pilot sequence on plural sub-carriers. The system includes plural down-converters for down-converting the received signal to baseband signals. A delay and channel estimator correlates at least one of the baseband signals with a single wideband pilot signal, the single wideband pilot signal including all of the known pilot sequences, to produce an estimate of channel gain and multi-path delay. Plural demodulators, one for each of the plural sub carriers, are operatively coupled to the delay and channel estimator, each for demodulating one of the plural baseband signals using the estimate of channel gain and multi-path delay.

Description:
BACKGROUND OF THE INVENTION 
   This invention relates to receivers for decoding signals received via multiple propagation paths having different propagation delays and, more particularly, to delay and channel estimation for multi-carrier systems. 
   Radio receivers are often used for decoding fading signals with the aid of estimates of the instantaneous propagation channel phase and amplitude characteristics. An exemplary application for such a radio receiver is a cellular phone for decoding signals transmitted by base stations using code division multiple access (CDMA) protocols. 
   A radio receiver, such as for a CDMA system, receives digitally coded and modulated signals from a transmitter. These signals include known, preselect signal patterns at known time intervals. Using known signal patterns, also referred to as pilot sequences, or pilot channel as commonly used in the CDMA literature, the receiver forms successive estimates of the delay and amplitude or complex value of propagation path characteristics between the transmitter and the receiver. These include estimates for multiple paths in the case of multi-path propagation. 
   In a typical CDMA system a signal is transmitted on a single carrier. However, this can limit data rate of transmission. More recently, a multi-carrier (MC) system is proposed in which the signal is transmitted using three sub-carriers. This effectively triples the data rate. However, the MC system requires that filtering, correlation and de-modulation be performed for each of the three sub-carriers. 
   The common approach for MC CDMA system delay and channel estimation is to use three baseband filters. The signal for the first sub-carrier is extracted using the first filter. A first correlator correlates the filtered signal using the known sequence. From this, the delay and complex gain can be determined. This process is repeated for the second and third sub-carriers. 
   In general, the signal transmitted by the k&#39;th carrier is given by
 
 u   k ( t )=[ s   k ( t )+ o   k ( t )] e   jφ     k   ,  (1)
 
where s k (t) is the known pilot signal of the k&#39;th carrier, o k (t) is the sum of all other Walsh-orthogonal channels in the same carrier and e jφ     k    is a constant phase term. Both s k (t) and o k (t) are baseband signals resulting from modulating data sequences on to streams of baseband pulse shape. The overall signal sent by the transmitter is 
               g   ⁡     (   t   )       =       ∑   k     ⁢         u   k     ⁡     (   t   )       ⁢     ⅇ     j   ⁢           ⁢   2   ⁢           ⁢     π   ⁡     (       f   0     +     f   k       )       ⁢   t                   (   2   )             
 
where f 0  is the center carrier frequency and f k  is the frequency separation of the k&#39;th carrier with respect to the center carrier frequency. The frequency spacing f k &#39;s are assumed wide enough so that there is no spectrum aliasing between sub-carriers.
 
   After propagating through a multi-path channel, the RF received signal can be expressed as 
                       r   ~     ⁡     (   t   )       =       ⁢         ∑   i     ⁢         c   ~     i     ⁢     g   ⁡     (     t   -     τ   i       )           +       n   ~     ⁡     (   t   )                       =       ⁢         ∑   i     ⁢         c   ~     i     ⁡     [       ∑   k     ⁢         u   k     ⁡     (     t   -     τ   i       )       ⁢     ⅇ     j   ⁢           ⁢   2   ⁢     π   ⁡     (       f   0     +     f   k       )       ⁢     (     t   -     τ   i       )             ]         +       n   ~     ⁡     (   t   )           ,                 (   3   )             
 
where {tilde over (c)} 1  is the complex channel gain of the multi-path, τ 1  is its delay and ñ(t) is the Additive White Gaussian Noise (AWGN) with power spectral density N 0 .
 
   SUMMARY OF THE INVENTION 
   In accordance with the invention a multi-carrier CDMA receiver identifies multi-paths and relative delays by considering the multi-carrier signal as an entire wide band signal and performs estimation using the known signals in all sub-carriers. 
   Particularly, the receiver receives a signal transmitted on plural sub-carriers and having a known pilot sequence. A plurality of down-converters down-convert the received signal to baseband signals. A delay and channel estimator correlates the baseband signals to produce an estimate of channel gain and multi-path delay. A plurality of demodulators, one for each of the plural sub-carriers, is coupled to the delay and channel estimator, each demodulating one of the baseband signals using the estimate of channel gain and multi-path delay. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
       FIG. 1  is a block diagram of a mobile terminal including a receiver according to the invention; 
       FIG. 2  is a block diagram of a prior art receiver; 
       FIG. 3  is a curve illustrating auto correlation functions for the prior art receiver and a receiver according to the invention; 
       FIG. 4  is a block diagram of a receiver according to one illustrated embodiment of the invention; 
       FIG. 5  is a block diagram of a receiver according to another illustrated embodiment of the invention; 
       FIG. 6  is a set of graphs illustrating a method of synthesizing a radio channel profile in accordance with the invention; and 
       FIG. 7  is a block diagram of a mobile communication system including a receiver according to the invention. 
   

   DETAILED DESCRIPTION OF THE INVENTION 
     FIG. 1  is a block diagram of a mobile terminal shown generally at  10 . The mobile terminal  10  includes an antenna  12 , a receiver  16 , a transmitter  18 , a speaker  20 , a processor  22 , a memory  24  a user interface  26  and a microphone  32 . The antenna  12  is configured to send and receive radio signals between the mobile terminal  10  and a wireless network (not shown). The antenna  12  is connected to a duplex filter  14  which enables the receiver  16  and the transmitter  18  to receive and broadcast (respectively) on the same antenna  12 . The receiver  16  demodulates, demultiplexes and decodes the radio signals into one or more channels Such channels include a control channel and a traffic channel for speech or data. The speech or data are delivered to the speaker  20  (or other output device, such as a modem or fax connector). 
   The receiver  16  delivers messages from the control channel to the processor  22 . The processor  22  controls and coordinates the functioning of the mobile terminal  10  responsive to messages on the control channel using programs and data stored in the memory  24 , so that the mobile terminal  10  can operate within the wireless network. The processor  22  also controls the operation of the mobile terminal  10  responsive to input from the user interface  26 . The user interface  26  includes a keypad  28  as a user-input device and a display  30  to give the user information. Other devices are frequently included in the user interface  26 , such as lights and special purpose buttons. The processor  22  controls the operations of the transmitter  18  and the receiver  16  over control lines  34  and  36 , respectively, responsive to control messages and user input. 
   The microphone  32  (or other data input device) receives speech signal input and converts the input into analog electrical signals. The analog electrical signals are delivered to the transmitter  18 . The transmitter  18  converts the analog electrical signals into digital data, encodes the data with error detection and correction information and multiplexes this data with control messages from the processor  22 . The transmitter  18  modulates this combined data stream and broadcasts the resultant radio signals to the wireless network through the duplex filter  14  and the antenna  12 . 
   The mobile terminal  10  may be used in a multi-carrier (MC), code division multiple access (CDMA) system in which the signal is transmitted using plural, such as, for example, three sub-carriers. Particularly, the receiver  16 , in conjunction with the processor  22  utilizes the multi-carrier signal as an entire wideband signal and performs channel estimation using the known pilot signals in all sub-carriers. 
   The conventional approach for multi-carrier CDMA system delay and channel estimation is solved using the single-carrier method, as discussed above.  FIG. 2  is a block diagram of such a conventional system. Equivalently, for the i&#39;th sub-carrier the RF signal received on the antenna  12  is first down-converted to baseband by multiplying it with e −j2π(f     0     +f     i     )t  using multipliers  40 -i. For simplicity hereinafter, elements common to each sub-carrier are labeled in the drawings with a suffix −i, where i=1,2 or 3, corresponding to the respective carrier, but referred to herein with the suffix omitted. The output of each multiplier  40  is filtered using a baseband filter  42  to remove the other sub-carriers. Then delay and channel estimation are performed independently on each sub-carrier using the single-carrier method with correlators  44 . The correlators  44  estimate the channel gain and multi-path delay. This information, along with the filtered signal, is applied to demodulators  46 . The demodulators  46  use the delay and channel estimates to demodulate the received signal for each sub-carrier in a conventional manner. Demodulated data is then sent to a decoder (not shown). 
   After down conversion, the resulting baseband signal for the i&#39;th sub-carrier is 
                       r   i     ⁡     (   t   )       =       ⁢         r   ~     ⁡     (   t   )       ⁢     ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢     π   ⁡     (       f   0     +     f   i       )       ⁢   t                     =       ⁢         ∑   i     ⁢         c   ~     i     ⁢     ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   0     ⁢     τ   i         ⁢     ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   i     ⁢     τ   i         ⁢       u   i     ⁡     (     t   -     τ   i       )           +                     ⁢         ∑   i     ⁢         c   ~     i     ⁢       ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   0     ⁢     τ   i         ⁡     [       ∑     k   =   i       ⁢         u   k     ⁡     (     t   -     τ   i       )       ⁢     ⅇ     j   ⁢           ⁢   2   ⁢           ⁢     π   ⁡     (       f   k     -     f   i       )       ⁢   t       ⁢     ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   k     ⁢     τ   i             ]           +       n   i     ⁡     (   t   )                       (   4   )             
 
where n i (t) is the down-converted Additive White Gaussian Noise (AWGN). Estimation of {tilde over (c)} 1  and τ 1  can be achieved by correlating the received signal r i (t) with a replica of the i&#39;th known pilot signal with a hypothesized delay τ. Since the pilot signal is a baseband signal, the correlation filters out the signals of other carriers, i.e., the second term in Eq. (4). Replacing {tilde over (c)} 1 e −j2πf     0     τ     1    with c 1  for simplification, the output of the correlation as a function of τ can then be expressed as 
                       λ   i     ⁡     (   τ   )       =       ⁢     ∫         r   i     ⁡     (   t   )       ⁢       s   i   *     ⁡     (     t   -   τ     )       ⁢     ⅇ       -   j     ⁢           ⁢     ϕ   i         ⁢     ⅆ   t                     =       ⁢     ∫       {         ∑   i     ⁢       c   i     ⁢       ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   i     ⁢     τ   i         ⁡     [         s   i     ⁡     (     t   -     τ   i       )       +       o   i     ⁡     (     t   -     τ   i       )         ]       ⁢     ⅇ     j   ⁢           ⁢     ϕ   i             +       n   i     ⁡     (   t   )         }     ⁢       s   i   *     ⁡     (     t   -   τ     )       ⁢     ⅇ       -   j     ⁢           ⁢     ϕ   i         ⁢     ⅆ   t                       =       ⁢         ∑   i     ⁢       c   i     ⁢       ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   i     ⁢     τ   i         ⁡     [         R     s   i       ⁡     (     τ   -     τ   i       )       +       R       s   i     ,     o   i         ⁡     (     τ   -     τ   i       )         ]           +       n   i     ⁡     (   τ   )           ,                 (   5   )             
 
where
 
 R   s     i   (τ)=∫ s   i ( t ) s   i *( t −τ) dt 
 
is the auto-correlation function of s i (t),
 
 R   s     i     ,o     i   (τ)=∫ o   i ( t ) s   i *( t −τ) dt 
 
is the cross-correlation between o i (t) and s i (k) and
 
 n   i (τ)=∫ n   i ( t ) s   i *( t −τ) e   −jφi   dt 
 
is the filtered noise.
 
   By varying the value of τ within the observation period, the delay profile of the channel as a function of τ can be obtained. The delays with correlation output exceeding a certain threshold are identified as possible multi-path echos. The channel gain of the echo is simply its corresponding correlation output. In particular, the correlation output of the m&#39;th echo is 
                       λ   i     ⁡     (     τ   m     )       =       ⁢         c   m     ⁢       ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   i     ⁢     τ   m         ⁡     [         R     s   i       ⁡     (   0   )       +       R       s   i     ,     o   i         ⁡     (   0   )         ]         +                     ⁢         ∑     i   ≠   m       ⁢       c   i     ⁢       ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   i     ⁢     τ   i         ⁡     [         R     s   i       ⁡     (       τ   m     -     τ   i       )       +       R       s   i     ,     o   i         ⁡     (       τ   m     -     τ   i       )         ]           +       n   i     ⁡     (     τ   m     )                     =       ⁢         c   m     ⁢     ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   i     ⁢     τ   m         ⁢     E     s   i         +       χ   i     ⁡     (     τ   m     )       +       n   i     ⁡     (     τ   m     )                       (   6   )             
 
where E s     i   =R s     i   (0)=∫|s i (t)| 2  dt is the energy of the pilot signal and 
                 χ   i     ⁡     (     τ   m     )       =       ∑     i   ≠   m       ⁢       c   i     ⁢       ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   i     ⁢     τ   i         ⁡     [         R     s   i       ⁡     (       τ   m     -     τ   i       )       +       R       s   i     ,     o   i         ⁡     (       τ   m     -     τ   i       )         ]                   (   7   )             
 
is the interference from other multi-paths. The cross-correlation term R s     i     ,o     i    (0) is removed due to the orthogonality between users in the same sub-carrier. In a typical CDMA system, the multi-path interference can be approximated by AWGN. Therefore, the performance of the channel estimation depends on the Signal to Noise Ratio (SNR) between the pilot signal and the sum of the multi-path interference and AWGN. The performance of the delay estimation, on the other hand, depends on the main lobe of the auto-correlation R s     i   (τ) of the pilot signal. The auto-correlation function with narrower main lobe has higher time resolution and therefore better performance in delay estimation.
 
   If the interference and noise terms in Eq. (6) are small,
 
λ i (τ m )/Ε s     i     ≈c   m   e   −j2πf     i     τ     m   ,  (8)
 
which gives the channel estimate of the m&#39;th path in the i&#39;th carrier. The effect of fading can then be reversed by multiplying the received signal with the complex conjugate of Eq. (8) and the coherent demodulation of the information bits in o i (t) can be achieved.
 
   The first step of the system according to the present invention may be to down-convert the received signal in Eq. (3) to baseband (with respect to f 0 ) by multiplying it with e −j2πf     0     τ . The resulting baseband signal is 
                     r   ⁡     (   t   )       =         r   ~     ⁡     (   t   )       ⁢     ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   0     ⁢   t                     =         ∑   i     ⁢       c   i     ⁡     [       ∑   k     ⁢         u   k     ⁡     (     t   -     τ   i       )       ⁢     ⅇ     j   ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢       f   k     ⁡     (     t   -     τ   i       )               ]         +     n   ⁡     (   t   )                       (   9   )             
 
From Eq. (9) it is clear that to fully utilize the entire wideband signal, the known signal to correlate the receive signal τ(t) with should be 
               ∑   k     ⁢         s   k   *     ⁡     (     t   -   τ     )       ⁢     ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢       f   k     ⁡     (     t   -   τ     )           ⁢       ⅇ       -   j     ⁢           ⁢     ϕ   k         .               (   10   )             
 
Thus, the correlation output as a function of τ is 
                     λ   ⁡     (   τ   )       =     ∫         r   ⁡     (   t   )       ⁡     [       ∑   k     ⁢         s   k   *     ⁡     (     t   -   τ     )       ⁢     ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢       f   k     ⁡     (     t   -   τ     )           ⁢     ⅇ       -   j     ⁢           ⁢     ϕ   k             ]       ⁢     ⅆ   t                     =       ∑   k     ⁢       ⅇ     j   ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   k         ⁢     ∫       [       r   ⁡     (   t   )       ⁢     ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   k     ⁢   t       ⁢       s   k   *     ⁡     (     t   -   τ     )       ⁢     ⅇ       -   j     ⁢           ⁢     ϕ   k           ]     ⁢     ⅆ   t                         =       ∑   k     ⁢       ⅇ     j   ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   k     ⁢   τ       ⁢     ∫         r   k     ⁡     (   t   )       ⁢       s   k   *     ⁡     (     t   -   τ     )       ⁢     ⅇ       -   j     ⁢           ⁢     ϕ   k         ⁢     ⅆ   t                         =       ∑   k     ⁢       ⅇ     j   ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   k     ⁢   τ       ⁢         λ   k     ⁡     (   τ   )       .                       (   11   )             
 
   Substituting Eq. (5) in Eq. (11) gives 
                     λ   ⁡     (   τ   )       =       ⁢       ∑   k     ⁢       ⅇ     j   ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   k     ⁢   τ       ⁢     {       ∑   l     ⁢       c   l     ⁢       ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   k     ⁢     r   t         [         R     s   k       ⁡     (     τ   -     τ   l       )       +                                     ⁢       R       s   k     ,     o   k         ⁡     (     τ   -     τ   l       )       ]     +       n   k     ⁡     (   τ   )         }               =       ⁢         ∑   l     ⁢       c   l     ⁢       ∑   k     ⁢     {       ⅇ     j   ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢       f   k     ⁡     (     τ   -     τ   l       )           ⁡     [         R     s   k       ⁡     (     τ   -     τ   l       )       +       R       s   k     ,     o   k         ⁡     (     τ   -     τ   l       )         ]       }           +                     ⁢       ∑   k     ⁢       ⅇ     j   ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   k     ⁢   τ       ⁢         n   k     ⁡     (   τ   )       .                       (   12   )             
 
   Comparing Eq. (12) with its single carrier counterpart in Eq. (5), it can be noted that the auto-correlation function dictating the estimation performance is now 
                 R   s     ⁡     (   τ   )       =       ∑   k     ⁢       ⅇ     j   ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   k     ⁢   τ       ⁢         R     s   k       ⁡     (   τ   )       .                 (   13   )             
 
Similarly, the correlation output of the m&#39;th echo is 
               λ   ⁡     (     τ   m     )       =         c   m     ⁢       ∑   k     ⁢     E     s   k           +       ∑   k     ⁢         ⅇ     j   ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   k     ⁢     τ   m         ⁡     [         χ   k     ⁡     (     τ   m     )       +       n   k     ⁡     (     τ   m     )         ]       .                 (   14   )             
 
   It is clear from Eq. (14) that if there are K sub-carriers in the system and all sub-carriers have the same power, the disclosed approach has a 10 log(K) dB SNR gain over the conventional approach discussed above relative to FIG.  2 . Furthermore, the accuracy of the delay estimation depends on the new composite auto-correlation function given in Eq. (13), which has a main lobe that is 1/K of that of a single carrier since the composite pilot signal has K times the bandwidth of the single carrier (A W. Rihaczek, “Principles of High-Resolution Radar,” Artech House Radar Library, 1996). 
   As an example, consider the pilot signal 
                   s   i     ⁡     (   t   )       =       ∑   n     ⁢       q   n     (   i   )       ⁢     p   ⁡     (     t   -     n   ⁢           ⁢     T   c         )             ,           (   15   )             
 
where q n   (i)  is a random sequence of QPSK (quadrature phase-shift keying) symbols, p(t) is a band-limited pulse-shaping signal generally referred to as a chip, and T c  is the chip interval. The pilot channels in the MC mode of IS-2000(TIA/EIA/IS-2000.2[Ballot Version], “Physical Layer Standard for cdma2000 Spread Spectrum Systems,” 1989) can be effectively modeled by Eq. (15) with 1/T c =1.2288 MHz and an approximate Nyquist pulse shaping function. There are a total of three sub-carriers separated by 1.25 MHz in the system.  FIG. 3  shows the real part of the auto-correlation for one of the single carrier pilot signals (1×) and that of the multi-carrier composite pilot signal (3×). A section of 128 chip duration is extracted randomly as the pilot signal and the SNR defined as the ratio of the energy per chip per carrier over N 0  is set to −7 dB. The resolution improvement in delay estimate is apparent from the narrower peak width of the 3× function which is centered at zero delay, and SNR improvement for channel estimate is evident from the higher peak of the 3× function.
 
   It is clear from Eq. (11), which is repeated here without the intermediate derivation steps, 
                 λ   ⁡     (   τ   )       =       ∑   k     ⁢       ⅇ     j   ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   k     ⁢   τ       ⁢       λ   k     ⁡     (   τ   )             ,           (   16   )             
 
that the correlation output according to the present invention can be obtained from the individual correlation outputs of the conventional approach of FIG.  2 . In other words, a channel profile with higher resolution and stronger SNR can be synthesized from several of those with lower resolution and weaker SNR using Eq. (16).
 
   The channel estimate derived from Eq. (16) at the delay τ m  is c m . For the coherent demodulation of the i&#39;th carrier, this coefficient needs to be rotated by a factor of e −j2πf   τ     m   . In cases where the coherent bandwidth of the fading channel is of the order of the bandwidth of a single carrier, the high resolution correlation output λ(r) will likely see more than one path in a chip period while the individual correlation output λ i (r) will see only a blurred image of one single path resulting from the superposition of several closely separated paths. The channel coefficients as observed by each individual sub-carrier will therefore differ not only in phase, but also in amplitude. However, they can still be derived from Eq. (16) with appropriate interpolation if needed. 
   In cases where the coherent bandwidth of the channel is so small that the interpolation of the higher-resolution channel profile into the lower-resolution channel profiles does not improve the performance of the individual subcarriers or does not justify the computational complexity, a switch function can be implemented in the processor to decide whether to use the conventional approach or the disclosed approach based on the measurement of the channel&#39;s coherent bandwidth. 
   The disclosed approach according to the present invention identifies all of the pilot (known) signals in the sub-carriers as a single wideband pilot signal and correlates it against the entire multi-carrier received signal. The resulting correlation output outlines the profile of the multi-path channel with higher temporal resolution and stronger SNR. 
   There may be several embodiments of the system according to the present invention. A receiver architecture implementing the above general description is shown in block diagram form in FIG.  4 . Where elements are similar to those shown in  FIG. 2 , like reference numerals are used. Initially, the received signal is converted to baseband with multipliers  40  and filtered using filters  42 , as with the conventional approach of FIG.  2 . The difference from the conventional approach is summarized in the following: 
   The RF signal is down-converted to baseband with respect to the center carrier frequency f 0  by multiplying the received signal with e j2πf     0     t  using a composite multiplier  50 :
 
 r ( t )={tilde over (r)}( t ) e   −j2πf     0     t .  (17)
 
The composite baseband signal is filtered with a filter  51  that passes all of the sub-carriers. Channel estimation and delay are determined by a correlator  52 . The correlator  52  correlates the down-converted wideband signal with s*(t)=Σ i s i *(t)e −j2πf     i     t e −jφ     i    as follows:
 
λ(τ)=∫ r ( t ) s *( t −τ) dt   (18)
 
From λ(r), a multi-path can be identified and its relative delay {tilde over (r)} m  estimated using a conventional technique such as threshold comparison. The channel coefficient estimate of this path is simply 
                 c   ^     m     =       λ   ⁡     (       τ   ^     m     )           ∑   k     ⁢     E     s   k                   (   19   )             
 
   Finally, ĉ m  is rotated by e −j2πf   {circumflex over (τ)}   m  to give the channel estimate for the i&#39;th carrier at delay τ m . The channel delay and estimates, along with the sub-carrier baseband signals from the filters  42 , are then supplied to the demodulators  46 , as with the conventional approach. 
   Eq. (16) suggests an alternative embodiment of a receiver architecture illustrated in FIG.  5 . It differs from the first embodiment of  FIG. 4 , only in the calculation of λ(τ). 
   As with the conventional approach, the alternative embodiment down-converts the RF signal of each individual sub-carrier to baseband with respect to its own center frequency by multiplying the received signal with e −j2π(f     0     +f     i)     t  above using multipliers  40 , as follows:
 
 r   i ( t )= {tilde over (r)} ( t ) e   −j2π(f     0     +f     i)     t .  (20)
 
The signals are then filtered with filters  42  to provide the sub-carrier baseband signals. For the i&#39;th sub-carrier, a correlator  44  correlates the down-converted signal with s i *(t)e −jφ     i   :
 
 λ i (τ)=∫ r   i ( t ) s   i *( t −τ) e   −jφ     i     dt.   (21)
 
In accordance with the present invention, the high resolution channel profile λ(τ) is synthesized by combining the individual correlation outputs. This is done by rotating the individual correlator outputs using multipliers  54 . The signals are then summed and derotated at a block  56 . This combination is expressed as 
               λ   ⁡     (   τ   )       =       ∑   i     ⁢       ⅇ     j   ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   i     ⁢   τ       ⁢         λ   i     ⁡     (   τ   )       .                 (   22   )             
 
From λ(τ), a multi-path can be identified and its relative delay {circumflex over (τ)} m  estimated using a conventional technique such as threshold comparison. The channel coefficient estimate of this path is simply 
                 c   ^     m     =         λ   ⁡     (       τ   ^     m     )           ∑   k     ⁢     E     s   k           .             (   23   )             
 
Finally, ĉ m  is derotated by e −j2πf     i     {circumflex over (τ)}   m  in the block  56  to give the channel estimate for the i&#39;th carrier at delay τ m .
 
   As is conventional, the filter  42  is implemented in hardware in the receiver  16 , see FIG.  1 . The equations described herein, and represented by blocks in the block diagrams of  FIGS. 4 and 5  are implemented in software by the processor  22 . However, the invention is not limited to such a division of functionality. As such, where the term receiver is used herein, the term encompasses functions implemented in hardware in the receiver block  16  and in software in the processor block  22 . 
   The embodiment of  FIG. 4  uses all of the known signals in the subcarriers as a single wideband reference signal and correlates this reference signal against the entire multi-carrier received signal. The resulting correlation output yields the underlying channel profile with stronger SNR and higher temporal resolution. Furthermore, this higher resolution channel profile can be synthesized by combining the individual lower resolution profiles of the sub-carriers using equation (11). 
   While equation (11) is expressed in continuous time, the correlations are performed on discrete samples in practice. Therefore, if the individual correlation output λ k (τ) is sampled every τ s  seconds, then a straightforward method for synthesizing and sampling λ(τ) is 
                 λ   k     ⁡     (     n   ⁢           ⁢     τ   s       )       =       ∑   k     ⁢       ⅇ     j   ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢     f   k     ⁢   n   ⁢           ⁢     τ   s         ⁢       λ   k     ⁡     (     n   ⁢           ⁢     τ   s       )                   (   24   )             
 
which has the same sampling rate as the individual sampled correlation output λ(nτ s ).
 
   In accordance with another aspect of the invention a receiver solves the problem of sampling and synthesizing the composite correlation output, or λ(τ) as expressed in mathematical term described above, required for improving channel estimation in a multi-carrier system. As will be described, the receiver can synthesize λ(τ) at any desired sampling rate if the sampling rate of the individual correlation outputs meets the Nyquist criterion. 
   Although very simple, equation (24) is not an optimal way of combining several time sequences from different frequency bands. In the frequency domain, the Fourier transform of λ(τ), denoted by Λ(f), is simply 
                   Λ   ⁡     (   f   )       =   Δ     ⁢     ∫       λ   ⁡     (   τ   )       ⁢     ⅇ       -   j     ⁢           ⁢   2   ⁢           ⁢   π   ⁢           ⁢   f   ⁢           ⁢   τ       ⁢     ⅆ   τ           =       ∑   k     ⁢       Λ   k     ⁡     (     f   -     f   k       )                 (   25   )             
 
where Λ k (f) is the Fourier transform of λ k (τ) centered at zero frequency. When sampled at or above the Nyquist rate (twice the bandwidth of Λ k (f)), λ k (nτ s ) contains sufficient information to reconstruct the continuous time signal λ k (t), and thus also its frequency-offset version e j2πf     kτ   λ k (τ). Therefore, the composite correlation output λ(τ) can be reconstructed fully and sampled at any desired rate if λ k (τ) is sampled at or above Nyquist rate for all sub-carriers.
 
   Furthermore, in order to reduce computational complexity, λ k (τ) is usually sampled at the Nyquist rate. Thus, equation (24) will not meet the Nyquist criterion since λ(τ) has K times the bandwidth of the individual spectrum for a system with K sub-carriers. To satisfy the Nyquist criterion, λ(τ) must be sampled at or above the rate of 
         K     τ   s       .       
 
The following explains how to synthesize λ(τ) at the desired sampling rate using Discrete Fourier Transform (DFT) from λ k (τ)&#39;s, which are sampled at or above the Nyquist rate. The sampling may be done, for example, at two samples per chip or greater.
 
   This aspect of the invention is explained by an example as shown in FIG.  6 . This example relates to the receiver architecture of FIG.  5 . Let
 
λ k   [n]=λ   k ( nτ   s ), for  n =0, 1 , . . . , N −1  (26)
 
denote the discrete samples over a period of Nτ s  of the individual correlation output sampled at the rate of 1/τ s  Hz, which is assumed to meet the Nyquist criterion. Graphs  60 ,  62  and  64  represent the individual correlation outputs for respective first, second and third sub-carriers in a three carrier system. The composite correlation output λ(τ) sampled at the rate of 
       L     N   ⁢           ⁢     τ   s           
 
Hz can be obtained for the same observation period by the following procedure:
         1. For each sub-carrier k=0, 1, . . . , K−1, compute the DFT of length N, denoted by F N {·}, for λ k [n]: 
                   Λ   k     ⁡     [   m   ]       ⁢     Δ     _   _       ⁢           ⁢     F   N     ⁢     {       λ   k     ⁡     [   n   ]       }       =       ∑     n   =   0       N   -   1       ⁢           ⁢         λ   k     ⁡     [   n   ]       ⁢     ⅇ     -       j2π   ⁢           ⁢   mn     N                     (   27   )             
   over the frequency range of m=−N/2, −N/2+1, . . . 0, 1, N/2−1. The results are represented by graphs  66 ,  68  and  70 .   2. Compute m k , the carrier frequency offset f k  in discrete domain, for each sub-carrier:
 
m k =f k Nτ s .  (28)
   3. Form the discrete Fourier transform of λ(τ) by summing all the individual DFT spectra, shown in graphs  66 ,  68  and  70 , shifted by the appropriate frequency offset: 
               Λ   ⁡     [   m   ]       =       ∑     k   =   0       K   -   1       ⁢           ⁢       Λ   k     ⁡     [     m   -     m   k       ]                 (   29   )             
 
for m=−L/2, −L/2+1, . . . , 0, 1, . . . , L/2−1. Zeroes are added if necessary to give a total of L samples. The resultant transform is represented by the graph  72 .
   4. Calculate the inverse DFT of length L for Λ[m]: 
                 λ   ⁡     [   n   ]       ⁢     Δ     _   _       ⁢     F   L     -   1       ⁢     {     Λ   ⁡     [   m   ]       }       =       ∑     m   =       -   L     /   2           L   /   2     -   1       ⁢           ⁢       Λ   ⁡     [   m   ]       ⁢       ⅇ       j2π   ⁢           ⁢   mn     L       .                 (   30   )             
   The resulting time domain sequence λ[n], represented by the graph  74 , is the composite correlation output sampled at the desired rate.       

   As is apparent, the resulting time domain sequence has a higher resolution profile illustrated by the graph  74  having two peaks at substantially higher correlation amounts compared to the individual correlation output curves  60 ,  62  and  64 . 
   The receiver embodiments discussed above relate to the mobile terminal  10 . As is  15  apparent similar receiver embodiments could be used in a receiver  76  of a base station  78 , as shown in FIG.  7 . The base station  78  communicates with the mobile terminal  10  via a mobile communication network, represented at  80 . The receiver  76  would be used in applications where the mobile terminal  10  transmits a multi-carrier signal.