Abstract:
In an orthogonal frequency division multiplexing system using a scattered pilot signal, after equalization and Fourier transformation of the received signal, the pilot signals are extracted and further processed to generate likelihood values. In one process, the transformed signal is multiplied by the reciprocal of a variance. In another process, the transformed signal is multiplied by the reciprocal of a mean amplitude and by a weighted signal-to-interference ratio. These processes enable appropriate likelihoods to be obtained despite fast fading, shadowing, and automatic gain control.

Description:
BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention relates to the demodulation of an orthogonal frequency division multiplexing (OFDM) signal, more particularly to a likelihood corrector and a likelihood correction method. 
     2. Description of the Related Art 
     Terrestrial integrated services digital broadcasting (ISDB-T) is one use of the OFDM digital modulation system, which effectively combats multi-path fading. The ISDB-T OFDM modulated signal (referred to as an OFDM signal below) has a scattered pilot, that is, pilot symbols are scattered through the signal in the frequency and time directions to provide reference amplitude and phase information for demodulation. 
     Correct demodulation of an OFDM signal requires correct channel estimation and estimation of the frequency offset between the transmitter and receiver. Maximum likelihood estimation can be used for these purposes. Japanese Patent Application Publication No. 8-293850 describes a method that compares likelihoods generated by two likelihood estimators, and updates the receiver&#39;s frequency according to the result, but fails to give details of the likelihood estimation process, saying only that the likelihood estimators employ a method used in decoding a convolutional code. This implies a continuous process rather than a process using scattered pilot signals, which are not mentioned in the disclosure. 
     When the channel and frequency offset estimates are derived from a scattered pilot signal, it is necessary to allow for the effect of the scattering of pilot signal information, but there is no teaching or suggestion in the above disclosure of how this might be done. 
     SUMMARY OF THE INVENTION 
     An object of the present invention is to provide a likelihood corrector and a likelihood correcting method that can correct likelihoods of a signal with a data structure having pilot symbols scattered among the data symbols. 
     A likelihood corrector according to one embodiment of the invention has a pilot symbol extractor for extracting pilot symbols included in an OFDM signal and operating on them to produce complex-valued results; a variance calculator for determining the variance of the complex-valued results; a reciprocal calculator for determining the reciprocal of the variance; and a multiplier for multiplying the OFDM signal by the reciprocal value. 
     A likelihood corrector according to another embodiment of the invention has a pilot symbol extractor for extracting pilot symbols included in an OFDM signal and operating on them to produce complex-valued results; a mean calculator for determining the mean amplitude of the complex-valued results; a reciprocal calculator for determining the reciprocal of the mean amplitude; a signal-to-interference ratio estimator for estimating a signal-to-interference ratio from the complex-valued results; a quantizing circuit for quantizing the estimated signal-to-interference ratio; a weighting circuit for weighting the quantized signal-to-interference ratio; and a multiplier for multiplying the OFDM signal by the reciprocal of the mean amplitude and the weighted signal-to-interference ratio. 
     The invention also provides corresponding likelihood correction methods. 
     The above apparatus and methods enable appropriately corrected likelihoods to be generated from a signal with a data structure having pilot symbols scattered among the data symbols. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       In the attached drawings: 
         FIG. 1  is a graph showing an arrangement of pilot symbols and data symbols; 
         FIG. 2  is a block diagram showing a likelihood corrector in a first embodiment of the invention; 
         FIG. 3  is a more detailed block diagram showing the internal structure of the variance calculator in  FIG. 2 ; 
         FIG. 4  is a block diagram showing a likelihood corrector in a second embodiment of the invention; 
         FIG. 5  is a more detailed block diagram showing the internal structure of the signal-to-interference ratio estimator in  FIG. 4 ; and 
         FIG. 6  is a more detailed block diagram showing the internal structure of the thresholding circuit and weighting circuit in  FIG. 4 . 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     Embodiments of the invention will now be described with reference to the attached drawings, in which like elements are indicated by like reference characters. 
     The embodiments are intended for use with an OFDM signal having a scattered pilot frame structure with pilot symbols scattered among the data symbols as shown in  FIG. 1 . The black circles in  FIG. 1  indicate pilot symbols; the white circles indicate data symbols. In this example, the same pattern of pilot symbols repeats at temporal intervals of four OFDM symbols, but the invention is not limited to this repeating period. 
     FIRST EMBODIMENT 
     Referring to  FIG. 2 , the likelihood corrector in the first embodiment of the invention comprises a pilot symbol extractor  200 , a variance calculator  201 , a reciprocal calculator  202 , and a multiplier  203 . The OFDM signal input from the left in this drawing is output from an equalizer (not shown) and has already been Fourier-transformed. 
     The pilot symbol extractor  200  receives the OFDM signal, extracts the pilot symbols included in the OFDM signal one at a time, performs the complex-valued operation given by the expression shown below on the extracted pilot symbols and their a-priori known values (referred to below as the known pilot symbols), and outputs the result as a vector (complex number) describing the phase rotation and amplitude attenuation effects of the transmission channel. 
                 (       SP_r   ⁢   _i     +     j   ×   SP_r   ⁢   _q       )     ×     (       SP_ref   ⁢   _i     -     j   ×   SP_ref   ⁢   _q       )           SP_ref   ⁢     _i   2       +     SP_ref   ⁢     _q   2               
The symbol ‘j’ in this expression represents a square root of minus one. The known pilot symbol SP_ref and the received pilot symbol SP_r are defined as follows, each having an in-phase component identified by a terminal ‘i’ and a quadrature component identified by a terminal ‘q’.
   SP _ref= SP _ref —   i+j×SP _ref —   q      SP   —   r=SP   —   r   —   i+j×SP   —   r   —   q    
     Accordingly, the pilot symbol extractor  200  multiplies the complex value of each received pilot signal by the complex conjugate of its known value, and divides the product by the product of the known value and its complex conjugate, which is equal to the sum of the square of the in-phase component of the known value and the square of the quadrature component of the known value. The result of this operation is a complex-valued result that estimates the phase delay and attenuation introduced by the channel at the frequency of a particular pilot symbol. Since the pilot signals have already undergone a Fourier transformation, the values output by the pilot signal extractor  200  will also be referred to as power values. 
     The variance calculator  201  finds the variance of the complex-valued results by taking the difference between their mean square and the square of their mean. Referring to  FIG. 3 , the variance calculator  201  comprises mean calculators  300 ,  303 , squaring circuits  301 ,  302 , and a subtractor  304 . The first mean calculator  300  determines the mean power of the complex-valued results received from the pilot symbol extractor  200 . More specifically, the cumulative power or sum of the complex-valued results is taken, and the resulting value is divided by the number of complex-valued results input. The first squaring circuit  301  squares the output of the mean calculator  300 . The second squaring circuit  302  squares the complex-valued results. The second mean calculator  303  takes the mean of the outputs of the squaring circuit  302 . Accordingly, the complex-valued results are squared, the sum of the squared values is taken, and the sum is divided by the number of complex-valued result values input. The subtractor  304  subtracts the output value of the squaring circuit  301  from the output value from the mean calculator  303 , thereby determining the variance. 
     The reciprocal calculator  202  takes the reciprocal of the variance output by the variance calculator  201 . The multiplier  203  takes the product of the OFDM signal and the output of the reciprocal calculator  202 , thereby generating a likelihood signal. 
     The likelihood corrector and likelihood correcting method in the first embodiment can estimate the variance of noise etc. included in the received signal even if the received signal amplitude is adjusted by automatic gain control (AGC) in the receiver unit due to fading or shadowing. By adjusting the received signal according to the reciprocal of the variance, it is possible to modify the received signal to a signal that generates likelihoods according to the noise power ratio etc. without being affected by the received signal amplitude. Therefore, the likelihood corrector and likelihood correcting method in the first embodiment make it possible to generate likelihoods in which the effects of fast fading and shadowing are reduced. In addition, the more appropriate likelihoods provided by the likelihood corrector and likelihood correcting method of the first embodiment can enhance the error correcting effect of Viterbi decoding, which is used in ISDB-T receivers because the received signal is convolutionally encoded. 
     SECOND EMBODIMENT 
     Referring to  FIG. 4 , the likelihood corrector in the second embodiment of the invention comprises a pilot symbol extractor  400 , a mean calculator  401 , a reciprocal calculator  402 , a signal-to-interference ratio (SIR) estimator  403 , a thresholding circuit  404  used as a quantizer, a weighting circuit  405 , and a multiplier  406 . The OFDM signal input from the left in this drawing is output from an equalizer (not shown) and has been Fourier-transformed as in the first embodiment. The pilot symbol extractor  400  is similar to the pilot symbol extractor  200  in the first embodiment, but outputs complex-valued results for ten pilot symbols at a time. 
     The mean calculator  401  determines the mean amplitude of the complex-valued results output from the pilot symbol extractor  400  by taking the sum of their complex values and dividing the sum by the number of complex values summed; that is, by the number of pilot signals extracted by the pilot symbol extractor  400 . The reciprocal calculator  402  takes the reciprocal of the mean amplitude. 
     The SIR estimator  403  estimates a signal-to-interference ratio (SIR) by taking a difference between the mean square of the complex-valued results output from the pilot symbol extractor  400  and the square of the mean of these complex-valued results and dividing the difference by the mean square of the complex-valued results. Referring to  FIG. 5 , the SIR estimator  403  comprises mean calculators  500 ,  503 , squaring circuits  501 ,  502 , a subtractor  504 , and a divider  505 . The first mean calculator  500  determines the mean power of the complex-valued results received from the pilot symbol extractor  400 . More specifically, the cumulative power or sum of the complex-valued results is taken, and the sum is divided by the number of complex-valued results received from the pilot symbol extractor  400 . The first squaring circuit  501  squares the mean value output from the first mean calculator  500 . The second squaring circuit  502  squares the complex-valued results received from the pilot symbol extractor  400 . The second mean calculator  503  takes the mean of the squares output from the second squaring circuit  502 . More specifically, the complex-valued results are squared, the sum of the squared values is taken, and the sum is divided by the number of complex-valued results received. The subtractor  504  subtracts the output value of the squaring circuit  501  from the output value from the mean calculator  503 , thereby determining the variance. The divider  505  divides the variance determined by the subtractor  504  by the mean square value output by the second mean calculator  503 , thereby estimating the SIR. 
     The thresholding circuit  404  quantizes the estimated SIR. The weighting circuit  405  assigns a weight to the estimated SIR. The thresholding circuit  404  and the weighting circuit  405  will now be described with reference to  FIG. 6 . 
     The thresholding circuit  404  comprises a plurality of comparators  600 ,  601 , . . . ,  60 m, where m is a positive integer. The comparators receive the estimated SIR and respective threshold values Th 1 , Th 2 , . . . , Thm as inputs, and compare the estimated SIR with the input threshold value. The output of the comparison operation is ‘1’ if the estimated SIR is larger than the input threshold value, and ‘0’ otherwise. For example, when m is 3, the estimated SIR is 2.5, and threshold values Th 1 , Th 2 , and Th 3  are 3, 2, and 1, the comparators  600 ,  601 , and  603  output ‘0’, ‘1’, and ‘1’, respectively. Alternatively, the output of the comparison operation is ‘0’ if the estimated SIR is larger than the input threshold value, and ‘1’ otherwise. The threshold values are not necessarily limited to integers. 
     The weighting circuit  405  comprises a plurality of switches  610 ,  611 , . . . ,  61 n, and an adder  620 , where n is a positive integer equal to m. The switches receive the outputs of respective comparators, a predetermined value (‘0’ in this case), and respective weighting coefficients W 1 , W 2 , . . . , Wn as inputs, and output either the weighting coefficient or the predetermined value responsive to the output received from the corresponding comparator. For example, when the output of comparator  600  is ‘1’, switch  610  outputs weighting coefficient W 1  (e.g., ‘19’); when the output of comparator  600  is ‘0’, switch  610  outputs ‘0’. Alternatively, switch  610  may output weighting coefficient W 1  when the output of comparator  600  is ‘0’ and output ‘0’ when the output of comparator  600  is ‘1’. The weighting coefficients are not necessarily limited to integers. The adder  620  takes the sum of the outputs of the switches  610 ,  611 , . . . ,  61 n, and outputs the sum as a weight W. 
     The multiplier  406  takes the product of the OFDM signal, the reciprocal of the mean amplitude output by the reciprocal calculator, and the weight W output by the weighting circuit, thereby generating a likelihood signal. 
     The likelihood corrector and likelihood correcting method in the second embodiment estimate the noise etc. included in the received signal by estimating the signal-to-interference ratio even if the received signal amplitude is adjusted by automatic gain control (AGC) in the receiver unit due to fading or shadowing. By adjusting the received signal according to the SIR estimation result and the reciprocal of the amplitude of the received signal, it is possible to modify the received signal to a signal that generates likelihoods according to the noise power ratio etc. without being affected by the received signal amplitude. Therefore, the likelihood corrector and likelihood correcting method in the second embodiment make it possible to generate appropriate likelihoods in the presence of fast fading and shadowing. In addition, the more appropriate likelihoods provided by the likelihood corrector and likelihood correcting method of the second embodiment can enhance the error correcting effect of Viterbi decoding. 
     In general, the optimal likelihood is not always proportional to the SIR; in a shadowing environment, for example, receiving characteristics may be improved by decreasing the likelihood for ambiguous information and increasing the likelihood for more definite information. The likelihood corrector and the likelihood correcting method of the second embodiment provide a weighting circuit and a weighting method that enable a non-linear likelihood correction in which the ambiguity and definiteness are converted to optimal values which are reflected as an optimal likelihood value, which results in better receiving characteristics in the presence of shadowing etc. 
     The invention is not limited to the preceding embodiments, and its applications are not limited to the reception of ISDB-T signals. A person understanding the foregoing discussion of reciprocal variance, reciprocal amplitude, and weighted SIR quantization will recognize that further variations are possible within the scope of the invention, which is defined in the appended claims.