Abstract:
Methods and apparatus are provided for non-linear scaling of log likelihood ratio (LLR) values in a decoder. A decoder according to the present invention processes a received signal by generating a plurality of log-likelihood ratios having a first resolution; applying a non-linear function to the plurality of log-likelihood ratios to generate a plurality of log-likelihood ratios having a lower resolution; and applying the plurality of log-likelihood ratios having a lower resolution to a decoder. The non-linear function can distribute the log-likelihood ratios, for example, such that the frequency of each LLR value is more uniform than a linear scaling.

Description:
FIELD OF THE INVENTION 
   The present invention relates generally to decoding techniques for turbo codes, and more particularly, to methods and apparatus for scaling values in a turbo decoder. 
   BACKGROUND OF THE INVENTION 
   Error correction techniques are used in a number of communication and storage systems. Error correction codes, such as Reed-Solomon codes, add one or more redundant bits to a digital stream prior to transmission or storage, so that a decoder can detect and possibly correct errors caused by noise or other interference. One class of error correction codes are referred to as “turbo” codes. Generally, turbo codes employ a combination of two or more systematic convolutional or block codes. Typically, an iterative decoding technique is employed where the output of each decoding step, for example, from an inner receiver, serves as an input to the subsequent decoding step performed by an outer receiver. In many implementations, the inner receiver generates log-likelihood ratios (LLRs) that are processed by the outer receiver. 
   In a CDMA receiver, for example, an inner receiver typically demodulates the received signal into symbols and the outer receiver forms, processes and decodes each frame, comprised of a collection of symbols. The output signal of the inner receiver is often quantized to a smaller number of bits and then processed by a soft input/soft output decoder. U.S. patent application Ser. No. 10/387,876, entitled “Method and Apparatus for Decoder Input Scaling Based on Interference Estimation in CDMA,” for example, discloses a technique for scaling the decoder input for a CDMA receiver to a smaller number of bits to reduce the memory requirement. In order to maintain the decoder performance for a smaller number of input bits, the disclosed method estimates the interference of the inner receiver output and scales the decoder input such that its variance is maintained. 
   A number of techniques have been proposed or suggested for adjusting various parameters of a turbo decoder to improve the throughput or Bit Error Rate (BER) performance. Y. Wu and B. Woerner, “The Influence of Quantization and Fixed Point Arithmetic Upon the BER Performance of Turbo Codes,” Proc. IEEE Veh. Tech. Conf., Houston, Tex. (May, 1999), for example, evaluates the influence of quantization and fixed point arithmetic upon the BER performance of turbo decoders. Wu and Woerner demonstrate that with proper scaling of the received signal prior to quantization, there is no degradation of the BER performance with eight bit quantization (or even four bit quantization). 
   Generally, the inner receiver in such conventional turbo decoding techniques generates floating point LLRs (soft bits) that are scaled in a linear manner, and then mapped to a fixed point. Most known techniques for scaling decoder inputs have used a gain control method. For example, the mean square or mean absolute values of the inner receiver output have been employed. The technique disclosed in the above-referenced U.S. patent application Ser. No. 10/387,876 employ a noise variance of the channel in order to scale the decoder input. A need exists for methods and apparatus for scaling or shaping the LLR distribution in a manner that improves the BER performance. A further need exists for methods and apparatus for scaling or shaping the LLR distribution in a non-linear manner. 
   SUMMARY OF THE INVENTION 
   Generally, methods and apparatus are provided for non-linear scaling of log likelihood ratio (LLR) values in a decoder, such as a universal mobile telecom system (UMTS) receiver. According to one aspect of the invention, a decoder processes a received signal by generating a plurality of log-likelihood ratios having a first resolution; applying a non-linear function to the plurality of log-likelihood ratios to generate a plurality of log-likelihood ratios having a lower resolution; and applying the plurality of log-likelihood ratios having a lower resolution to a decoder. The non-linear function can distribute the log-likelihood ratios, for example, such that the frequency of each LLR value is more uniform than a linear scaling. 
   The plurality of log-likelihood ratios having a first resolution may be generated by an inner receiver, such as a Rake receiver, a minimum mean squared error (MMSE) receiver, a decorrelating receiver, an equalizer or an interference canceller. The plurality of log-likelihood ratios having a lower resolution can be processed by an outer decoder, such as a Turbo decoder or a Viterbi decoder. 
   A more complete understanding of the present invention, as well as further features and advantages of the present invention, will be obtained by reference to the following detailed description and drawings. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
       FIG. 1  is a schematic block diagram of an exemplary receiver incorporating features of the present invention; 
       FIG. 2  illustrates an example of an LLR mapping performed by the correction block of  FIG. 1  in accordance with the present invention; 
       FIG. 3  illustrates the frequency of each LLR value for both a conventional linear mapping and a non-linear mapping in accordance with the present invention; and 
       FIG. 4  is a schematic block diagram of a memory coupled to a processor. 
   

   DETAILED DESCRIPTION 
   The present invention provides methods and apparatus for scaling or shaping the LLR distribution in a manner that improves the BER performance. According to one aspect of the present invention, the LLR distribution is shaped in a non-linear manner. 
     FIG. 1  is a schematic block diagram of an exemplary receiver  100  incorporating features of the present invention. While the present invention is illustrated in the context of a universal mobile telecom system (UMTS) receiver, in accordance with a 3rd Generation Partnership Project (3GPP) standard, the present invention may be implemented in any decoder employing soft decision decoding, as would be apparent to a person of ordinary skill in the art. For a detailed discussion of the 3GPP specification, see, for example, 3GPP TS 25.212, “Multiplexing and Channel Coding (FDD),” and 3GPP TS 25.101, “User Equipment (UE) Radio Transmission And Reception (FDD),” incorporated by reference herein 
   As shown in  FIG. 1 , the exemplary receiver  100  comprises an inner receiver  110 , a correction block  120 , a bit rate processing block  130  and a decoder  140 . The inner receiver  110  may be implemented, for example, as a Rake receiver, a minimum mean squared error (MMSE) receiver, a decorrelating receiver, an equalizer or an interference canceller, or some combination of the foregoing, as would be apparent to a person of ordinary skill. Generally, the inner receiver  110  generates log-likelihood ratios (LLRs), in a known manner, that are processed by the decoder  140 . The inner receiver  110  operates at the chip rate, while the bit rate processing block  130  and decoder  140  operate at the bit rate. 
   As previously indicated, it is known to quantize the output signal of the inner receiver  110  from a set of LLRs with a first resolution to a set of LLRs with a lower resolution (i.e., having a smaller number of bits). The LLRs with a lower resolution are then processed by bit rate processing block  130  and the decoder  140 . Generally, the inner receiver  110  in conventional turbo decoding techniques generates LLRs that are scaled in a linear manner, for example, using a gain control method. 
   According to one aspect of the present invention, the correction block  120  maps the LLR values into a lower resolution using a non-linear function. The present invention recognizes that the LLRs generated by the inner receiver  110  may not have the right shape for optimal processing in the bit rate processing block  130 . In this manner, the correction block  120  can apply a non-linear function to the LLRs to shape them such that the bit and block error rate performance metrics (BER and BLER) are improved. 
   In one exemplary implementation, the non-linear correction block  120  applies the following non-linear function to the LLRs generated by the inner receiver  110 : 
   LLRout=(−0.5+sqrt(0.5**2+4/30*LLRin) for LLRin&gt;=0, 
   LLRout=−(−0.5+sqrt(0.5**2+4/30*−LLRin) for LLRin&lt;0. 
   It is noted that the LLRout values produced by the correction block  120  are typically fixed point values up to five bits and the LLRin values are typically higher resolution fixed point values. The step size for each step can be optimized for the intended scenario, as would be apparent to a person of ordinary skill. A heuristic process is employed to identify a suitable non-linear function. Generally, the LLRs are skewed in such a way that distributes the LLRs a bit more evenly, and thus provides additional information to the turbo decoder  140  about the different LLRs. 
   The bit rate processing block  130  implements a number of bit rate processing steps in accordance with the exemplary 3GPP standard, such as rate matching, HARQ processing and buffering. The decoder  140  may be implemented, for example, as a Turbo or Viterbi decoder. 
     FIG. 2  illustrates the LLR mapping performed by the correction block  120  in accordance with the present invention. As shown in  FIG. 2 , the correction block  120  applies a non-linear function  220  to the LLRs generated by the inner receiver  110  (LLR IN ). In addition, a conventional linear mapping  210  is also shown. 
   It is noted that the correction block  120  could be implemented in hardware or software. For a hardware implementation, the non-linear function  220  could be implemented, for example, in the form of a lookup table. If the higher resolution LLR (LLR IN ) has a 7 bit resolution including one bit sign, and assuming the lookup table is symmetrical around 0, the lookup table can be implemented with 6 bits input and 4 bits output and the sign bit would be maintained from input to output. 
     FIG. 3  is a plot  300  illustrating the frequency of each LLR value for both a conventional linear mapping and a non-linear mapping in accordance with the present invention. As shown in  FIG. 3 , each data point for a conventional linear mapping is shown using a square bullet and each data point for a non-linear mapping is shown using a diamond bullet. Thus,  FIG. 3  illustrates the LLR distribution before and after reshaping. It is noted that the frequency of the LLR value at zero (0) is approximately 6500 in the exemplary embodiment, although not shown in the scale presented in  FIG. 3 . 
   Among other benefits, the present invention optimizes the BER/BLER over the whole receiver processing chain. In addition, the throughput with the non-linear reshaping of the present invention has been observed to perform better than without an LLR reshaping. 
   System and Article of Manufacture Details 
   As is known in the art, the methods and apparatus discussed herein may be distributed as an article of manufacture that itself comprises a computer readable medium having computer readable code means embodied thereon. The computer readable program code means is operable, in conjunction with a computer system, to carry out all or some of the steps to perform the methods or create the apparatuses discussed herein. The computer readable medium may be a recordable medium (e.g., floppy disks, hard drives, compact disks, or memory cards) or may be a transmission medium (e.g., a network comprising fiber-optics, the world-wide web, cables, or a wireless channel using time-division multiple access, code-division multiple access, or other radio-frequency channel). Any medium known or developed that can store information suitable for use with a computer system may be used. The computer-readable code means is any mechanism for allowing a computer to read instructions and data, such as magnetic variations on a magnetic media or height variations on the surface of a compact disk. 
     FIG. 4  is a schematic block diagram of a memory coupled to a processor. The computer systems and servers described herein each contain a memory  410  that will configure associated processors  420  to implement the methods, steps, and functions disclosed herein. The memories  410  could be distributed or local and the processors  420  could be distributed or singular. The memories  410  could be implemented as an electrical, magnetic or optical memory, or any combination of these or other types of storage devices. Moreover, the term “memory” should be construed broadly enough to encompass any information able to be read from or written to an address in the addressable space accessed by an associated processor. With this definition, information on a network is still within a memory because the associated processor can retrieve the information from the network. 
   It is to be understood that the embodiments and variations shown and described herein are merely illustrative of the principles of this invention and that various modifications may be implemented by those skilled in the art without departing from the scope and spirit of the invention.