Improved Analysis of List Decoding and Its Application to Convolutional Codes and Turbo Codes

A list decoder generates a list of more than one codeword candidates, and decoding is erroneous if the transmitted codeword is not included in the list. This decoding strategy can be implemented in a system that employs an inner error correcting code and an outer error detecting code that is used to choose the correct codeword from the list. Probability of codeword error analysis for a linear block code with list decoding is typically based on the "worst case" lower bound on the effective weights of codewords for list decoding evaluated from the weight enumerating function of the code. In this paper, the concepts of generalized pairwise error event and effective weight enumerating function are proposed for evaluation of the probability of codeword error of linear block codes with list decoding. Geometrical analysis shows that the effective Euclidean distances are not necessarily as low as those predicted by the lower bound. An approach to evaluate the effective weight enumerating function of a particular code with list decoding is proposed. The effective Euclidean distances for decisions in each pairwise error event are evaluated taking into consideration the actual Hamming distance relationships between codewords, which relaxes the pessimistic assumptions upon which the traditional lower bound analysis is based. Using the effective weight enumerating function, a more accurate approximation is achieved for the probability of codeword error of the code with list decoding. The proposed approach is applied to codes of practical interest, including terminated convolutional codes and turbo codes with the parallel concatenation structure     

A direct geometrical method for bounding the error exponent for anyspecific family of channel codes. I. Cutoff rate lower bound for blockcodes

A direct, general, and conceptually simple geometrical method for determining lower and upper bounds on the error exponent of any specific family of channel block codes is presented. It is considered that a specific family of codes is characterized by a unique distance distribution exponent. The tight linear lower bound of slope -1 on the code family error exponent represents the code family cutoff rate bound. It is always a minimum of a sum of three functions. The intrinsic asymptotic properties of channel block codes are revealed by analyzing these functions and their relationships. It is shown that the random coding technique for lower-bounding the channel error exponent is a special case of this general method. The requirements that a code family should meet in order to have a positive error exponent and at best attain the channel error exponent are stated in a clear way using the (direct) distance distribution method presented     

Average digit error probability in decoding a linear block code

An upper bound on the average digit error probability of a linear block code is given which is dependent only upon the minimum distance of the code. The tightness of this bound is also demonstrated, and an example is given where knowledge of the average digit error probability is important.     

Worst-case error probability of a spread-spectrum system inenergy-limited interference

We consider a communication channel corrupted by thermal noise and by an unknown and arbitrary interference of bounded energy. For this channel, we derive a simple upper bound to the worst-case error probability suffered by a direct sequence (DS) communication system with error-correction coding, pseudorandom interleaving, and a correlation receiver. This bound is exponentially tight as the block length of the error correcting code becomes large. Numerical examples are given that illustrate the dependence of the bound on the choice of error correcting code, the type of interleaving used, and the relative energy of the Gaussian noise and arbitrary interference     

A comparison of known codes, random codes, and the best codes

This paper calculates new bounds on the size of the performance gap between random codes and the best possible codes. The first result shows that, for large block sizes, the ratio of the error probability of a random code to the sphere-packing lower bound on the error probability of every code on the binary symmetric channel (BSC) is small for a wide range of useful crossover probabilities. Thus even far from capacity, random codes have nearly the same error performance as the best possible long codes. The paper also demonstrates that a small reduction k-k˜ in the number of information bits conveyed by a codeword will make the error performance of an (n,k˜) random code better than the sphere-packing lower bound for an (n,k) code as long as the channel crossover probability is somewhat greater than a critical probability. For example, the sphere-packing lower bound for a long (n,k), rate 1/2, code will exceed the error probability of an (n,k˜) random code if k-k˜>10 and the crossover probability is between 0.035 and 0.11=H^-1(1/2). Analogous results are presented for the binary erasure channel (BEC) and the additive white Gaussian noise (AWGN) channel. The paper also presents substantial numerical evaluation of the performance of random codes and existing standard lower bounds for the BEC, BSC, and the AWGN channel. These last results provide a useful standard against which to measure many popular codes including turbo codes, e.g., there exist turbo codes that perform within 0.6 dB of the bounds over a wide range of block lengths     

Upper bounds on the number of errors corrected by a convolutional code

We derive upper bounds on the weights of error patterns that can be corrected by a convolutional code with given parameters, or equivalently we give bounds on the code rate for a given set of error patterns. The bounds parallel the Hamming bound for block codes by relating the number of error patterns to the number of distinct syndromes.     

Performance of a turbo coded multicarrier DS/CDMA system withnonuniform repetition coding

This paper presents a turbo coded multicarrier direct sequence code division multiple access (DS/CDMA) system, where the outputs of a turbo encoder are repetition coded at multiple rates and transmitted in parallel over a number of subchannels. A performance bound useful in the so-called error floor region is obtained for Rayleigh fading channels when different diversity orders are given to each turbo code symbol. Simulation results are also provided for the low signal-to-noise ratio (SNR) region where the bound is not applicable. It is observed that the error floor can be lowered, with some performance loss in the low SNR region, by applying nonuniform repetition coding to the turbo code symbols     

Performance of trellis-coded direct-sequence spread spectrum withnoncoherent reception in a fading environment

In this paper, we consider the performance of different coding schemes for direct-sequence spread spectrum (DS-SS) in a nonselective Rician faded channel. The Nordstrom-Robinson (NR) code, a nonlinear code that has a large distance for a given rate combined with a trellis code, is examined. A bound is developed on the error probability for this trellis-coded NR (TCNR) code with noncoherent reception over a frequency-nonselective Rayleigh or Rician fading channel with additive white Gaussian noise (AWGN). This bound is tighter than the standard union bound. Our results indicate that the standard union bound can be significantly different from the more accurate results obtained from the improved union bound. In addition, there is a considerable coding gain at high signal-to-noise ratio (SNR) for the TCNR code over the conventional DS-SS code at the same data rate     

Analysis of recurrent codes

A definition of a recurrent code is given in a framework which renders it amenable to mathematical analysis. Recurrent codes for both independent and burst errors are considered, and a necessary and sufficient condition for either type of error correction is established. For burst-error-correcting codes, the problem treated is (for a fixed burst length and redundancy) the minimization of the error-free distance ("guard space") required between bursts. A lower bound is obtained on the guard space, and in certain cases, codes which realize this bound are given. A general code which is close to the lower bound in many cases is also given. For independent errors, a code which will correct any error, provided that no consecutive "n" positions have more than "e" digits in error, is discussed. Fore = 1, a necessary and sufficient condition onnis derived; fore > 1, a lower bound onnis obtained, and for the case of redundancy1/2, an upper bound onnis also derived.     

The random coding bound is tight for the average code (Corresp.)

The random coding bound of information theory provides a well-known upper bound to the probability of decoding error for the best code of a given rate and block length. The bound is constructed by upper-bounding the average error probability over an ensemble of codes. The bound is known to give the correct exponential dependence of error probability on block length for transmission rates above the critical rate, but it gives an incorrect exponential dependence at rates below a second lower critical rate. Here we derive an asymptotic expression for the average error probability over the ensemble of codes used in the random coding bound. The result shows that the weakness of the random coding bound at rates below the second critical rate is due not to upperbounding the ensemble average, but rather to the fact that the best codes are much better than the average at low rates.     

On trellis codes with a delay processor and a signal mapper

It is already known that a trellis code T, which is constructed by using the encoder of a convolutional code C with short constraint length followed by a delay processor and a signal mapper, is equivalent to a trellis code with large constraint length. In this paper, we derive a new lower bound on the free distance of T, which, in some cases, is better than the previously derived bound. Moreover, instead of the decoding used in earlier publications, we apply iterative decoding on both tailbiting and zero-tail representations of T to take advantage of the new lower bound and, in the meantime, to decrease the associated error coefficient caused by the decoding used in earlier publications. Comparisons among various designs of such a trellis code and some well-known coding methods are also provided.     

The Augmented State Diagram and its Application to Convolutional and Turbo Codes

Convolutional block codes, which are commonly used as constituent codes in turbo code configurations, accept a block of information bits as input rather than a continuous stream of bits. In this paper, we propose a technique for the calculation of the transfer function of convolutional block codes, both punctured and nonpunctured. The novelty of our approach lies in the augmentation of the conventional state diagram, which allows the enumeration of all codeword sequences of a convolutional block code. In the case of a turbo code, we can readily calculate an upper bound to its bit error rate performance if the transfer function of each constituent convolutional block code has been obtained. The bound gives an accurate estimate of the error floor of the turbo code and, consequently, our method provides a useful analytical tool for determining constituent codes or identifying puncturing patterns that improve the bit error rate performance of a turbo code, at high signal-to-noise ratios.     

Bounds on the decoding error probability of binary linear codes viatheir spectra

Bounds on the error probability of maximum likelihood decoding of a binary linear code are considered. The bounds derived use the weight spectrum of the code and they are tighter than the conventional union bound in the case of large noise in the channel. The bounds derived are applied to a code with an average spectrum, and the result is compared to the random coding exponent. The author shows that the bound considered for the binary symmetrical channel case coincides asymptotically with the random coding bound. For the case of AWGN channel the author shows that Berlekamp's (1980) tangential bound can be improved, but even this improved bound does not coincide with the random coding bound, although it can be very close to it     

Optimal codes for single-error correction, double-adjacent-errordetection

In certain memory systems the most common error is a single error and the next most common error is two errors in positions which are stored physically adjacent in the memory. In this correspondence we present optimal codes for recovering from such errors. We correct single errors and detect double adjacent errors. For detecting adjacent errors we consider codes which are byte-organized. In the binary case, it is clear that the length of the code is at most 2^r-r-1, where r is the redundancy of the code. We summarize the known results and some new ones in this case. For the nonbinary case we show an upper bound, called “the pairs bound,” on the length of such code. Over GF(3) codes with bytes of size 2 which attain the bound exist if and only if perfect codes with minimum Hamming distance 5 over GF(3) exist. Over GF(4) codes which attain the bound with byte size 2 exist for all redundancies. For most other parameters we prove the nonexistence of codes which attain the bound     

On Randomized Linear Network Codes and Their Error Correction Capabilities

Randomized linear network code for single source multicast was introduced and analyzed in Ho et al. (IEEE Transactions on Information Theory, October 2006) where the main results are upper bounds for the failure probability of the code. In this paper, these bounds are improved and tightness of the new bounds is studied by analyzing the limiting behavior of the failure probability as the field size goes to infinity. In the linear random coding setting for single source multicast, the minimum distance of the code defined in Zhang, (IEEE Transactions on Information Theory, January 2008) is a random variable taking nonnegative integer values that satisfy the inequality in the Singleton bound recently established in Yeung and Cai (Communications in Information and Systems, 2006) for network error correction codes. We derive a bound on the probability mass function of the minimum distance of the random linear network code based on our improved upper bounds for the failure probability. Codes having the highest possible minimum distance in the Singleton bound are called maximum distance separable (MDS). The bound on the field size required for the existence of MDS codes reported in Zhang, (IEEE Transactions on Information Theory, January 2008) and Matsumoto (arXiv:cs.IT/0610121, Oct. 2006) suggests that such codes exist only when field size is large. Define the degradation of a code as the difference between the highest possible minimum distance in the Singleton bound and the actual minimum distance of the code. The bound for the probability mass function of the minimum distance leads to a bound on the field size required for the existence of network error correction codes with a given maximum degradation. The result shows that allowing minor degradation reduces the field size required dramatically.     

On the probability of symbol error in Viterbi decoders

An upper bound is derived on the probability that at least one of a sequence of B consecutive bits at the output of a Viterbi (1979) decoder is in error. Such a bound is useful for the analysis of concatenated coding schemes employing an outer block code over GF(2^B) (typically a Reed-Solomon (RS) code), an inner convolutional code, and a symbol (GF(2^B)) interleaver separating the two codes. The bound demonstrates that in such coding schemes a symbol interleaver is preferable to a bit interleaver. It also suggests a new criterion for good inner convolutional codes     

Optical orthogonal codes with large crosscorrelation and their performance bound for asynchronous optical CDMA systems

Optical orthogonal codes (OOCs) are commonly used as signature codes for optical code-division multiple-access (OCDMA) communication systems. Many OOCs have been proposed and investigated. Asynchronous OCDMA systems using conventional OOCs have a very limited number of subscribers and few simultaneous users. Recently, we reported a new code family with large code size by relaxing the crosscorrelation constraint to 2. In this paper, by further loosening the crosscorrelation constraint, we adopt the random greedy algorithm to construct a code family which has larger code size and more simultaneous users. We also derive an upper bound of the number of simultaneous users for a given code length, code weight, and bit error rate. The study shows that it is possible to have codes approaching this bound.     

Truncation Error Probability in Viterbi Decoding

An upper bound on the bit error probability due to truncation of the path length in Viterbi decoding is obtained for any given convolutional code. This bound is then used to determine the path length at which the additional error probability due to truncation becomes negligible compared to the maximum likelihood decoding error probability. These results are tested by simulation using several short constraint length codes.     

Commutative group codes for the Gaussian channel

A class of codes for the Gaussian channel is analyzed. The code class is a subclass of the group codes for the Gaussian channel described by Slepian. Using the vector model for the Gaussian channel, the code vectors are obtained by transformations of an initial vector. The class of codes in which the transformations form a commutative group is called the class of commutative group codes. The performance of the codes is evaluated using the union bound on the error probability as a performance measure. The union bound is shown to be closely related to the moments of the scalar product between the code vectors. Commutative group codes are described. It is shown that linear algebraic codes may be represented as commutative group codes. The code class is also shown to include simplex and biorthogonal codes in all dimensions.     

Quantum error detection .II. Bounds

For pt.I see ibid., vol.46, no.3, p.778-88 (2000). In Part I of this paper we formulated the problem of error detection with quantum codes on the depolarizing channel and gave an expression for the probability of undetected error via the weight enumerators of the code. In this part we show that there exist quantum codes whose probability of undetected error falls exponentially with the length of the code and derive bounds on this exponent. The lower (existence) bound is proved for stabilizer codes by a counting argument for classical self-orthogonal quaternary codes. Upper bounds are proved by linear programming. First we formulate two linear programming problems that are convenient for the analysis of specific short codes. Next we give a relaxed formulation of the problem in terms of optimization on the cone of polynomials in the Krawtchouk basis. We present two general solutions of the problem. Together they give an upper bound on the exponent of undetected error. The upper and lower asymptotic bounds coincide for a certain interval of code rates close to 1