On the complexity of multicovering radii

The multicovering radius is a generalization of the covering radius. In this correspondence, we show that lower-bounding the m-covering radius of an arbitrary binary code is NP-complete when m is polynomial in the length of the code. Lower-bounding the m-covering radius of a linear code is /spl Sigma//sub 2//sup P/-complete when m is polynomial in the length of the code. If P is not equal to NP, then the m-covering radius of an arbitrary binary code cannot be approximated within a constant factor or within a factor n/sup /spl epsi// where n is the length of the code and /spl epsi/<1, in polynomial time. Note that the case when m=1 was also previously unknown. If NP is not equal to /spl Sigma//sub 2//sup P/,then the m-covering radius of a linear code cannot be approximated within a constant factor or within a factor n/sup /spl epsi// where n is the length of the code and /spl epsi/<1, in polynomial time.     

The MMD codes are proper for error detection

The undetected error probability of a linear code used to detect errors on a symmetric channel is a function of the symbol error probability /spl epsi/ of the channel and involves the weight distribution of the code. The code is proper, if the undetected error probability increases monotonously in /spl epsi/. Proper codes are generally considered to perform well in error detection. We show in this correspondence that maximum minimum distance (MMD) codes are proper.     

Distance properties of expander codes

The minimum distance of some families of expander codes is studied, as well as some related families of codes defined on bipartite graphs. The weight spectrum and the minimum distance of a random ensemble of such codes are computed and it is shown that it sometimes meets the Gilbert-Varshamov (GV) bound. A lower bound on the minimum distances of constructive families of expander codes is derived. The relative minimum distance of the expander code is shown to exceed the product bound, i.e., the quantity /spl delta//sub 0//spl delta//sub 1/ where /spl delta//sub 0/ and /spl delta//sub 1/ are the minimum relative distances of the constituent codes. As a consequence of this, a polynomially constructible family of expander codes is obtained whose relative distance exceeds the Zyablov bound on the distance of serial concatenations.     

Random codes: minimum distances and error exponents

Minimum distances, distance distributions, and error exponents on a binary-symmetric channel (BSC) are given for typical codes from Shannon's random code ensemble and for typical codes from a random linear code ensemble. A typical random code of length N and rate R is shown to have minimum distance N/spl delta//sub GV/(2R), where /spl delta//sub GV/(R) is the Gilbert-Varshamov (GV) relative distance at rate R, whereas a typical linear code (TLC) has minimum distance N/spl delta//sub GV/(R). Consequently, a TLC has a better error exponent on a BSC at low rates, namely, the expurgated error exponent.     

On the stopping distance and the stopping redundancy of codes

It is now well known that the performance of a linear code /spl Copf/ under iterative decoding on a binary erasure channel (and other channels) is determined by the size of the smallest stopping set in the Tanner graph for /spl Copf/. Several recent papers refer to this parameter as the stopping distance s of /spl Copf/. This is somewhat of a misnomer since the size of the smallest stopping set in the Tanner graph for /spl Copf/ depends on the corresponding choice of a parity-check matrix. It is easy to see that s /spl les/ d, where d is the minimum Hamming distance of /spl Copf/, and we show that it is always possible to choose a parity-check matrix for /spl Copf/ (with sufficiently many dependent rows) such that s=d. We thus introduce a new parameter, the stopping redundancy of /spl Copf/, defined as the minimum number of rows in a parity- check matrix H for /spl Copf/ such that the corresponding stopping distance s(H) attains its largest possible value, namely, s(H)=d. We then derive general bounds on the stopping redundancy of linear codes. We also examine several simple ways of constructing codes from other codes, and study the effect of these constructions on the stopping redundancy. Specifically, for the family of binary Reed-Muller codes (of all orders), we prove that their stopping redundancy is at most a constant times their conventional redundancy. We show that the stopping redundancies of the binary and ternary extended Golay codes are at most 34 and 22, respectively. Finally, we provide upper and lower bounds on the stopping redundancy of MDS codes.     

Locally testable cyclic codes

Cyclic linear codes of block length n over a finite field F/sub q/ are linear subspaces of F/sub q//sup n/ that are invariant under a cyclic shift of their coordinates. A family of codes is good if all the codes in the family have constant rate and constant normalized distance (distance divided by block length). It is a long-standing open problem whether there exists a good family of cyclic linear codes. A code C is r-testable if there exists a randomized algorithm which, given a word x/spl isin//sub q//sup n/, adaptively selects r positions, checks the entries of x in the selected positions, and makes a decision (accept or reject x) based on the positions selected and the numbers found, such that 1) if x/spl isin/C then x is surely accepted; ii) if dist(x,C) /spl ges/ /spl epsi/n then x is probably rejected. ("dist" refers to Hamming distance.) A family of codes is locally testable if all members of the family are r-testable for some constant r. This concept arose from holographic proofs/PCP's. Recently it was asked whether there exist good, locally testable families of codes. In this paper the intersection of the two questions stated is addressed. Theorem. There are no good, locally testable families of cyclic codes over any (fixed) finite field. In fact the result is stronger in that it replaces condition ii) of local testability by the condition ii') if dist (x,C) /spl ges/ /spl epsi/n then x has a positive chance of being rejected. The proof involves methods from Galois theory, cyclotomy, and diophantine approximation.     

Improved inapproximability of lattice and coding problems with preprocessing

We show that the closest vector problem with preprocessing (CVPP) is NP-hard to approximate to within /spl radic/3-/spl epsi/ for any /spl epsi/>0. In addition, we show that the nearest codeword problem with preprocessing (NCPP) is NP-hard to approximate to within 3-/spl epsi/. These results improve previous results of Feige and Micciancio. We also present the first inapproximability result for the relatively nearest codeword problem with preprocessing (RNCP). Finally, we describe an n-approximation algorithm to CVPP.     

Using linear programming to Decode Binary linear codes

A new method is given for performing approximate maximum-likelihood (ML) decoding of an arbitrary binary linear code based on observations received from any discrete memoryless symmetric channel. The decoding algorithm is based on a linear programming (LP) relaxation that is defined by a factor graph or parity-check representation of the code. The resulting "LP decoder" generalizes our previous work on turbo-like codes. A precise combinatorial characterization of when the LP decoder succeeds is provided, based on pseudocodewords associated with the factor graph. Our definition of a pseudocodeword unifies other such notions known for iterative algorithms, including "stopping sets," "irreducible closed walks," "trellis cycles," "deviation sets," and "graph covers." The fractional distance d/sub frac/ of a code is introduced, which is a lower bound on the classical distance. It is shown that the efficient LP decoder will correct up to /spl lceil/d/sub frac//2/spl rceil/-1 errors and that there are codes with d/sub frac/=/spl Omega/(n/sup 1-/spl epsi//). An efficient algorithm to compute the fractional distance is presented. Experimental evidence shows a similar performance on low-density parity-check (LDPC) codes between LP decoding and the min-sum and sum-product algorithms. Methods for tightening the LP relaxation to improve performance are also provided.     

Stopping set distribution of LDPC code ensembles

Stopping sets determine the performance of low-density parity-check (LDPC) codes under iterative decoding over erasure channels. We derive several results on the asymptotic behavior of stopping sets in Tanner-graph ensembles, including the following. An expression for the normalized average stopping set distribution, yielding, in particular, a critical fraction of the block length above which codes have exponentially many stopping sets of that size. A relation between the degree distribution and the likely size of the smallest nonempty stopping set, showing that for a /spl radic/1-/spl lambda/'(0)/spl rho/'(1) fraction of codes with /spl lambda/'(0)/spl rho/'(1)<1, and in particular for almost all codes with smallest variable degree >2, the smallest nonempty stopping set is linear in the block length. Bounds on the average block error probability as a function of the erasure probability /spl epsi/, showing in particular that for codes with lowest variable degree 2, if /spl epsi/ is below a certain threshold, the asymptotic average block error probability is 1-/spl radic/1-/spl lambda/'(0)/spl rho/'(1)/spl epsi/.     

More results on the weight enumerator of product codes

We consider the product code C/sub p/ of q-ary linear codes with minimum distances d/sub c/ and d/sub r/. The words in C/sub p/ of weight less than d/sub r/d/sub c/+max(d/sub r//spl lceil/(d/sub c//g)/spl rceil/,d/sub c//spl lceil/(d/sub r//q)/spl rceil/) are characterized, and their number is expressed in the number of low-weight words of the constituent codes. For binary product codes, we give an upper bound on the number of words in C/sub p/ of weightless than min(d/sub r/(d/sub c/+/spl lceil/(d/sub c//2)/spl rceil/+1)), d/sub c/(d/sub r/+/spl lceil/(d/sub r//2)/spl rceil/+1) that is met with equality if C/sub c/ and C/sub r/ are (extended) perfect codes.     

Asymptotically Gaussian weight distribution and performance of multicomponent turbo block codes and product codes

It was suggested by Battail that a good long linear code should have a weight distribution close to that of random coding, rather than a large minimum distance, and a turbo code should be also designed using a random-like criterion. In this paper, we first show that the weight distribution of a high-rate linear block code is approximately Gaussian if the code rate is close enough to one, and then proceed to construct a low-rate linear block code with approximately Gaussian weight distribution by using the turbo-coding technique. We give a sufficient condition under which the weight distribution of multicomponent turbo block (MCTB) codes (multicomponent product (MCP) codes, respectively) can approach asymptotically that of random codes, and further develop two classes of MCTB codes (MCP codes) satisfying this condition. Simulation results show that MCTB codes (MCP codes) having asymptotically Gaussian weight distribution can asymptotically approach Shannon's capacity limit. MCTB codes based on single parity-check (SPC) codes have a far poorer minimum distance than MCP codes based on SPC codes, but we show by simulation that when the bit-error rate is in the important range of 10/sup -1/-10/sup -5/, these codes can still offer similar performance for the additive white Gaussian noise channel, as long as the code length of the SPC codes is not very short. These facts confirm in a more precise way Battail's inference about the "nonimportance" of the minimum distance for a long code.     

Long nonbinary codes exceeding the Gilbert-Varshamov bound for any fixed distance

Let A(q,n,d) denote the maximum size of a q-ary code of length n and distance d. We study the minimum asymptotic redundancy as n grows while q and d are fixed. For any d and q/spl ges/d-1, long algebraic codes are designed that improve on the Bose-Chaudhuri-Hocquenghem (BCH) codes and have the lowest asymptotic redundancy known to date. Prior to this work, codes of fixed distance that asymptotically surpass BCH codes and the Gilbert-Varshamov bound were designed only for distances 4,5, and 6.     

Improving the Gilbert-Varshamov bound for q-ary codes

Given positive integers q,n, and d, denote by A/sub q/(n,d) the maximum size of a q-ary code of length n and minimum distance d. The famous Gilbert-Varshamov bound asserts that A/sub q/(n,d+1)/spl ges/q/sup n//V/sub q/(n,d) where V/sub q/(n,d)=/spl Sigma//sub i=0//sup d/ (/sub i//sup n/)(q-1)/sup i/ is the volume of a q-ary sphere of radius d. Extending a recent work of Jiang and Vardy on binary codes, we show that for any positive constant /spl alpha/ less than (q-1)/q there is a positive constant c such that for d/spl les//spl alpha/n A/sub q/(n,d+1)/spl ges/cq/sup n//V/sub q/(n,d)n. This confirms a conjecture by Jiang and Vardy.     

Blind source separation of signals with known alphabets using /spl epsi/-approximation algorithms

We show that blind separation of signals in given alphabets can be formulated into a quadratic optimization problem with integer constraints. Then, efficient /spl epsi/-approximation algorithms are applied to directly estimate the transmitted signals. The proposed approach does not require any high order statistics. Moreover, the algorithms converge to an /spl epsi/ neighborhood of the global optimum with polynomial computational complexity. Simulations show that the algorithm achieves satisfactory performance using a short length of data.     

Combinatorial bounds for list decoding

Informally, an error-correcting code has "nice" list-decodability properties if every Hamming ball of "large" radius has a "small" number of codewords in it. We report linear codes with nontrivial list-decodability: i.e., codes of large rate that are nicely list-decodable, and codes of large distance that are not nicely list-decodable. Specifically, on the positive side, we show that there exist codes of rate R and block length n that have at most c codewords in every Hamming ball of radius H^-1(1-R-1/c)·n. This answers the main open question from the work of Elias (1957). This result also has consequences for the construction of concatenated codes of good rate that are list decodable from a large fraction of errors, improving previous results of Guruswami and Sudan (see IEEE Trans. Inform. Theory, vol.45, p.1757-67, Sept. 1999, and Proc. 32nd ACM Symp. Theory of Computing (STOC), Portland, OR, p. 181-190, May 2000) in this vein. Specifically, for every ε > 0, we present a polynomial time constructible asymptotically good family of binary codes of rate Ω(ε⁴) that can be list-decoded in polynomial time from up to a fraction (1/2-ε) of errors, using lists of size O(ε^-2). On the negative side, we show that for every δ and c, there exists τ < δ, c₁ > 0, and an infinite family of linear codes {C_i}_i such that if n_i denotes the block length of C_i, then C _i has minimum distance at least δ · n_i and contains more than c₁ · n_i^c codewords in some Hamming ball of radius τ · n_i. While this result is still far from known bounds on the list-decodability of linear codes, it is the first to bound the "radius for list-decodability by a polynomial-sized list" away from the minimum distance of the code     

On the capacity of network coding for random networks

We study the maximum flow possible between a single-source and multiple terminals in a weighted random graph (modeling a wired network) and a weighted random geometric graph (modeling an ad-hoc wireless network) using network coding. For the weighted random graph model, we show that the network coding capacity concentrates around the expected number of nearest neighbors of the source and the terminals. Specifically, for a network with a single source, l terminals, and n relay nodes such that the link capacities between any two nodes is independent and identically distributed (i.i.d.) /spl sim/X, the maximum flow between the source and the terminals is approximately nE[X] with high probability. For the weighted random geometric graph model where two nodes are connected if they are within a certain distance of each other we show that with high probability the network coding capacity is greater than or equal to the expected number of nearest neighbors of the node with the least coverage area.     

Exact thresholds and optimal codes for the binary-symmetric channel and Gallager's decoding algorithm A

We show that for the case of the binary-symmetric channel and Gallager's decoding algorithm A the threshold can, in many cases, be determined analytically. More precisely, we show that the threshold is always upper-bounded by the minimum of (1-/spl lambda//sub 2//spl rho/'(1))/(/spl lambda/'(1)/spl rho/'(1)-/spl lambda//sub 2//spl rho/'(1)) and the smallest positive real root /spl tau/ of a specific polynomial p(x) and we observe that for most cases this bound is tight, i.e., it determines the threshold exactly. We also present optimal degree distributions for a large range of rates. In the case of rate one-half codes, for example, the threshold x/sub 0//sup */ of the optimal degree distribution is given by x/sup *//sub 0//spl sim/0.0513663. Finally, we outline how thresholds of more complicated decoders might be determined analytically.     

Improved Upper Bounds on Stopping Redundancy

For a linear block code with minimum distance d, its stopping redundancy is the minimum number of check nodes in a Tanner graph representation of the code, such that all nonempty stopping sets have size d or larger. We derive new upper bounds on stopping redundancy for all linear codes in general, and for maximum distance separable (MDS) codes specifically, and show how they improve upon previous results. For MDS codes, the new bounds are found by upper-bounding the stopping redundancy by a combinatorial quantity closely related to Turan numbers. (The Turan number, T(v,k,t), is the smallest number of t-subsets of a v-set, such that every k-subset of the v-set contains at least one of the t-subsets.) Asymptotically, we show that the stopping redundancy of MDS codes with length n and minimum distance d >1 is T(n,d-1,d-2)(1+O(n^-1)) for fixed d, and is at most T (n,d-1,d-2)(3+O(n^-1)) for fixed code dimension k=n-d+1. For d=3,4, we prove that the stopping redundancy of MDS codes is equal to T(n,d-1,d-2), for which exact formulas are known. For d=5, we show that the stopping redundancy of MDS codes is either T(n,4,3) or T(n,4,3)+1     

Concatenated codes with large minimum distance (Corresp.)

Some concatenated codes of length 128 and less are constructed. Nineteen of these codes are superior to the best previously known linear codes, as shown by the fact that the wellknown lower bound on the minimum distance of the concatenated code as the product of the minimum distances of its component codes exceeds the minimum distance of the best previously known code.     

A construction of resilient functions with high nonlinearity

We provide a construction technique for multiple-output resilient functions F:F/sub 2//sup n//spl rarr/F/sub 2//sup m/ with high nonlinearity. The construction leads to the problem of finding a set of linear codes with a fixed minimum distance, having the property that the intersection between any two codes is the all-zero codeword only. This problem is considered, and existence results are provided. Moreover, the constructed functions obtain a nonlinearity superior to previous construction methods.