A fast algorithm for determining the linear complexity of periodic sequences

A fast algorithm is presented for determining the linear complexity and the minimal polynomial of periodic sequences over GF(q) with period q n p m, where p is a prime, q is a prime and a primitive root modulo p2. The algorithm presented here generalizes both the algorithm in [4] where the period of a sequence over GF(q) is p m and the algorithm in [5] where the period of a binary sequence is 2 n p m . When m=0, the algorithm simplifies the generalized Games-Chan algorithm.Comment: 7 page

The kk-error linear complexity distribution for 2n2^n-periodic binary sequences

The linear complexity and the $k$-error linear complexity of a sequence have been used as important security measures for key stream sequence strength in linear feedback shift register design. By studying the linear complexity of binary sequences with period $2^n$, one could convert the computation of $k$-error linear complexity into finding error sequences with minimal Hamming weight. Based on Games-Chan algorithm, the $k$-error linear complexity distribution of $2^n$-periodic binary sequences is investigated in this paper. First, for $k=2,3$, the complete counting functions on the $k$-error linear complexity of $2^n$-periodic balanced binary sequences (with linear complexity less than $2^n$) are characterized. Second, for $k=3,4$, the complete counting functions on the $k$-error linear complexity of $2^n$-periodic binary sequences with linear complexity $2^n$ are presented. Third, as a consequence of these results, the counting functions for the number of $2^n$-periodic binary sequences with the $k$-error linear complexity for $k = 2$ and 3 are obtained. Further more, an important result in a recent paper is proved to be not completely correct

An algorithm for the k-error linear complexity of a sequence with period 2pn over GF(q)

The union cost is used, so that an efficient algorithm for computing the k-error linear complexity of a sequence with period 2pn over GF(q) is presented, where p and q are odd primes, and q is a primitive root of modulo p2.Comment: 6 page

On the kk-error linear complexity for 2n2^n-periodic binary sequences via Cube Theory

The linear complexity and k-error linear complexity of a sequence have been used as important measures of keystream strength, hence designing a sequence with high linear complexity and $k$-error linear complexity is a popular research topic in cryptography. In this paper, the concept of stable $k$-error linear complexity is proposed to study sequences with stable and large $k$-error linear complexity. In order to study k-error linear complexity of binary sequences with period $2^n$, a new tool called cube theory is developed. By using the cube theory, one can easily construct sequences with the maximum stable $k$-error linear complexity. For such purpose, we first prove that a binary sequence with period $2^n$ can be decomposed into some disjoint cubes and further give a general decomposition approach. Second, it is proved that the maximum $k$-error linear complexity is $2^n-(2^l-1)$ over all $2^n$-periodic binary sequences, where $2^{l-1}\le k<2^{l}$. Thirdly, a characterization is presented about the $t$th ($t>1$) decrease in the $k$-error linear complexity for a $2^n$-periodic binary sequence $s$ and this is a continuation of Kurosawa et al. recent work for the first decrease of k-error linear complexity. Finally, A counting formula for $m$-cubes with the same linear complexity is derived, which is equivalent to the counting formula for $k$-error vectors. The counting formula of $2^n$-periodic binary sequences which can be decomposed into more than one cube is also investigated, which extends an important result by Etzion et al..Comment: 11 pages. arXiv admin note: substantial text overlap with arXiv:1109.4455, arXiv:1108.5793, arXiv:1112.604

On the kk-error linear complexity for pnp^n-periodic binary sequences via hypercube theory

The linear complexity and the $k$-error linear complexity of a binary sequence are important security measures for key stream strength. By studying binary sequences with the minimum Hamming weight, a new tool named as hypercube theory is developed for $p^n$-periodic binary sequences. In fact, hypercube theory is based on a typical sequence decomposition and it is a very important tool in investigating the critical error linear complexity spectrum proposed by Etzion et al. To demonstrate the importance of hypercube theory, we first give a standard hypercube decomposition based on a well-known algorithm for computing linear complexity and show that the linear complexity of the first hypercube in the decomposition is equal to the linear complexity of the original sequence. Second, based on such decomposition, we give a complete characterization for the first decrease of the linear complexity for a $p^n$-periodic binary sequence $s$. This significantly improves the current existing results in literature. As to the importance of the hypercube, we finally derive a counting formula for the $m$-hypercubes with the same linear complexity.Comment: 16 pages. arXiv admin note: substantial text overlap with arXiv:1309.1829, arXiv:1312.692

Structure Analysis on the kk-error Linear Complexity for 2n2^n-periodic Binary Sequences

In this paper, in order to characterize the critical error linear complexity spectrum (CELCS) for $2^n$-periodic binary sequences, we first propose a decomposition based on the cube theory. Based on the proposed $k$-error cube decomposition, and the famous inclusion-exclusion principle, we obtain the complete characterization of $i$th descent point (critical point) of the k-error linear complexity for $i=2,3$. Second, by using the sieve method and Games-Chan algorithm, we characterize the second descent point (critical point) distribution of the $k$-error linear complexity for $2^n$-periodic binary sequences. As a consequence, we obtain the complete counting functions on the $k$-error linear complexity of $2^n$-periodic binary sequences as the second descent point for $k=3,4$. This is the first time for the second and the third descent points to be completely characterized. In fact, the proposed constructive approach has the potential to be used for constructing $2^n$-periodic binary sequences with the given linear complexity and $k$-error linear complexity (or CELCS), which is a challenging problem to be deserved for further investigation in future.Comment: 19 pages. arXiv admin note: substantial text overlap with arXiv:1309.1829, arXiv:1310.0132, arXiv:1108.5793, arXiv:1112.604

Characterization of 2n2^n-periodic binary sequences with fixed 3-error or 4-error linear complexity

The linear complexity and the $k$-error linear complexity of a sequence have been used as important security measures for key stream sequence strength in linear feedback shift register design. By using the sieve method of combinatorics, the $k$-error linear complexity distribution of $2^n$-periodic binary sequences is investigated based on Games-Chan algorithm. First, for $k=2,3$, the complete counting functions on the $k$-error linear complexity of $2^n$-periodic binary sequences with linear complexity less than $2^n$ are characterized. Second, for $k=3,4$, the complete counting functions on the $k$-error linear complexity of $2^n$-periodic binary sequences with linear complexity $2^n$ are presented. Third, for $k=4,5$, the complete counting functions on the $k$-error linear complexity of $2^n$-periodic binary sequences with linear complexity less than $2^n$ are derived. As a consequence of these results, the counting functions for the number of $2^n$-periodic binary sequences with the 3-error linear complexity are obtained, and the complete counting functions on the 4-error linear complexity of $2^n$-periodic binary sequences are obvious.Comment: 7 page

The 4-error linear complexity distribution for 2n2^n-periodic binary sequences

By using the sieve method of combinatorics, we study $k$-error linear complexity distribution of $2^n$-periodic binary sequences based on Games-Chan algorithm. For $k=4,5$, the complete counting functions on the $k$-error linear complexity of $2^n$-periodic balanced binary sequences (with linear complexity less than $2^n$) are presented. As a consequence of the result, the complete counting functions on the 4-error linear complexity of $2^n$-periodic binary sequences (with linear complexity $2^n$ or less than $2^n$) are obvious. Generally, the complete counting functions on the $k$-error linear complexity of $2^n$-periodic binary sequences can be obtained with a similar approach.Comment: 15 pages. arXiv admin note: substantial text overlap with arXiv:1108.5793, arXiv:1112.6047, arXiv:1309.182

Periodic sequences with stable kk-error linear complexity

The linear complexity of a sequence has been used as an important measure of keystream strength, hence designing a sequence which possesses high linear complexity and $k$-error linear complexity is a hot topic in cryptography and communication. Niederreiter first noticed many periodic sequences with high $k$-error linear complexity over GF(q). In this paper, the concept of stable $k$-error linear complexity is presented to study sequences with high $k$-error linear complexity. By studying linear complexity of binary sequences with period $2^n$, the method using cube theory to construct sequences with maximum stable $k$-error linear complexity is presented. It is proved that a binary sequence with period $2^n$ can be decomposed into some disjoint cubes. The cube theory is a new tool to study $k$-error linear complexity. Finally, it is proved that the maximum $k$-error linear complexity is $2^n-(2^l-1)$ over all $2^n$-periodic binary sequences, where $2^{l-1}\le k<2^{l}$

Embedding Constructions of Tail-Biting Trellises for Linear Block Codes

In this paper, embedding construction of tail-biting trellises for linear block codes is presented. With the new approach of constructing tail-biting trellises, most of the study of tail-biting trellises can be converted into the study of conventional trellises. It is proved that any minimal tail-biting trellis can be constructed by the recursive process of embedding constructions from the well-known Bahl-Cocke-Jelinek-Raviv (BCJR) constructed conventional trellises. Furthermore, several properties of embedding constructions of tail-biting trellises are discussed. Finally, we give four sufficient conditions to reduce the maximum state-complexity of a trellis with one peak