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Families of sequences with good family complexity and cross-correlation measure

Kenan Doğan, Murat Şahin, Oğuz Yayla

TL;DR

The paper addresses constructing large families of pseudorandom sequences with high $f$-complexity and low cross-correlation for binary and $k$-symbol alphabets. It advances this goal by generalizing Legendre-symbol constructions and irreducible-polynomial-based families over finite fields, applying Weil-type bounds to control cross-correlation, and extending the $f$-complexity framework to $k$-ary alphabets and dual families. Key contributions include explicit bounds such as $\Phi_\ell(\mathcal{F}) \ll \cdots$ and $C(\mathcal{F}) \ge (\tfrac{1}{2}-o(1))\frac{\log(p/d^2)}{\log 2}$ (binary) and $C(\mathcal{F}) \ge (\tfrac{d}{2}-1)\log_2 p - \log_2((d-1)\log_2 p)$ (binary/large $d$), along with constructions yielding family sizes $|\mathcal{F}|$ on the order of $p^{d-1}/d$ and analogous $k$-ary results. These findings provide systematic methods to generate extensive pseudorandom sequence families with provable guarantees suitable for communications and cryptography.

Abstract

In this paper we study pseudorandomness of a family of sequences in terms of two measures, the family complexity ($f$-complexity) and the cross-correlation measure of order $\ell$. We consider sequences not only on binary alphabet but also on $k$-symbols ($k$-ary) alphabet. We first generalize some known methods on construction of the family of binary pseudorandom sequences. We prove a bound on the $f$-complexity of a large family of binary sequences of Legendre-symbols of certain irreducible polynomials. We show that this family as well as its dual family have both a large family complexity and a small cross-correlation measure up to a rather large order. Next, we present another family of binary sequences having high $f$-complexity and low cross-correlation measure. Then we extend the results to the family of sequences on $k$-symbols alphabet.

Families of sequences with good family complexity and cross-correlation measure

TL;DR

The paper addresses constructing large families of pseudorandom sequences with high -complexity and low cross-correlation for binary and -symbol alphabets. It advances this goal by generalizing Legendre-symbol constructions and irreducible-polynomial-based families over finite fields, applying Weil-type bounds to control cross-correlation, and extending the -complexity framework to -ary alphabets and dual families. Key contributions include explicit bounds such as and (binary) and (binary/large ), along with constructions yielding family sizes on the order of and analogous -ary results. These findings provide systematic methods to generate extensive pseudorandom sequence families with provable guarantees suitable for communications and cryptography.

Abstract

In this paper we study pseudorandomness of a family of sequences in terms of two measures, the family complexity (-complexity) and the cross-correlation measure of order . We consider sequences not only on binary alphabet but also on -symbols (-ary) alphabet. We first generalize some known methods on construction of the family of binary pseudorandom sequences. We prove a bound on the -complexity of a large family of binary sequences of Legendre-symbols of certain irreducible polynomials. We show that this family as well as its dual family have both a large family complexity and a small cross-correlation measure up to a rather large order. Next, we present another family of binary sequences having high -complexity and low cross-correlation measure. Then we extend the results to the family of sequences on -symbols alphabet.

Paper Structure

This paper contains 6 sections, 5 theorems, 68 equations.

Key Result

Theorem 1

Let ${\mathcal{F}}_f$ be a family of binary sequences for some $f \in \Omega_{p,d}$ defined as where $f_i(X) = i^df(X/i)$ for $i \in \{1,2,\ldots , p-1 \}$ and $p \nmid d$. Let $\overline{{\mathcal{F}}_f}$ be the dual of ${\mathcal{F}}_f$. Then we have for each integer $k \in \{1,2,\ldots , p-1\}$ and

Theorems & Definitions (11)

  • Definition 1
  • Definition 2
  • Theorem 1
  • Example 1
  • Corollary 1
  • Theorem 2
  • Example 2
  • Definition 3
  • Definition 4
  • Theorem 3
  • ...and 1 more