TDCS-based Cognitive Radio Networks with Multiuser Interference Avoidance

TL;DR

This paper introduces a novel TDCS-based cognitive radio network framework that employs joint sequence and modulation design to effectively avoid multiuser interference, enhancing decentralized network performance.

Contribution

It proposes a new sequence design and modulation scheme that achieve multiuser interference avoidance in TDCS-based cognitive radio networks.

Findings

Sequences with zero cross-correlation for most shifts

Improved network performance under interference conditions

Effective MUI avoidance in decentralized settings

Abstract

For overlay cognitive radio networks (CRNs), transform domain communication system (TDCS) has been proposed to support multiuser communications through spectrum bin nulling and frequency domain spreading. In TDCS-based CRNs, each user is assigned a specific pseudorandom spreading sequence. However, the existence of multiuser interference (MUI) is one of main concerns, due to the non-zero cross-correlations between any pair of TDCS signals. In this paper, a novel framework of TDCS-based CRNs with the joint design of sequences and modulation schemes is presented to realize MUI avoidance. With the uncertainty of spectrum sensing results in CRNs, we first introduce a unique sequence design through two-dimensional time-frequency synthesis and obtain a class of almost perfect sequences. That is, periodic auto-correlation and cross-correlations are identically zero for most circular shifts. These correlation properties are further exploited in conjunction with a specially-designed cyclic code shift keying in order to achieve the advantage of MUI avoidance. Numerical results demonstrate that the proposed TDCS-based CRNs are considered as preferable candidates for decentralized networks against the near-far problem.