location: Current position: Home >> Scientific Research >> Paper Publications

Blind Central-Symmetry-Based Feature Detection for Spatial Spectrum Sensing

Hits:

Indexed by:期刊论文

Date of Publication:2016-12-01

Journal:IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY

Included Journals:SCIE、EI、Scopus

Volume:65

Issue:12

Page Number:10147-10152

ISSN No.:0018-9545

Key Words:Angle of arrival (AoA) estimation; cognitive radio (CR); random matrix theory; spatial spectrum; spatial spectrum sensing

Abstract:State-of-the-art sensing methods mostly detect the spectrum holes by exploring the feature in frequency, time, and geography dimensions. In this paper, we analyze the sensing problem from angle/space domain by using the angle of arrival (AoA) estimation technology. We show a property that the spatial spectrum of noise has the feature of central symmetry, which the arriving signal does not have in general. Hence, the existence of the central symmetry feature depends on the presence or absence of the primary user signal. Motivated by this, we introduce a novel spatial spectrum sensing framework and propose a blind central-symmetry- based feature detection (CSFD) method correspondingly. Different from conventional spectrum sensing, the designed sensing framework reduces the complexity of spatial spectrum sensing and is available for spectrum access. Taking advantage of the inherent central symmetry feature of noise spatial spectrum, the proposed CSFD can achieve higher probability of detection even at low signal-to-noise ratios (SNRs) and offer AoA information. Theoretical performance analysis of the proposed CSFD method is also provided. Simulation results are presented to verify the efficiency of the proposed algorithm.

Pre One:远程虚拟仿真实验教学中心建设

Next One:空间调制系统低复杂度的天线选择算法