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A low-latency zone-based cooperative spectrum sensing

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
<mark>Journal publication date</mark>1/08/2016
<mark>Journal</mark>IEEE Sensors Journal
Issue number15
Volume16
Number of pages15
Pages (from-to)6028-6042
Publication StatusPublished
Early online date6/06/16
<mark>Original language</mark>English

Abstract

In this paper we propose a spectrum sensing scheme for wireless systems with low latency requirement such as machine-to-machine communications. In such systems with high spatial density of the base stations and users/objects, spectrum sharing enables spectrum reuse across very small regions. This however needs efficient incorporation of sensors’ location information
into spectrum sensing. We propose a multi-channel cooperative spectrum sensing technique in which an independent network of sensors, namely monitoring network, detects the spectrum availability. The monitoring network divides the coverage area into overlapped but independent zones. This enables exploiting high spatial distribution without incorporating exact sensors’ location. Corresponding to each zone, a zone aggregator (ZA) is introduced which processes the sensors’ output. The aggregated decision in each zone associated with the ZA’s location
is then passed to a decision fusion center (DFC). The secondary base station (SBS) accordingly allocates the available channels to maximize the spectral efficiency. We formulate the function of the DFC as an optimization problem with the objective of maximizing the spectral efficiency. For energy detector sensors, we further obtain optimal detection threshold for different cases with various spatial densities of ZAs and SBSs. This provides extra degrees of freedom in designing the spectrum monitoring network and provides quantitative insight on network design. We further
devise an efficient protocol for the proposed technique with very low signaling complexity and show that the proposed method reduces the spectrum sensing latency and results in a higher
spectrum efficiency. Extensive simulations confirm our analytical results and indicate a significant improvement in sensing latency and accuracy.