Wideband Collaborative Spectrum Sensing using Massive MIMO Decision Fusion
I. Dey, D. Ciuonzo, and P. Salvo Rossi

TL;DR
This paper proposes a wideband collaborative spectrum sensing framework using massive MIMO decision fusion with OFDM reporting, employing novel TR-based rules to improve interference mitigation and detection performance in cognitive radio networks.
Contribution
It introduces TR-WL, TR-MRC, and TR-mMRC rules for decision fusion in wideband spectrum sensing with massive MIMO, enhancing interference suppression and detection accuracy.
Findings
TR-based rules outperform conventional methods in interference mitigation
Closed-form expressions for false-alarm and detection probabilities are derived
Large-scale channel effects significantly influence fusion rule performance
Abstract
In this paper, in order to tackle major challenges of spectrum exploration \& allocation in Cognitive Radio (CR) networks, we apply the general framework of Decision Fusion (DF) to wideband collaborative spectrum sensing based on Orthogonal Frequency Division Multiplexing (OFDM) reporting. At the transmitter side, we employ OFDM without Cyclic Prefix (CP) in order to improve overall bandwidth efficiency of the reporting phase in networks with high user density. On the other hand, at the receiver side (of the reporting channel) we device the Time-Reversal Widely Linear (TR-WL), Time-Reversal Maximal Ratio Combining (TR-MRC) and modified TR-MRC (TR-mMRC) rules for DF. The DF Center (DFC) is assumed to be equipped with a large antenna array, serving a number of unauthorized users competing for the spectrum, thereby resulting in a ``virtual'' massive Multiple-Input Multiple-Output (MIMO)…
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Taxonomy
TopicsCognitive Radio Networks and Spectrum Sensing · Distributed Sensor Networks and Detection Algorithms · Sparse and Compressive Sensing Techniques
