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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) channel. The effectiveness of the proposed TR-based rules in combating (a) inter-symbol and (b) inter-carrier interference over conventional (non-TR) counterparts is then examined, as a function of the Signal-to-Interference-plus-Noise Ratio (SINR).Closed-form performance, in terms of system false-alarm and detection probabilities, is derived for the formulated fusion rules. Finally, the impact of large-scale channel effects on the proposed fusion rules is also investigated, via Monte-Carlo simulations.

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In this paper, we investigate the practical implications of employing virtual multiple-input-multiple output (MIMO) systems for prototyping future-generation wireless sensor networks, especially in the light of recently proposed distributed detection based decision fusion rules. In order to do that, an indoor-to-outdoor measurement campaign has been conducted recently for investigating the propagation characteristics of an 8 ⇥ 8 virtual multiple-input-multiple-output (MIMO) system. The campaign is conducted with transmit antennas representing the sensors deployed in different indoor environments and receive antennas mounted on an outside tower representing the decision fusion center. Channel measurements are reported when a 20 MHz wide signal is transmitted at 2.53 GHz. Measurements are collected for different spatial combinations of the transmit antennas. After analyzing the collected data, performance of different decision fusion rules are compared and tested over the measured channel. The results show that the fusion rules perform differently over different sets of measured channels. The results obtained here are important for maximizing performance and enabling air-interface design of next-generation wireless sensor networks.

In this paper, we investigate the practical implication of employing virtual massive multiple-input-multiple output (MIMO) based distributed decision fusion (DF) for collaborative wideband spectrum sensing (WSS) in a cognitive radio (CR)-like network. Towards that end, an indoor-only measurement campaign has been conducted to capture the propagation statistics of a 4 × 64 massive MIMO system with one authorized primary user (PU) and 4 unauthorized secondary users (SUs) transmitting simultaneously over a 20 MHz band divided into 1200 subcarriers. The frequency subcarriers belong to an Orthogonal-frequency-division-multiplexing (OFDM)-like set-up without the addition of cyclic prefix (CP) to the transmit symbols. Measurements are accumulated for different relative positions of the SUs which are analyzed to extract fading, shadowing, noise and interference power statistics. Log-likelihood ratio (LLR) based fusion rule and three different sets of sub-optimum fusion rules along with their time-reversed versions are formulated for combining decisions on the availability of each subcarrier transmitted by the SUs. The extracted channel characteristics are incorporated in both analytical and simulated performance analysis of the devised fusion rules for comparison and testing the validity of distributed DF in realistic collaborative WSS scenario.