Abstract
Line of sight (LoS) and security are the fundamental requirement for any secure visual MIMO communication based vehicular networks. Uneven speed, irregular terrains, and uncertain appearance of obstacles disgrace LoS between the visual multiple-input multiple-output (MIMO) transmitter and receiver. This paper proposes optimal tracking techniques to maintain LoS using a novel quick response (QR) inspired light emitting array (LEA) pattern. Automatic geometric transformation of the QR code in conjunction with the particle filter is used to track the dynamically varying LEA position. In addition to that, an adaptive threshold technique (ATT) has been proposed to minimize error caused by ambient light variations and interferences. A novel key generation algorithm is also proposed to improve the security of the visual MIMO communication system. It utilizes a customized linear feedback shift register (LFSR) and synthetic color image to generate a stronger key. The randomness test demonstrates the robustness of the proposed key generation technique with a minimal probability value of 0.1223 (>0.01). Simulation and real-time studies have been carried out in the presence of geometric distortions, and the bit error rate (BER) performance is evaluated. Results illustrate that the proposed techniques make the visual MIMO system more secure and reliable for vehicular networks.
Highlights
The visual multiple-input multiple-output (MIMO) system uses a visible light spectrum with optical spatial modulation (OSM) or color-space-based modulation (CSBM) techniques [1,2,3,4] for parallel communication
The images are subjected to translating, rotating, and scaling perturbations that commonly occurs in the leader-follower configuration
bit error rate (BER) is considered as a performance index to evaluate the proposed system in all these scenarios
Summary
The visual MIMO system uses a visible light spectrum with optical spatial modulation (OSM) or color-space-based modulation (CSBM) techniques [1,2,3,4] for parallel communication. Detection of the LEA initial position is highly challenging due to discontinuous visibility of vehicles in the receivers field of view (FOV) To overcome this problem, the particle filter has been employed in the proposed work. Light interference in the visual-MIMO communication is addressed with the use of the polarization technique [5], which minimizes the BER even at a high data rate. Performance, a boosting neural network (BNN) model has been proposed [26] Another approach uses the Strokes transform in a uniform colored LEA to translate the Euclidean distributed LEDs to a 3-D stroke space. To facilitate real-time applications, a spatial clustering-based adaptive threshold technique has been proposed to minimize ambient and adjacent interference As this MIMO communication uses a visible spectrum, it makes the masquerade aware of the transmission and vulnerable to attack.
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