This article introduces an integrated polarization divesity cognitive radio (CR) and Ultrawide Band (UWB) Multiple Inputs and Multiple Output (MIMO) antenna systems for CR wireless sensor networks (CR‐WSN) and short‐range HD video transmission applications. This proposed integrated antenna system's main purpose is to overcome the impediments of frequency re‐configurable UWB/Narrow Band (NB) antenna system. The proposed integrated system consists of two antenna systems: the CR antenna and the UWB MIMO antenna system. The first part of the integrated antenna system is the CR antenna that comprises vertical and horizontal oriented UWB antennas to sense the spectrum and four NB antennas for communication purposes. The second part of the integrated antenna system is a 2 × 2 MIMO antenna that comprises a veritical and horizontal oriented UWB antenna with notch characteristics for MIMO applications. High isolation is achieved without using a decoupling structure by placing radiators in the horizontal and vertical planes. The proposed integrated 3D antenna system is designed with a compact size of 50 × 50 mm2. The antenna's essential parameters, such as the reflection coefficient, mutual coupling, peak gain, the radiation pattern, and radiation efficiency, are analyzed to evaluate the antenna's performance. The proposed integrated antenna system is suitable for off‐device applications in industries or Laboratories. The real‐time implementation of CR‐WSN and short‐range wireless HD video transmission applications are demonstrated using National Instruments (NI) Universal Software Radio Peripheral (USRP) and CC2538 kit.
This paper discusses the equivalent circuit model and functional verification of an integrated antenna system as its main focus. The integrated antenna system consists of two independent antenna systems, namely the Cognitive Radio antenna and the Ultra Wide Band Multiple Iinput Multiple Output antenna. This article is split into two parts: The first part discusses the equivalent circuit of an integrated antenna system by optimizing the RLC values. The developed lumped equivalent circuit model produces the NB resonant frequencies, which is the same as the S-parameter obtained through EM simulation. The second part of this paper aims to discuss the experimental verification of an integrated CR antenna system with Bayesian learning-based spectrum sensing algorithms using Universal Software Radio Peripheral devices. Real-time sensing and communication functionalities are visualized in the LABVIEW monitor. The integrated antenna system is fabricated and measured after the simulation.
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