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In the early 1940s, electromagnetic (EM) waves in the RF and microwave frequency range were used to transmit messages between New York and Philadelphia [1]. Telecom operators and broadcasters immediately adopted this method because it made data transmission quite easy. Today, recent advances in satellite, cellular, and fiber-optic communication have significantly increased the data delivery rate. In the telecommunications industry, large numbers of RF and microwave technologies integrated with digital transmission have now been adopted. Meanwhile, RF and microwave technologies have also been extensively utilized for non-telecommunications applications, including the imaging and sensing of objects and structures of arbitrary shapes and dimensions. The process of using RF technology for imaging and sensing applications arises from the fact that microwaves can penetrate objects to provide valuable information.

In essence, all microwave devices are designed to operate exclusively in their specified frequency ranges; thus, the humorous statement that “all the world is a filter” [1]. This may sound funny, but it reveals the importance of microwave filters, which are employed to pass signals in the desired frequency bands while attenuating needless out-of-band interference and noise.

With the recent developments in the field of ultralow-power wearable and portable electronic gadgets and wireless sensor networks, the number of devices and sensors in a system has increased significantly [1]. The emergence of the Internet of Things has added many additional devices and sensors connected via the Internet [2], [3]. It is also anticipated that the number of connected devices will continue to increase in the coming years [4]. Currently, batteries remain the only source of power for these interconnected devices and systems.

With the recent rapid improvement of wireless communication rates [1], [2], the cutoff frequency of semiconductor devices has gradually increased [3], [4], and products with large signal bandwidth circuits have become a hot topic [5], [6], [7]. Port-to-port signal transmission and coupling mechanisms are also becoming more complex with the increases in frequency, presenting a challenge for high-frequency on-chip measurement [8], [9]. An accurate calibration must be applied to eliminate deviations between the probe terminal and the internal port of the device [10]. Unlike device under test (DUT), the reference plane for calibration of a vector network analyzer is from A to A’, as shown in Figure 1. This inevitably leads to an interconnection structure being utilized to address the mismatch between A to B and A’ to B’ [11], [12]. In response, the de-embedding technique has been developed to eliminate this extra step from the measurement data [13], [14].

Joint communication and sensing (JCAS) holds great potential in a variety of applications because it combines radar signaling and data transmission into a single system. This means that both applications share their spectrum or even their waveform within the RF spectrum, a scarce and expensive resource. Meanwhile, research on beyond 5G and 6G is increasing tremendously. The advance of software-defined radio, where the signal processing mainly takes place in software, allows different implementations for communication and sensing [1]. Another reason for the integration of both into one system is the growing sensor density, which entails mutual interference. Furthermore, sharing hardware requires a sustainable and resource-efficient solution in the field of RF engineering.

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