A novel reconfigurable antenna covering an 11.5:1 bandwidth is designed and fabricated for cognitive radio applications. The proposed novel antenna has two independent paths to cover 430 MHz to 5 GHz frequency range. The first path is directly connected to an ultrawide-band antenna, which covers 1-5 GHz operation frequency range. The second path, for the frequency range between 430 MHz and 1 GHz, goes through a dc-controlled varactor based matching network. The switching functionality between wideband (1 to 5 GHz) and reconfigurable region (430 MHz to 1 GHz) is realized by two discrete switches. The designed antenna has a simple structure and compact size of 60 mm × 100 mm. The proposed novel antenna has great potential for use in cognitive radio systems. Index Terms-reconfigurable antenna; UWB; cognitive radio. I. INTRODUCTIONMassive data traffic and high data rate are very critical issues in modern communication. Today there are more than 400 million wireless subscribers in the USA, equal to 1.2 wireless devices for every person in the country and wireless data traffic increased by nearly four times between 2014 and 2017 [1]. The ever-growing data demand creates a shortage in the wireless spectrum. Besides this wellknown spectrum shortage, spectrum usage is not uniformly distributed which leads to inefficiency. In order to overcome spectrum crowdedness and address inefficient spectrum usage, cognitive radio systems that are aware of unoccupied and/or idle state frequency bands and then adaptively change its operation to establish a reliable communication are required. Wideband antennas that can operate at any spectrum are very attractive for cognitive radio systems. In addition, compact antenna size is demanded to be suitable for portable and mobile devices.Most of the antennas currently used in wireless systems such as cellular network are classified as "resonant" antennas and intrinsically narrow band, for example, they can only operate at a fixed frequency with a small fractional bandwidth ranging from ~ 3% (for patch antennas) to ~ 10% (for dipole antennas). Thus, they are not suitable for realizing a robust cognitive radio whose operating frequency needs to hop over multiple octaves of the frequency range.Broader band antennas exist that can operate over a large bandwidth, for example, log-periodic antennas, horn antennas, etc. However, they belong to the other antenna class -"traveling wave" antennas, and are much larger in size (i.e., with electrical size several Manuscript received May 9, 2019.

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Carrier frequency offset (CFO) arises from the intrinsic mismatch between the oscillators of a wireless transmitter and the corresponding receiver, as well as their relative motion (i.e., Doppler effect). Despite advances in CFO estimation and tracking techniques, estimation errors are still present. Residual CFO creates a time-varying phase error, which degrades the decoder's performance by increasing the symbol error rate. The impact is particularly visible in dense constellation maps (e.g., high-order QAM modulation), often used in modern wireless systems such as 5G NR, 802.11ax, and mmWave, as well as in physical security techniques, such as modulation obfuscation (MO). In this paper, we first derive the probability distribution function for the residual CFO under Gaussian noise. Using this distribution, we compute the maximum-likelihood demodulation boundaries for OFDM signals in a non-closed form. For modulation schemes with unequal-amplitude reference constellation points (e.g., 16-QAM and higher, APSK, etc.), the "optimal" boundaries have irregular shapes, and more importantly, they depend on the time since the last CFO correction instance, e.g., reception of frame preamble. To approximate the optimal boundaries and provide a practical (real-time) demodulation scheme, we explore machine learning techniques, specifically, support vector machine (SVM). Our SVM approach exhibits better accuracy and lower complexity in the test phase than other state-of-the-art machine-learning approaches. As a case study, we apply our CFO-aware demodulation to enhance the performance of a MO technique. Our analytical results show a gain of up to 3 dB over conventional demodulation schemes, which exceeds 3 dB in complete system simulations. Finally, we implement our scheme on USRPs and experimentally corroborate our analytic and simulation-based findings.

Abstract-Contractive interference functions introduced by Feyzmahdavian et al. is the newest approach in the analysis and design of distributed power control laws. This approach can be extended to several cases of distributed power control. One of the distributed power control scenarios wherein the contractive interference functions have not been employed is the power control in MIMO systems. In this paper, this scenario will be analyzed. In addition, the optimal linear precoder is employed in each user to achieve maximum point-to-point information rate. In our approach, we use the same amount of signaling as the previous methods did. However, we show that the uniqueness of Nash equilibria is more probable in our approach, suggesting that our proposed method improves the convergence performance of distributed power control in MIMO systems. We also show that the proposed power control algorithm can be implemented asynchronously, which gives a noticeable flexibility to our algorithm given the practical communication limitations.