Search

This paper presents a Vlasov antenna with curved cut shape and improved reflector position and geometry suitable for high power microwave applications. The curved shape of the proposed cut totally eliminates the sharp edges and angles present in Vlasov antennas with step and bevel cuts. Furthermore, with the proposed reflector configuration, the wave is radiated in the direction of the axis of the waveguide. A Vlasov antenna, designed for operation at 3 GHz, is used to compare the three cut types. An additional comparison is conducted to validate the concept of the enhanced reflector position, using the bevel-cut antenna and the improved cut. The proposed antenna results in increased antenna gain and in good performance in terms of sidelobe level and half-power beamwidth, with maximum radiation directed toward the axis of the waveguide center.

This paper presents multiband circularly polarized (CP) antennas for radio frequency identification (RFID). A coax-fed and a microstrip-line-fed antennas having optimized cross-slots in their patches are first designed for dual-band CP operation. The microstrip-line-fed design is then modified, by incorporating a U-shaped slot in its partial ground plane, to achieve additional operation band with a CP characteristic. Simulation and measured results of the presented designs are reported. The measured results are in accordance with the computed ones. The compact size and CP property make these designs suitable for RFID applications.

A cognitive transceiver is required to opportunistically use vacant spectrum resources licensed to primary users. Thus, it relies on a complete adaptive behavior composed of: reconfigurable radio frequency (RF) parts, enhanced spectrum sensing algorithms, and sophisticated machine learning techniques. In this paper, we present a review of the recent advances in CR transceivers hardware design and algorithms. For the RF part, three types of antennas are presented: UWB antennas, frequency-reconfigurable/tunable antennas, and UWB antennas with reconfigurable band notches. The main challenges faced by the design of the other RF blocks are also discussed. Sophisticated spectrum sensing algorithms that overcome main sensing challenges such as model uncertainty, hardware impairments, and wideband sensing are highlighted. The cognitive engine features are discussed. Moreover, we study unsupervised classification algorithms and a reinforcement learning (RL) algorithm that has been proposed to perform decision-making in CR networks.

Spectrum scarcity has emerged as a primary problem in the communications technology. The combination of cognitive radio (CR) and ultra-wideband impulse radio (UWB-IR) has been proposed to solve the shortage problem by allowing smart and adaptive spectrum management, leading to UWB-CR. In a UWB-CR scheme, secondary users are supposed to ensure interference avoidance by adaptively selecting the portions of the spectrum not being used by primary users. In this paper, three different techniques for the generation of adaptive UWB pulses are studied. The Parks-McClellan algorithm is employed, a neural network is trained, and a reconfigurable band stop filter is designed to generate an adaptive waveform with nulls at specific frequencies. Simulations, measurements, and analysis show that each generated UWB pulse has remarkable advantages in the frequency utilization, spectrum avoidance, and hardware implementation.