In this paper, the design of a circularly polarized (CP) multiple-input–multiple-output (MIMO) antenna system is presented, utilizing a dielectric resonator (DR). This presented antenna system is subsequently integrated with a multifunctional filter, all meticulously structured on a single substrate. The multifunctional filter operates in three modes: reconfigurable band-pass and band-reject filter as well as all-pass filter. The overall structure works as a tunable filtenna. The designed filtenna is expanded into a two-port MIMO system on a unified substrate, providing strong port isolation below −28.5 dB. The overall dimension of proposed radiator is 180 × 180 × 1.6 mm3. The value of peak gain is 5.19 dBic. By switching the states of PIN diodes, the designed filtenna operates as a sensing and communicating antenna for interweave and underlay cognitive radios (CRs). The proposed antenna supports the CP waves within the working band, i.e., 3.6–4.5 GHz. The simulated results are validated by comparing them with the measured results showing less variation among them. MIMO parameters, including the envelope correlation coefficient and diversity gain, have been calculated for the proposed filtenna, representing its suitability for 5G-CR applications.

This paper presents the design and development of broadband modified Koch curve microstrip patch antenna with multiband characteristics for spectrum sensing in cognitive radio applications. The proposed spectrum sensing antenna is designed specifically for its efficient operation in the spectrum (1.683–3.05, 4.246–9.714, and 11.25–18 GHz) specified for L, S, C, X, Ku with broadband characteristics and omnidirectional radiation pattern. The validity of the proposed shape is proved by having a comparison with other fractal shapes available in the literature.

We analyse the coverage performance of cognitive radio networks powered by renewable energy. Particularly, with an energy harvesting module and energy storage module, the primary transmitters (PTs) and the secondary transmitters (STs) are assumed to be able to collect ambient renewables, and store them in batteries for future use. Upon harvesting sufficient energy, the corresponding PTs and STs (denoted by eligible PTs and STs) are then allowed to access the spectrum according to their respective medium access control (MAC) protocols. For the primary network, an Aloha-type MAC protocol is considered, under which the eligible PTs make independent decisions to access the spectrum with probability $\unicode[STIX]{x1D70C}_{p}$. By applying tools from stochastic geometry, we characterize the transmission probability of the STs. Then, with the obtained results of transmission probability, we evaluate the coverage (transmission nonoutage) performance of the overlay CR network powered by renewable energy. Simulations are also provided to validate our analysis.

This paper presents a simple reconfigurable bandpass filter switching from 2.4 to 5 GHz based on PIN diodes. The proposed filter is intended to add frequency-tunability to antenna systems used in cognitive radio applications. It consists of a bent connecting stub with two open-circuited quarter-wave stubs grounded via PIN diodes. By controlling the didoes states, the electrical length of the stubs can be switched from quarter-wave to half-wave and vice versa, so as to tune the filter center frequency. The proposed design approach consists of ensuring communication at 2.4 GHz while blocking the 5 GHz band in the ON state, whereas in the OFF state, the filter is intended to reject the 2.4 GHz band and passing the 5 GHz band. A prototype of the proposed filter is fabricated and measured to validate the proposed concept. Both simulated and measured results show a two-state filter with a wide tuning range from 2.4 to 5 GHz and a good stopband rejection level better than 40 dB. Moreover, a flat group delay of about 0.55–0.7 ns is achieved within the operating bandwidth in both states. The proposed filter is able to achieve simultaneous bandwidth and frequency control, showing an important tool to meet modern system requirements.

In this paper, the benefits of adaptive preselect filtering are investigated by analyzing mote-to-mote throughput in the presence of interference. In a city-wide deployment of a sensor network, of the 150 wireless sensor nodes deployed in our urban test system, five nodes were electrically “lost”. Surprisingly, the limiting factor was not the signal strength, but the neighboring cell towers that caused nearby interference. Therefore, we explored the effect of an adaptive front end to mitigate these nearby interferers. The sensor motes operated at a fixed band, the unlicenced band of 902 to 928 MHz, and did not have the frequency adaptability of future cognitive radios. However, the effect was demonstrative of the potential benefits of adaptive preselect filtering. The measured result shows substantial improvements over the fixed band system by even slight tuning of the bandwidth and/or the center frequency of the preselect filter. Experimentally and numerically, we show that both tuning in the filter bandwidth and/or center frequency can significantly improve the packet reception rate. Guidelines for achieving an optimized filtering technique are given to provide a broad understanding of how the adaptable preselect filtering can be utilized.

The measurements of physical level parameters can become the area where decisions about cognitive radio will have the most striking effect. Field-programmable gate array (FPGA) enables real-time analyses of physical layer data to satisfy constraints like dynamic spectrum allocations, data throughput, and the coding rate. Cognitive radio will be based on simple network management techniques, using remote procedure calls. Intelligent knowledge-base system (IKBS) techniques will be used to search the parameter space in selecting changes to the system. Worldwide Interoperability for Microwave Access (WiMAX) PHY-layer functions will be managed cognitively by a FPGA-based controller to optimize the performance of the system. Instead of simple bit loading methods, the global multi-criteria optimization promise possibility to adapt more parameters with respect to several objectives. In this paper, the application of particle swarm optimization to fixed WiMAX-OFDM (Orthogonal Frequency Division Multiplexing) parameter adaptation is presented and compared with the greedy bit loading algorithm.