A new compact UWB multiple-input–multiple-output (MIMO) antenna is presented in this paper. The proposed antenna, with a compact size of 30 × 20 × 1.6 mm³, consists of a two-element microstrip line-fed pentagonal-shaped patch associated with a parasitic element and a partial ground plane. Three complementary split-ring resonator (CSRR) structures are integrated into the defected ground with the aims of reducing the mutual coupling and enhancing the bandwidth. A UWB impedance bandwidth is achieved covering the FCC band (3.1–10.6 GHz), corresponding to a reflection coefficient below −10 dB and a reduced mutual coupling below −22 dB. Additionally, acceptable limits of the diversity performance parameters are obtained. Furthermore, all the simulated outcomes of the suggested antenna are convenient for UWB-MIMO wireless applications. Measures carried out on the fabricated prototype of the antenna demonstrate good agreement between both the simulation and measurement results of the optimized two-port MIMO antenna.

Display field communication (DFC) is a frequency-domain unobtrusive display-to-camera (D2C) communication, in which an electronic display serves as a transmitter and a camera serves as a receiver. In this paper, we propose a machine learning-based DFC scheme and evaluate its performance in a lab test scenario. First of all, we adopt the Discrete Cosine Transform (DCT) to transform a spatial-domain image into its spectral-domain equivalent. To reduce the computational complexity during the data-embedding process, addition allocation and subtraction data retrieval techniques are used. Moreover, channel coding is applied to overcome the data error caused by the optical wireless channel. In particular, robust turbo coding is used for error detection and correction. Afterward, we perform the experiments to validate the performance of the proposed system. After capturing the displayed image with a camera, data restoration is done using a deep learning technique. Extensive real-world experiments were performed considering various geometric distortions, noise, and different standard input images. As a result, we found that by increasing the transmit display image size (upsampling), the overall error rate can be reduced. In addition, real-world noise analysis is performed and it is notified that the actual noise is dominant in the low-frequency region of an image. The experimental results confirm the robust performance of the proposed DFC scheme and show that an error-free performance can be achieved up to a distance of 1 m in the given lab test environment setting.

Terahertz band (0.1–10 THz) nanocommunications are expected to have a plethora of biomedical, industrial, and military applications. A pulse‐based modulation scheme could enable communications among nano‐devices. Nevertheless, synchronisation could be a significant performance limiting factor and an arduous task to accomplish considering the huge bandwidth of the transmitted pulse, and the simple design and energy constraint requirements of the nano‐transceivers. This study proposes a novel synchronisation scheme for pulse‐based nanocommunication based on a continuous‐time moving average (CTMA) algorithm. Since CTMA uses an energy collection approach, it does not increase the energy and complexity requirements of nano‐transceivers. This approach is based on continuously moving sub‐integration windows and searching for the maximum energy over the entire preamble duration. The simulation results showed that using the proposed scheme, for a distance of up to 5 mm, a synchronisation probability of >0.7 was obtained for a signal energy to noise ratio (SNR) of 20 dB. The results showed good performance in terms of the tradeoff among the synchronisation probability, SNR, and distance between nanonodes. Moreover, synchronisation error was also evaluated to check the overall performance of the scheme. Altogether, the proposed scheme makes an appropriate step forward to enable nanocommunication among resource‐constrained nanonetworks.

Terahertz (THz)-band nanocommunication is envisioned to revolutionize the future of wireless communications by enabling applications in nanoscale domains such as the Internet of Nanothings, wireless on-chip communications, and advanced health monitoring. However, communication between nanodevices is hindered by the highly frequency-selective and distance-dependent nature of the THz channel, which ultimately restricts nanocommunication distances to a few millimeters. Moreover, attempts by multiple nanodevices to access the channel simultaneously increase the interference in the overall communication system. In this study, a new pulse-based modulation scheme for nanonetworks called time-hopping multilevel pulse position modulation (TH ML-PPM) is proposed and its performance in a multiuser nanocommunication scenario is analyzed. In ML-PPM, each nanomachine in the nanonetwork first transforms the transmitted bits into multilevels by using several orthogonal codes and then modulates each multilevel code into a pulse position. The generated ML-PPM signal is subsequently time-hopped to achieve multiple access. Employing orthogonal coding results in spreading gain at the nanoreceiver, which improves the performance of the proposed scheme. The bit error rate and link capacity of the time-hopped multilevel PPM scheme are evaluated for different THz propagation conditions and system design parameters. The results show that for a THz channel with 10% water vapor concentration, a link capacity of more than 100 gigabits per second is achieved across a transmission distance of 0.5 mm.

The widespread growth of the Internet-of-Things (IoT) and its dependence on the license-exempt Industrial, Scientific, and Medical (ISM) bands have made spectrum resources scarce. IoT can nonetheless get advantage from the Cognitive Radio (CR) technology to resolve the spectrum shortage issue. Since in CR networks the unlicensed Secondary Users (SUs) can exploit the white spaces in licensed channels of Primary Users (PUs) opportunistically. CR ad hoc networks are more useful in IoT due to ease of installation, low cost, and less complexity. However, CR ad hoc networks are prone to the rendezvous issue and hidden primary terminal problem. Moreover, the available channels in the CR system are not identical, PUs’ and SUs’ activities can diversify them as well. In this connection, channel selection by SUs is a complex balancing act since the transmission opportunities are space, frequency and time bounded. In this paper, we hence proposed a new Ranked Sense Multiple Access with Collision Avoidance (RSMA/CA) protocol for multichannel CR-based IoT networks. Our proposed RSMA/CA protocol not only resolves the hidden primary terminal problem but also avoids hidden and exposed terminal problems at the same time by mutual spectrum sensing. We suggest a new channel ranking mechanism to rank the available channels based on the long term qualities of the channels, PUs’ return rate, and SUs’ activities and tailor-made the algorithms in an existing scheme to make the rendezvous process more efficient. We analyze the performance of our proposed RSMA/CA in terms of normalized throughput through the Markov chain model and compared with that of the existing scheme. Simulation results show that our RSMA/CA protocol outperforms the existing scheme due to efficient rendezvous and access mechanisms.