The Department of Transport in the United Kingdom recorded 25,080 motor vehicle fatalities in 2019. This situation stresses the need for an intelligent transport system (ITS) that improves road safety and security by avoiding human errors with the use of autonomous vehicles (AVs). Therefore, this survey discusses the current development of two main components of an ITS: (1) gathering of AVs surrounding data using sensors; and (2) enabling vehicular communication technologies. First, the paper discusses various sensors and their role in AVs. Then, various communication technologies for AVs to facilitate vehicle to everything (V2X) communication are discussed. Based on the transmission range, these technologies are grouped into three main categories: long-range, medium-range and short-range. The short-range group presents the development of Bluetooth, ZigBee and ultra-wide band communication for AVs. The medium-range examines the properties of dedicated short-range communications (DSRC). Finally, the long-range group presents the cellular-vehicle to everything (C-V2X) and 5G-new radio (5G-NR). An important characteristic which differentiates each category and its suitable application is latency. This research presents a comprehensive study of AV technologies and identifies the main advantages, disadvantages, and challenges.

The existing sub-6 GHz band is insufficient to support the bandwidth requirement of emerging data-rate-hungry applications and Internet of Things devices, requiring ultrareliable low latency communication (URLLC), thus making the migration to millimeter-wave (mmWave) bands inevitable. A notable disadvantage of a mmWave band is the significant losses suffered at higher frequencies that may not be overcome by novel optimization algorithms at the transmitter and receiver and thus result in a performance degradation. To address this, Intelligent Reflecting Surface (IRS) is a new technology capable of transforming the wireless channel from a highly probabilistic to a highly deterministic channel and as a result, overcome the significant losses experienced in the mmWave band. This paper aims to survey the design and applications of an IRS, a 2-dimensional (2D) passive metasurface with the ability to control the wireless propagation channel and thus achieve better spectral efficiency (SE) and energy efficiency (EE) to aid the fifth and beyond generation to deliver the required data rate to support current and emerging technologies. It is imperative that the future wireless technology evolves toward an intelligent software paradigm, and the IRS is expected to be a key enabler in achieving this task. This work provides a detailed survey of the IRS technology, limitations in the current research, and the related research opportunities and possible solutions.

This paper proposes low complexity detection for internet of underwater things communication. The signal is transmitted from the source to the destination using several sensors. To simplify the computational operations at the transmitter and the sensory nodes, a single carrier frequency domain equalizer is proposed and amplify-and-forward protocols are employed. Fast Fourier transform and use of cyclic prefix are also proposed to simplify these algorithms when compared to time-domain equalization. As precise channel data is difficult to capture in underwater communications, the adaptive implementation of FDE is proposed as a solution that can be employed when the channel experiences a fast doppler shift. The two adaptive detectors are based on the least mean-square and recursive least square principles. Numerical simulations show that the performance of the bit error rate performance of the proposed detectors is close to that of the ideal minimum mean square error.

In this paper, an analytical framework is presented for device detection in an impulse radio (IR) ultra-wide bandwidth (UWB) system and its performance analysis is carried out. The Neyman–Pearson (NP) criteria is employed for this device-free detection. Different from the frequency-based approaches, the proposed detection method utilizes time domain concepts. The characteristic function (CF) is utilized to measure the moments of the presence and absence of the device. Furthermore, this method is easily extendable to existing device-free and device-based techniques. This method can also be applied to different pulse-based UWB systems which use different modulation schemes compared to IR-UWB. In addition, the proposed method does not require training to measure or calibrate the system operating parameters. From the simulation results, it is observed that an optimal threshold can be chosen to improve the ROC for UWB system. It is shown that the probability of false alarm, $P_{FA}$, has an inverse relationship with the detection threshold and frame length. Particularly, to maintain $P_{FA}<{10}^{-5}$ for a frame length of 300 ns, it is required that the threshold should be greater than $2.2$. It is also shown that for a fix $P_{FA}$, the probability of detection $P_D$ increases with an increase in interference-to-noise ratio (INR). Furthermore, $P_D$ approaches 1 for INR $>-2$ dB even for a very low $P_{FA}$ i.e., $P_{FA}=1\times {10}^{-7}$. It is also shown that a 2 times increase in the interference energy results in a 3 dB improvement in INR for a fixed $P_{FA}=0.1$ and $P_D=0.5$. Finally, the derived performance expressions are corroborated through simulation.

Electronically steerable parasitic array radiator (ESPAR) technology enables the implementation of antenna arrays of a number of elements with a single radio frequency (RF) source. Two approaches to achieve stable transmission using an ESPAR antenna (EA) are to increase the self-resistance of an EA or to transmit signals closely approximating the actual signals that keep the EA stable. Both approaches did not take into account the impact of limited power on an EA transmission, which is a practical constraint on power amplifier design. We propose a new transmission scheme to enable an EA to provide stable multiple antenna functionality taking into account the instantaneous total power requirement. This problem is formulated as a non-convex optimization problem and it is solved analytically by coordinate transformation and geometric analysis. The optimal approximate signals are obtained using root finding and interior-point algorithms. Moreover, it is shown through simulations that our proposed scheme achieves similar symbol error rate performance to that of the standard multiple antenna transmitter with multiple RF chains under power limited single-user and multi-user transmission scenarios. Furthermore, it is shown that increasing the self-resistance of an EA to achieve stability is highly power inefficient.

This paper proposes low complexity detection for internet of underwater things (IoUT)s communication. The signal is transmitted from the source to the destination using several sensors. To simplify the computational operations at the transmitter and the sensory nodes, a single carrier frequency domain equalizer (SC-FDE) is proposed and amplify-and-forward (AF) protocols are employed. Fast Fourier transform (FFT) and use of cyclic prefix (CP) are also proposed to simplify these algorithms when compared to time-domain equalization. As precise channel data is difficult to capture in underwater communications, the adaptive implementation of FDE is proposed as a solution that can be employed when the channel experiences a fast doppler shift. The two adaptive detectors are based on the least mean-square (LMS) and recursive least square (RLS) principles. Numerical simulations show that the performance of the bit error rate (BER) performance of the proposed detectors is close to that of the ideal minimum mean square error (MMSE).