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.

Abstract-The design of high-efficiency low-complexity detection schemes for ultrawide bandwidth (UWB) systems is highly challenging. This paper proposes a reduced-rank adaptive multiuser detection (MUD) scheme that is operated in least bit-error-rate (LBER) principles for hybrid direct-sequence time-hopping UWB (DS-TH UWB) systems. The principal component analysis (PCA)-assisted rank-reduction technique is employed to obtain a detection subspace, where the reduced-rank adaptive LBER-MUD is carried out. The reduced-rank adaptive LBER-MUD is free from channel estimation and does not require knowledge about the number of resolvable multipaths and the multipaths' strength. In this paper, the BER performance of the hybrid DS-TH UWB systems using the proposed detection scheme is investigated, assuming communications over UWB channels modeled by the Saleh-Valenzuela channel model. Our studies and performance results show that, given a reasonable rank of the detection subspace, the reduced-rank adaptive LBER-MUD can efficiently mitigate both multiuser and intersymbol interference (ISI) and achieve the diversity gain promised by the UWB systems.Index Terms-Adaptive detection, direct sequence, least bit error rate (LBER), principal component analysis (PCA), reduced-rank detection, time hopping, ultrawide bandwidth (UWB).

This paper investigates and compares the performance of various ultrawide bandwidth (UWB) systems when communicating over Nakagami-m fading channels. Specifically, the directsequence (DS), time-hopping (TH) and hybrid direct-sequence time-hopping (DS-TH) UWB systems are considered. The performance of these UWB systems is studied, when using the conventional single-user correlation detector or the minimum mean-square error (MMSE) multiuser detector. Our simulation results show that the hybrid DS-TH UWB system may outperform a corresponding pure TH-UWB or pure DS-UWB system in terms of the achievable error performance. Given the total spreading gain of the hybrid DS-TH UWB system, there is an optimal setting of the TH spreading factor and DS spreading factor, which results in the best error performance.

In this paper a range of reduced-rank adaptive multiuser detectors (MUDs) are proposed and investigated for the hybrid direct-sequence time-hopping ultrawide bandwidth (DS-TH UWB) systems. The adaptive MUDs are operated based on the recursive least square (RLS) principles. Three types of reduced-rank techniques are investigated, which are the principal component (PC), cross-spectral metric (CSM) and Taylor polynomial approximation (TPA). These reduced-rank adaptive techniques are beneficial to achieving low-complexity, high spectral-efficiency and robust detection in hybrid DS-TH UWB systems. In this contribution bit error rate (BER) performance of the hybrid DS-TH UWB systems using proposed reduced-rank adaptive MUDs is investigated by simulations, when communicating over UWB channels modelled by the SalehValenzuela (S-V) channel model. Our simulation results show that, given a sufficiently high rank of the detection subspace, the reduced-rank adaptive MUDs are capable of achieving a similar BER performance as that of the full-rank ideal minimum meansquare error MUD (MMSE-MUD) but with significantly lower detection complexity. Furthermore, the TPA-based reduced-rank adaptive MUD is capable of yielding a better BER performance than the PC-or CSM-based reduced-rank adaptive MUD, when the same but relatively low rank detection subspace is assumed.Index Terms-Ultrawide bandwidth, hybrid direct-sequence time-hopping, adaptive detection, reduced-rank detection, recursive least square.

Multivariate generalized Gaussian density (MGGD) is used to approximate the multiple access interference (MAI) and additive white Gaussian noise in pulse-based ultrawide bandwidth (UWB) system. The MGGD probability density function (pdf) is shown to be a better approximation of a UWB system as compared to multivariate Gaussian, multivariate Laplacian and multivariate Gaussian-Laplacian mixture (GLM). The similarity between the simulated and the approximated pdf is measured with the help of modified Kullback-Leibler distance (KLD). It is also shown that MGGD has the smallest KLD as compared to Gaussian, Laplacian and GLM densities. A receiver based on the principles of minimum bit error rate is designed for the MGGD pdf. As the requirement is stringent, the adaptive implementation of the receiver is also carried out in this paper. Training sequence of the desired user is the only requirement when implementing the detector adaptively.Index Terms-Ultrawide bandwidth, bit error rate, multiple access interference, Kullback-Leibler distance.

Abstract-In this letter, a new detector is proposed for amplifyand-forward (AF) relaying system when communicating with the assistance of L relays. The major goal of this detector is to improve the bit error rate (BER) performance of the receiver. The probability density function is estimated with the help of kernel density technique. A generalized Gaussian kernel is proposed. This new kernel provides more flexibility and encompasses gaussian and uniform kernels as special cases. The optimal window width of the kernel is calculated. Simulations results show that a gain of more than 1 dB can be achieved in terms of BER performance as compared to the minimum mean square error (MMSE) receiver when communicating over Rayleigh fading channels.

This paper investigates and compares the performance of wireless sensor networks where sensors operate on the principles of cooperative communications. We consider a scenario where the source transmits signals to the destination with the help of L sensors. As the destination has the capacity of processing only U out of these L signals, the strongest U signals are selected while the remaining (L − U) signals are suppressed. A preprocessing block similar to channel-shortening is proposed in this contribution. However, this preprocessing block employs a rank-reduction technique instead of channel-shortening. By employing this preprocessing, we are able to decrease the computational complexity of the system without affecting the bit error rate (BER) performance. From our simulations, it can be shown that these schemes outperform the channel-shortening schemes in terms of computational complexity. In addition, the proposed schemes have a superior BER performance as compared to channel-shortening schemes when sensors employ fixed gain amplification. However, for sensors which employ variable gain amplification, a tradeoff exists in terms of BER performance between the channel-shortening and these schemes. These schemes outperform channel-shortening scheme for lower signal-to-noise ratio. Index Terms-Cooperative communications, channel shortening, reduced-rank techniques, selection combining. I. INTRODUCTION In wireless sensor networks (WSNs), the fundamental task is to broadcast data from the origin sensor to the destination. However, due to the limited size, power and cost of these sensors, a low power signal is often transmitted to the destination [1-3]. This low power signal is further attenuated due to the propagation loss. To combat this problem, the signal is sometimes measured by as many sensors as possible [1, 2]. These sensors form a distributed cooperative sensor network,

Device-to-device (D2D) assisted offloading heavily depends on the participation of human users. The content preference and sharing willingness of human users are two crucial factors in the D2D assisted offloading. In this paper, with consideration of these two factors, the optimal content pushing strategy is investigated by formulating an optimization problem to maximize the offloading gain measured by the offloaded traffic. Users are placed into groups according to their content preferences, and share content with intergroup and intragroup users at different sharing probabilities. Although the optimization problem is nonconvex, the closed-form optimal solution for a special case is obtained, when the sharing probabilities for intergroup and intragroup users are the same. Furthermore, an alternative group optimization (AGO) algorithm is proposed to solve the general case of the optimization problem. Finally, simulation results are provided to demonstrate the offloading performance achieved by the optimal pushing strategy for the special case and AGO algorithm. An interesting conclusion drawn is that the group with the largest number of interested users is not necessarily given the highest pushing probability.It is more important to give high pushing probability to users with high sharing willingness.