A novel physical layer (PHY) transmission technique for increasing the channel capacity of transmission, termed as Orthogonal Generalized Frequency Division Multiplexing (OGFDM), has been proposed, investigated and evaluated in this paper. A combination of the Digital Hilbert Filter (DHF) with Generalized Frequency Division Multiplexing (GFDM) has been shown to double wireless channel capacity for each transmitted frequency sub-carrier at acceptable Bit Error Rate (BER) limits. By making use of the great properties of Hilbert transforms, orthogonality is achieved between the traditionally non-orthogonal GDFM subcarriers improving the BER and wireless channel capacity of the transmission. The OGFDM seems to combine the attributes of GFDM and Orthogonal Frequency Division Multiplexing (OFDM) in one sustainable system. The proposed solution achieves orthogonality between the filters of adjacent frequencies of subcarriers instead of between the frequencies of subcarriers themselves. Also, an OGFDM system model is presented, based on which, the relation between the main filter parameters and the system BER and channel capacity performance is specified in a wireless electrical back-to-back transmission system. Finally, by means of simulations, the impact of applying the proposed advanced filters on the aggregated system performance of the BER and channel capacity is shown in an Additive White Gaussian Noise (AWGN) wireless channel.

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In this paper, a new multi-carrier candidate waveform for the future generation of mobile (5G) is introduced, explored and evaluated. The newly developed design of the Orthogonal Generalized Frequency division multiplexing (OGFDM) can improve the performance in terms of the channel capacity and Bit Error Rate (BER) for the wireless transmission of the multi-carrier system. In addition, compared to the most candidate waveform, Generalized Frequency Division Multiplexing (GFDM), the innovative multi-carrier OGFDM can double, boost and even maximize the capacity of wireless channel at the acceptable level of the BER. This is essentially achieved due to major adaptations have been made on the Filtration level, Oversampling level and Modulation level of the currently recommended GFDM. Thus, depending on the Digital Hilbert Filter (DHF), the presented solution can attain the orthogonality between the un-orthogonal filtered subcarriers of the multicarrier GFDM technique. Moreover, by utilizing an adjustable oversampling factor, the examined system can stay reliable even in the worst conditions of the wireless channel. Furthermore, employing the adaptive bit loading instead of the fixed modulation format, the announced waveform can reach the maximum rate of transmission with the venial limit of error. The main parameters of each promoted level are precisely specified in accordance with the optimum system performance. Besides, the different levels of the multi-carrier OGFDM are presented in the physical layer (PHY) of a wireless electrical back-to-back transceiver system. A MATLAB simulation was introduced to evaluate the system performance (BER & channel capacity) in presence of the Additive White Gaussian Noise (AWGN).

Neighbor Discovery Protocol (NDP) is stateless and lacks of authentication which exposes it to flooding attacks. Securing NDP is critical due to the large deployment of open network. Commonly existing solutions for securing NDP violate its design principle in terms of overhead and complexity. Other solutions suffer from high false positive alerts which affects solution trustiness. This paper aims to investigate the use of machine learning mechanism for detecting NDP flooding attacks. It was found that the advantage of using machine learning is that the detection can be done without relying on attack signatures they can learn broader definitions of attack attributes.

Due to high mobility and nature of vehicular adhoc environment, routing decisions in such a network are becoming a hard task. Therefore, the routing protocol must be robust to frequent link disruptions and aware of the environment surrounding the network. It is noticeable that routing-based position protocols are more appropriate for high dynamic and fast topology change networks. Many routing protocols have been proposed to enhance the delivery of data packets in a vehicular network. The goal of this paper is to review the current position-based routing protocols, in order to get more insight on the capability of these routing protocols in handling different challenges of vehicular ad-hoc networks.

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The characteristics of Vehicular Ad-Hoc Networks (VANETs) such as highly dynamic topology impose various challenges and constraints on routing protocols. These challenges should be managed effectively by the routing protocol. Geographic forwarding-based routing protocols are found to be effective in VANET, where geographic location information is utilized to select the next-hop for packet forwarding. Forwarding strategy is known as the core of such protocols to select the suitable forwarder among neighbouring nodes that can enhance the performance of routing strongly. Several research works have been developed to improve the forwarding strategy in VANET. However, some key issues such as utilizing the vehicle density to improve forwarding decision and reduce network congestion were not addressed. In this paper, an innovative forwarding strategy, called Density-aware Directional (DAD), with a joint consideration of vehicle density factor and directional forwarding is proposed for next-hop selection. It is aimed to manage the number of candidate next-hops as function of density and reduce routing loop by involving a directional angle. The proposed forwarding strategy was analyzed numerically to verify that it achieves the target properties.