Search

The ever-increasing demands of vehicular networks pose significant challenges such as availability, computation complexity, security, trust, authentication, etc. This becomes even more complicated for high-speed moving vehicles. As a result, increasing the capacity of these networks has been attracting considerable awareness. In this regard, the next generation of cellular networks, 5G, is expected to be a promising solution enabling high data rates, capacity, and quality of service as well as low latency communications. However, 5G networks still face challenges in providing ubiquitous and reliable connections among high-speed vehicles. Thus, to overcome the gaps in the existing solutions, we propose a software defined network (SDN)-based consolidated framework providing end-to-end security and privacy in 5G enabled vehicular networks. The framework simplifies network management through SDN, while achieving optimized network communications. It operates in two phases: first, an elliptic curve cryptographic based authentication protocol is proposed to mutually authenticate the cluster heads and certificate authority in SDN-based vehicular setups, and, second, an intrusion detection module supported by tensor based dimensionality reduction is designed to reduce the computational complexity and identify the potential intrusions in the network. In order to assess the performance of the proposed framework, an extensive evaluation is performed on three simulators; NS3, SUMO, and SPAN. To harness the potential benefits of the proposed model, the first module, is evaluated on the basis of security features, whereas the second module is evaluated, and compared with the existing state-of-the-art models, on the basis of detection rate, false positive rate, accuracy, detection time, and communication overhead. The simulation results indicate the superiority of the proposed framework as compared to the existing models. [ABSTRACT FROM AUTHOR]

Evidence indicates that demands from mobile users (MU) on popular cloud content, e.g., video clips, account for a dramatic increase in data traffic over cellular networks. The repetitive downloading of hot content from cloud servers will inevitably bring a vast quantity of redundant data transmissions to networks. A strategy of distributively pre-storing popular cloud content in the memories of small-cell base stations (SBS), namely, small-cell caching, is an efficient technology for reducing the communication latency whilst mitigating the redundant data streaming substantially. In this paper, we establish a commercialized small-cell caching system consisting of a network service provider (NSP), several video providers (VP), and randomly distributed MUs. We conceive this system in the context of 5G cellular networks, where the SBSs are ultra-densely deployed with the intensity much higher than that of the MUs. In such a system, the NSP, in charge of the SBSs, wishes to lease these SBSs to the VPs for the purpose of making profits, whilst the VPs, after pushing popular videos into the rented SBSs, can provide faster local video transmissions to the MUs, thereby gaining more profits. Specifically, we first model the MUs and SBSs as two independent Poisson point processes, and develop, via stochastic geometry theory, the probability of the specific event that an MU obtains the video of its choice directly from the memory of an SBS. Then, with the help of the probability derived, we formulate the profits of both the NSP and the VPs. Next, we solve the profit maximization problem based on the framework of contract theory, where the NSP acts as a monopolist setting up the optimal contract according to the statistical information of the VPs. Incentive mechanisms are also designed to motivate each VP to choose a proper resource-price item offered by the NSP. Numerical results validate the effectiveness of our proposed contract framework for the commercial caching system. [ABSTRACT FROM AUTHOR]

Abstract Non-orthogonal multiple access (NOMA) schemes have been recognized as a promising multiple access method for the fifth generation (5G) communication systems. In NOMA, multiple users can share the same physical channel, which allows for a substantial increase in capacity gains when comparing to conventional orthogonal multiple access (OMA) techniques. This paper considers the downlink transmission of NOMA schemes combined with single-carrier (SC) signals. We present a multi-antenna transmission technique that is compatible with highly efficient power amplifiers without requiring any pre-processing. Furthermore, a multi-user detection scheme based on iterative frequency-domain equalization (FDE) is presented. We show that besides the high power-efficiency of the transmission scheme, the system's performance can be close to the matched filter bound (MFB). [ABSTRACT FROM AUTHOR]

This research work explores small cell densification as a key technique for next generation wireless network (NGWN). Small cell densification comprises space (i.e, dense deployment of femtocells) and spectrum (i.e., utilization of frequency band at large). The usage of femtocells not only improves the spectral efficiency (SE) of the Heterogeneous two-tier networks against conventional approach, but also it alleviates outage probability and enhances the achievable capacity. We yield an analytical framework to establish the density of the femto base station (FBS) to a monotonically increasing or decreasing function of distance or radius, respectively. This ensures the enhanced performance in spectrum sharing Orthogonal Frequency Division Multiple Access (OFDMA) femtocell network models. We also illustrate the influence of active Femto users (i.e., users in femtocells, and they are usually low mobility and located closer to the cell center with less fading), cluster size (i.e., a group of adjacent macrocells which use all of the systems frequency assignments) via simulation results. [ABSTRACT FROM AUTHOR]

Modern fog network architectures, empowered by IoT applications and 5G communications technologies, are characterized by the presence of a huge number of mobile nodes, which undergo frequent handovers, introducing a significant load on the involved network entities. Considering the distributed and flat nature of these architectures, DMM can be the only viable option for efficiently managing handovers in these scenarios. The existing DMM solutions are capable of providing smooth handovers, but lack robustness from the security point of view. Indeed, DMM depends on external mechanisms for handover security and uses a centralized device, which has obvious security and performance implications in flat architectures where hierarchical dependencies can introduce problems. We propose a new DMM schema based on the blockchain, capable of resolving hierarchical security issues without affecting the network layout, and also satisfying fully distributed security requirements with less consumption of energy. [ABSTRACT FROM PUBLISHER]

With the rapid development of future wireless networks, device-to-device (D2D) technology is widely used as the communication system in the Internet of Things (IoT) fifth generation (5G) network. The IoT 5G network based on D2D communication technology provides pervasive intelligent applications. However, to realize this reliable technology, several issues need to be critically addressed. Firstly, the device's energy is constrained during its vital operations due to limited battery power; thereby, the connectivity will suffer from link failures when the device's energy is exhausted. Similarly, the device's mobility alters the network topology in an arbitrary manner, which affects the stability of established routes. Meanwhile, traffic congestion occurs in the network due to the backlog packet in the queue of devices. This paper presents a Mobility, Battery, and Queue length Multipath-Aware (MBMQA) routing scheme for the IoT 5G network based on D2D communication to cope with these key challenges. The back-pressure algorithm strategy is employed to divert packet flow and illuminate the device selection's estimated value. Furthermore, a Multiple-Attributes Route Selection (MARS) metric is applied for the optimal route selection with load balancing in the D2D-based IoT 5G network. Overall, the obtained simulation results demonstrate that the proposed MBMQA routing scheme significantly improves the network performance and quality of service (QoS) as compared with the other existing routing schemes. [ABSTRACT FROM AUTHOR]

The fog computing-based device-driven network is a promising solution for high data rates in modern cellular networks. It is a unique framework to reduce the generated-data, data management overheads, network scalability challenges, and help us to provide a pervasive computation environment for real-time network applications, where the mobile data is easily available and accessible to nearby fog servers. It explores a new dimension of the next generation network called fog networks. Fog networks is a complementary part of the cloud network environment. The proposed network architecture is a part of the newly emerged paradigm that extends the network computing infrastructure within the device-driven 5G communication system. This work explores a new design of the fog computing framework to support device-driven communication to achieve better Quality of Service (QoS) and Quality of Experience (QoE). In particular, we focus on, how potential is the fog computing orchestration framework? How it can be customized to the next generation of cellular communication systems? Next, we propose a mobility management procedure for fog networks, considering the static and dynamic mobile nodes. We compare our results with the legacy of cellular networks and observed that the proposed work has the least energy consumption, delay, latency, signaling cost as compared to LTE/LTE-A networks. [ABSTRACT FROM AUTHOR]

In this paper, we present a few novel simultaneous wireless information and power transfer (SWIPT) schemes that can be effectively used in various 5G wireless network implementations. First, we study the possibility of integrating distributed energy beamforming with the data rate fairness beamforming in a cooperative communication system with multiple cooperative relays and multiple destination users communicating simultaneously. We show that the system exploits significant performance gain using such a joint energy and data rate fairness beamforming scheme. Further, we propose an enhanced version of the SWIPT scheme, the energy-efficient modulation-based non-orthogonal multiple access (M-NOMA) SWIPT scheme, and observe its system efficiency in terms of more harvested energy. Finally, we consider an energy-harvesting SWIPT scheme where the channel response is estimated using the energy-harvesting signal as pilots superimposed on the information signal. For such a scheme, we compute the optimum transmit power ratio between the pilot and information signals under varying SNR conditions and improve the accuracy of the decoding process at the reception. [ABSTRACT FROM AUTHOR]