Forward error correction in 5G heterogeneous network

In this research, the feasibility of developing a complete polar FEC chain of 5th generation cellular mobile communication standard in software. Specifically, on general purpose processors. Paper work attempts to achieve stringent latency requirements through software, algorithmic and platform specific optimizations. Many algorithms in FEC chain are optimized for hardware implementations. Direct implementation of these algorithms in software results in poor performance. To obtain best performance in terms of latency on general purpose processors, these algorithms are modified or reformulated to suit processor architecture and software implementation. Initially both encoding and decoding FEC chains are implemented naively without any optimization. Code profiling is performed on this naive implementation to identify the significant latency contributors. The research split algorithms of significant latency contributing components into primitive operations. These primitive operations are optimized either with software optimizations or mapped to specialized functional units of a general-purpose processor to achieve best performance using CRC calculation in 5G cellular networks. Optimizations reduced the worst-case latency of the encoding FEC chain from 158µs which is more than 10x reduction in latency with communication rate

Caching D2D connections in small-cell networks

Small-cell network is a promising solution to high video traffic. However, with the increasing number of devices, it cannot meet the requirements from all users. Thus, we propose a caching device-to-device (D2D) scheme for small-cell networks, in which caching placement and D2D establishment are combined. In this scheme, a limited cache is equipped at each user, and the popular files can be prefetched at the local cache during off-peak period. Thus, dense D2D connections can be established during peak time aided by these cached users, which will reduce the backhaul pressure significantly. To do this, first, an optimal caching scheme is formulated according to the popularity to maximize the total offloading probability of the D2D system. Thus, most edge users can obtain their required video files from the caches at users nearby, instead from the small-cell base station. Then, the sum rate of D2D links is analyzed in different signal-to-noise ratio (SNR) regions. Furthermore, to maximize the throughput of D2D links with low complexity, three D2Dlink scheduling schemes are proposed with the help of bipartite graph theory and Kuhn-Munkres algorithm for low, high and medium SNRs, respectively. Simulation results are presented to show the effectiveness of the proposed scheme

Transceiver design and multi-hop D2D for UAV IoT coverage in disasters

When natural disasters strike, the coverage for Internet of Things (IoT) may be severely destroyed, due to the damaged communications infrastructure. Unmanned aerial vehicles (UAVs) can be exploited as flying base stations to provide emergency coverage for IoT, due to its mobility and flexibility. In this paper, we propose multi-antenna transceiver design and multi-hop device-to-device (D2D) communication to guarantee the reliable transmission and extend the UAV coverage for IoT in disasters. Firstly, multi-hop D2D links are established to extend the coverage of UAV emergency networks due to the constrained transmit power of the UAV. In particular, a shortest-path-routing algorithm is proposed to establish the D2D links rapidly with minimum nodes. The closed-form solutions for the number of hops and the outage probability are derived for the uplink and downlink. Secondly, the transceiver designs for the UAV uplink and downlink are studied to optimize the performance of UAV transmission. Due to the non-convexity of the problem, they are first transformed into convex ones and then, low-complexity algorithms are proposed to solve them efficiently. Simulation results show the performance improvement in the throughput and outage probability by the proposed schemes for UAV wireless coverage of IoT in disasters

Trust and reputation management for securing collaboration in 5G access networks: the road ahead

Trust represents the belief or perception of an entity, such as a mobile device or a node, in the extent to which future actions and reactions are appropriate in a collaborative relationship. Reputation represents the network-wide belief or perception of the trustworthiness of an entity. Each entity computes and assigns a trust or reputation value, which increases and decreases with the appropriateness of actions and reactions, to another entity in order to ensure a healthy collaborative relationship. Trust and reputation management (TRM) has been investigated to improve the security of traditional networks, particularly the access networks. In 5G, the access networks are multi-hop networks formed by entities which may not be trustable, and so such networks are prone to attacks, such as Sybil and crude attacks. TRM addresses such attacks to enhance the overall network performance, including reliability, scalability, and stability. Nevertheless, the investigation of TRM in 5G, which is the next-generation wireless networks, is still at its infancy. TRM must cater for the characteristics of 5G. Firstly, ultra-densification due to the exponential growth of mobile users and data traffic. Secondly, high heterogeneity due to the different characteristics of mobile users, such as different transmission characteristics (e.g., different transmission power) and different user equipment (e.g., laptops and smartphones). Thirdly, high variability due to the dynamicity of the entities’ behaviors and operating environment. TRM must also cater for the core features of 5G (e.g., millimeter wave transmission, and device-to-device communication) and the core technologies of 5G (e.g., massive MIMO and beamforming, and network virtualization). In this paper, a review of TRM schemes in 5G and traditional networks, which can be leveraged to 5G, is presented. We also provide an insight on some of the important open issues and vulnerabilities in 5G networks that can be resolved using a TRM framework

Secure Social Networks in 5G Systems with Mobile Edge Computing, Caching, and Device-to-Device Communications

Mobile social networks (MSNs) have continuously been expanding and trying to be innovative. Recent advances of mobile edge computing (MEC), caching, and device-to-device (D2D) communications can have significant impacts on MSNs in 5G systems. In addition, the knowledge of social relationships among users is important in these new paradigms to improve the security and efficiency of MSNs. In this article, we present a social trust scheme that enhances the security of MSNs. When considering the trust-based MSNs with MEC, caching, and D2D, we apply a novel deep reinforcement learning approach to automatically make a decision for optimally allocating the network resources. Google TensorFlow is used to implement the proposed deep reinforcement learning approach. Simulation results with different network parameters are presented to show the effectiveness of the proposed scheme

Survey and taxonomy of clustering algorithms in 5G

The large-scale deployment of fifth generation (5G) is expected to produce a massive amount of data with high variability due to ultra-densification and the rapid increase in a heterogeneous range of applications and services (e.g., virtual reality, augmented reality, and driver-less vehicles), and network devices (e.g., smart gadgets and sensors). Clustering organizes network topology by segregating nodes with similar interests or behaviors in a network into logical groups in order to achieve network-level and cluster-level enhancements, particularly cluster stability, load balancing, social awareness, fairness, and quality of service. Clustering has been investigated to support mobile user equipment (UE) in access networks, whereby UEs form clusters themselves and may connect to BSs. In this paper, we present a comprehensive survey of the research work of clustering schemes proposed for various scenarios in 5G networks and highlight various aspects of clustering schemes, including objectives, challenges, metrics, characteristics, performance measures. Furthermore, we present open issues of clustering in 5G