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The sixth-generation (6G) wireless cellular network integrates several wireless bands and modes with the objectives of improving quality of service (QoS) and increasing network connectivity. The 6G environment includes asymmetrical heterogeneous networks (HetNets) with the intention of making effective use of the available frequencies. However, selecting a suitable gNB and a communication channel that works for users in the network is an enormous challenge in 6G HetNets. This paper investigates a joint user association (UA) and channel allocation (CA) problem in two-tier HetNets by considering the downlink scenario to improve QoS. Our study presents an innovative scheme for user association and channel allocation, wherein the user can be connected to either the macro base station (MBS) or a possible small base station (SBS) in a direct or relay-assisted link. Furthermore, the proposed scheme identifies the optimal channel to be allocated to each user so that the overall network QoS can be maximized. A symmetric matching game-based user association is proposed to find the optimal association for users. Moreover, a modified auction game is applied to allocate the optimal channel by considering the quota of each gNB. Regarding connection probability, throughput, energy efficiency (EE), and spectrum efficiency (SE), the simulation results show that the proposed approach performs well over the state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

Long Term Evolution (LTE) is the prominent technology in Fourth Generation (4G) communication standards, which provides higher throughput and better Quality of Service (QoS) to all users. However, users in the cell-edge area are receiving comparatively low QoS due to the distance from eNodeB (eNB) and bad channel conditions. The Conventional Modified Largest Weighted Delay First (MLWDF) algorithm is unable to resolve this issue, as it does not consider the location of the user. This paper proposes an extended MLWDF (EMLWDF) downlink scheduling algorithm to provide better services to the cell-edge user as well as to the cell-center user. The proposed algorithm divides the eNB cell area into inner and outer regions. It includes the distance of the user from attached eNB, received Signal to Interference plus Noise Ratio (SINR) and error probability into the original algorithm. The simulated results are compared with other well-known algorithms and the comparison shows that the proposed algorithm enhances overall 56.23% of cell-edge user throughput and significantly improves the average user throughput, fairness index, and spectral efficiency. [ABSTRACT FROM AUTHOR]

Proactive content caching in a fog radio access network (F-RAN) is an efficient technique used to alleviate delivery delay and traffic congestion. However, the symmetric caching of the content is impractical due to the dissimilarity among the contents popularity. Therefore, in this paper, a multi-objective random caching scheme to balance the successful transmission probability (STP) and delay in wireless backhauled F-RAN is proposed. First, stochastic geometry tools are utilized to derive expressions of the association probability, STP, and average delivery delay. Next, the complexity is reduced by considering the asymptotic STP and delay in the high signal-to-noise ratio (SNR) regime. Then, aiming at maximizing the STP or minimizing the delay, the multi-objective cache placement optimization problem is formulated. A novel projected multi-objective cuckoo search algorithm (PMOCSA) is proposed to obtain the Pareto front of the optimal cache placement. The numerical results show that PMOCSA outperforms the original multi-objective cuckoo search algorithm (MOCSA) in terms of convergence to a feasible Pareto front and its rate. It also shows that the proposed multi-objective caching scheme significantly outperforms the well-known benchmark caching schemes by up to 40 % higher STP and 85 % lower average delay. [ABSTRACT FROM AUTHOR]

The application of super-hydrophobic nanomaterials for synthesizing membranes with unique physiochemical properties has gained a lot of interest among researchers. The presence of super-hydrophobic materials inside the membrane matrix can play a vital role not only in the separation of toxins, but also to achieve higher water flux with lower fouling tendencies required for an efficient membrane distillation process. In this research, super-hydrophobic carbon nanomaterials (CNMs) were synthesized using powder activated carbon (PAC) as a precursor, whereby the growth was initiated using a bimetallic catalyst of iron (Fe) and molybdenum (Mo). Until recently, no research has been conducted for synthesis and to observe the catalytic influence of bimetallic catalysts on the physiochemical characteristics of the derived CNMs. The synthesis process was carried out using the chemical vapor deposition (CVD) process. The CVD process was optimized using Box–Behnken factorial design (BBD), whereby 15 experiments were carried out under different conditions. Three input variables, which were percentage composition of catalysts (percentage of Fe and Mo) and reaction time (tr), were optimized with respect to their impact on the desired percentage output of yield (CY) and contact angle (CA). Analysis of variance (ANOVA) testing was carried out. It was observed that the developed model was statistically significant. The highest CY (320%) and CA (172°) were obtained at the optimal loading of 5% Fe and 2% Mo, with a reaction time of 40 min. Surface morphological features were observed using field emission scanning electron microscopic (FESEM) and transmission electron microscopic (TEM) analysis. The images obtained from FESEM and TEM revealed the presence of two types of CNMs, including carbon nanofibers (CNFs) and multiwall carbon nanotubes (CNTs). Thermogravimetric analysis was carried out to observe the temperature degradation profile of the synthesized sample. Raman spectroscopic analysis was also used in order to have a better understanding regarding the proportion of ordered and disordered carbon content inside the synthesized sample. [ABSTRACT FROM AUTHOR]

Coping with the skyrocketing needs for massive amounts of data for the future Fifth Generation (5G) network, Device-to-Device (D2D) communications technology will provide seamless connectivity, high data rates, extended network coverage, and spectral efficiency. The D2D communications are a prevalent emerging technology to achieve the vision of symmetry in the Internet of Things (IoT) services. However, energy resource constraints, network stability, traffic congestion, and link failure of the devices are the crucial impediments to establish an optimal route in the D2D communications based IoT 5G network. These obstacles induced packet drop, rapid energy depletion, higher end-to-end delay, and unfairness across the network, leading to significant route and network performance degradation. Therefore, in this paper, an energy, mobility, queue length, and link quality-aware routing (EMBLR) approach is proposed to overcome the challenges and boost network performance. Moreover, a multicriteria decision making (MCDM) technique is utilized for the selection of the intermediate device in an optimal route. Extensive simulation has been conducted and proven that the proposed routing approach significantly enhances network performance. Overall, results have been carried out in Quality of Service (QoS) performance metrics and compared with other well-known routing approaches. [ABSTRACT FROM AUTHOR]

This paper describes a smart ray-tracing method based on the ray concept. From the literature review, we observed that there is still a research gap on conventional ray-tracing methods that is worthy of further investigation. The herein proposed smart 3D ray-tracing method offers an efficient and fast way to predict indoor radio propagation for supporting future generation networks. The simulation data was verified by measurements. This method is advantageous for developing new ray-tracing algorithms and simulators to improve propagation prediction accuracy and computational speed. [ABSTRACT FROM AUTHOR]

The Millimeter-Wave (mmW) technology is going to mitigate the global higher bandwidth carriers. It will dominate the future network system by the attractive advantages of the higher frequency band. Higher frequency offers a wider bandwidth spectrum. Therefore, its utilizations are rapidly increasing in the wireless communication system. In this paper, an indoor mmW propagation prediction is presented at 38 GHz based on measurements and the proposed Three-Dimensional (3-D) Ray Tracing (RT) simulation. Moreover, an additional simulation performed using 3-D Shooting Bouncing Ray (SBR) method is presented. Simulation using existing SBR and the proposed RT methods have been performed separately on a specific layout where the measurement campaign is conducted. The RT methods simulations results have been verified by comparing with actual measurement data. There is a significant agreement between the simulation and measurement with respect to path loss and received signal strength indication. The analysis result shows that the proposed RT method output has better agreement with measurement output when compared to the SBR method. According to the result of the propagation prediction analysis, it can be stated that the proposed method's ray tracing is capable of predicting the mmW propagation based on a raw sketch of the real environment. [ABSTRACT FROM AUTHOR]