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Resource allocation is a very crucial part of non-orthogonal multiple access(NOMA)-based device-to-device(D2D) systems. It must be fast, effective and flexible because devices, especially vehicles in the system move at high speed. In this paper, we propose a resource allocation method for NOMA-based D2D communication systems based on a genetic algorithm(GA) approach. We have designed a novel concept of genetic algorithm that is suitable for resource allocation in NOMA-based D2D systems. The proposed method quickly maximizes the total throughput of paired devices including cellular user equipment(CUE) and moving vehicles(V). The proposed method is a faster and more reasonable way to converge than an exhaustive search method, which requires up to factorial time complexity.

The attention in the use of permanent magnet motors has highlighted the importance of IPM (Interior Permanent Magnet) structure, high power and high efficiency rotor design. This paper puts forward the optimal design method for unmanned aerial vehicles (UAVs) and interior permanent magnet motors for drones that require high thrust of high rotational speed. The size of the motor stator was fixed to minimize the number of variables in the analysis and only the rotor shape was modified to compare torque and output power.

In this study, the energy resource management strategy applied to the agricultural Range-extended Electric Vehicles (Re-EVs) is proposed. The strategy alerts users based on their power consumption trends and preventing the vehicle from being fully discharged. A strategy of making the most of fuel resources by determining when to operate the generator is introduced. This strategy can be applied to other types of ReEVs with different battery capacity and generator output.

As the society emphasizes individuality, various demands on vehicles are also increasing. Accordingly, development of vehicle technology, suitable for small quantity batch production, is needed. To meet the requirements, this paper studied the technology of the variable architecture chassis platform, and this chassis platform will contribute to the autonomous industrial EV (Electric Vehicle).

This work presents a facile identification method for the crystal orientations of graphene using the directional alignment between AgCN microwires and the underlying graphene. Because the microwires in the present work are visible with conventional optical microscopy, large-area graphene can be inspected with simple procedures. In the experimental study, we confirmed that the microwires can indicate graphene's crystal orientations with an acceptable accuracy as well as can be removed with a simple wet-etching process.

By using the microfluidic spinning technology we generated tiny hydrogel tubular scaffolds. Fibroblast (NIH/3T3) cell cultures were performed for seventeen days to demonstrate the potential of cell attachment on surfaces and encapsulation in the wall of he microscopic scaffolds for blood vessel-like structure forming. Over theculture period, the NIH/3T3 confluence reached around 80\%, and 100\% on the inside and outside scaffolds' surface respectively while cells proliferated and coalesced in cell group in the hydrogel wall. These results could further be applied to endothelial co-culturing for forming engineered blood vessel.

An orthogonal frequency division multiple access-based primary user (PU) network is considered, which provides different spectral access/energy harvesting opportunities in RF-powered cognitive radio networks. In this scenario, we propose an optimal spectrum sensing policy for opportunistic spectrum access/energy harvesting under both the PU collision and energy causality constraints. PU subchannels can have different traffic patterns and exhibit distinct idle/busy frequencies, due to which the spectral access/energy harvesting opportunities are application specific. Secondary user (SU) collects traffic pattern information through observation of the PU subchannels and classifies the idle/busy period statistics for each subchannel. Based on the statistics, we invoke stochastic models for evaluating SU capacity by which the energy detection threshold for spectrum sensing can be adjusted with higher sensing accuracy. To this end, we employ the Markov decision process model obtained by quantizing the amount of SU battery and the duty cycle model obtained by the ratio of average harvested energy and energy consumption rates. We demonstrate the effectiveness of the proposed stochastic models through comparison with the optimal one obtained from an exhaustive method.

In this paper, we proposes an algorithm to estimate the overall arm motion using the MYO armband attached to the upper arm. Thus, we can get EMG data of biceps brachii and triceps brachii when the human stretch or bend his/her arm. The motion of the lower arm is estimated through the EMG signal of the upper arm. The motion of the upper arm is detected through the IMU sensor. To increase the reliability of the data, experimental environment is set up and process of filtering and initialization are performed before motion estimation. Finally, we propose an algorithm with average, sum and rate sequence based on the signals measured on 8 EMG channels of MYO. If the user takes an arbitrary action based on motion in this paper, it is shown by a simulation after algorithm processing.

We consider the downlink of a wireless cellular network which consists of one Macro Base Station (MBS), multiple relays and User Equipments (UEs). In this scenario, we propose relay clustering algorithms to address the problem of inter-cluster interference. In each cluster, we adopt a time-division relaying scheme to avoid intra-cluster interference, but the inter-cluster interference still remains. In interference-aware network, an optimal clustering algorithm requires an exhaustive search, which is infeasible. Hence, we propose a clustering algorithm which improves the system capacity by exploiting the inter-cluster information. But this algorithm is implemented in a centralized manner with high complexity that requires the calculation of inter-cluster information. To circumvent this, we propose a cluster-wise distributed algorithm with manageable complexity, which shows the performance within acceptable range from the optimal one, far better than simple and intuitive algorithms because of the effect of inter-cluster interference.

We consider the downlink of a realistic cellular network composed of multiple clusters, each of which includes multiple relays and a destination terminal. In this scenario, the interference among the clusters is a critical issue, affecting the end-to-end performance of the system significantly. Considering the inter-cluster interference, we propose optimal and suboptimal relay selection schemes to maximize the sum rate of the network. The first algorithm is a truly optimal network-wise relay selection scheme which provides the ultimate performance upper bound. However, the computational complexity and the signaling overhead involved with the optimal scheme are fairly high. Addressing the issues, we propose a suboptimal cluster-wise scheme with a much less computational complexity and signaling overhead. Numerical results demonstrate that the proposed algorithms provide excellent performance.

Mitigating inter-cell interference has become more crucial than before because there is a growing number of base stations (BSs) being placed into the network as a solution to increase the network capacity. To deal with the problem, cache-induced CoMP was recently proposed. It is based on caching a portion of media files, and taking benefits of sharing payload data (CoMP joint processing), but without the need of expensive backhaul. However, the on-off selection of CoMP transmission mode in the recent work [1] limits the efficient usage of cached data. It results in decreasing the chances to enjoy the CoMP joint processing, and hence causes the performance degradation. In this paper, we propose a cache-induced hybrid CoMP to cope with such limitation. By adding additional transmission mode, where some selected base stations are allowed to take advantage of CoMP joint processsing, more portions of cached data are made use of, and hence, CoMP utilization is increased. We optimize the beamforming vectors and the cache control, and simulation results demonstrate that our proposed hybrid CoMP scheme notably reduces the total power consumption of BSs to meet a certain QoS level.

For extended cell coverage and green communication, various small-cell networks, such as femtocells and picocells, are applied to cellular networks. This leads to the reduction of shadow areas and an increase of spectral efficiency with higher cell-edge capacity. Due to increasing heterogeneity, however, small cells cause co-tier and cross-tier interferences which are the critical issue that aggravates the signal-to-interference-plus-noise ratio (SINR) of macro user equipment (MUE). Especially, a MUE in the cell-edge area can be a victim owing to a nearby small-cell access point despite its low transmit power. We propose an interference forwarding (IF) scheme in a dual link for enhancing the SINR at victim MUE, considering a two-tier network where a macrocell and underlaid closed-access small cells coexist, along with device-to-device (D2D) communication between close-by peer MUEs supported. Numerical results with 3-dimensional plot demonstrates that our proposed IF scheme notably improves the achievable spectral efficiency at victim MUE.