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Transportation and installation of a wind turbine system is one of the main factors for business availability of offshore wind power due to its high cost and technical difficulty. The purpose of this study is to develop an innovative transportation and installation method for offshore wind turbines. We refer to this installation process as an All-In-One-Installation (A.I.O.I), and the special vessel used is referred to as a multipurpose mobile base (MMB). In this study, the short-range transportation and penetration and pull-out tests of the entire wind turbine system are performed before field demonstration. All the offshore wind turbine systems were transported and installed safely at one time. Field demonstration was conducted on the installation site approximately 15 km from the harbor in approximately 5 h using the suction method. In the actual A.I.O.I demonstration test, stable values were obtained. The respective changes in inclination at the center of the MMB and the tower were within 0.1° and 0.2° during operation, respectively, because of the reduction of longitudinal and transverse sway of the MMB induced by the self-weight assembly and ballast. The presented method constitutes an innovative transportation and installation method useful for the offshore wind power industry demonstrating single-day installation feasibility. This installation method can be used to configure the fleet in the development of large-scale offshore wind farms, but it is also possible to install turbines in individual units for research or small businesses. With minor A-Frame modifications, it can be applied as a multipurpose vessel to maintain the blades or heavy components, or can be used for pile driving, or for the lifting/installation of offshore structures. [ABSTRACT FROM AUTHOR]

In this letter, we have studied how to use simultaneous collision-free duplexing (SCD) in point-to-multipoint environment. SCD is a method exchanging uplink and downlink signals simultaneously using the same resource for each link and has the advantages in that it does not need complicated self-interference cancellation unlike full duplexing. In addition, SCD is different from dynamic time division duplexing (D-TDD) in which interlink interference can be completely avoided. Therefore, to analyze the effect of interlink interference on SCD, we have derived the upper bound of link capacity and the required value of interlink isolation level for better SCD performance than D-TDD. We have verified the analyzed isolation level and confirmed that SCD has good performance even in practical point-to-multipoint environment through simulation. [ABSTRACT FROM AUTHOR]

The convenience and energy efficiency of electric trams have resulted in their rapid adoption in many areas of the world. Despite trams’ many advantages, overhead lines installed along the track cause severe problems, such as safety issues, maintenance problems, and difficulty in renovating the urban road system. To solve these problems, a wireless charging electric tram system has been developed to replace the overhead lines, catenary, and pantograph. With wireless charging segments installed underground, a tram can operate freely without any support from overhead lines. In order to successfully commercialize a wireless charging tram system, it is essential to minimize the energy cost of the wireless charging tram system. In this article, a model of a wireless charging electric tram system and an energy cost minimization algorithm are proposed. The Manchester Metrolink tram network is modeled using the Google Maps API, the Google Transit API, and the Metrolink API to simulate the wireless charging system under massive public transportation network. To determine the minimum energy cost, an energy cost minimization algorithm for the wireless charging tram system is proposed based on decentralized multiagent reinforcement learning with feedback. The numerical results show that the proposed algorithm can reduce costs while ensuring stable operation. [ABSTRACT FROM AUTHOR]

In heterogeneous network, it is important to mitigate cross-tier interference. Resource partitioning is the one of solution to reduce interference. However, most of studies on partitioning assumed that there was only one network operator to cooperate with. In this letter, we study the network selection problem of small access points in heterogeneous networks, which are provided by multiple network operators. We model the multiple network operators scenario as a congestion game. To solve the equilibrium point of suggested game, we analyze some features of proposed model such as potential game property, smoothed best response dynamics and logit equilibrium. Then, we propose a reinforcement learning algorithm that can reach logit equilibrium in distributed way. Moreover, we also suggest the adjustment of learning parameters to enhance adaptability. By means of simulations, it is shown that proposed algorithm has near-optimal performance in view of throughput, fairness and adaptability. [ABSTRACT FROM AUTHOR]

In a massive machine-type communication (MTC) environment, a traffic control algorithm is essential to solving traffic congestion problems. Additionally, as MTC applications have diverse quality-of-service requirements, traffic control should be applied in a way that guarantees diverse requirements. Therefore, we propose a priority-based access class barring (PACB) scheme, in which MTC devices are divided into multiple classes according to their delay requirements, and a different access class barring (ACB) factor is used for each class. This article suggests an approach to choose multiple ACB factors that can maximize the number of successful access events and can also guarantee the low delay requirement of the high-priority class. Then, an analytical model is proposed for the ideal case, and throughput, drop probability, and access delay are derived to evaluate the performance. For a realistic environment, we also suggest an estimation algorithm for the PACB scheme, in which a base station estimates the number of active devices for each class. Numerical and simulation results showed that the analytical model is consistent with the simulation results. Additionally, the performance of the estimation algorithm was similar to that of the ideal case. Furthermore, the proposed PACB scheme can decrease the delay of a high-priority class and improve the throughput and drop probability compared to existing algorithms. [ABSTRACT FROM AUTHOR]

Recent advancements in machine learning for communications show that channel autoencoders could revolutionize conventional communication systems through end-to-end optimization. For channel autoencoders to reliably transmit over the air, a scheme to enable adaptive use of resources is needed. Thus, we propose ConvAE-Advanced, an improved channel autoencoder structure that can adaptively transmit across multiple timeslots. ConvAE-Advanced utilizes an unexploited input dimension in ConvAE by the use of the resource-aware residual block and whole resource power normalization. This enabled ConvAE-Advanced to adaptively transmit information according to channel conditions. Simulations for a 2-by-2 multiple-input multiple-output system under the WINNER2 A1 scenario shows that ConvAE-Advanced outperforms ConvAE across all SNR ranges. Most importantly, ConvAE-Advanced can achieve a better BER and achievable rate performance without additional wireless resource usage compared to ConvAE. [ABSTRACT FROM AUTHOR]

This communication presents foliage channel measurements at 28 GHz using a directional channel sounder. The measurements were conducted in vegetated areas of typical residential environments in Daejeon, South Korea. We first propose a pattern matching algorithm that allows us to overcome the angle resolution of a directional antenna and to estimate a more accurate receiving angle. Then propagation paths received from the vegetation and the surrounding buildings are classified and their power ratios are analyzed. Furthermore, foliage attenuation was determined from the measurement data according to the foliage depth, and appropriate models based on the modified exponential decay (MED) model and the maximum attenuation (MA) model are presented. In addition, the effect of foliage attenuation on seasonal variation is studied. These results will be useful for predicting path losses through the vegetated areas at 28 GHz by modeling the foliage loss as an additional path loss term. Finally, spatial–temporal channel characteristics in a vegetated environment were statistically analyzed including delay spread, coherence bandwidth, and angular spreads. [ABSTRACT FROM AUTHOR]

This article proposes a four-port integrated antenna structure with a dielectric medium, which can be used to increase the pattern gain. To enhance the multiple-input–multiple-output (MIMO) performance, a low correlation is required between antenna elements. First, the refraction effect of the proposed medium is explained, including a derivation of the phase variation. Second, a new four-port integrated monopole antenna is proposed, which operates at 2.4 GHz and is appropriate for supporting a beamforming technique with high gain and small size. The proposed antenna can be useful for reducing correlation with the use of a dielectric medium to increase the pattern gain. This allows the achievable MIMO channel capacity to be increased to the ideal MIMO gain by increasing the pattern gain. [ABSTRACT FROM AUTHOR]

Traffic congestion of a random access (RA) link can be resolved by clustering machine type communication devices (MTCDs) and using an aggregator. However, since a packet needs to wait in the aggregator, clustering may cause an additional delay. To solve this problem, this letter suggests a partially clustered access scheme (PCAS) in which direct-access MTCDs (dMTCDs) and clustered-access MTCDs (cMTCDs) are serviced together. We provided an analytical model and an energy consumption model for PCAS. Numerical and simulation results showed that clustering may improve a success ratio. Furthermore, the delay requirement of dMTCDs and the energy consumption requirement of cMTCDs can be guaranteed by using PCAS. [ABSTRACT FROM AUTHOR]

In this letter, we propose ConvAE, a new channel autoencoder structure. ConvAE uses residual blocks with convolutional layers. This configuration increases performance while decreasing computational complexity at run-time compared with conventional channel autoencoders. The simulations using both conventional and proposed autoencoders for a 2-by-2 multiple-input multiple-output (MIMO) system under Rayleigh and Nakagami-m fading show that the ConvAE is able to attain a lower bit error rate and higher achievable rate relative to the conventional channel autoencoder schemes. [ABSTRACT FROM AUTHOR]

In this paper, we consider a dynamic time division duplex system based on a cloud radio access network (RAN) to support the ultimate goal of efficient resource utilization. To optimize the performance of both remote radio heads (RRHs) and user equipments (UEs) which have multiple antennas, we propose an iterative scheme consisting of four types of beamforming, namely downlink (DL) transmit beamforming, DL receive beamforming, uplink (UL) transmit beamforming, and UL receive beamforming, in an attempt to minimize mean squared error (MSE). The proposed beamforming scheme makes it possible to allow DL and UL transmission be supported simultaneously by managing interference between RRHs and UEs. Our simulation results show that the MSE and the bit error rate (BER) are greatly improved under the proposed beamforming algorithm compared to conventional schemes. From intensive system level simulations, the proposed algorithm points out more than 3 dB performance improvement in terms of the required signal-to-noise-ratio (SNR) to achieve the BER less than $10^{-3}$ compared to conventional schemes. [ABSTRACT FROM AUTHOR]

In this paper, a means of transmit power control for underlaid device-to-device (D2D) communication is proposed based on deep learning technology. In the proposed scheme, the transmit power of D2D user equipment (DUE) is autonomously learned via a deep neural network such that the weighted sum rate (WSR) of DUEs can be maximized by considering the interference from cellular user equipment. Unlike conventional transmit power control schemes in which complex optimization problems have to be solved in an iterative manner, which possibly requires long computation time, in our proposed scheme the transmit power can be determined with a relatively low computation time. Through simulations, we confirm that the proposed scheme achieves a sufficiently high WSR with a sufficiently low computation time. [ABSTRACT FROM AUTHOR]

A modified uplink sparse code multiple access (SCMA) scheme with receive beamforming is herein proposed. Although a base station equipped with multiple antennas can support many users simultaneously using multi-beams, the complexity of the optimal SCMA system may be too large to be implemented in view of a practical system. Therefore, a two stage SCMA system with receive beamforming is proposed, based on uplink scheduling and three step layer selection. Analysis and simulation results of the proposed scheme showed the advantage of large complexity reduction with little performance degradation. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel method of managing a semidynamic cluster through the use of a reinforcement learning. We derive some concepts from reinforcement learning that could be suitable for cooperative networks. We also verify the performance of proposed algorithm by means of a simulation, in which we examined spectral efficiency and convergence properties. The proposed algorithm represents a considerable improvement for edge users in particular. In addition, we analyze the complexity of the clustering schemes. Our proposed algorithm is effective in the environment where there is a limited computational resource. [ABSTRACT FROM AUTHOR]

This letter presents a calibration technique for uniform circular array orbital angular momentum systems that can estimate and compensate for gain/phase mismatch among radio-frequency (RF) chains in the transmitter and the receiver simultaneously. The basic idea is that the RF chain mismatch parameters can be estimated from a mathematical model of channel estimates when the ideal channel matrix is knowna priori. It is shown that the maximum-likelihood (ML) channel estimation error becomes a zero-mean complex Gaussian random variable, and then, a joint ML solution for the RF mismatch parameters is derived. [ABSTRACT FROM AUTHOR]

In this paper, we try to solve the imbalance problem of communication data service and energy supply among receivers in energy harvesting based wireless networks, with receivers equipped with modules that could either decode information or harvest energy from radio frequency signals. We formulate a biconvex optimization problem and find the solutions for subchannel and power allocation. Based on the obtained solutions, we propose a proportional fair resource allocation algorithm using an iterative method, and also show the convergence of the proposed algorithm to the partial optimum solution. Simulation results show that the proposed algorithm improves, to a remarkable extent, fairness among the receivers in terms of both the data rate and the harvested energy. At the same time, the proposed algorithm is found to lead to a negligible loss of system throughput compared with other conventional algorithms. [ABSTRACT FROM AUTHOR]

In energy-limited networks, battery-powered nodes suffer from energy famine, which can reduce network lifetime and affect the robustness of networks. To alleviate an energy problem, it is possible to harvest energy from ambient radio frequency signals. In this paper, we consider a proportional fair energy efficiency, which jointly considers energy efficiency and fairness in energy-harvesting-based wireless networks. We formulate a nonconvex optimization problem for solving subchannel and power allocation in order to maximize proportional fair energy efficiency. Using nonlinear fractional programming, we transform the optimization problem into a tractable convex problem. We also derive the solution of the transformed problem and propose a resource allocation algorithm using an iterative method. In addition, we prove the convergence of the proposed algorithm in view of a suboptimal point. Through intensive simulations, we compare the performance of our proposed algorithm with those of conventional algorithms. It is shown that the proposed algorithm improves fairness considerably while maintaining energy efficiency, compared with conventional algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we propose a non orthogonal multiple access (NOMA) system using coexisting narrow and wide beams to increase total capacity. In our proposed system, a base station considers the state of user mobility and supports users with either a narrow or a wide beam according to the mobility state. The proposed NOMA system uses the beam gain between a narrow and a wide beam, as well as the power gain from the pathloss difference in NOMA scheme. The system is thus less influenced by user mobility at the point of NOMA pairing. In the proposed system, we consider two power allocation schemes, namely the max and fair power allocation methods, and propose a pairing algorithm to maximize the capacity by minimizing the interference between narrow and wide beam user. The result verifies that the proposed system improves sum throughput, compared with the OMA and conventional NOMA system. [ABSTRACT FROM AUTHOR]

In this letter, deep power control (DPC), which is the first transmit power control framework based on a convolutional neural network (CNN), is proposed. In DPC, the transmit power control strategy to maximize either spectral efficiency (SE) or energy efficiency (EE) is learned by means of a CNN. While conventional power control schemes require a considerable number of computations, in DPC, the transmit power of users can be determined using far fewer computations enabling real-time processing. We also propose a form of DPC that can be performed in a distributed manner with local channel state information, allowing the signaling overhead to be greatly reduced. Through simulations, we show that the DPC can achieve almost the same or even higher SE and EE than a conventional power control scheme, with a much lower computation time. [ABSTRACT FROM AUTHOR]

Sparse code multiple access (SCMA) is a promising code-based non-orthogonal multiple-access technique that can provide improved spectral efficiency and massive connectivity meeting the requirements of 5G wireless communication systems. We propose a deep learning-aided SCMA (D-SCMA) in which the codebook that minimizes the bit error rate (BER) is adaptively constructed, and a decoding strategy is learned using a deep neural network-based encoder and decoder. One benefit of D-SCMA is that the construction of an efficient codebook can be achieved in an automated manner, which is generally difficult due to the non-orthogonality and multi-dimensional traits of SCMA. We use simulations to show that our proposed scheme provides a lower BER with a smaller computation time than conventional schemes. [ABSTRACT FROM PUBLISHER]

High peak-to-average power ratio (PAPR) has been one of the major drawbacks of orthogonal frequency division multiplexing (OFDM) systems. In this letter, we propose a novel PAPR reduction scheme, known as PAPR reducing network (PRNet), based on the autoencoder architecture of deep learning. In the PRNet, the constellation mapping and demapping of symbols on each subcarrier is determined adaptively through a deep learning technique, such that both the bit error rate (BER) and the PAPR of the OFDM system are jointly minimized. We used simulations to show that the proposed scheme outperforms conventional schemes in terms of BER and PAPR. [ABSTRACT FROM PUBLISHER]

The millimeter-wave (mm-wave) band will be a key component of fifth-generation (5G) wireless communication systems. This paper presents radio propagation measurements and analysis investigating the wideband directional channel characteristics of the mm-wave transmission for in-building and urban cellular communication systems in the 28-GHz band. Based on the measurements, we analyze and model the spatio-temporal channel characteristics such as multipath delay, angular statistics, and path loss. In particular we investigate the clustering of the multipath components, and investigate both the intra-cluster and inter-cluster distributions. Based on these investigations, we present a complete channel model suitable for system simulations in the in-building and urban environments. [ABSTRACT FROM PUBLISHER]

Multihop cellular networks offer a cost-effective solution to the problem of achieving higher capacity and extending coverage by using relay stations (RSs) deployed within the coverage area of a base station (BS). We herein consider directional transmission based on adaptive beamforming in which multiple users are served at the same time using multiple directional beams; this represents one promising technology that could improve the capacity of multihop cellular network. In directional transmission, severe intra-BS/RS, inter-BS-RS, and inter-RS interferences can occur due to the concurrent transmission and accordingly, system performance can be degraded severely. In this paper, we propose resource allocation to maximize the system capacity of multihop cellular networks by taking into account these severe interferences caused in multihop cellular network using directional transmission. To alleviate the problem of high computational complexity, we propose a sub-optimal scheme. A heuristic scheme is also proposed which can be performed in distributed manner with lower computational complexity. Through simulation results, we show that the use of our proposed schemes increases system capacity. [ABSTRACT FROM AUTHOR]

We investigate the stability of the transmission efficiency (TE) in nonradiative wireless power transfer (WPT) using a relay resonator. An equivalent circuit model is used to show mathematically that two suppositions are satisfied in an overcoupled region: first, the TE of relay-based WPT systems is always larger than that of conventional two-coil-based WPT systems, and second, as the coupling coefficient increases, the TE of two-coil-based WPT systems decreases severely, while the TE of relay-based WPT systems increases slightly. Consequently, we surmise that an intermediate relay can be used to achieve higher TE and stability, compared with conventional two-coil-based WPT systems. We verify that our analytical results are in good agreement with the experimental ones. [ABSTRACT FROM AUTHOR]

The problem of spectrum scarcity has raised the prospect of coexisting network. For example, long-term evolution-licensed-assisted access (LTE-LAA & Wi-Fi) can operate in the same frequency band. However, interference between the two different radio access technologies can severely reduce the performances of both networks. To mitigate this interference, the concept of an almost blank subframe (ABS) has been proposed. However, because the LTE-LAA macrocell must remain silent, this provides no incentive for its throughput enhancement. In this letter, we propose a transaction between LTE-LAA and Wi-Fi using ABS together with offloading. We model a time-resource utility model by jointly considering the resource consumed for ABS and offloading, and then formulate a coalition game. To achieve the solution of a coalition game, we consider two fairness concepts: min-max and Shapley fairness. We then verify the performance of the proposed game using simulations. It is shown that the proposed game model can improve resource utilization through the joint use of ABS and offloading. [ABSTRACT FROM PUBLISHER]

We herein consider directional transmission based on adaptive beamforming in which multiple vehicles are served at the same time using multiple directional beams; this represents one promising technology that could improve the capacity of vehicle-to-infrastructure (V2I) communication. We propose an iterative resource-allocation method to maximize the capacity of V2I communication by taking into proper account the interference between directional beams, which reduces capacity. We also consider a heuristic resource allocation scheme, which has significantly less computational complexity than the iterative scheme and negligible performance degradation. We make use of computer simulations to show that the capacity of V2I communication can be improved using our proposed schemes. [ABSTRACT FROM PUBLISHER]

Recently, self-healing has been actively investigated for mitigating an unforeseen network failure. In particular, to enable self-healing operations in indoor wireless communications systems, an autonomous mechanism to resolve unforeseen network failure problems should be considered. Therefore, we here address the issue of autonomous self-healing, in which continuous connectivity can be provided to users by resolving unexpected network failures. To overcome this problem, we propose a low-complexity resource allocation algorithm based on an optimization approach with reduced message passing. In the proposed algorithm, normal base stations perform subchannel and power allocations with a minimum amount of information sharing (NH(M-1)) to provide reliable service to users in faulty cells autonomously. We also show that the proposed algorithm converges to a unique fixed point in the low-interference region by using a contraction mapping technique. Through simulation results, we demonstrate that the proposed algorithm achieves good performances with respect to the average cell capacity, user fairness, and outage probability while reducing the message passing overhead and computational complexity. [ABSTRACT FROM PUBLISHER]

Many alternative systems have been studied based on compact single-RFs for multiple-input multiple-output (MIMO) systems. However, the implementation of such systems has been limited by a lack of robustness in relation to system environment. In this letter, we propose a novel MIMO system based on a repetitive pulse width modulation, which requires a single-RF and switches only, without the need for a phase shifter. The mathematical formulations for the proposed system are derived and the signal difference between our proposed system and a conventional MIMO system is shown mathematically. The performance of the proposed system is verified by comparing its channel capacity with that of a conventional MIMO system. [ABSTRACT FROM PUBLISHER]

In this letter, we consider the asynchronous detection of diffusion-based molecular communications in timing modulation channel. We propose a symbol detection algorithm that can be used in asynchronous systems. Using the variance of the arrival time of a large number of information molecules arriving at a receiver, it is possible to estimate an average propagation time and the emitting time of each bit from a transmitter, and a transmitted bit sequence can also be decoded. The error probability of the proposed algorithm is analyzed, and it is shown that there is good agreement between analysis and simulation results. [ABSTRACT FROM PUBLISHER]

The need for a new version of a next-generation wireless communication system to handle coinstantaneous downlink (DL) and uplink (UL) traffic is increasing as the asymmetry in DL and UL traffic increases and the traffic flows become more variable. We here propose a DL transmit beamforming algorithm for DL radio remote heads (RRHs), a UL receive beamforming algorithm for UL RRHs, and a power allocation algorithm for UL users. These algorithms are designed to maximize the energy efficiency of a dynamic time division duplex (TDD) based cloud radio access network (C-RAN) system that simultaneously supports DL and UL transmission. Simulation results show that the system developed is more energy efficient to a remarkable degree than conventional algorithms. [ABSTRACT FROM PUBLISHER]

Opportunistic scheduling schemes based on random linear network coding (RLNC) are proposed in this letter. The schemes are developed taking into consideration channel state information and acknowledgement information in time varying channels. We derived an overall success probability and a total symbol length (or a total transmission delay) to evaluate conventional RLNC and proposed RLNC schemes. Numerical results showed that the proposed RLNC schemes offer significant advantages over the conventional RLNC scheme in various environments. [ABSTRACT FROM PUBLISHER]

To improve the packet success probability, random linear network coding (RLNC) based on non-orthogonal multiple access (NOMA) for multicast services was employed in wireless downlink networks where a source superposes multiple coded packets before transmitting these packets to multiplexing groups of receivers in a power domain. Using a successive interference cancellation (SIC) and a Gauss-Jordan elimination process, receivers can recover their original packets. We derive expressions for the total packet success probability for the case of NOMA (or OMA) with (or without) RLNC, and propose group based power allocation schemes in order to improve performance with a low overhead. Through the results of simulations, we verify our derivations and show that RLNC based on NOMA improves the packet success probability and decreases the packet delay. [ABSTRACT FROM PUBLISHER]

Scheduling based on random linear network coding is an effective way of improving system performance in a wireless network. In a time-varying channel environment, it is important to take the effects of outdated channel-state information (CSI) into consideration when scheduling because the CSI used may be different from the real CSI for data transmissions due to mobility and feedback delays. Here, we analyze the outage probability for scheduling based on random linear network coding in an outdated CSI environment. Practical scenarios are assessed so that the outage probability performance can be evaluated reliably. [ABSTRACT FROM PUBLISHER]

Wi-Fi networks are widely deployed for provision of Internet-centric data services. Since the inception of the Wi-Fi network in 1997 with its technical specification rooted in the IEEE 802.11 standard, much progress for higher data throughput has been made. Currently popular IEEE 802.11n Wi-Fi network in 2.4/5 GHz can deliver 600 Mb/s over a 40 MHz channel, which works well for most types of Internet-centric data services, and a later version of a Wi-Fi network based on IEEE 802.11ac is able to transmit at about 7 Gb/s. A simple configuration of a Wi-Fi network consisting of an AP and multiple stations for bidirectional data transmission enables low-cost implementation. High data rate provided at low cost as well as the abundance of Wi- Fi-capable mobile stations recently led to dense deployment of Wi-Fi networks, particularly in residential areas, business offices, and indoor/ outdoor hotspots. However, dense deployment of Wi-Fi networks (e.g., Wi-Fi DenseNets) causes significantly increased overall interference, and as a result a significantly lowered achievable data rate. Thus, it is sensible to consider technologies that can resolve or mitigate deteriorated throughput of Wi-Fi DenseNets. In this article, technologies to deal with throughput enhancement of Wi-Fi DenseNets are addressed from three different perspectives: exploiting cellular technology for data transmission, elevating spectral efficiency, and controlling overall interference levels. Evaluation of interference control for Wi-Fi DenseNets is carried out in this article, and it is found that significant per-node throughput enhancement can be achieved. [ABSTRACT FROM PUBLISHER]