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Rail transportation, especially, high-speed rails (HSR), is an important infrastructure for the development of national economy and the promotion of passenger experience. Due to the large bandwidth, millimeter wave (mmWave) communication is regarded as a promising technology to meet the demand of high data rates. However, since mmWave communication has the characteristic of high attenuation, mobile relay (MR) is considered in this paper. Also, full-duplex (FD) communications have been proposed to improve the spectral efficiency. However, because of the high speed, as well as the problem of penetration loss, passengers on the train have a poor quality of service. Consequently, an effective user association scheme for HSR in mmWave band is necessary. In this paper, we investigate the user association optimization problem in mmWave mobilerelay systems where the MRs operate in the FD mode. To maximize the system capacity, we propose a cooperative user association approach based on coalition formation game, and develop a coalition formation algorithm to solve the challenging NP-hard problem. We also prove the convergence and Nashstable property of the proposed algorithm. Extensive simulations are done to show the system performance of the proposed scheme under various network settings. It is demonstrated that the proposed distributed low complexity scheme achieves a nearoptimal performance and outperforms two baseline schemes in terms of average system throughput., Comment: 11 pages, 11 figures

With the development of wireless communication, higher requirements arise for train-ground wireless communications in high-speed railway (HSR) scenarios. The millimeter-wave (mm-wave) frequency band with rich spectrum resources can provide users in HSR scenarios with high performance broadband multimedia services, while the full-duplex (FD) technology has become mature. In this paper,we study train-ground communication system performance in HSR scenarios with mobile relays (MRs) mounted on rooftop of train and operating in the FD mode. We formulate a nonlinear programming problem to maximize network capacity by allocation of spectrum resources. Then, we develop a sequential quadratic programming (SQP) algorithm based on the Lagrange function to solve the bandwidth allocation optimization problem fortrack-side base station (BS) and MRs in this mm-wave train-ground communication system. Extensive simulation results demonstrate that the proposed SQP algorithm can effectively achieve high network capacity for train-ground communication in HSR scenarios while being robust to the residual self-interference (SI).

With the rapid development of connecting massive devices to the Internet, especially for remote areas without cellular network infrastructures, space-air-ground integrated networks (SAGINs) emerge and offload computation-intensive tasks. In this paper, we consider a SAGIN, where multiple low-earth-orbit (LEO) satellites providing connections to the cloud server, an unmanned aerial vehicle (UAV), and nearby base stations (BSs) providing edge computing services are included. The UAV flies along a fixed trajectory to collect tasks generated by Internet of Things (IoT) devices, and forwards these tasks to a BS or the cloud server for further processing. To facilitate efficient processing, the UAV needs to decide where to offload as well as the proportion of offloaded tasks. However, in practice, due to the variability of environment and actual demand, the amount of arrival tasks is uncertain. If the deterministic optimization is utilized to develop offloading strategy, unnecessary system overhead or higher task drop rate may occur, which severely damages the system robustness. To address this issue, we characterize the uncertainty with a data-driven approach, and formulate a distributionally robust optimization problem to minimize the expected energy-constrained system latency under the worst-case probability distribution. Furthermore, the distributionally robust latency optimization algorithm is proposed to reach the suboptimal solution. Finally, we perform simulations on the realworld data set, and compare with other benchmark schemes to verify the efficiency and robustness of our proposed algorithm., 12 pages, 6 figures, IEEE TVT

Unmanned aerial vehicle (UAV) communications have been considered as one of the promising technologies to support numerous applications in the fifth and sixth generations wireless networks. A deep understanding of propagation channel is necessary for the design of wireless communication systems. A three-dimensional (3D) wideband non-stationary geometry-based stochastic model (GBSM) is proposed for UAV multiple-input multiple-output (MIMO) channels in this paper. The proposed GBSM considers the both line-of-sight (LoS) and non-LoS (NLoS) components in the transmission links from a UAV transmitter (Tx) to a ground receiver (Rx), the proposed 3D GBSM is used for the first time to investigate the impact of UAV rotation, which results in time-varying channel parameters and reflects the non-stationarity of channel. Based on the proposed model, we derive and study some significant statistical properties, including the transfer function, space-time-frequency correlation function, Doppler power spectrum, and quasi-stationary interval. Numerical results show that the UAV rotation has a significant impact on channel statistical properties and non-stationarity. It is found that, even for a low range of UAV rotations, channel correlations are significantly affected, and the time correlation gradually increases with the pitch angle of UAV. Finally, the impact of using directional antennas at Tx on channel characteristics is analyzed. It is found that the channel correlation with directional antenna is significantly increased compared with the results with omnidirectional antenna. These observations and conclusions can be used as a reference for the system design and performance analysis of UAV-MIMO communication systems.

This paper investigates a heterogeneous cellular network (HCN) topology, where multiple sub-6 GHz bands are available for access and device-to-device (D2D) links with the full-duplex (FD) mode, and an integrated millimeter-wave (mm-wave) band is added to the D2D links’ sub-channel resource options. D2D links share spectrum resources of cellular users or dedicated mm-wave sub-channel. Densely deployed small cells scenario provides an ideal platform to implement mm-wave, FD and D2D communications. With large bandwidths available, mm-wave has the potential to meet the expected extreme data rate demands. Leveraging highly directional beamforming, severe transmission loss and the blockage phenomenon of mm-wave can be alleviated. Theoretically, FD communications can double the spectral efficiency due to bi-directional communications with the same spectral and temporal resources. However, such benefit comes at the cost of residual self-interference (RSI). Multi-user interference (MUI) and RSI among network uplink, downlink and D2D links are the main challenges. In the paper, we formulate an optimization problem for FD access and D2D links sub-channel allocation underlaying HCNs combining sub-6 GHz and mm-wave bands to make the system transmission rate maximized. Then, a scheme based on the coalition formation game is proposed to deal with this challenging NP-complete optimization. Finally, performance evaluation investigates the suitable conditions for FD and HD operations. Under different network parameter settings, we quantify associated performance of proposed scheme.

Unmanned aerial vehicle (UAV) communications have recently drawn great attention. To analyze and optimize the UAV communication systems, accurate and efficient UAV channel models are essential. Most existing UAV channel models are based on the assumption that both transmitter (Tx) and receiver (Rx) have fixed velocity and moving direction. However, in the realistic communication scenarios, the Tx and Rx of UAV may experience changes in both speeds and trajectories. In this paper, a three-dimensional (3D) non-stationary geometry-based stochastic model (GBSM) is proposed for air-to-air (A2A) channels in UAV communication scenarios. A 3D Markov mobility model is used to characterize the movements of the UAV in both horizontal and vertical directions. The mobility model enables to adjust the degree of mobility randomness and covers different UAV mobility trajectories, which makes it more realistic and suitable for simulating various scenarios. In addition, some important statistical properties such as time-frequency correlation function and Doppler power spectrum are derived and analyzed. The numerical results show that the impact of vertical movement of the UAV on the time correlation function under constant-speed is larger than that of horizontal movement, however, the above phenomenon is mitigated and the non-stationarity properties of the channel are significantly affected when randomness of the mobility model is introduced. Furthermore, it is found that the movement properties of the UAV only lead to non-stationarity in the time domain. The results are useful for A2A non-stationary channel simulation and UAV communication system evaluation.

In recent years, with the spectrum resources in low frequency bands becoming increasingly insufficient, the carrier frequency of wireless communication has started its evolution to the Terahertz (THz) frequency band, and meanwhile the THz communication system has become one of the research hot spots. In this paper, we investigate the problem of concurrent transmission scheduling for THz wireless backhaul network. To increase the weighted sum of completed flows with their quality of service (QoS) requirements satisfied in THz wireless backhaul network, we propose an algorithm of QoS-aware bandwidth allocation and concurrent scheduling (IHQB). Considering the priority of the flow, the reciprocal of the priority is taken as the weight of the flow. In this algorithm, QoS awareness and bandwidth allocation are exploited to achieve more successfully scheduled flows and higher network throughput. The concurrent scheduling with the maximum independent set (MIS) is allocated to different frequency bands. And the mentioned MIS is obtained from the conflict graph which has been established under the conditions of half-duplex and interference threshold. Simulation results show that IHQB performs better than other algorithms in terms of the weighted sum of completed flows and system throughput, especially compared with STDMA.

The rapid development of smart grid causes a large increase of power equipments. Power insulator is one of the most important infrastructures in the power transmission lines which is vital to ensure the safe operation of power system. As a common defect, the missing-cap issues will affect the structural strength of power insulators and the safe operation of power lines. Consequently, the monitoring and assessment of abnormal power insulators are of extreme importance for the safe power transmission lines. Due to the good feature expression ability, machine learning algorithms have got much applications on power line inspection, and they could be divided into two categories: shallow learning and deep learning algorithms. Nevertheless, the defect recognition issues on power insulators are always against complex power inspection environment. It will bring a certain effect to the handcrafted feature design of shallow learning algorithms. Meanwhile, the small-scale defect data set will affect the model training of the deep network model. To address the above issues, aimed at the feature of the limited processing power of airborne processor, a novel lightweight defect detection algorithm is proposed for the defects of power insulators which fuses the advantages of shallow learning and deep learning models. Firstly, an insulator location algorithm based on lightweight deep convolutional neural network (DCNN) model is proposed to remove the disturbance of complex backgrounds and serve the high-precision defect detection. On the basis, the high-level image feature based on the improved transfer learning is acquired to effectively distinguish the normal and abnormal power insulators. Finally, a defect recognition method based on Support Vector Machine (SVM) is proposed to solve the small-scale defect detection issue. Experiments show that the proposed method could well meet the precision and speed demands of power system compared with other inspection methods.

High speed train system has proven to be a very flexible and attractive system that can be developed under various circumstances and in different contexts and cultures. As a result, high speed trains are widely deployed around the world. Providing more reliable and higher data rate communication services for high speed trains has become one of the most urgent challenges. With vast amounts of spectrum available, the millimeter wave (mmWave) system is able to provide transmission rates of several gigabits per second for high speed trains. At the same time, mmWave communication also suffers from high attenuation, thus higher energy efficiency should be considered. This paper proposes an energy efficient power control scheme of train-ground mmWave communication for high speed trains. Considering a beam switching method for efficient beam alignment, we first establish position prediction model, the realistic direction antenna model and receive power model. And then we allocate the transmission power rationally through the power minimization algorithm while ensuring the total amount of transmission data. Based on this, this paper also develops a hybrid optimization scheme and finds the limit of total energy consumption when the number of segments goes to infinity. Through simulation with various system parameters and taking velocity estimation error into account, we demonstrate the superior performance of our schemes., Comment: 11 pages, 17 figures, IEEE Transactions on Vehicular Technology

Ultra-high-dimensional data with grouping structures arise naturally in many contemporary statistical problems, such as gene-wide association studies and the multi-factor analysis-of-variance (ANOV...

Heterogeneous cellular networks (HCNs) with millimeter wave (mm-wave) communications are considered as a promising technology for the fifth generation mobile networks. Mm-wave has the potential to provide multiple gigabit data rate due to the broad spectrum. Unfortunately, additional free space path loss is also caused by the high carrier frequency. On the other hand, mm-wave signals are sensitive to obstacles and more vulnerable to blocking effects. To address this issue, highly directional narrow beams are utilized in mm-wave networks. Additionally, device-to-device (D2D) users make full use of their proximity and share uplink spectrum resources in HCNs to increase the spectrum efficiency and network capacity. Towards the caused complex interferences, the combination of D2D-enabled HCNs with small cells densely deployed and mm-wave communications poses a big challenge to the resource allocation problems. In this paper, we formulate the optimization problem of D2D communication spectrum resource allocation among multiple micro-wave bands and multiple mm-wave bands in HCNs. Then, considering the totally different propagation conditions on the two bands, a heuristic algorithm is proposed to maximize the system transmission rate and approximate the solutions with sufficient accuracies. Compared with other practical schemes, we carry out extensive simulations with different system parameters, and demonstrate the superior performance of the proposed scheme. In addition, the optimality and complexity are simulated to further verify effectiveness and efficiency., 13 pages, 11 figures, IEEE Transactions on Vehicular Technology

Heterogeneous cellular networks with small cells in the millimeter wave (mmWave) band densely deployed have become one of promising candidates for future wireless networks due to huge bandwidth available in the mmWave band. To overcome high path loss in the mmWave band, the beamforming technique of directional antennas is adopted. Consequently, concurrent transmissions of links can be enabled to improve network capacity. On the other hand, multicast services can support many applications like popular content downloading and broadcast communication services. In user intensive region where multicast services usually happen, device-to-device (D2D) communications in physical proximity provide better channel conditions, and can improve multicast efficiency. In this paper, we develop an efficient multicast scheduling scheme for mmWave small cells, referred to as CONMD2D, where both concurrent transmissions and D2D communications are exploited based on a multi-level antenna codebook to optimize network performance. In CONMD2D, the multicast group is partitioned into subgroups, and D2D transmission paths are established between subgroups. Then, a concurrent scheduling algorithm schedules the multicast links concurrently into the transmission stage. Performance evaluation under various system parameters demonstrates CONMD2D achieves significant improvement in network throughput and energy efficiency compared with other state-of-the-art schemes.

Fog computing is an epitome to enable provisioning resources and services beyond the cloud, at the edge of the network, and nearer to end devices. Fog computing is not a counterfeit for cloud computing but a persuasive counterpart. However, the mobility of end users and/or fog nodes brings a major dilemma in the implementation of real-life scenarios. Therefore, we deliver the state-of-the-art research about mobility in fog computing. By identifying the mobility problems, requirements, and features of different proposals, we discover the open problems from subsisting studies and summarize the advantages of mobility for readers. This will help the researchers and developers avoid the current misapprehensions and capture the real-life scenarios, such as business, government, and education institutions. In spite of the extensive state-of-the-art research work, we also present the diverse mobility factors to investigate the correlation between dynamic nodes with fog nodes in order to accomplish better successful tasks. We conceive that the investigations of mobility factors in the fog computing will furnish the novel perspective on not only dynamic connections but also network dynamics. To revolutionize the follow-up research, we distinguish and foreground futurity directions concerning real-life scenarios of people and vehicles in a dynamic fog environment.

The millimeter wave (mmWave) has been extensively utilized for its rich spectrum resource. With the development of self-interference (SI) cancellation technology, full-duplex (FD) communications have become possible recently. In order to get larger network capacity, we introduce FD communications into mmWave wireless network. However, mmWave links are easily blocked by obstacles, and the blockage makes some flows fail to be transmitted directly. For the communication problems of shadow coverage area, a relay path selection algorithm is proposed to select optimal multi-hop paths for these blocked flows. This proposed algorithm not only can relay the blocked flows by other unblocked links, but also select the appropriate relay paths to minimize transmission time of the entire transmission process. To further improve the system transmission efficiency, we develop a concurrent scheduling algorithm by using FD communications. The scheduling algorithm continuously schedules the links until the throughput requirements of flows are accommodated. Through extensive simulations at 60 GHz mmWave wireless network, the proposed scheme can solve the problem for a certain degree of blocked flows and complete the transmission with the least time consumption. Compared with other existing schemes, the proposed scheme shows superior performances on relaying capability and scheduling duration.

In the fifth generation (5G) era, dense deployment of small cells and full-duplex (FD) technology applications are two key features of millimeter-wave (mmWave) wireless communication systems, which offer the opportunity to meet the explosive growth of data service requirements. It is the beamforming and advances in analog as well as digital self-interference (SI) cancellation schemes that improve the network capacity in mmWave wireless backhaul networks. To achieve power saving and further network performance optimization, we propose a FD concurrent transmission mechanism employed in a mmWave backhaul network. Contention graph is constructed in consideration of multi-user interference (MUI), SI, and FD transmission constraints. Then flow-grouping and power control algorithms are proposed based on the contention graph. We evaluate the performance of the proposed algorithm in terms of energy consumption, achievable network throughput, and energy efficiency. The impact of the interference threshold on the system performance is also investigated when the distribution of base stations (BSs), traffic loads, and maximum transmission powers change. Simulation results illustrate that with proper SI cancellation and interference threshold, the proposed concurrent mechanism outperforms time-division multiple access (TDMA), half-duplex (HD) concurrent transmission, and FD concurrent transmission without power control.

Hybrid analog-digital (A/D) transceivers designed for millimeter wave (mmWave) systems have received substantial research attention, as a benefit of their lower cost and modest energy consumption compared to their fully-digital counterparts. We further improve their performance by conceiving a Tomlinson-Harashima precoding (THP) based nonlinear joint design for the downlink of multiuser multiple-input multipleoutput (MIMO) mmWave systems. Our optimization criterion is that of minimizing the mean square error (MSE) of the system under channel uncertainties subject both to realistic transmit power constraint and to the unit modulus constraint imposed on the elements of the analog beamforming (BF) matrices governing the BF operation in the radio frequency domain. We transform this optimization problem into a more tractable form and develop an efficient block coordinate descent (BCD) basedalgorithm for solving it. Then, a novel two-timescale nonlinear joint hybrid transceiver design algorithm is developed, which can be viewed as an extension of the BCD-based joint design algorithm for reducing both the channel state information (CSI) signalling overhead and the effects of outdated CSI. Moreover, we determine the near-optimal cancellation order for the THP structure based on the lower bound of the MSE. The proposed algorithms can be guaranteed to converge to a Karush-Kuhn-Tucker (KKT) solution of the original problem. The simulation results demonstrate that our proposed nonlinear joint hybrid transceiver design algorithms significantly outperform the existing linear hybrid transceiver algorithms and approach the performance of the fully-digital transceiver, despite its lower cost and power dissipation.

This paper considers an intelligent reconfigurable surface (IRS) assisted high-speed train communication system to address blockage issues, thus enhancing the spectrum efficiency and reducing the outage probability. However, instantaneous channel state information (CSI) at the base station is hard to be acquired in high-speed railway communication scenarios. To deal with the channel uncertainty, the outage performance is investigated by exploiting the statistical CSI in the downlink multiple-input multiple-output system, and we derive a closed-form expression of the outage probability. Moreover, an outage probability minimization problem is formulated to facilitate the IRS phase shift design and transceiver beam-forming design at the BS and the mobile relay on the train, subject to the transmit power constraint. Simulation results validate the efficacy of the proposed algorithm in terms of outage probability and effective rate, which is in close agreement with the theoretical analysis. Besides, the impacts of critical system parameters including the transmit power and the signal-to-noise ratio (SNR) threshold on the system performance are presented.

With the increasing shortage of wireless spectrum resources, it is urgent to monitor and utilize the limited wireless spectrum resources rationally. In this paper, a scattered wireless spectrum sensor network system is proposed and applied to electromagnetic spectrum monitoring in a city environment. We design a wireless spectrum sensor node and wireless spectrum sensor network, then develop a city wireless spectrum monitoring software system. We describe the network architecture and software design process in detail and then design several experiments to test the system. The results show that our system can satisfy the electromagnetic spectrum environment monitor requirements.

The millimeter wave (mmWave) communication has drawn intensive attention with abundant band resources. In this paper, we consider the popular content distribution (PCD) problem in the mmWave vehicular network. In order to offload the communication burden of base stations (BSs), vehicle-to-vehicle (V2V) communication is introduced into the PCD problem to transmit contents between on-board units (OBUs) and improve the transmission efficiency. We propose a full-duplex (FD) cooperative scheme based on coalition formation game, and the utility function is provided based on the maximization of the number of received contents. The contribution of each member in the coalition can be transferable to its individual profit. While maximizing the number of received contents in the fixed time, the cooperative scheme also ensures the individual profit of each OBU in the coalition. We evaluate the proposed scheme by extensive simulations in mmWave vehicular networks. Compared with other existing schemes, the proposed scheme has superior performances on the number of possessed contents and system fairness. Besides, the low complexity of the proposed algorithm is demonstrated by the switch operation number and CPU time., Comment: 12 pages, 8 figures, IEEE Transactions on Vehicular Technology

In this paper, we focus on the reconfigurable intelligent surface (RIS) assisted single-cell uplink communication network scenario. In the network, one cellular link and multiple device-to-device (D2D) links sharing the same spectrum resources combine direct and reflective channel transmissions with the assistance of the RIS, which is adopted to alleviate the interference by fully using the beamforming capability. Subjected to qualityof-service (QoS) and total power constraints, a system sumrate maximization problem is formulated by jointly optimizing transmission powers of all links and discrete phase shifts of all RIS elements. Since it is a mixed integer non-convex non-linear problem, we decompose it into two sub-problems, and apply the alternating optimization to obtain a sub-optimal solution efficiently. For the power allocation sub-problem, it is a difference of concave functions (DC) problem, which is transformed to a convex one by the multivariate Taylor expansion and then solved with the gradient descent method. For the phase shift subproblem, a local search algorithm is utilized. Simulation results verify that our proposed scheme can eliminate the interference of D2D networks better than the scheme without RIS and other benchmark schemes.

In this paper, we investigate a QoE-aware coordinated caching scheme to adaptively satisfy the diversified video streaming requirements in a high-speed railway network, which consists of multiple cells endowed with cache storage capacity. However, traditional QoS-based video streaming schemes may not accurately reflect the influence of video adaption on user satisfaction. What’s more, dynamic user demands and frequent handover impose serious challenges in terms of unknown uncertainties and short dwelling time. To overcome these challenges, we first define a perceptual QoE considering both video quality and video stalling. Second, we formulate a long-term optimization problem to maximize the perceptual QoE, with the cache storage and system stability constraints. Then, we propose a distributed online algorithm based on the Lyapunov optimization theory, which does not require future system information and is efficient for implementation. Finally, theoretical analysis and simulation results are presented to validate the effectiveness of the proposed algorithm.

Millimeter wave communication requires a highly directional transmission link between the base station and the user equipment, which may increase the time of initial access and affect the experience of delay-sensitive users. Considering the initial access technique based on analog beamforming, this paper proposes a fast beam training method for random combination of beam pairs. The method first divides the beam directions of the base station and the user into several groups, and then randomly selects beams from both groups to determine whether it meets the requirement for establishing a link. If so, the algorithm stops the search, otherwise it continues to select beams randomly from the remaining part until a proper beam pair is found. This paper first introduces the beam training process of random combination method, and then compares it with exhaustive method and iterative method in terms of discover delay and misdetection probability. Simulation results show that the random combination method can effectively reduce discover delay and shorten the initial access time.

With the evolution of the 5G, 6G and beyond, device-to-device (D2D) communication has been developed as an energy-, and spectrum-efficient solution. In cellular network, D2D links need to share the same spectrum resources with the cellular link. A reconfigurable intelligent surface (RIS) can reconfigure the phase shifts of elements and create favorable beam steering, which can mitigate aggravated interference caused by D2D links. In this paper, we study a RIS-assisted single cell uplink communication network scenario, where the cellular link and multiple D2D links utilize direct propagation and reflecting one-hop propagation. The problem of maximizing the total system rate is formulated by jointly optimizing transmission powers of all links and discrete phase shifts of all elements. The formulated problem is an NP-hard mixed integer non-convex non-linear problem. To obtain practical solutions, we capitalize on alternating maximization and the problem is decomposed into two sub-problems. For the power allocation, the problem is a difference of concave functions (DC) problem, which is solved with the gradient descent method. For the phase shift, a local search algorithm with lower complexity is utilized. Simulation results show that deploying RIS and optimizing the phase shifts have a significant effect on mitigating D2D network interference., 11 pages, 9 figures

As the sophisticated applications with latency constrained are difficult to operate on mobile devices with lower computing capability, fog-computing based radio access networks (F-RANs) have become a research hotspot as a revolutionary network architecture. It can offload a proportion of user's input tasks and provide scalable computation services at the fog-computing access points (F-APs), which reduce the task processing time and extend the battery life of local devices. In addition, the incorporation of millimeter-wave (mm-wave) band further improves the network performance with the uploading rate greatly increased. In this paper, we consider the multi-user uplink scenario, and formulate the problem of minimizing the total energy consumption of all users within the required latency. On the one hand, the optimization of user association joint with sub-channel allocation is studied to determine the connection status between users and edge F-AP nodes. It is modeled as a two-sided matching game representing the resource competition among users. As a result, the sub-optimal solution is obtained at lower complexity. On the other hand, the optimization of computation offloading for all users is also performed. Local devices can adjust CPU computing speed using dynamic voltage scaling (DVS) technology, and the offloading ratio is solved by convex programming. Both yield closed-form solutions. To this end, performance evaluation under multiple system parameters demonstrates the lower energy consumption and higher effectiveness of our proposed scheme in comparison with the baseline schemes.

To keep up with the rapid growth of mobile data, there are increasing interests to deploy small cells in millimeter wave (mmWave) bands to underlay the conventional homogeneous macrocell network as well as in exploiting device-to-device (D2D) communications to improve the efficiency of the multicast service that supports content-based mobile applications. To compensate for high propagation loss in the mmWave band, high-gain directional antennas have to be employed, while it is critical to optimize multicast service in order to improve the network performance. In this paper, we develop an efficient multicast scheduling scheme for small cells in the mmWave band, called MD2D, where both D2D communications in close proximity and multi-level antenna codebook are utilized. Specifically, a user partition and multicast path planning algorithm is proposed to partition the users in the multicast group into subsets and to determine the transmission node for each subset, so as to achieve optimal utilization of D2D communications and multi-level antenna codebook. Then a multicast scheduling algorithm schedules the transmission for each subset. Furthermore, in order to optimize the network performance, the optimal choice of user partition thresholds is analyzed. Extensive simulations demonstrate that the MD2D achieves the best performance, in terms of network throughput and energy efficiency, compared with other existing state-of-the-art schemes. MD2D improves the network throughput compared with the second-best scheme by about 27%.

Heterogeneous cellular networks (HCNs) with millimeter wave (mmWave) communications included are emerging as a promising candidate for the fifth generation mobile network. With highly directional antenna arrays, mmWave links are able to provide several-Gbps transmission rate. However, mmWave links are easily blocked without line of sight. On the other hand, D2D communications have been proposed to support many content based applications, and need to share resources with users in HCNs to improve spectral reuse and enhance system capacity. Consequently, an efficient resource allocation scheme for D2D pairs among both mmWave and the cellular carrier band is needed. In this paper, we first formulate the problem of the resource allocation among mmWave and the cellular band for multiple D2D pairs from the view point of game theory. Then, with the characteristics of cellular and mmWave communications considered, we propose a coalition formation game to maximize the system sum rate in statistical average sense. We also theoretically prove that our proposed game converges to a Nash-stable equilibrium and further reaches the near-optimal solution with fast convergence rate. Through extensive simulations under various system parameters, we demonstrate the superior performance of our scheme in terms of the system sum rate compared with several other practical schemes., 13 pages, 12 figures

STRs vary not only in the length of the repeat units and the number of repeats but also in the region with which they conform to an incremental repeat pattern. Massively parallel sequencing (MPS) offers new possibilities in the analysis of STRs since they can simultaneously sequence multiple targets in a single reaction and capture potential internal sequence variations. Here, we sequenced 34 STRs applied in the forensic community of China with a custom-designed panel. MPS performance were evaluated from sequencing reads analysis, concordance study and sensitivity testing. High coverage sequencing data were obtained to determine the constitute ratios and heterozygous balance. No actual inconsistent genotypes were observed between capillary electrophoresis (CE) and MPS, demonstrating the reliability of the panel and the MPS technology. With the sequencing data from the 200 investigated individuals, 346 and 418 alleles were obtained via CE and MPS technologies at the 34 STRs, indicating MPS technology provides higher discrimination than CE detection. The whole study demonstrated that STR genotyping with the custom panel and MPS technology has the potential not only to reveal length and sequence variations but also to satisfy the demands of high throughput and high multiplexing with acceptable sensitivity.

With the rapid deployment of high speed railway (HSR) worldwide, both safety operation and comfort experience can be desired to evolve into a future era of intelligent transportation system. To eliminate boredom and provide entertainment for passengers, an intranet for internal communications among passengers named as onboard social network system (SNS) is needed. In this paper, the latest progress in HSR network architectures and technology building blocks are discussed to enable the implementation of the SNS. Meanwhile, based on the device-to-device (D2D) communication technology for proximal information interaction, SNS can be efficiently facilitated. A dynamic resource allocation algorithm is proposed to maximize the total utility of the onboard SNS, which is solved with the matching theory method. Simulation results verify the convergence and efficiency of the proposed algorithm.

Millimeter-wave (mm-Wave) MIMO systems have been proposed to achieve higher spectral efficiency via the hybrid beamforming structure, which consists of analog beamforming and digital beamforming. In analog beamforming, each antenna subarray generates a codebook-based directional beam, which determines the equivalent MIMO channel. Then, digital beamforming can be applied to fully exploit the spatial multiplexing gain of MIMO channels. In this paper, we propose a low-complexity analog beam selection scheme to achieve near-optimal spectral efficiency for the split hybrid beamforming system. The core of our scheme is the beam selection criterion, which is derived from capacity analysis. Furthermore, we propose a beam switching algorithm to ensure the robustness when blockage occurs. Through simulations under different channel conditions, the near-optimal performance of our scheme is demonstrated, and the beam switching algorithm is able to ensure robust network connectivity and achieve higher channel capacity when the blockage is relived.

The small cells in millimeter wave (mmWave) have been utilized extensively for the fifth generation (5G) mobile networks. And full-duplex (FD) communications become possible with the development of self-interference (SI) cancellation technology. In this paper, we focus on the optimal allocation of the sub-channels in the small cells deployed densely underlying the mmWave networks. In order to improve the resource utilization and network capacity, device-to-device (D2D) communications are adopted in networks. For maximizing the system throughput, we propose a cooperative sub-channel allocation approach based on coalition formation game, and theoretically prove the convergence of the proposed allocation algorithm. The utility of the coalition formation game is closely related to the sum system throughput in this paper, and each link makes an individual decision to leave or join any coalition based on the principle of maximizing the utility. Besides, a threshold of the minimum transmission rate is given to improve the system fairness. Through extensive simulations, we demonstrate that our proposed scheme has a near-optimal performance on sum throughput. In addition, we verify the low complexity of the proposed scheme by simulating the number of switch operations., 15 pages, 11 figures, IEEE Transactions on Vehicular Technology

Multiuser multiple input multiple output (MU-MIMO) millimeter wave (mmWave) communication is considered as a key technology to provide multi-gigabit train-to-ground wireless connections in the high-speed railway (HSR) system. Considering the power consumption and hardware constraint, the hybrid beamforming (BF), which combines analog BF and digital BF, is widely adopted in the MU-MIMO mmWave systems. In this paper, we target on an efficient hybrid BF structure design in HSR scenario with taking the practical HSR mmWave channel model into consideration. Specifically, the hybrid BF design aims at maximizing the overall throughput and is formulated as an optimization problem which is proved to be nonconvex and NP-hard. Therefore, a suboptimal yet efficient two-stage solution is proposed, where a weighted minimum mean square error (WMMSE) based beamforming strategy is exploited to devise the hybrid beamformer at the base station (BS) at the first stage, and the orthogonal matching pursuit (OMP) approach is leveraged to decouple the digital BF and analog BF at BS at the second stage. Simulation results demonstrate that higher overall throughput can be achieved by the proposed hybrid BF scheme compared to other state-of-the-art benchmarks.

With extraordinary growth in the Internet of Things (IoT), the amount of data exchanged between IoT devices is growing at an unprecedented scale, which is an important requirement for Fifth generation (5G) networks. Current Long Term Evolution (LTE) system is not able to efficiently support massive connectivity, especially on the uplink (UL). The contention based transmission enables to transmit data packet without waiting for dynamic and explicit scheduling grant from base station, and is more efficient for small packet transmission in terms of lower signaling overhead, lower latency and lower energy consumption. However, this may lead to high collision rates and a large amount of retransmissions. New low complexity recovery mechanism of non-successful transmissions is needed. So in this paper, a new Hybrid Automatic Repeat reQuest (HARQ) mode, called Backoff HARQ, is proposed for contention-based (CB) transmission in 5G uplink. For Backoff HARQ mode, round trip time (RTT) is set to a longer random time. We can get more HARQ processes and put off the retransmission information for the longer random backoff time as we set. We evaluate the proposed backoff HARQ mode using system simulations and show that the new mode provides superior system performance.

Small cells in the millimeter wave band densely deployed underlying the macrocell have been regarded as one of promising candidates for the next generation mobile networks. In the user intensive region, device-to-device (D2D) communication in physical proximity can save power and improve spectral efficiency. In this paper, we focus on the optimal sub-channel allocation for access and D2D links in the scenario of densely deployed multiple mmWave small cells. The problem is modeled as a coalitional game to maximize the system sum rate of access and D2D links in the system. Then we propose a coalition formation game based algorithm for sub-channel allocation. Performance evaluation results demonstrate superior performance in terms of the system sum rate compared with other practical schemes., Comment: 4 pages, 2 figures, URSI

With the explosive growth of mobile demand, small cells in millimeter wave (mmWave) bands underlying the macrocell networks have attracted intense interest from both academia and industry. MmWave communications in the 60 GHz band are able to utilize the huge unlicensed bandwidth to provide multiple Gbps transmission rates. In this case, device-to-device (D2D) communications in mmWave bands should be fully exploited due to no interference with the macrocell networks and higher achievable transmission rates. In addition, due to less interference by directional transmission, multiple links including D2D links can be scheduled for concurrent transmissions (spatial reuse). With the popularity of content-based mobile applications, popular content downloading in the small cells needs to be optimized to improve network performance and enhance user experience. In this paper, we develop an efficient scheduling scheme for popular content downloading in mmWave small cells, termed PCDS (popular content downloading scheduling), where both D2D communications in close proximity and concurrent transmissions are exploited to improve transmission efficiency. In PCDS, a transmission path selection algorithm is designed to establish multi-hop transmission paths for users, aiming at better utilization of D2D communications and concurrent transmissions. After transmission path selection, a concurrent transmission scheduling algorithm is designed to maximize the spatial reuse gain. Through extensive simulations under various traffic patterns, we demonstrate PCDS achieves near-optimal performance in terms of delay and throughput, and also superior performance compared with other existing protocols, especially under heavy load., Comment: 12 pages, to appear in IEEE Transactions on Vehicular Technology

60-GHz millimetre-wave (mm-wave) communication is gradually becoming a promising candidate for the next generation wireless system to meet the demands of mobile applications. To compensate for high path loss, directional links are established in mm-wave communication system, which adds opportunity for spatial reuse. As one of its most promising protocols for commercial production, IEEE 802.11ad standard provides a mechanism to support space-time division multiple access (STDMA) within a single network. However, the interference level among different co-channel networks is much lower than that inside a network, which provides greater potential for spatial reuse. In this study, based on the architecture and timing structure of IEEE 802.11ad, the authors propose a spatial reuse strategy among multiple co-channel networks. They formulate the problem as a mixed-integer non-linear programming problem, and then propose an inter-network STDMA scheduling algorithm, which considers clustering frame structure in IEEE 802.11ad, and combines greedy principle and mutual interference avoidance strategy. Extensive simulation results have shown that the proposed scheme enlarges total throughput in comparison with STDMA inside each network, as well as non-STDMA scheme. Meanwhile, it achieves the lowest packet loss rate under heavy traffic load.

Heterogeneous networks, which deploy small cells in the mmWave band underlying the macrocell network, have attracted intense interest from both academia and industry. Different from the communication systems using lower carrier frequencies, mmWave communications have unique features, such as high propagation loss, directional communications, and sensitivity to blockage. Aiming to overcome the challenging problems in mmWave networks, such as interference management, spatial reuse, anti-blockage, QoS guarantee, and load balancing, we architecturally borrow the ideas of heterogeneous cloud radio access networks and software-defined networking to propose a software-defined mmWave mobile broadband system via a cross-layer design approach. In this architecture, a centralized controller is introduced by abstracting the control functions from the network layer to the physical layer. Through quantitative simulations in a realistic indoor scenario, we demonstrate the performance advantages of our system in terms of network throughput and flow throughput. This work is the first cross-layer and software-defined design for mmWave communications, which opens up an opportunity for mmWave communications to make a significant impact on future 5G networks.

Over the recent times, there has been great enhancement towards online shopping and platforms that provide commerce. Hence, great research and work has been done and is being done in field of recommendation systems. With this great development, there has been an exponential increase in online inventory due to the great number of users excessing these online platforms for buying and selling purposes and companies are often looking for advanced recommendation systems to provide their customers with the best online experience in respect towards each individual customer. It is believed that recent advancements in Deep Learning may provide an optimal solution for better recommendation systems, but it requires validation. The main aim of this paper is to follow through different research and investigate whether modern Deep Learning algorithms live up to the expectations and demands. Different reviews have been given in support with experiments. This literature review provides an analysis of different practices, state of the industrial methodologies and current research.

In the scenario where small cells are densely deployed, the millimeter wave (mmWave) wireless backhaul network has been widely used. However, mmWave is easily blocked by obstacles, and how to forward the data of the blocked flows is still a significant challenge. To ensure backhauling capacity, the quality of service (QoS) requirements of flows should be satisfied. In this paper, we investigate the problem of optimal scheduling to maximize the number of flows satisfying their QoS requirements with relays exploited to overcome blockage. To achieve a practical solution, we propose a relay-assisted and QoS aware scheduling scheme for the backhaul networks, called RAQS. It consists of a relay selection algorithm and a transmission scheduling algorithm. The relay selection algorithm selects non-repeating relays with high link rates for the blocked flows, which helps to achieve the QoS requirements of flows as soon as possible. Then, according to the results of relay selection, the transmission scheduling algorithm exploits concurrent transmissions to satisfy the QoS requirements of flows as much as possible. Extensive simulations show RAQS can effectively overcome the blockage problem, and increase the number of completed flows and network throughput compared with other schemes. In particular, the impact of relay selection parameter is also investigated to further guide the relay selection., 11 pages, 10 figures

The development of self-interference (SI) cancelation technology makes full-duplex (FD) communication possible. Considering the quality of service (QoS) of flows in small cells densely deployed scenario with limited time slot (TS) resources, this paper introduces the FD communication into the concurrent scheduling problem of millimeter-wave (mmWave) wireless backhaul network. We propose a QoS-aware FD concurrent scheduling algorithm to maximize the number of flows with their QoS requirements satisfied. Based on the contention graph, the algorithm makes full use of the FD condition. Both residual self-interference (RSI) and multi-user interference (MUI) are considered. Besides, it also fully considers the QoS requirements of flows and ensures the flows can be transmitted at high rates. Extensive simulations at 60GHz demonstrate that with high SI cancelation level and appropriate contention threshold, the proposed FD algorithm can achieve superior performance in terms of the number of flows with their QoS requirements satisfied and the system throughput compared with other stateof-of-the-art schemes., 9 pages, 10 figures

As an extension of cloud computing, fog computing at the edge of networks provides low latency, location awareness, and real-time interactions. At the same time, millimeter wave (mmWave) communications are able to provide directional multi-gigabit transmission rates with large available bandwidth. Based on the user mobile trajectories in a region, several activity hotspots that users pass by frequently can be obtained. By caching popular content at the edge nodes near the hotspots, users can download the cached content directly at a short distance, and the user experience can be significantly improved. Considering multiple hotspots in a region, how to efficiently schedule the transmission for the caching at edge nodes becomes a key problem. In this paper, we focus on the problem of mobility aware transmission scheduling for caching at edge nodes near hotspots, and utilize multi-hop relaying and concurrent transmissions to achieve better performance. After formulating the optimal scheduling problem as a stochastic nonlinear mixed integer program, we propose a mobility aware caching scheduling scheme, called MHRC (Multi-Hop Relaying based Caching), where multi-hop D2D paths are established for edge nodes, and concurrent transmissions are exploited in the scheduling of caching at edge nodes. Extensive performance evaluation demonstrates MHRC achieves more than 1x higher expected cached data amount compared with state-of-the-art schemes., 12 pages, 12 figures, to appear in IEEE ACCESS

With the increasing quality of service (QoS) demands for indoor multimedia applications, millimeter wave (mmWave) communications are emerging as a promising candidate for the wireless personal area networks (WPANs). On the one hand, it has the advantage of providing several-Gbps transmission rate. However, due to the unique characteristics in 60-GHz frequency band, such as high propagation loss, beamforming is fully exploited for mmWave links to achieve directional transmission and reception. In this paper, we propose a novel QoS aware scheduling algorithm for concurrent transmission in mmWave WPANs based on coalition game. First, we formulate the problem of concurrent transmission scheduling into a non-convex integer programming problem. Then, we propose a coalition game based algorithm to maximize the number of flows satisfying the corresponding QoS requirements, while improving the network resource utilization effectively. Besides, our proposed algorithm converges to a Nash-stable equilibrium with greatly reduced complexity. Through extensive simulations under various system parameters, we demonstrate our scheme achieves better network performance in terms of the throughput and the number of flows scheduled successfully, compared with existed protocols.

With the explosive growth of mobile traffic, millimeter wave (mmWave) systems have gained considerable attention from both academia and industry. Although relaying and concurrent transmissions have been utilized to improve the system performance, dynamics due to human mobility are still challenges for mmWave systems. In this paper, we propose a high throughput service scheduling (HTSS) scheme, which exploits multi- hop relay and concurrent transmissions to enhance throughput with the consideration of human mobility. In HTSS, we develop a relay path planning algorithm to establish multi-hop relay paths, and then utilize a global time scheduling algorithm to compute transmission scheme to achieve mobility-aware optimization. Through extensive evaluations under realistic human mobility trajectories, we demonstrate the superior performance of HTSS in terms of the system throughput compared with the state-of-the-art schemes.

With the worldwide deployment of the railway, high-speed railway (HSR) tends to evolve into an intelligent transportation system with efficient and green transportation characteristics. To meet the explosive growth of wireless data traffic in “smart rail”, millimeter-wave (mmWave) communications are used to offer several Gbps data rate via beamforming structures by utilizing huge unlicensed bandwidth. In this paper, the beam tracking strategies for mmWave HSR communications are investigated, and a dynamic beam tracking strategy is proposed by adjusting the beam direction and beam width jointly, where the main idea is to maximize the sum-rate capacity while satisfying the critical quality of service (QoS) requirements. Then it boils down to a demanding non-convex problem, and a near-optimal solution is provided based on the problem decomposition and the genetic algorithm. Finally, along with the moving trains the proposed beam tracking scheme can provide near-optimal capacity performance with a low outage probability, and reduce the implementation complexity.

With the explosive growth of mobile traffic, diverse mobile applications with high throughput demands have gained considerable attention from both academia and industry. However, dynamics due to human mobility impose serious issues on high throughput communications. Although millimeter-wave (mm-wave), relays, and concurrent transmission have been applied for throughput improvement, how to achieve high throughput transmission in mobility-aware scenarios is still challenging. In this paper, we propose a throughput-efficient service scheduling (TESS) scheme, which exploits multi-hop relay and concurrent transmissions with the consideration of human mobility. In TESS, we first propose a mobility-aware transmission scheduling scheme in single mm-wave cell. The proposed scheduling scheme consists of a relay path planning algorithm and a global time scheduling algorithm. In the relay path planning algorithm, we establish multi-hop relay transmission paths from base station to service points. In the global time scheduling algorithm, we schedule concurrent transmission in relay paths. Furthermore, the proposed TESS scheme is extended for multi-cell scenarios. Through extensive performance evaluations under realistic human mobility trajectories, we demonstrate the superior performance of TESS in terms of system throughput compared with the state-of-the-art schemes.

With the explosive growth of mobile data demand, the fifth generation (5G) mobile network would exploit the enormous amount of spectrum in the millimeter wave (mmWave) bands to greatly increase communication capacity. There are fundamental differences between mmWave communications and existing other communication systems, in terms of high propagation loss, directivity, and sensitivity to blockage. These characteristics of mmWave communications pose several challenges to fully exploit the potential of mmWave communications, including integrated circuits and system design, interference management, spatial reuse, anti-blockage, and dynamics control. To address these challenges, we carry out a survey of existing solutions and standards, and propose design guidelines in architectures and protocols for mmWave communications. We also discuss the potential applications of mmWave communications in the 5G network, including the small cell access, the cellular access, and the wireless backhaul. Finally, we discuss relevant open research issues including the new physical layer technology, software-defined network architecture, measurements of network state information, efficient control mechanisms, and heterogeneous networking, which should be further investigated to facilitate the deployment of mmWave communication systems in the future 5G networks.

To keep pace with the rapid growth of mobile traffic demands, dense deployment of small cells in millimeter wave (mmWave) bands has become a promising candidate for next generation wireless communication systems. With a greatly increased data rate from huge bandwidth of mmWave communications, energy consumption should be mitigated for higher energy efficiency. Due to content popularity, many content-based mobile applications can be supported by the multicast service. mmWave communications exploit directional antennas to overcome high path loss, and concurrent transmissions can be enabled for better multicast service. On the other hand, device-to-device (D2D) communications in physical proximity should be exploited to improve multicast performance. In this paper, we propose an energy efficient multicast scheduling scheme, referred to as EMS, which utilizes both D2D communications and concurrent transmissions to achieve high energy efficiency. In EMS, a D2D path planning algorithm establishes multi-hop D2D transmission paths, and a concurrent scheduling algorithm allocates the links on the D2D paths into different pairings. Then the transmission power of links is adjusted by the power control algorithm. Furthermore, we theoretically analyze the roles of D2D communications and concurrent transmissions in reducing energy consumption. Extensive simulations under various system parameters demonstrate the superior performance of EMS in terms of energy consumption compared with the state-of-the-art schemes. Furthermore, we also investigate the choice of the interference threshold to optimize network performance., 17 pages, 15 figures

Millimeter wave MIMO systems have been proposed to achieve higher spectral efficiency via the hybrid beamforming structure, which consists of analog beamforming and digital beamforming. In analog beamforming, each antenna subarray generates a codebook based directional beam, which determines the equivalent MIMO channel. Then digital beamforming can be applied to fully exploit the spatial multiplexing gain of MIMO channels. In this paper, we propose a low complexity analog beam selection scheme to achieve near-optimal spectral efficiency. The core of our scheme is the beam selection criterion, which is derived from capacity analysis. Through simulations under different channel conditions, the near-optimal performance of our scheme is demonstrated, and our scheme is able to achieve good enough performance with a small number of candidate beam combinations.

Enhancing throughput gain is an important target in the development of millimeter-wave (mmWave) communications. Spatial reuse is an important approach for throughput enhancement, which works well in mmWave networks due to directional links. In addition, multicast transmissions are highly desirable in mmWave systems, and become feasible with recent advances in antenna technology. In this paper, we address the problem of spatial reuse scheduling with multicast transmissions for mmWave communications. We formulate the problem as a Mixed Integer Non-Linear Programming (MINLP) problem and propose a low-computational-complexity heuristic algorithm, where potential links are fully utilized to exploit spatial reuse gain by dividing multicast demands into multiple unicast/multicast transmissions. Extensive simulation results demonstrate that the proposed scheme achieves near-optimal performance, and obtains high throughput gain with low packet loss rate.

Millimeter wave mmWave communications in 60 GHz band have become a hot topic in wireless communications. New medium access control MAC protocols are needed because of the fundamental differences between mmWave communications and existing other communication systems. In mmWave wireless personal area networks, the channel transmission rates of links vary significantly because of the difference in the distance between nodes, the accuracy of beamforming, and the existence of obstructions. Owning to the directivity of mmWave links, spatial reuse should be exploited to improve network capacity. In this paper, we develop a channel transmission rate aware directional MAC protocol, termed RDMAC, in which both the multirate capability of links and spatial reuse are exploited to improve network performance. RDMAC has two stages. The first stage measures the channel transmission rates of links, and a heuristic algorithm is proposed to compute near-optimal measurement schedules with respect to the total number of measurements. The second stage accommodates the traffic demand of links, and a heuristic transmission scheduling algorithm is proposed to compute near-optimal transmission schedules with respect to the total transmission time. Simulations under various traffic modes show that compared with existing protocols, RDMAC has lower network latency, higher network throughput, and also a good fairness performance. Copyright © 2014 John Wiley & Sons, Ltd.