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Maritime activities are on the rise, there is a growing demand for high-quality communication services that can cover larger areas. However, the transmission of high data rates to maritime users is challenging due to path loss from land base stations, which limits the transmission power. To overcome this challenge, researchers have been exploring the use of buoys in a marine environment as relays for communication technology. This paper proposes a simulation-based approach to investigate the impact of various beamwidths on communication performance when using a buoy as a relay. The objective is to determine the optimal beamwidth that yields the highest data rate for the target location. The approach is based on an offshore wave model where the direction of the buoy changes according to the height of the wave. The study investigates the performance of the relay in the downlink situation using receive beamforming, and the capacity at the user in the three-hop situation is verified using an amplify-and-forward (AF) relay that uses transmit beamforming to the user. The simulation results suggest that the beamwidth of the relay should be adjusted according to the wave conditions to optimize the data rate and relay position that satisfies a data rate superior to the direct path to the target position. Using a buoy as a relay can be a promising solution for enhancing maritime communications, and the simulation-based approach proposed in this paper can provide insights into how to optimize beamwidth for effective communication system design and implementation. In conclusion, the study results suggest that the use of buoys as relays for maritime communication is a feasible solution for expanding coverage and enhancing communication quality. The proposed simulation-based approach provides a useful tool for identifying relay beamwidths for achieving higher data rates in different wave conditions. These findings have significant implications for the design and deployment of communication systems in maritime environments. [ABSTRACT FROM AUTHOR]

Due to laws, regulations, privacy, etc., between 70-90 percent of providers do not share medical data, forming a "data island". It is essential to collaborate across multiple institutions without sharing patient data. Most existing methods adopt distributed learning and centralized federal architecture to solve this problem, but there are problems of resource heterogeneity and data heterogeneity in the practical application process. This paper proposes a collaborative deep learning modelling method based on the blockchain network. The training process uses encryption parameters to replace the original remote source data transmission to protect privacy. Hyperledger Fabric blockchain is adopted to realize that the parties are not restricted by the third-party authoritative verification end. To a certain extent, the distrust and single point of failure caused by the centralized system are avoided. The aggregation algorithm uses the FedProx algorithm to solve the problem of device heterogeneity and data heterogeneity. The experiments show that the maximum improvement of segmentation accuracy in the collaborative training mode proposed in this paper is 11.179% compared to local training. In the sequential training mode, the average accuracy improvement is greater than 7%. In the parallel training mode, the average accuracy improvement is greater than 8%. The experimental results show that the model proposed in this paper can solve the current problem of centralized modelling of multicenter data. In particular, it provides ideas to solve privacy protection and break "data silos", and protects all data. [ABSTRACT FROM AUTHOR]

In edge computing scenarios, IoT end devices play a crucial role in relaying and forwarding data to significantly improve IoT network performance. However, traditional routing mechanisms are not applicable to this scenario due to differences in network size and environment. Therefore, it becomes crucial to establish an effective and reliable data transmission path to ensure secure communication between devices. In this paper, we propose a trusted path selection strategy that comprehensively considers multiple attributes, such as link stability and edge cooperation, and selects a stable and secure data transmission path based on the link life cycle, energy level, trust level, and authentication status. In addition, we propose the Stability-based On-demand Multipath Distance Vector (STAOMDV) protocol based on the Ad hoc AOMDV protocol. The STAOMDV protocol implements the collection and updating of link stability attributes during the route discovery and maintenance process. By integrating the STAOMDV protocol with the proposed path selection strategy, a dependable and efficient routing mechanism is established for IoT networks in edge computing scenarios. Simulation results validate that the proposed STAOMDV model achieves a balance in network energy consumption and extends the overall network lifespan. [ABSTRACT FROM AUTHOR]

Recently, various security threats such as data leakage and data forgery have been possible in the communication and storage of data shared in the cloud environment. This paper conducted a study on the CP-ABSC scheme to solve these security threats. In the existing CP-ABSC scheme, if the data is obtained by the unsigncryption of the data user incorrectly, the identity of the data owner who uploaded the ciphertext cannot be known. Also, when verifying the leaked secret key, the identity information of the data user who leaked the secret key cannot be known. In terms of efficiency, the number of attributes can affect the ciphertext. In addition, a large amount of computation is required for the user to unsigncrypt the ciphertext. In this paper, we propose ECP-ABSC that provides data user traceability, and use it in a cloud environment to provide an efficient and secure data sharing scheme. The proposed ECP-ABSC scheme can trace and verify the identity of the data owner who uploaded the ciphertext incorrectly and the data user who leaked the secret key for the first time. In addition, the ciphertext of a constant size is output and the efficiency of the user's unsigncryption computation were improved. [ABSTRACT FROM AUTHOR]

Due to increasing spectrum demand for new wireless devices applications, cooperative spectrum sensing (CSS) paradigm is the most promising solution to alleviate the spectrum shortage problem. However, in the interweave cognitive radio (CR) system, the inherent nature of CSS opens a hole to Byzantine attack, thereby resulting in a significant drop of the CSS security and efficiency. In view of this, a weighted differential sequential single symbol (WD3S) algorithm based on MATLAB platform is developed to accurately identify malicious users (MUs) and benefit useful sensing information from their malicious reports in this paper. In order to achieve this, a dynamic Byzantine attack model is proposed to describe malicious behaviors for MUs in an interweave CR system. On the basis of this, a method of data transmission consistency verification is formulated to evaluate the global decision's correctness and update the trust value (TrV) of secondary users (SUs), thereby accurately identifying MUs. Then, we innovatively reuse malicious sensing information from MUs by the weight allocation scheme. In addition, considering a high spectrum usage of primary network, a sequential and differential reporting way based on a single symbol is also proposed in the process of the sensing information submission. Finally, under various Byzantine attack types, we provide in-depth simulations to demonstrate the efficiency and security of the proposed WD3S. [ABSTRACT FROM AUTHOR]

For an energy harvesting sensor network, when the network lifetime is not the only primary goal, maximizing the network performance under environmental energy harvesting becomes a more critical issue. However, clustering protocols that aim at providing maximum information throughput have not been thoroughly explored in Energy Harvesting Wireless Sensor Networks (EH-WSNs). In this paper, clustering protocols are studied for maximizing the data transmission in the whole network. Based on a long short-term memory (LSTM) energy predictor and node energy consumption and supplement models, an uneven clustering protocol is proposed where the cluster head selection and cluster size control are thoroughly designed for this purpose. Simulations and results verify that the proposed scheme can outperform some classic schemes by having more data packets received by the cluster heads (CHs) and the base station (BS) under these energy constraints. The outcomes of this paper also provide some insights for choosing clustering routing protocols in EH-WSNs, by exploiting the factors such as uneven clustering size, number of clusters, multiple CHs, multihop routing strategy, and energy supplementing period. [ABSTRACT FROM AUTHOR]

A current autonomous vehicle determines its driving strategy by considering only external factors (Pedestrians, road conditions, etc.) without considering the interior condition of the vehicle. To solve the problem, this paper proposes "An Optimal Driving Support Strategy(ODSS) based on an Genetic Algorithm for Autonomous Vehicles" which determines the optimal strategy of an autonomous vehicle by analyzing not only the external factors, but also the internal factors of the vehicle(consumable conditions, RPM levels etc.). The proposed ODSS consists of 4 modules. The first module is a Data Communication Module (DCM) which converts CAN, FlexRay, and HSCAN messages of vehicles into WAVE messages and sends the converted messages to the Cloud and receives the analyzed result from the Cloud using V2X. The second module is a Data Management Module (DMM) that classifies the converted WAVE messages and stores the classified messages in a road state table, a sensor message table, and a vehicle state table. The third module is a Data Analysis Module (DAM) which learns a genetic algorithm using sensor data from vehicles stored in the cloud and determines the optimal driving strategy of an autonomous vehicle. The fourth module is a Data Visualization Module (DVM) which displays the optimal driving strategy and the current driving conditions on a vehicle monitor. This paper compared the DCM with existing vehicle gateways and the DAM with the MLP and RF neural network models to validate the ODSS. In the experiment, the DCM improved a loss rate approximately by 5%, compared with existing vehicle gateways. In addition, because the DAM improved computation time by 40% and 20% separately, compared with the MLP and RF, it determined RPM, speed, steering angle and lane changes faster than them. [ABSTRACT FROM AUTHOR]

One of the main goals of wireless sensor networks (WSNs) is to utilize the energy of sensor nodes effectively and maximize the network lifetime. Thus, this paper proposed a routing protocol for WSNs based on virtual force disturbing mobile Sink node (VFMSR). According to the number of sensor nodes in the cluster, the average energy and the centroid factor of the cluster, a new cluster head (CH) election fitness function was designed. At the same time, a hexagonal fixed-point moving trajectory model with the best radius was constructed, and the virtual force was introduced to interfere with it, so as to avoid the frequent propagation of sink node position information, and reduce the energy consumption of CH. Combined with the improved ant colony algorithm (ACA), the shortest transmission path to Sink node was constructed to reduce the energy consumption of long-distance data transmission of CHs. The simulation results showed that, compared with LEACH, EIP-LEACH, ANT-LEACH and MECA protocols, VFMSR protocol was superior to the existing routing protocols in terms of network energy consumption and network lifetime, and compared with LEACH protocol, the network lifetime was increased by more than three times. [ABSTRACT FROM AUTHOR]

Cloud Computing has emerged as an extensively used technology not only in the IT sector but almost in all sectors. As the nature of the cloud is distributed and dynamic, the jeopardies present in the current implementations of virtualization, numerous security threats and attacks have been reported. Considering the potent architecture and the system complexity, it is indispensable to adopt fundamentals. This paper proposes a secure authentication and data sharing scheme for providing security to the cloud data. An efficient IPSO-KELM is proposed for detecting the malicious behaviour of the user. Initially, the proposed method starts with the authentication phase of the data sender. After authentication, the sender sends the data to the cloud, and the IPSO-KELM identifies if the received data from the sender is an attacked one or normal data i.e. the algorithm identifies if the data is received from a malicious sender or authenticated sender. If the data received from the sender is identified to be normal data, then the data is securely shared with the data receiver using SHA256-RSA algorithm. The upshot of the proposed method are scrutinized by identifying the dissimilarities with the other existing techniques to confirm that the proposed IPSO-KELM and SHA256-RSA works well for malicious user detection and secure data sharing in the cloud. [ABSTRACT FROM AUTHOR]

The collaborative content caching system is an effective solution developed in recent years to reduce transmission delay and network traffic. In order to decrease the service end-to-end transmission delay for future 5G ultra-dense networks (UDN), this paper proposes a novel service migration method that can guarantee the continuity of service and simultaneously reduce the traffic flow in the network. In this paper, we propose a service migration optimization model that minimizes the cumulative transmission delay within the constraints of quality of service (QoS) guarantee and network condition. Subsequently, we propose an improved firefly algorithm to solve this optimization problem. Simulation results show that compared to traditional collaborative content caching schemes, the proposed algorithm can significantly decrease transmission delay and network traffic flow. [ABSTRACT FROM AUTHOR]

This paper describes transformations between elemental image arrays and a RGBD image for three-dimensional integral imaging and transmitting systems. Two transformations are introduced and analyzed in the proposed method. Normally, a RGBD image is utilized in efficient 3D data transmission although 3D imaging and display is restricted. Thus, a pixel-to-pixel mapping is required to obtain an elemental image array from a RGBD image. However, transformations and their analysis have little attention in computational integral imaging and transmission. Thus, in this paper, we introduce two different mapping methods that are called as the forward and backward mapping methods. Also, two mappings are analyzed and compared in terms of complexity and visual quality. In addition, a special condition, named as the hole-free condition in this paper, is proposed to understand the methods analytically. To verify our analysis, we carry out experiments for test images and the results indicate that the proposed methods and their analysis work in terms of the computational cost and visual quality. [ABSTRACT FROM AUTHOR]

Recent studies have revealed the efficacy of incorporating delayed channel state information at transmit side (CSIT) in transmission scheme design. This paper focuses on transmit precoder design to maximize the ergodic sum-rate in a two-user Multiple-Input Single-Output (MISO) system with delayed and statistical CSIT. A new transmit strategy which precodes signals in all transmit slots is proposed in this paper, denoted as all time-slots precoding Alternative MAT (AAMAT). There is a common procedure in conventional delayed-CSIT based schemes, which is retransmitting the overheard interferences. Since the retransmitting signal is intended to both users, all previous schemes tend to use only one antenna. We however figure out an improvement in spectral efficiency could be realized if all antennas can be utilized. In this paper, we detail the design of the procoder which enabling all antennas and also we compute a lower bound of the ergodic sum-rate in an ideal condition. In addition, simulation results demonstrate the superiority of our proposed scheme. [ABSTRACT FROM AUTHOR]

By means of compressive sensing (CS) technique, this paper considers the collection of sensor data with spatiotemporal correlations in wireless sensor networks (WSNs). In energy-constrained WSNs, one-dimensional CS methods need a lot of data transmissions since they are less applicable in fully exploiting the spatiotemporal correlations, while the Kronecker CS (KCS) methods suffer performance degradations when the signal dimension increases. In this paper, an appropriate sensing matrix as well as an efficient sensing method is proposed to further reduce the data transmissions without the loss of the recovery performance. Different matrices for the temporal signal of each sensor node are separately designed. The corresponding energy-efficient data gathering method is presented, which only transmitting a subset of sensor readings to recover data of the entire WSN. Theoretical analysis indicates that the sensing structure could have the relatively small mutual coherence according to the selection of matrix. Compared with the existing spatiotemporal CS (CS-ST) method, the simulation results show that the proposed efficient measurement method could reduce data transmissions by about 25% with the similar recovery performance. In addition, compared with the conventional KCS method, for 95% successful recovery, the proposed sensing structure could improve the recovery performance by about 20%. [ABSTRACT FROM AUTHOR]

The distribution of popular videos incurs a large amount of traffic at the base stations (BS) of networks. Device-to-multi-device (D2MD) communication has emerged an efficient radio access technology for offloading BS traffic in recent years. However, traditional studies have focused on synchronous user requests whereas asynchronous user requests are more common. Hence, offloading BS traffic in case of asynchronous user requests while considering their time-varying characteristics and the quality of experience (QoE) of video request users (VRUs) is a pressing problem. This paper uses social stability (SS) and video loading duration (VLD)- tolerant property to group VRUs and seed users (SUs) to offload BS traffic. We define the average amount of data transmission (AADT) to measure the network's capacity for offloading BS traffic. Based on this, we formulate a time-varying bipartite graph matching optimization problem. We decouple the problem into two subproblems which can be solved separately in terms of time and space. Then, we propose the socially aware D2MD user selection (SAD2MD- S) algorithm based on finite horizon optimal stopping theory, and propose the SAD2MD user matching (SA-D2MD-M) algorithm to solve the two subproblems. The results of simulations show that our algorithms outperform prevalent algorithms. [ABSTRACT FROM AUTHOR]

In the Vehicular Ad-hoc Network (VANET), the data transmission of time-sensitive applications requires low latency, such as accident warnings, driving guidance, etc. However, frequent changes of topology in VANET will result in data transmission failures. In order to improve the efficiency of VANETs data transmission and increase the timeliness of data, this paper proposes a relay scheme based on Recurrent Neural Network (RNN) trajectory prediction, which can be used to select the optimal relay vehicle to transmit data. The proposed scheme learns vehicle trajectory in a distributed manner and calculates the predicted trajectory, and then the optimal vehicle can be selected to complete the data transmission, which ensures the timeliness of the data. Finally, we carry out a set of simulations to demonstrate the performance of the algorithm. Simulation results show that the proposed scheme enhances the timeliness of the data and the accuracy of the predicted driving trajectory. [ABSTRACT FROM AUTHOR]

This paper proposes a novel data prioritization and transmission mechanism to minimize the number of packets transmitted and reduce network overload using the constrained application protocol (CoAP) in resource-constrained networks. The proposed scheme adopts four classification parameters to classify and prioritize data from a sensor. With the packet prioritization scheme, the sensed data having the lowest priority is only delivered using the proposed keep-alive message notification to decrease the number of packets transmitted. The performance evaluation demonstrates that the proposed scheme shows the improvement of resource utilization in energy consumption, and bandwidth usage compared with the existing CoAP methods. Furthermore, the proposed scheme supports quality-of-service (QoS) per packet by differentiating transmission delays regarding priorities. [ABSTRACT FROM AUTHOR]

Reliable and secure data transmission in the application environment assisted by the wireless sensor network is one of the major challenges. Problem like blind forwarding and data inaccessibility affect the efficiency of overall infrastructure performance. This paper proposes routing protocol for forwarding and error recovery during packet loss. The same is achieved by energy and hops distance-based formulation of the routing mechanism. The reachability of the intermediate node to the source node is the major factor that helps in improving the lifetime of the network. On the other hand, intelligent hop selection increases the reliability over continuous data transmission. The number of hop count is factor of hop weight and available energy of the node. The comparison over the previous state of the art using QualNet-7.4 network simulator shows the effectiveness of proposed work in terms of overall energy conservation of network and reliable data delivery. The simulation results also show the elimination of blind forwarding and data inaccessibility. [ABSTRACT FROM AUTHOR]

Multicast Mesh based Mobile Ad-hoc NETworks (MANETs) provide efficient data transmission in energy restraint areas without a fixed infrastructure. In this paper, the authors present an improved version of protocol SLIMMER developed by them earlier, and name it SLIMMER-SN. Most mesh-based protocols suffer from redundancy; however, the proposed protocol controls redundancy through the concept of forwarding nodes. The proposed protocol uses remaining energy of a node to decide its energy efficiency. For measuring stability, a new metric called Stability of Node (SN) has been introduced which depends on transmission range, node density and node velocity. For data transfer, a weighted cost function selects the most energy efficient nodes / most stable nodes or a weighted combination of both. This makes the node selection criteria more dynamic. The protocol works in two steps: (1) calculating SN and (2) using SN value in the weighted cost function for selection of nodes. The study compared the proposed protocol, with other mesh-based protocols PUMA and SLIMMER, based on packet delivery ratio (PDR), throughput, end-to-end delay and average energy consumption under different simulation conditions. Results clearly demonstrate that SLIMMER-SN outperformed both PUMA and SLIMMER. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) based sensor networks have gained unprecedented popularity in recent years. With the exponential explosion of the objects (sensors and mobiles), the bandwidth and the speed of data transmission are dwarfed by the anticipated emergence of IoT. In this paper, we propose a novel heterogeneous IoT model integrated the power line communication (PLC) and WiFi network to increase the network capacity and cope with the rapid growth of the objects. We firstly propose the mean transmission delay calculation algorithm based the 3D Markov chain according to the multi-priority of the objects. Then, the attractor selection algorithm, which is based on the adaptive behavior of the biological system, is exploited. The combined the 3D Markov chain and the attractor selection model, named MASM, can select the optimal path adaptively in the heterogeneous IoT according to the environment. Furthermore, we verify that the MASM improves the transmission efficiency and reduce the transmission delay effectively. The simulation results show that the MASM is stable to changes in the environment and more applicable for the heterogeneous IoT, compared with the other algorithms. [ABSTRACT FROM AUTHOR]

Vehicular ad-hoc networks (VANETs) have become increasingly significant in intelligent transportation systems, they play a great role in improving traffic safety and efficiency. In the deployment of intelligent VANETs, intelligent vehicles can efficiently exchange important or urgent traffic information and make driving decisions. Meanwhile, secure data communication and vehicle's identity privacy have been highlighted. To cope with these security issues, in this paper, we construct an efficient anonymous authentication scheme with secure communication in intelligent VANETs. Combing the ElGamal encryption technique with a modified Schnorr signature technique, the proposed scheme provides secure anonymous authentication process for encrypted message in the vehicle-to-infrastructure communication model, and achieves identity privacy, forward security, and reply attack resistance simultaneously. Moreover, except the trusted authority (TA), any outside entity cannot trace the real identity of an intelligent vehicle. The proposed scheme is designed on an identity-based system, which can remove the costs of establishing public key infrastructure (PKI) and certificates management. Compared with existing authentication schemes, the proposed scheme is much more practical in intelligent VANETs. [ABSTRACT FROM AUTHOR]

Multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) is widely applied in wireless communication by virtue of its excellent properties in data transmission rate and transmission accuracy. However, as a major drawback of MIMO-OFDM systems, the high peak-to-average power ratio (PAPR) complicates the design of the power amplifier at the receiver end. Some available PAPR reduction methods such as selective mapping (SLM) suffer from high computational complexity. In this paper, a low-complexity SLM method based on active constellation extension (ACE) and joint space-time selective mapping (AST-SLM) for reducing PAPR in Alamouti STBC MIMO-OFDM systems is proposed. In SLM scheme, two IFFT operations are required for obtaining each transmission sequence pair, and the selected phase vector is transmitted as side information(SI). However, in the proposed AST-SLM method, only a few IFFT operations are required for generating all the transmission sequence pairs. The complexity of AST-SLM is at least 86%..less than SLM. In addition, the SI needed in AST-SLMis at least 92.1% less than SLMby using the presented blind detection scheme to estimate SI. We show, analytically and with simulations, that AST-SLM can achieve significant performance of PAPR reduction and close performance of bit error rate (BER) compared to SLM scheme. [ABSTRACT FROM AUTHOR]

Considering that the existing Long Term Evolution is not suitable for the fast and frequent handovers of high-speed trains, this paper proposes a relay-assisted handover mechanism to solve the problems of long handover authentication time and vulnerable to security attacks. It can achieve mutual authentication for train-ground wireless communication, and data transmission is consistent with one-time pad at the same time. The security analysis, efficiency analysis and simulation results show that the proposed mechanism not only realizes the forward security and resists many common attacks, but also effectively reduces the computational overhead of train antenna during the secure handover process. When the running speed of a train is lower than 500km/h, the handover delay is generally lower than 50ms and the handover outage probability is less than 1.8%. When the running speed of a train is 350km/h, the throughput is higher than 16.4mbps in the process of handover. Therefore, the secure handover mechanism can improve the handover performance of high-speed trains. [ABSTRACT FROM AUTHOR]

In opportunistic networks, nodes may appear some selfishness while transmitting the message, however, most of the existing research works consider the individual selfishness or social selfishness respectively, and these two types of selfishness may coexist in opportunistic networks. In this paper, we propose an Incentive Aware Routing based on Game Theory for selfish OPPNETs, named IAR-GT, which uses Rubinstein-Stahl bargaining game model to incentivize selfish nodes cooperation in data forwarding. IAR-GT scheme not only considers the resources of nodes, but also uses a new method to calculate the social ties between them. Trace-driven simulations show that our incentive aware routing scheme achieves better performances than comparing schemes under two types of selfishness coexistence environments. [ABSTRACT FROM AUTHOR]

BeiDou navigation satellite system (BDS) is one of the four main types of global navigation satellite systems. The current system has been widely used by the military and by the aerospace, transportation, and marine fields, among others. However, challenges still remain in the BeiDou system, which requires rapid responses for delay-sensitive devices. A differential positioning algorithm called the data center-based differential positioning (DCDP) method is widely used to avoid the influence of errors. In this method, the positioning information of multiple base stations is uploaded to the data center, and the positioning errors are calculated uniformly by the data center based on the minimum variance or a weighted average algorithm. However, the DCDP method has high delay and overload risk. To solve these problems, this paper introduces edge computing to relieve pressure on the data center. Instead of transmitting the positioning information to the data center, a novel method called edge computing-based differential positioning (ECDP) chooses the nearest reference station to perform edge computing and transmits the difference value to the mobile receiver directly. Simulation results and experiments demonstrate that the performance of the ECDP outperforms that of the DCDP method. The delay of the ECDP method is about 500ms less than that of the DCDP method. Moreover, in the range of allowable burst error, the median of the positioning accuracy of the ECDP method is 0.7923m while that of the DCDP method is 0.8028m. [ABSTRACT FROM AUTHOR]

In this paper, a full-duplex NOMA relaying based underlay device-to-device (D2D) communication scheme is proposed, in which D2D transmitter assists cellular downlink transmission as a full-duplex relay. Specifically, D2D transmitter receives signals from base station and transmits the superposition signals to D2D receiver and cellular user in NOMA scheme simultaneously. Furthermore, we investigate the power allocation under the proposed scheme, aiming to maximize D2D link's achievable transmit rate under cellular link's transmit rate constraint and total power constraint. To tackle the power allocation problem, we first propose a power allocation method based on linear fractional programming. In addition, we derive closed-form expressions of the optimal transmit power for base station and D2D transmitter. Simulation results show that the performance of two solutions matches well and the proposed full-duplex NOMA relaying based underlay D2D communication scheme outperforms existing full-duplex relaying based D2D communication scheme. [ABSTRACT FROM AUTHOR]

The transform domain communication system (Hereinafter referred to as TDCS) takes on numerous advantages, inclusive of anti-jamming and low probability of detection. Yet its application is confined by the consistent spectrum in the transmitter and receiver, which is not possible in the case of a huge distance exsits between them. In this paper, a TDCS based modified weighted fractional fourier transform (WFRFT) is proposed to solve the problem resulting from spectrum mismatching for TDCS application. The amplitude and phase information are incorporated with the TDCS signals and transmit to the receiver together in the wake of a modified WFRFT. The basic function and the TDCS signals shall be accessible to the receivers in the wake of an inverse WFRFT transform, which make sure that the original information can be demodulated properly. The system's reliability while transmitting signals with different modulation methods and with spectrum mismatching is demonstrated by bit error rate (BER). In the meantime, the constellations of the signals and the BER performances at the eavesdropper demonstrate the proposed system is better secured. [ABSTRACT FROM AUTHOR]

In sensor medium access control (SMAC) protocol, sensor nodes can only access the channel in the scheduling and listening period. However, this fixed working method may generate data latency and high conflict. To solve those problems, scheduling duty in the original SMAC protocol is divided into multiple small scheduling duties (micro duty MD). By applying different micro-dispersed contention channel, sensor nodes can reduce the collision probability of the data and thereby save energy. Based on the given micro-duty, this paper presents an adaptive duty cycle (DC) and back-off algorithm, aiming at detecting the fixed duty cycle in SMAC protocol. According to the given buffer queue length, sensor nodes dynamically change the duty cycle. In the context of low duty cycle and low flow, fair binary exponential back-off (F-BEB) algorithm is applied to reduce data latency. In the context of high duty cycle and high flow, capture avoidance binary exponential back-off (CA-BEB) algorithm is used to further reduce the conflict probability for saving energy consumption. Based on the above two contexts, we propose an improved SMAC protocol, micro duty adaptive SMAC protocol (MDA-SMAC). Comparing the performance between MDA-SMAC protocol and SMAC protocol on the NS-2 simulation platform, the results show that, MDA-SMAC protocol performs better in terms of energy consumption, latency and effective throughput than SMAC protocol, especially in the condition of more crowded network traffic and more sensor nodes. [ABSTRACT FROM AUTHOR]

In recent years, dense small cell network has been deployed to address the challenge that has resulted from the unprecendented growth of mobile data traffic and users. It has proven to be a cost efficeient solution to offload traffic from macro-cells. Software defined heterogeneous wireless network can decouple the control plane from the data plane. The control signal goes through the macro-cell while the data traffic can be offloaded by small cells. In this paper, we propose a framework for cell virtualization and user association in order to satisfy versatile requirements of multiple tenants. In the proposed framework, we propose an interference graph partioning based virtual-cell association and customized physical-cell association for multi-homed users in a software defined small cell network. The proposed user association scheme includes 3 steps: initialization, virtual-cell association and physical-cell association. Simulation results show that the proposed virtual-cell association outperforms the other schemes. For physical-cell association, the results on resource utilization and user fairness are examined for mobile users and infrastructure providers. [ABSTRACT FROM AUTHOR]

The dynamic opportunistic device-to-device (DO-D2D) network will frequently emerge in the fifth generation (5G) wireless communication due to high-density and fast-moving mobile devices. In order to improve the Quality of Experience (QoE) of users with different computing capacity devices in the DO-D2D network, in this paper, we focus on the study of how to reduce the packets retransmission delay and satisfy heterogeneous devices. To select as many devices as possible to transmit simultaneously without interference, the concurrent transmitters-selecting algorithm is firstly put forward. It jointly considers the number of packets successfully received by each device and the device's connectivity. Then, to satisfy different devices' demands while primarily ensuring the base-layer packets successfully received by all the devices, the layer-cooperation instantly decodable network coding is presented, which is used to select transmission packets combination for each transmitter. Simulation results illustrate that there is an appreciable retransmission delay gain especially in the poor channel quality network compared to the traditional base-station (BS) retransmission algorithm. In addition, our proposed algorithms perform well to satisfy the different demands of users with heterogeneous devices. [ABSTRACT FROM AUTHOR]

One of the most innovative paradigms for the next-generation of wireless cellular networks is the cloud-radio access networks (C-RANs). In C-RANs, base station functions are distributed between the remote radio heads (RHHs) and base band unit (BBU) pool, and a communication link is defined between them which is referred as the fronthaul. This leveraging link is expected to reduce the CAPEX (capital expenditure) and OPEX (operating expense) of envisioned cellular architectures as well as improves the spectral and energy efficiencies, provides the high scalability, and efficient mobility management capabilities. The fronthaul link carries the baseband signals between the RRHs and BBU pool using the digital radio over fiber (RoF) based common public radio interface (CPRI). CPRI based optical links imposed stringent synchronization, latency and throughput requirements on the fronthaul. As a result, fronthaul becomes a hinder in commercial deployments of C-RANs and is seen as one of a major bottleneck for backbone networks. The optimization of fronthaul is still a challenging issue and requires further exploration at industrial and academic levels. This paper comprehensively summarized the current challenges and requirements of fronthaul networks, and discusses the recently proposed system architectures, virtualization techniques, key transport technologies and compression schemes to carry the time-sensitive traffic in fronthaul networks. [ABSTRACT FROM AUTHOR]

With the recent popularity of smart terminals, the demand for high-data-rate transmission is growing rapidly, which brings a new challenge for the traditional cellular networks. Both device-to-device (D2D) communication and small cells are effective to improve the transmission efficiency of local communication. In this paper, we apply D2D communication into a small cell network system (SNets) and study about the optimization problem of resource allocation for D2D communication. The optimization problemincludes system scheduling and resource allocation, which is exponentially complex and the optimal solution is infeasible to achieve. Therefore, in this paper, the optimization problem is decomposed into several smaller problems and a hierarchical scheme is proposed to obtain the solution. The proposed hierarchical scheme consists of three steps: D2D communication groups formation, the estimation of sub-channels needed by each D2D communication group and specific resource allocation. From numerical simulation results, we find that the proposed resource allocation scheme is effective in improving the spectral efficiency and reducing the outage probability of D2D communication. [ABSTRACT FROM AUTHOR]

Rendezvous is a process of two or more cognitive radio nodes gathering on the same channel at the same time for a negotiation to establish data communications. This paper discusses rendezvous issues in cognitive radio networks. It details why rendezvous is an issue in cognitive radio networks and how rendezvous works. It classifies channel access methods, and details sequence-based channel-hopping methods. It surveys existing works on blind rendezvous and compares the proposed algorithms in terms of the maximum time to rendezvous. This paper discusses the properties that an efficient channel-hopping rendezvous algorithm should have and illustrates common issues in the existing rendezvous methods. It also explains open research issues in the rendezvous area. [ABSTRACT FROM AUTHOR]

In this paper, optimal sensing time allocation for adaptive multiband spectrum sensing-transmission procedure is investigated. The sensing procedure consists of an exploration phase and a detection phase. We first formulate an optimization problem to maximize the throughput by designing not only the overall sensing time, but also the sensing time for every stage in the exploration and detection phases, while keeping the miss detection probability for each channel under a pre-defined threshold. Then, we transform the initial non-convex optimization problem into a convex bilevel optimization problem to make it mathematically tractable. Simulation results show that the optimized sensing time setting in this paper can provide a significant performance gain over the previous studies. [ABSTRACT FROM AUTHOR]

This paper investigates the power allocation and outage performance of MIMO full-duplex relaying (MFDR), based on orthogonal space-time block codes (OSTBC), in cognitive radio systems. OSTBC transmission is used as a simple means to achieve multi-antenna diversity gain. Cognitive MFDR systems not only have the advantage of increasing spectral efficiency through spectrum sharing, but they can also extend coverage through the use of relays. In cognitive MFDR systems, the primary user experiences interference from the secondary source and relay simultaneously, owing to full duplexing. It is therefore necessary to optimize the transmission powers at the secondary source and relay. In this paper, we propose an optimal power allocation (OPA) scheme based on minimizing the outage probability in cognitive MFDR systems. We also analyse the outage probability of the secondary user in noise-limited and interference-limited environments in Nakagami-m fading channels. Simulation results show that the proposed schemes achieve performance improvements in terms of reducing outage probability. [ABSTRACT FROM AUTHOR]

Lenstra-Lenstra-Lovász (LLL) is an effective receiving algorithm for Multiple-Input-Multiple-Output (MIMO) systems, which is believed can achieve full diversity in MIMO detection of fading channels. However, the LLL algorithm features polynomial complexity and shows poor performance in terms of convergence. The reduction of algorithmic complexity and the acceleration of convergence are key problems in optimizing the LLL algorithm. In this paper, a variant of the LLL algorithm, the Hybrid-Fix-and-Round LLL algorithm, which combines both fix and round measurements in the size reduction procedure, is proposed. By utilizing fix operation, the algorithmic procedure is altered and the size reduction procedure is skipped by the hybrid algorithm with significantly higher probability. As a consequence, the simulation results reveal that the Hybrid-Fix-and-Round-LLL algorithm carries a faster rate of convergence compared to the original LLL algorithm, and its algorithmic complexity is at most one order lower than original LLL algorithm in real field. Comparing to other families of LLL algorithm, Hybrid-Fix-and-Round-LLL algorithm can make a better compromise in performance and algorithmic complexity. [ABSTRACT FROM AUTHOR]

Source routing is the routing scheme that arranges the whole path from source to target at the origin node that may suit the requirements from the upper layer applications' perspective. The centralized control in SDN (Software-Defined Networking) networks enables the awareness of the global topology at the controller. Therefore, augmented source routing schemes can be designed to achieve various purposes. This paper proposes a source routing scheme that conducts the top-K QoS-aware paths discovery in SDN. First, the novel non-invasive QoS over LLDP scheme is designed to collect QoS information based on LLDP in a piggyback fashion. Then, variations of the KSP (K Shortest Paths) algorithm are derived to find the unconstrained/constrained top-K ranked paths with regard to individual/overall path costs, reflecting the Quality of Service. The experiment results show that the proposed scheme can efficiently collect the QoS information and find the top-K paths. Also, the performance of our scheme is applicable in QoS-sensitive application scenarios compared with previous works. [ABSTRACT FROM AUTHOR]

Mobile opportunistic network is a kind of ad hoc networks, which implements the multi-hop routing communication with the help of contact opportunity brought about by the mobility of the nodes. It always uses opportunistic data transmission mode based on store-carry-forward to solve intermittent connect problem of link. Although many routing schemes have been proposed, most of them adopt the greedy transmission mode to pursue a higher delivery efficient, which result in unfairness extremely among nodes. While, this issue has not been paid enough attention up to now. In this paper, we analyzed the main factors that reflect fairness among nodes, modeled routing selection as a multiple attribute decision making problem, and proposed our Fairness-aware Routing Strategy, named FARS. To evaluate the performance of our FARS, extensive simulations and analysis have been done based on a real-life dataset and a synthetic dataset, respectively. The results show that, compared with other existing protocols, our FARS can greatly improve the fairness of the nodes when ensuring the overall delivery performance of the network. [ABSTRACT FROM AUTHOR]

A wireless body-sensor network (WBSN) refers to a network-configured environment in which sensors are placed on both the inside and outside of the human body. The sensors are much smaller and the energy is more constrained when compared to traditional wireless sensor network (WSN) environments. The critical nature of the energy-constraint issue in WBSN environments has led to numerous studies on the reduction of energy consumption of WBSN sensors. The transmission-power-control (TPC) technique adjusts the transmission-power level (TPL) of sensors in the WBSN and reduces the energy consumption that occurs during communications. To elaborate, when transmission sensors and reception sensors are placed in various parts of the human body, the transmission sensors regularly send sensor data to the reception sensors. As the reception sensors receive data from the transmission sensors, real-time measurements of the received signal-strength indication (RSSI), which is the value that indicates the channel status, are taken to determine the TPL that suits the current-channel status. This TPL information is then sent back to the transmission sensors. The transmission sensors adjust their current TPL based on the TPL that they receive from the reception sensors. The initial TPC algorithm made linear or binary adjustments using only the information of the current-channel status. However, because various data in the WBSN environment can be utilized to create a more efficient TPC algorithm, many different types of TPC algorithms that combine human movements or fuse TPC with other algorithms have emerged. This paper defines and discusses the design and development process of an efficient TPC algorithm for WBSNs. We will describe the WBSN characteristics, model, and closed-loop mechanism, followed by an examination of recent TPC studies. [ABSTRACT FROM AUTHOR]

Mobile computing environment is subject to the constraints of bounded network bandwidth, frequently encountered disconnections, insufficient battery power, and system asymmetry. To meet these constraints and to gain high scalability, data broadcasting has been proposed on data transmission techniques. However, updates made to the database in any broadcast cycle are deferred to the next cycle in order to appear to mobile clients with lower data currency. The main goal of this paper is to enhance the transaction performance processing and database currency. The main approach involves decomposing the main broadcast cycle into a number of sub-cycles, where data items are broadcasted as they were originally sequenced in the main cycle while appearing in the most current versions. A concurrency control method AOCCRBSC is proposed to cope well with the cycle decomposition. The proposed method exploits predeclaration and adapts the AOCCRB method by customizing prefetching, back-off, and partial backward and forward validation techniques. As a result, more than one of the conflicting transactions is allowed to commit at the server in the same broadcast cycle which empowers the processing of both update and read-only transactions and improves data currency. [ABSTRACT FROM AUTHOR]

In this paper, an error-detection-coding-aided iterative hard decision interference cancellation (EDC-IHIC) scheme for multiple-input multiple-output systems employing hybrid automatic repeat request (HARQ) for multi-packet transmission is developed and investigated. In the EDC-IHIC scheme, only packets identified as error-free by the EDC are submitted to the interference cancellation (IC) stage for cancellation from the received signals. Therefore, the possibility of error propagation, including inter-transmission error propagation, can be eliminated using EDC-IHIC. Because EDC must be implemented in systems that employ HARQ to determine packet retransmission, error propagation can be prevented without the need for additional redundancy. The results of simulations conducted herein verify that the EDC-IHIC scheme outperforms conventional hard decision IC schemes in terms of the packet error rate in various environments. [ABSTRACT FROM AUTHOR]

This paper presents a novel and efficient data transmission scheme based on mobile edge computing for the massive IoT environments which should support various type of services and devices. Based on an accurate and precise synchronization process, it maximizes data transmission throughput, and consistently maintains a flow's latency. To this end, the proposed efficient software defined data transmission scheme (ESD-DTS) configures and utilizes synchronization zones in accordance with the 4 usage cases, which are end node-to-end node (EN-EN), end node-to-cloud network (EN-CN), end node-to-Internet node (EN-IN), and edge node-to-core node (EdN-CN); and it transmit the data by the required service attributes, which are divided into 3 groups (low-end group, medium-end group, and high-end group). In addition, the ESD-DTS provides a specific data transmission method, which is operated by a buffer threshold value, for the low-end group, and it effectively accommodates massive IT devices. By doing this, the proposed scheme not only supports a high, medium, and low quality of service, but also is complied with various 5G usage scenarios. The essential difference between the previous and the proposed scheme is that the existing schemes are used to handle each packet only to provide high quality and bandwidth, whereas the proposed scheme introduces synchronization zones for various type of services to manage the efficiency of each service flow. Performance evaluations show that the proposed scheme outperforms the previous schemes in terms of throughput, control message overhead, and latency. Therefore, the proposed ESD-DTS is very suitable for upcoming 5G networks in a variety of massive IoT environments with supporting mobile edge computing (MEC). [ABSTRACT FROM AUTHOR]

Recently interest in Internet of Things(IoT) has attracted significant attention at national level. IoT can create new services as a technology to exchange data through connections among a huge number of objects around the user. Data communication between objects provides not only information collected in the surrounding environment but also various personalized information. IoT services which provide these various types of data are exposed to numerous security vulnerabilities. If data is maliciously collected and used by an attacker in an IoT environment that deals with various data, security threats are greater than those in existing network environments. Therefore, security of all data exchanged in the IoT environment is essential. However, lightweight terminal devices used in the IoT environment are not suitable for applying the existing encryption algorithm. In addition, IoT networks consisting of many sensors require group communication. Therefore, this paper proposes a secure multicast scheme using the proxy re-encryption method based on Vehicular ad-hoc networks(VANET) environment. The proposed method is suitable for a large-scale dynamic IoT network environment using unreliable servers. [ABSTRACT FROM AUTHOR]

In this Paper, we propose 8K UHD (Ultra High Definition) encapsulation method for efficient transmission and reception based on MMT (MPEG Media Transport). Broadcasting services for 8K UHD allow users to feel the maximized reality. However, present technology is difficult to provide 8K UHD in broadcasting networks, because the 8K UHD bitrate is too high to be transmitted in the current broadcasting networks. Research for transmitting 8K UHD is underway. In some researches, a receiver is implemented with four 4K UHD display instead of a 8K UHD display. In order to transmit 8K UHD within the limited transmission bitrate of broadcasting network, 8K UHD contents encoded by SHVC (Scalable High Efficiency Video Coding) and then transmitted over heterogeneous network. For using the broadcasting and communication networks, MMT standard is used. MMT is IP based transmission protocol as the next generation transmission protocol. According to the MMT standard, video stream encapsulated and transmitted in MMTP (MMT Protocol) packet. IP-based broadcasting and communication networks can be used to transmit simultaneously, and the receiver can synchronize and play it. We propose an encapsulation method that can efficiently transmit and receive 8K UHD. The proposed method increases a payload rate and decreases an initial delay at the receiver. We show that the efficiency of the proposed method is verified by experimental tests. [ABSTRACT FROM AUTHOR]

Recently, the biometric-based authentication systems such as FIDO (Fast Identity Online) are increased in mobile computing environments. The biometric-based authentication systems are performed on the mobile devices with the battery, the improving energy efficiency is important issue. In the case, the size of images (i.e., face, fingerprint, iris, and etc.) affects both recognition accuracy and energy consumption, and hence the tradeoff analysis between the both recognition accuracy and energy consumption is necessary. In this paper, we propose an energy-efficient way to authenticate based on biometric information with tradeoff analysis between the both recognition accuracy and energy consumption in multimedia IoT (Internet of Things) transmission environments. We select the facial information among biometric information, and especially consider the multicore-based mobile devices. Based on our experimental results, we prove that the proposed approach can enhance the energy efficiency of GABOR+LBP+GRAY VALUE, GABOR+LBP, GABOR, and LBP by factors of 6.8, 3.6, 3.6, and 2.4 over the baseline, respectively, while satisfying user's face recognition accuracy. [ABSTRACT FROM AUTHOR]

In view of personal health and disease management based on cost effective healthcare services, there is a growing need for real-time monitoring services. The electrocardiogram (ECG) signal is one of the most important of health information and real-time monitoring of the ECG can provide an efficient way to cope with emergency situations, as well as assist in everyday health care. In this system, it is essential to continuously collect and transmit large amount of ECG data within a given time and provide maximum user convenience at the same time. When considering limited wireless capacity and unstable channel conditions, appropriate signal processing and transmission techniques such as compression are required. However, ISO/IEEE 11073 standards for interoperability between personal health devices cannot properly support compressed data transmission. Therefore, in the present study, the problems for handling compressed data are specified and new extended agent and manager are proposed to address the problems while maintaining compatibility with existing devices. Extended devices have two PM-stores enabling compression and a novel transmission scheme. A variety of compression techniques can be applied; in this paper, discrete cosine transformation (DCT) is used. And the priority of information after DCT compression enables new transmission techniques for performance improvement. The performance of the compressed signal and the original uncompressed signal transmitted over the noisy channel are compared in terms of percent root mean square difference (PRD) using our simulation results. Our transmission scheme shows a better performance and complies with 11073 standards. [ABSTRACT FROM AUTHOR]

In this paper, we study the cross-layer design for the AMC/HARQ-based wireless networks, and propose a new dynamic transmission-mode selection scheme to improve system spectrum efficiency. In the proposed scheme, dynamic thresholds for transmission-mode selection in each packet transmission and retransmission are jointly designed under the constraint of the overall packet error rate. Comparing with the existing schemes, the proposed scheme is inclined to apply higher modulation order at the first several (re)transmissions, which corresponds to higher-rate transmission modes thus higher average system spectrum efficiency. We also extend the cross-layer design to MIMO (Multi-input Multi-output) communication scenarios. Numerical results show that the proposed new dynamic transmission-mode selection scheme generally achieves higher average spectrum efficiency than the conventional and existing cross-layer design. [ABSTRACT FROM AUTHOR]

In the last decade, the 2.4 GHz band of IEEE 802.11 WLANs has become heavily congested due to the explosive increase in demand of Wi-Fi connectivity. With the current deployment of enterprise WLANs, channel switching mechanism continues to exhibit inefficiencies because it cannot adapt to real-time channel condition and the inability to support seamless channel switching. Software Defined Networking (SDN) as an emerging architecture is promising to introduce flexibility and programmability for wireless network management. Leveraging SDN to existing enterprise WLANs, channel switching method can be improved significantly. This paper presents a software-defined enterprise WLAN framework with a load aware automatic channel switching solution, which utilizes AP load and channel interference factor (CIF) to provide seamless channel switching. Two automatic channel switching algorithms named Single Switch (SS) and Double Switch (DS) are proposed to improve the overall user experience and the experience of users with highest traffic load respectively. Experiment results demonstrate that our solution can efficiently improve user experience in terms of jitter, transmission delay and network throughout when compared to the conventional channel switching mechanism. [ABSTRACT FROM AUTHOR]

The IEEE 802.11 compliant stations can transmit at multiple transmission rates. Selection of an appropriate transmission rate plays a significant role in determining the overall efficiency of a communication system. The technique which determines the channel state information and accordingly selects an appropriate transmission rate is called rate-adaptation protocol. The IEEE 802.11 standard does not provide standard specification for implementing a rate-adaptation protocol for its multi-rate capable wireless stations. Due to the lack of standard specification, there is a myriad of rate-adaptation protocols, proposed by industry and various research institutes. This paper surveys the existing rate-adaptation schemes, discusses various features which contribute significantly in the process of rate-adaptation, the timing constraints on such schemes, and the performance gains in terms of throughput, delay and energy efficiency; which can be gained by the use of rate-adaptation. The paper also discusses the implication of rate-adaptation schemes on the performance of overall communication and identifies existing research challenges in the design of rate-adaptation schemes. [ABSTRACT FROM AUTHOR]

In this paper, we consider the discrete memoryless user relaying channel (DMURC) in which a user-relay switches its operational mode symbol-by-symbol. In particular, we obtain upper and lower bounds on the channel capacity for the general DMURC and then show that these the upper and lower bounds coincide for degraded DMURC. It is also shown that the capacity of the degraded DMURC can be achieved using two separate codebooks corresponding to the two UR states. While the UR is assumed to switch states symbol-by-symbol, the results in this paper is the same as when the UR switches states packet-by-packet. [ABSTRACT FROM AUTHOR]

The concept of an "intelligent building" received significant attention from academic, industry and standard development organizations when technically termed a building management system (BMS). Wireless sensor networks (WSNs) and their recent development enhanced monitoring and control applications for the building's areas. This paper surveys and analyzes advantages of the main current and emerging approaches that may be fit for BMS. Specifically, we discuss challenges including interoperability, integration, overhead, and bandwidth limitation of WSNs in BMS. Based on analyses, we highlight the advantages of an IP-based and RESTful architecture approach as the most suitable solution for BMS using WSNs (BMS-WSN). The paper also describes our future direction and design for BMS-WSN based on these advantages. The purpose is to enable interaction of users with BMS-WSN in the same way as with any website while ensuring energy efficiency. A test-bed implementation and evaluation of a BMS application is also introduced in this paper to demonstrate the feasibility and benefits of IP-based and RESTful architecture for BMS. [ABSTRACT FROM AUTHOR]