Communications and Networking

Harvesting energy from the environment is a method to improve the energy utilization efficiency. However, most renewable energy has a poor stability due to the weather and the climate. The reliability of the communication systems will be influenced to a large extent. In this paper, an energy-efficient downlink resource allocation problem is investigated in the energy harvesting communication systems by exploiting wireless power transfer technology. The resource allocation problem is formulated as a mixed-integer nonlinear programming problem. The objective is to maximize the energy efficiency while satisfying the energy causality and the data rate requirement of each user. In order to reduce the computational complexity, a suboptimal solution to the optimization problem is obtained by employing a quantum-behaved particle swarm optimization (QPSO) algorithm. Simulation results show that the QPSO algorithm has a higher energy efficiency than the traditional particle swarm optimization (PSO) algorithm.

Harvesting energy from the radio-frequency signal is an appealing approach to replenish energy in energy-constrained networks. In this paper, relay selection (RS) in a half-duplex decode-and-forwarding multi-relay network with an energy harvesting source is investigated. Without relying on dedicated wireless power transfer, in our system the source is powered by salvaging energy from the relaying signals. In this network, RS will affect both the current transmission quality and the source energy state in the following transmission block, which is not considered in the traditional RS schemes. Thus, a two-step distributed RS scheme is proposed to improve the system performance and is compared with the max-min signal-to-noise ratio strategy. In our proposed RS scheme, the system outage probability is derived in a closed form, and the diversity gain is shown to achieve the full diversity order. Finally, numerical results are given to evaluate the performance and verify the analysis.

In this paper, we consider a wireless communication node with hybrid energy harvesting (EH) sources which results in great difficulty in obtaining the statistical knowledge of joint EH process. In addition, the wireless channel fluctuates randomly due to fading. Our goal is, under this condition, to develop a dynamic power control policy for the transmitter such that the time average throughput of the system is maximized over an infinite horizon, taking into account the circuit energy consumption and inefficiency of the rechargeable battery. Such a dynamic power control problem is formulated as a stochastic network optimization problem. The problem is solved by utilizing Lyapunov optimization and an efficient on-line algorithm with quite low complexity is obtained. Simulation results illustrate that the proposed algorithm has the same performance as the optimal one with giving statistical knowledge of the stochastic processes.

Cellular network can use renewable energy through energy harvesting technology in green communication. In this paper, power allocation for heterogeneous cellular networks (HetNets) with energy harvesting is proposed to maximize the system energy efficiency. Considering the minimal transmit rate of the users and the battery capacity of the system, a low complexity power allocation algorithm based on fractional programming is proposed to maximize the energy efficiency of the system. Simulation results demonstrate the effectiveness of the proposed algorithm.

In this letter, a wireless cooperative network is considered, in which multiple source-destination pairs communicate with each other via an energy harvesting relay. We propose a price-based power allocation scheme to distribute the harvested energy among the multiple users. We model the interaction between the relay and the destinations as a Stackelberg game and then study the joint utility maximization of the relay and the destination. The Stackelberg equilibriums for the proposed game are characterized. Simulation results show the effectiveness of the proposed algorithm in comparison with the uniform pricing algorithm.

To meet the requirements of high system capacity and coverage of 5G network, ultra-dense network is viewed as the key technology for networking evolution. And for densely deployed small cell network, self-optimization is crucial in the aspect of reducing the cost of network management while optimizing the network performance. This paper focuses on the coverage and capacity optimization, proposing a mathematical combined optimization function to balance the conflicting key performance indicators. And under this model, we propose the tabu search algorithm for generating new antenna transmit power to optimize the performance. Simulation results show that our proposed algorithm gets significant improvement in network performance and outperforms the adaptive simulated annealing in convergence speed while optimizing.

Ultra dense Network (UDN) is considered as a promising technology for 5G. With dense access points (APs), one user can be served by several APs cooperatively. Hence, how to choose APs and group them is a big challenge. In this paper, a dynamic APs grouping scheme is proposed for the downlink of User-centric UDN (UUDN). This scheme takes terrain and network topology into consideration to divide the APs into several available candidate sets (ACSs). The APs can be chosen from the ACS as the group member for UE’s APs group (APG). Once the service requirement changes or user moves, the group should be changed accordingly. The optimal objective is maximum energy efficiency under the constraints of transmission power and user’s data rate requirements. This scheme solves the problem of AP selection and power allocation. It is modeled as a discrete mixed combinational optimization problem, and a quantum-behaved particle swarm optimization (QPSO) algorithm is adopted to solve it efficiently. In addition, simulation results have also proved the effectiveness and flexibility of the proposed scheme.

Ultra-Dense Network (UDN) is regarded as a major development trend in the evolution of future networks, due to its ability to provide larger sum rate to the whole system and meet higher users’ Quality of Service (QoS). Different from the existing heterogeneous network, UDN has a smaller cell radius and a new network structure. The core concept of UDN is to deploy the low power Base Stations (BSs), i.e. Virtual Small Cells (VSCs). First, we derive an ergodic sum rate expression. To acquire the maximum ergodic sum rate of all the users, then we adopt the selection mode based on minimum distance. Due to the consideration of the computation complexity of the above VSC selection scheme, we finally propose a novel VSC selection scheme based on pattern search. The simulation results demonstrate the correctness of the ergodic sum rate expression and show the lower computation complexity of the proposed VSC selection scheme comparing with the above reference scheme.

The ultra-dense network (UND) has been considered as an effective scheme to satisfy the growing demands on data rate in the wireless network. And it can easily improve the throughput by increasing the number of base stations. In this paper, the performance of UDN with various small cell densities is evaluated. And the throughput, spectrum efficiency and energy efficiency are taken into consideration to evaluate the performance of the deployment strategies. As can be seen from the simulation results, the throughput and area spectrum efficiency are obviously improved with the increasingly dense cells. However, as the network densification the positive influence on throughput and spectrum efficiency would be decreased.

Considering both system energy efficiency (EE) and the implementation of distributed power control algorithm in multi-user cognitive radio networks (CRNs), a multi-leader Stackelberg power control game algorithm is proposed to achieve continuous Pareto improvements in non-cooperative power control game (NPG) in this paper. By combining the advantages of cooperative and non-cooperative games with consideration of secondary users’ quality of service (QoS) requirements, the problems of low system EE of non-cooperative game and limited Pareto improvement of single leader Stackelberg game are solved. Simple utility function and time back-off are utilized to facilitate the implementation of distributed algorithm. Simulations show that the proposed algorithm improves the system EE as Pareto improvement is reached. Meanwhile, primary user’s QoS is guaranteed as secondary users transmit with lower power.

We develop the joint optimal channel selection and power control scheme for video streaming with D2D communications in cognitive radio networks. In particular, we build the virtual queue model to evaluate the delays experienced by various streaming, which reflects the video distortion. To minimize the video distortion, we formulate an optimization problem, which is proved to be a quasi-convex optimization problem. Using the hypo-graph form, we convert the original problem into an equivalent convex optimization problem, solving which we can derive the joint channel selection and power control scheme in D2D communications based cognitive radio networks. The extensive simulation results obtained validate our developed joint channel selection and power control scheme. We also show that our developed scheme can significantly increase the average peak signal-to-noise ratio (PSNR) as compared with the existing research works.

The real-time camera-equipped mobile devices have been widely researched recently. And cloud computing has been used to support those applications. However, the high communication latency and unstable connections between cloud and users influence the Quality of Service (QoS). To address the problem, we integrate fog computing and Software Defined Network (SDN) to the current architecture. Fog computing pushes the computation and storage resources to the network edge, which can efficiently reduce the latency and enable mobility support. While SDN offers flexible centralized control and global knowledge to the network. For applying the software defined cloud-fog network (SDC-FN) architecture in the real-time mobile face recognition scenario effectively, we propose leveraging the SDN centralized control and fireworks algorithm (FWA) to solve the load balancing problem in the SDC-FN. The simulation results demonstrate that the SDN-based FWA could decrease the latency remarkably and improve the QoS in the SDC-FN architecture.

Current traditional IP networks start to be complex as the demands of the users is ever-growing. Software Defined Network (SDN) is a new paradigm to ease the management of the network and make the network programmable by decoupling the control plane and forwarding plane (such as switch and router). A centralized controller is used to manage the control plane, and it interacts with forwarding plane using a standardized OpenFlow protocol. However, many controllers are used recently such as POX, Ryu, ONOS, and OpenDaylight. The important question is which is the best controller to use in our network and fits our network’s goals? To answer this question, a decision making method is proposed in this paper. First, four SDN controllers are selected, and five criteria are analyzed to collect these controllers’ properties. Then a Multi-Criteria Decision Making method named TOPSIS is used to rank the controllers and choose the best one. By applying this method, a comparative study is done to evaluate the four controllers in an environment of LAN topology, and “Ryu” controller is selected as the best one based on our criteria.

In today’s networks, two new concepts have emerged aiming at cost reduction and control network congestion, namely Network Functions Virtualization (NFV) and Software Defined Networking (SDN). NFV proposes to run the network functions as software instances on datacenters (DC), while SDN presents a new network architecture where the control plane is shifted to a centralized controller. Wireless Software Defined Networking (WSDN) is considered based on the wireless environments, such as propagation delay and external interference. It is critical to keep the network stable at the ideal stable state during congestion control. However, stability control is insufficient to achieve these aims in the presence of propagation delay and external interference.In this paper, we propose robust congestion control to tackle these problems. Firstly, the traditional WNCS model is introduced to present a basic control model with delay. Then, a robust congestion control model in NFVs and WSDNs is presented, which is extended the traditional WNCS model by utilizing Lyapunov-Krasovskii functionals. Next, Lyapunov-Krasovskii functionals and linear matrix inequalities (LMIs) are adopted to analyze system stabilization with external disturbance. The sufficient conditions are formulated by Linear Matrix Inequalities (LMIs). Finally, a numerical simulation is conducted to indicate the effectiveness of the proposed scheme.

Most existing research on controller placement in Software-Defined Networking (SDN) investigated controller placements without jointly taking into account both the communication reliability and the communication latency between controllers and switches if any link in the network fails. In this paper, we first introduce a new latency metric that considers the communication delay between the switches and the controllers with and without the single-link-failure. We then formulate a novel SDN controller placement problem with the aim to minimize the communication delay, for which we propose an efficient algorithm. We also show that there is a non-trivial trade-off between a primary path and its backup path in terms of communication delay. We finally conduct experiments through simulations. Experimental results demonstrate that the proposed algorithm is very promising.

Multiantenna based spectrum sensing algorithms are widely used in cognitive radio networks on account of improving the system reliability. Utilizing the difference between the received signal and the noise statistical covariances, two kinds of novel spectrum sensing algorithms, binomial distribution based detection (BD) and wilcoxon signed rank test based detection (WSD), are proposed based on the sample covariance matrix calculated from a limited number of received signal samples. BD and WSD algorithms do not need any priori information of the primary signal and the noise. In addition, their thresholds are found via the statistical theory. Compared with energy detection (ED), maximum-minimum eigenvalue (MME) and covariance absolute value (CAV), those two algorithms can obtain better performance. Finally, the performance of the proposal is verified by simulations.

Goodness of Fit tests have been used to find available spectrum with excellent detection performance in Cognitive Radio System. To extend those works, in this paper, we reformulate the spectrum sensing as a unilateral Goodness of Fit testing problem. With difference to previous available works, a random variable that obeys central F distribution with presence of primary user (PU) signal and a non-F distribution with absence of PU signal, which provides technical support for achieving blind spectrum sensing; furthermore, inspired by the thought of unilateral hypothesis test, we apply Right Anderson Darling (RAD) test to achieve bind spectrum sensing and derive a blind spectrum sensing called RAD sensing. Finally, the validness of proposed algorithm is proved by enormous Monte Carlo simulations.

This paper investigates the problem of two dimensional (2-D) directions-of-arrival (DOA) estimation of multiple signals in co-prime planar arrays. The array consists of two uniform planar arrays with their respective inter-element spacing being both larger than half wavelength, which can enhance the resolution but at the cost of phase ambiguity. The phase ambiguity problem can be addressed by combining the results of two subarrays. Specifically, we apply the multiple signal classification (MUSIC) algorithm to each subarray to acquire their respective spectrum; then we obtain the joint spatial spectrum, which is defined as the product of the respective spatial spectrums; Finally, according to co-prime property, we search over the angular field for the spectral peaks to estimate the DOA uniquely. Finally, we verify the effectiveness of the proposed method via simulations.

Signal detection algorithm based on the linear minimum mean square error (LMMSE) criteria can achieve quasi-optimal performance in uplink of massive MIMO systems where the base stations are equipped with hundreds of antennas. However, it introduces complicated matrix inversion operations, thus making it prohibitively difficult to implement rapidly and effectively. In this paper, we first propose a low complexity signal detection approach by exploiting the weighting symmetric successive over-relaxation (WSSOR) iterative method to circumvent the computations in the matrix inversion. We then present a proper initial solution, relaxation parameter, and scope of the weighting factor to accelerate the convergence speed. Simulation results prove that the proposed simplified method can reach its performance quite close to that of the LMMSE algorithm with no more than three iterations.

In cognitive radio networks (CRNs), in the case that primary users (PUs) reclaim their channels, the secondary users occupying the spectrum of PUs may have to stop their transmission, waiting at current channel or perform spectrum handoff, i.e., switch to other channels. For handoff SUs, designing target spectrum selection schemes is of particular importance for it may affect the transmission performance and user quality of service (QoS) significantly. In this paper, we study spectrum handoff scheme design for a CRN deployed multiple channels. Jointly taking into account the characteristics of handoff candidate channels and user QoS requirements, we propose a channel characteristics and user QoS aware handoff target spectrum selection scheme for handoff SUs. Simulation results demonstrate the effectiveness of the proposed scheme.

In Heterogeneous networks (HetNets), the power difference between macro base stations (MBSs) and small base stations (SBSs) causes severe load unbalance. Therefore, cell range expansion (CRE) is proposed as an effective method to extend the coverage of SBSs and achieve balanced utilization of BSs. However, the downlink (DL) quality for offloaded user equipment (UE) cannot be guaranteed. In this paper, a traffic-aware user association scheme is proposed in HetNets. Distinct association biases are applied to different UEs according to their requirements. System performance of the proposed scheme is analyzed using the tool of stochastic geometry. The results show that the proposed scheme can improve DL throughput by enhancing the rate coverage of UEs, meanwhile signal-to-interference-plus-noise ratio (SINR) requirement with low data rate demand UEs is ensured. Moreover, the optimal association bias, which maximizes DL throughput, can be derived through particle swarm optimization (PSO), and it changes with different densities of BSs and UEs.

In recent years, radio access technologies have experienced rapid development and gradually achieved effective coordination and integration, resulting in heterogeneous networks (HetNets). User equipments (UEs) located in the overlapping area of various networks of HetNets are capable of selecting the base station (BS) of one network for association and conduct information interaction. In this paper, we study user association and power allocation problem for HetNets with eavesdroppers. To achieve secrecy data transmission in a secret and energy-efficient manner, the concept of joint secrecy energy efficiency of the network is introduced and is defined as the ratio of secrecy transmission rate and the power consumption of the BSs. An optimization problem is formulated which maximizes the joint secrecy energy efficiency under the constraints of maximum power of the BSs and the minimum data rate requirement of the UEs, and the optimal user association and transmit power strategy is obtained through applying iterative algorithm and Lagrange dual method. Numerical results demonstrate the efficiency of the proposed algorithm.

In this paper, we present a network energy-efficient resource-allocation scheme for dense small cell heterogeneous networks by jointly controlling femtocell base stations active/idle strategies and load balancing with SINR constraints among users. The optimization problem is NP-hard, thus obtaining the optimal solution is extremely computationally complex. Therefore, we formulate the optimization problem to two sub-optimization problems: the load balancing design and the femtocell base stations active/idle switch strategies control. In load balancing design scheme, we optimize the load balancing of the small cell heterogeneous networks under the fixed femtocell base stations active/idle strategies. In femtocell base stations active/idle switch strategies scheme, we optimize the network energy efficiency while achieving the minimum service requirement among users. Combined with the optimal load balancing design, we solve the femtocell base stations active/idle switch strategies scheme by observation that the network energy efficiency is an increasing function of both user number and femtocell number. Simulation results show that the proposed algorithm could achieve a considerable performance improvement in terms of network energy efficiency compared with the traditional algorithms.

With the development of aerial platforms, it becomes possible for aerial platform-based base stations to coordinate with terrestrial cellular networks and provide services for terrestrial users immediately and effectually. Hence, in the paper, a heterogeneous air-ground cellular network is proposed which can provide high data rate for local users while enhancing energy efficiency of the heterogeneous network. Different from regular topology of terrestrial cellular networks, performance of heterogeneous air-ground networks are analyzed with a random topology of aerial and terrestrial base stations using Poisson point process with different densities respectively. And the relationship between energy efficiency of heterogeneous networks and densities of aerial and terrestrial base stations is given in an explicit form. Simulations are carried out and show that energy efficiency of the heterogeneous network can be significantly improved with appropriate densities of terrestrial and aerial base stations.

Small cells are widely being deployed to enhance the performance of cellular networks, which results in a random distribution of base stations as well as a complex interference problem. Therefore, it becomes considerably challenging to derive a closed-form expression for the capacity of small cell enhanced heterogeneous cellular network especially when the cognitive radio (CR) technology is utilized to mitigate the possible interference. In this paper, we first use the discrete time Markov chain (DTMC) to achieve the spectrum mobility of macro base station (MBS) users, i.e. primary users (PUs) in the cognitive heterogeneous cellular networks (CHCNs). Meanwhile, by modeling MBSs and small base stations (SBSs) as two independent homogeneous Poisson point processes (HPPPs), we propose an integral way based on stochastic geometry (SG) to get the calculation of the interference. Simulation results show that our capacity analysis method of CHCNs serves well in approximating the network capacity by conquering the complex interference and the uncertainty of spectrum mobility, which turns out to be an efficient and promising approach.

Heterogeneous networks (HetNets) composed of macrocells and small cells are expected to improve the transmission performance of users significantly. In this paper, a joint bandwidth and power allocation scheme is proposed for femto base stations (FBSs) in HetNets. By taking into account bandwidth requirements of femto user equipments and bandwidth resource characteristics of the network, a bankruptcy game based bandwidth resource scheme is proposed for the FBSs, based on which a multi-objective optimization based power allocation scheme is proposed in which the energy efficiency optimization problem of each FBS is formulated respectively and is solved via ideal point method and genetic algorithm. Simulation results demonstrate the efficiency of the proposed scheme.

The IEEE 802.11ah Task Group is going to specify a global WLAN standard. However, .ah drafts still employs the carrier sense multiple access with collision avoidance (CSMA/CA) medium access protocol, which is an energy-consuming protocol and not suitable for networks where STAs are generally battery supplied. Besides, since .ah could support up to 6000 stations at most to be scheduled within one BSS, the introduced overhead and corresponding processing delay are non-trivial. In this paper, a power saving scheduling scheme is proposed which could greatly reduce the introduced overhead while successfully scheduling the uplink/downlink traffic of meters. Our model could also save the station’s battery with best efforts thus making our protocol specifically suitable for Smart-Grid networks where battery changing for stations is difficult. Numerical results show that our scheme outperforms the PSM (Power Saving Mechanism) and PSMP (Power Save Multi-Poll) protocols in terms of overheads, throughput and energy consumptions.

Preamble is widely used for initial synchronization, channel estimation, user identification, and collision detection in communication systems. For machine-type communication (MTC), there are massive machines within one cell. Contention-based random access could be a candidate protocol in this scenario. However, simultaneous transmission of multiple users can lead to signal aliasing. This paper designs a novel structure of preamble. Collisions of multiple users can be detected based on well-designed structure of the preamble. Furthermore, channel state information (CSI) can be estimated as a byproduct in the process of collision detection. We claim that the proposed preambles applies in flat-fading channel, multipath channel and asynchronous scenario. The simulation results validate the accuracy and robustness of the proposed scheme.

In a vehicular network, the vehicles generally need to handoff among RSUs (Road Side Units) frequently on highways due to their rapid mobility and the limit of RSU’s radio coverage. This issue may cause a series of problems such as data transmission interruption or increasing of the transmission delay. In this paper, we took advantages of the emerging idea of SDN to improve the performance of the vehicular networks. Specifically, we proposed a SDN-based framework for the vehicular networks. In this framework, we developed three function modules over the SDN application layer. And then by installing appropriate rules on OpenFlow enabled RSUs, the controller can execute a wise scheduling of RSUs’ downlink streams. In addition, based on this framework, we proposed a data dissemination strategy when a vehicle handoff among the RSUs to reduce the latency especially for bulk traffic. Simulation results demonstrate that our solution can significantly reduce the latency and the retransmission rate. In the paper, we adopted classical DCF mechanism in the IEEE 802.11p standard to implement our protocol, which makes our solution practical and compatible with previous drafts.

Boolean functions can be used in Cryptography (especially, the global avalanche characteristics of one Boolean function is an important property in symmetric Cipher). In this paper, when an n-variable balanced Boolean function satisfies the minimum the sum-of-squares indicator, we give some new properties of $$(n-1)$$-variable decomposition Boolean functions. Meanwhile, we derive a new condition on the sum-of-squares indicator, if the sum-of-squares indicator of a balanced Boolean function with n-variable is greater than $$2^{2n}+2^{n+3}$$ for $$n\ge 3$$.

This paper analyses the smart grid’s facing challenges and the features of new energy source, then proposes the distributed frameworks for Cognitive Radio based Smart Grid (CRSG) on Home Area Network (HAN), on Neighbour Area Network (NAN), and on distributed power generators respectively. The basic protocols such as the communication protocols of cognitive radio networks, power transmission protocols among different users, and power transmission protocols between users and distributed power plants are presented. Those protocols are evaluated in the proposed distributed CRSG with network simulation platform, and the results show that distributed framework is economic and effective.

Different from traditional intelligent transportation systems, vehicular platoon systems pay more attention to interactive communications of vehicle-to-vehicle (V2V) and vehicle-to-road (V2R). Both V2V and V2R communications in platoon have higher demands of real-time and active safety applications, where low-latency transmission and strong perception capability are the fundamental guarantee of platoon cooperation. This paper proposed a cooperative vehicular platoon system based on Zynq-7000 all programmable SoC architecture, in which six miniature vehicles are designed through Zynq modules for evaluating the platooning performance. We use the Vivado development kit to create the system architecture, and evaluate cooperative communication and coordinated control technology of the platoon. The test results show that the Zynq architecture can improve the real-time processing and information interaction performance of cooperative platoon systems.

This paper presents a 24-bit fixed-point multi-mode Coordinate Rotation Digital Computer (CORDIC) engine for VLSI implementation of Independent Component Analysis (ICA). Three different modes are integrated for computing sine/cosine, arc tangent and square root to save system resource. We describe the design method for deciding iteration time and fixed-point bits, and present the architecture of a pipelined VLSI implementation. An approximation method is proposed to decrease the data to be pre-stored. The CORDIC engine is designed and implemented with SMIC 65 nm CMOS technology. The performance and computation results of this engine are shown to be very high-accurate and area-efficient.

However applying encryption in physical layer reveals high levels of security, it can increase the system complexity and it can affect the communication reliability. This paper shows how to overcome these problems, where it doesn’t only show the design of combined Low Density Parity Check (LDPC) code and Customized Stream Advanced Encryption Standard (CSAES) to increase the security level, but it also introduces a practical implementation for it. The proposed algorithm is designed in order to optimally exploit the hardware resources, and FPGA parallelism to achieve high throughput and to save hardware size. The design method shows how channel coding can be exploited to increase the security and resist attacks without affecting the communication reliability. The proposed algorithm is implemented on (Cyclone-IV4CE115) to achieve variable throughputs. It achieves 604 Mbps and 10−6 BER at SNR = 3.25 dB, while it can achieve 2 Gbps for SNR greater than 6 dB. NIST tests are applied to check the ciphered output randomness, and also the resistance of the algorithm against some attacks is discussed.

Modularization and integration are becoming the mainstream trend in the development of data center. However, the integrated monitoring of power and environment has been a challenge in data centers. An All-in-One monitoring system design and implementation has been developed based on Internet of Things (IoT) architecture in this paper. The hardware is composed of two levels: one integrated monitoring gateway and several monitoring modules through the CAN-BUS network. The two-level structure design enables us to achieve module splicing and flexible deployment easily as well as rapid troubleshooting. A series of software applications are developed to establish the sensor network and collect sensor data. In addition, a web interface is provided for users to master the state of data center conveniently. Laboratory tests verify that the proposed system is able to offer automatic and intelligent support for data center management, thus significantly reducing the cost of labor and operation.

In this paper, based on ambient light sensor and camera sensor, two different receiving methods of visible light signal are experimentally studied. For ambient light sensor, its response time and light intensity are analyzed. The results show that it is available to transmit data with 0.2 kbps data rate over 2 m. For camera sensor, the relationship and difference between original data and corresponding image are studied for the first time. Besides, a series of methods are used to process the original data instead of the image, including data adjustment, histogram equalization and polynomial fitting. Using camera sensor, 2 kbps data rate over 0.3 m transmission with real-time processing of data in mobile phone is achieved even if the stripes are not clear enough, which is faster and more robust. The research is beneficial for practical application of visible light communication (VLC).

Flying Ad hoc Network (FANET) is a special type of Mobile Ad hoc Network (MANET) consisting of a swarm of Unmanned Aerial Vehicles (UAVs), and simulation is the dominant method for its research. Mobility models that generate the trajectories of UAVs in a flying session are the foundation for constructing a realistic simulation environment. However, existing mobility models targeting general MANETs are not adaptable to FANET, as the mobility patterns of UAVs are fundamentally different from general mobile nodes on the ground. In this paper, we propose a group mobility model called STGM (SpatioTemporally correlated Group Mobility model) for UAVs in a FANET. The distinct feature of STGM is that both the temporal property on the trajectory of a UAV itself and the spatial correlation across multiple UAVs that fly as a coordinated group are taken into account. In addition, the collision-free distribution of UAVs are maintained in STGM. Built on top of mathematical principles, STGM provides a parameterized framework. By adjusting its parameters, it is able to provide UAV trajectories covering different application scenarios. We validate the effectiveness of STGM with a set of important metrics, and the results show that STGM is a suitable and configurable mobility model, which will facilitate FANET research at upper layers.

In the Long Term Evolution-Advanced (LTE-A) systems, coordinated Multi-Point (CoMP) transmission/reception technology is widely used to improve cell-edge throughput and system throughput. With the introduction of CoMP technology, handover scenes have changed and traditional handover algorithms are no longer able to meet the requirements of current handover scenes. Different from traditional CoMP handover trigger mechanism, we adopt the event based handover trigger mechanism to update the CoMP coordinating set (CCS) and transmission points (CTP). Furthermore, under the constraints of the reference signal received power (RSRP) and the load of the base stations (BSs), we propose the cycle selection algorithm to choose CCS and CTP based on the radial velocity and SINR. Simulation results show that the proposed handover algorithm can effectively reduce the total number of handover, system delay and signaling overhead in the practical CoMP system.

In order to cope with the traffic exploding, operators are looking for offloading solutions which can efficiently offload high-volume Internet traffic from not only mobile access but also mobile core network. WLAN requires no expensive network planning and leverages unlicensed spectrum to add capacity. To expand the reach of revenue-generating services and applications, operators can make use of already-existing WLAN networks. The paper presents a new product concept of Wireless Access Broker (WAB) as well as the innovation solution on how to provide network-based IP flow mobility support and Internet traffic breakout. In contrast with current solutions, this new solution enables the legacy UE to support selective IP flow offloading to the WLAN network. Unlike the IFOM solution defined in 3GPP, our solution does not require the UE to install DSMIPv6 stack and related interacting module. Serving as a breakout point, WAB enables the Internet traffic directly bypass through the fixed access network while bringing no effect on other network elements.

Current space-ground IP networks cannot achieve real-time signaling interaction between aircraft users and GEO freely in large service ranges, so there is packet drop rate when aircraft users hand off between different GEO satellites. This paper proposes a new scheme to provide seamless handover service for aircraft users. Since the control center can obtain the orbit and position of aircraft can be obtained timely and accurately, during the handover process, it initiates the control signaling in different aspects to fulfill a complete handover process based on standard mobile IP protocol. Compared with other schemes, the proposed scheme can reduce packet drop rate in the handover process. Moreover, the time delay for data transmission is reduced based on mobile IPv6 technique.

Single Frequency Network (SFN) is considered as a vital deployment method in High Speed Train (HST) scenario. HST channel model is of much importance to LTE performance assessment. And SFN channel models are non-stationary. Since the train moves fast, the impact of Doppler rises significantly. The consideration of the effect of Doppler shift in SFN scenario is of much difference from in traditional stationary channels. In this paper, we build a link level simulation system and evaluate the performance of TD-LTE system with single-tap and two-tap SFN High Speed Train (HST) channel models without frequency compensation. The results show that when the Doppler shift exceeds 1000 Hz, the performance degrades much more obviously. Additionally, the absolute value of Doppler shift has great influence on TD-LTE system and the impact of Doppler shift variation on the system performance is not obvious. This paper provides reference for the design of next generation railway mobile communication system and lay a foundation for the LTE high-speed adaptability research.

The past decade has witnessed the rapid development of cloud computing. Virtualization, which is the fundamental technique in providing Infrastructure as a Service (IaaS), has led to an explosive growth of the cloud computing industry. Fault-tolerance is a significant requirement of cloud computing due to the Service Level Agreements (SLA). In order to achieve high reliability and resilience of real-time systems in virtualized clouds, a Virtualization-based Fault-Tolerant Scheduling (VFTS) algorithm is proposed. In this paper, fault tolerance is implemented by using primary-backup approach. VFTS is designed for periodic and preemptive tasks in homogeneous environment. Simulation results demonstrate an impressing saving of processing resources compared with those needed by the dual-system hot backup approach, which proves the feasibility and effectiveness of the proposed VFTS algorithm.

Due to the spread of mobile Internet and development of many new multimedia applications, there are much different quality-of-service (QoS) requirements of users in fifth generation (5G) communication system. In this paper, we consider two types of users with different QoS requirements in OFDMA based cloud radio access network (C-RAN). One type QoS requirements of users are joint bit error rate (BER) and data rate (type I users), and the other type is the data rate (type II users). We formulate the resource allocation problem in OFDMA-based C-RAN, the problem is maximal weighted sum rate for type II users subject to the QoS requirements of type I users and the fronthaul capacity constraint. Since the formulated problem is a non-convex problem, two subproblems are reformulated firstly, and then based on the CPLEX package, time-sharing and alternating methods, we proposed an iterative algorithm. Simulation results confirm that the proposed algorithm can achieve good performance.

Cloud computing technology achieves enormous scale by routing service requests from users to geographically distributed servers, typically located at different data centers. On one hand, energy consumption of data centers and networks has been receiving increasing attention in recent years. On the other hand, users require low latency during data access from data centers. In this paper, we tackle the problem of energy-efficient data placement in data centers, taking into account access latency, energy consumption of data centers and network transport. We propose two request-routing algorithms to determine the number of copies for each data chunk and the data centers accommodating the data chunk. Our simulation results have shown that the proposed algorithms are effective in terms of the tradeoff among the data access latency, the energy consumed by network transport and data centers.

Space Information Flow (SIF), also known as Space Network Coding, is a new research paradigm which studies network coding in Euclidean space, and it is different with Network Information Flow proposed by Ahlswede etal. This paper focuses on the problem of Constrained Space Information Flow (CSIF), which aims to find a min-cost multicast network in 2-D Euclidean space under the constraint on the number of relay nodes to be used. We propose a new polynomial-time heuristic algorithm that combines Delaunay triangulation and linear programming techniques to solve the problem. Delaunay triangulation is used to generate several candidate relay nodes, after which linear programming is applied to choose the optimal relay nodes and to compute their connection links with the terminal nodes. The simulation results shows the effectiveness of the proposed algorithm.

There are two types of roadside devices for advertisement dissemination in the Vehicular Cyber-Physical Systems (VCPS), one is roadside units (RSUs) and the other is roadside access points (RAPs). The placement cost of RSUs is lower than RAPs. However, the coverage of RSUs is limited. In this paper, we investigate the hybrid roadside device placement problem in the Vehicular Cyber-Physical Systems (VCPS). Given the budget constraint and the distribution of traffic conditions, our goal is to optimize the deployment of the hybrid roadside device for the merchants to maximize their benefits from advertisement dissemination. With the purpose of all advertisement can be effectively served, we propose a corresponding hybrid greedy placement algorithm. Our algorithm not only obtains the more benefits, but also consider the placement cost. Finally, we evaluate the performance of our proposed algorithm. Extensive simulations show that the performance of our proposed algorithm is superior to the other algorithms.

Due to the high dynamic in Satellite Navigation, the vital restriction for P-code Acquisition should be the Doppler frequency offset and large uncertainty of P code. To speed up the P-code acquisition, this paper proposed a novel acquisition method, based on the Local Frequency Folding method (LFF), by folding local frequency cells and generating code with little burden increase. Meanwhile, the coherent integration results storing structure of the method was modified to fit the parallel non-coherent integration, which accelerated the detection process of P-code acquisition. Preliminary result shows that the mean acquisition reduces significantly, with only −2 dB degradation in detection performance. Furthermore, it can be eliminated when the SNR exceed −10 dB.

Localization in wireless sensors networks (WSNs) has been increasingly significant recently due to the demand of the location-aware services. The low cost and high accuracy requirements make many positioning systems adopt high-accuracy quasi-synchronization method. However it remains synchronization errors which lower positioning and tracking precision within such systems. Hence, we propose a tracking system with low-accuracy quasi-synchronization method based on dual-tone radio interferometric signals. A mobile target emits dual-tone signals whose phases contain range information. Several anchors with known positions receive the dual-tone signals and extract their phase information. We cancel the synchronization error by differentiating two phases estimated from two consecutive time instants to increase accuracy. The tracking accuracy is evaluated by simulations. The tracking system enjoys low complexity, low cost and obtains a reasonable accuracy.

In mobile ad hoc networks, nonparametric belief propagation (NBP) algorithm is a promising cooperative localization scheme because of high accuracy, applicability to non-Gaussian uncertainty. However, the high computational cost limits the application of NBP. To solve the problem, an efficient and practical NBP-based cooperative localization scheme is proposed. In the scheme, the issues of anchor node selection, node mobility and non-Gaussian uncertainty are considered. Firstly, anchor nodes are selected based on a distributively clustered network. Then the cooperative localization process is performed, in which a practical ranging error model is employed. Moreover, to mitigate the influence of node mobility, the re-selection process of anchor nodes is conducted when necessary. The simulation results demonstrate the efficiency of the proposed scheme in improving the positioning accuracy and reducing the computational cost compared with the conventional NBP method.

Most super-resolution direction finding methods need to know the array manifold exactly, but there is usually mutual coupling error in application, which directly leads to the performance degradation, and even failure. The paper proposed a novel calibration method in super-resolution direction finding for wideband signals based on spatial domain sparse optimization when mutual coupling exists in the array. First, the optimization functions are founded by the signals of every frequency bin, then the functions are optimized iteratively, after that the information of all frequencies is integrated for the calibration, finally, the actual directions of arrival (DOA) can be acquired, the performance of the method has been proved by simulations.

In recent years, mobile devices (e.g., smartphones, tablets and etc.) equipped with various inertial sensors have been increasingly popular in daily life, and a large number of mobile applications have been developed based on such built-in inertial sensors. In particular, many of these applications, such as healthcare, navigation, and etc., rely on the knowledge of whether a user is walking or not, so that walking detection thus has attained much attention. This paper deals with walking detection by using the gyroscope of any commercial off-the-shelf (COTS) smartphone, which can be placed at different positions of the user. Inspired by the fact that the walking activity often results in notable features in the frequency domain, we propose a novel algorithm based on fast Fourier transformation (FFT) to identify the walking activity of a user who may perform various activities and may hold the smartphone in different manners. A thorough experiment involving three testers and multiple activities is carried out and confirms that the proposed algorithm is superior to the existing well-known counterparts.

In this paper, we propose a spectrum access method based on energy harvesting with optimal power allocation. Specifically, in the first phase, the primary user broadcasts its signal. The cognitive user receives the primary signal, and splits the power into two parts, one is to decode information, another is to harvest energy. In the second phase, the cognitive user forwards the primary signal by using the power harvested in the first phase, whlich assists the primary user to achieve the target rate. The cognitive user can access the primary spectrum to transmit its own signal by using its own power as a reward. We study the optimal power allocation to maximize the cognitive achievable rate, meanwhile the target rate of the primary user is achieved. Simulation results indicate that the proposed method can improve the performances of both the primary and cognitive users.

A physical-layer network coding (PNC) scheme based on CEEFQPSK (constant envelope enhanced FQPSK) is established for satellite communications. The scheme is implemented for uplink and downlink. In the uplink, the two signals to be sent are modulated into electromagnetic wave signal by CEEFQPSK in two channels (I, Q) and broadcasted to the relay node. At the same time, the electromagnetic wave signal is superimposed on the relay node and mapped into a binary bit, and then it will be modulated and broadcasted to the two terminals. In the downlink, soft information is received according to the maximum posterior probability criterion, and the required information is de-mapped with its own information. The bit-error rate (BER) and throughput of the entire system are analyzed by simulation. Theoretical analysis and simulation results show that the BER of the physical-layer network coding scheme using this method is close to that of the traditional scheme and network coding scheme, but the throughput is higher than the other two.

In 5G and future mobile networks, multi-carrier techniques will greatly multiply data rate to meet people’s requirements of high-speed mobile services. Traditionally, Orthogonal Frequency Division Multiplexing (OFDM) got a wide application for past decade. While OFDM has many nice aspects, it also has some disadvantages making it less attractive in the fifth generation (5G). Based on this, several advanced techniques supposed in latest literature were expected to replace OFDM because of their respective technical advantages in spectrum efficiency, complexity, compatibility and some aspects. Filter Bank Multi Carrier (FBMC), Generalized Frequency Division Multiplexing (GFDM) and Filter Bank OFDM (FB-OFDM) were reviewed in this paper. Also, their characteristics were compared with each other briefly.

Various positioning techniques have been widely developed based on received signal strength indicator (RSSI) in Wireless Sensor Network (WSN) positioning systems. Multilateration-based positioning technique is simple and easy to realize, but it can not provide very high positioning accuracy caused by fluctuation of range measurement. Fingerprinting technique is a promising method benefitting from its high precision. However, the process of building radio map cost too much time and labor. In this paper, a fusion algorithm based on both multilateration and fingerprinting is proposed to reduce cost and maintain high accuracy at the same time. An adaptive radio propagation mode is presented in this algorithm as well as a multilateration approaches based on sparse fingerprint. Factor graph is adopted to fuse the results of these two positioning techniques. Simulation experiments demonstrate that the proposed positioning fusion algorithm performs much better than any of the original algorithms participated in the fusion process.

To save labor and time costs, crowdsourcing has been used to collect received signal strength (RSS) for building radio-map of Wi-Fi fingerprinting localization with common users’ mobile devices. However, usually a great number of crowdsourcing data should be collected to calculate a satisfactory localization result. Therefore, we proposed a crowdsourcing-based indoor propagation model (PM) localization system in this paper. Our system only needs to collect crowdsourcing data at a few locations called crowdsourcing points, which can be easily finished in a short time. The system first eliminates RSS outliers in crowdsourcing data and then optimizes PM parameters using the processed data. Furthermore, the processed data is also used to estimate a distance between a user and the nearest crowdsourcing point for coordinate correction. Experimental results show that our system is able to achieve a comparable performance and the mean error of PM localization method is reduced from 7.12 m to 3.78 m.