Interpolation Fitting Algorithm in Time-Space Domain of Differential Barometric Altimetry

In order to overcome the limitations of a unitary reference station in mobile communication positioning network differential barometric altimetry(DBA)and broaden the action scope of the reference station and improve positioning accuracy of elevation,an integrated interpolation algorithm model based on generalized extended approximation(GEA)algorithm and Kriging interpolation in time-space domain of reference station is proposed.In the time domain,barometric measured data is considered the maximum value estimated by bilateral extension to avoid wrong direction of estimation,which is approaching true value.In the spatial domain,barometric relevance among multiple reference stations is utilized,the weighted coefficients of multiple reference stations is calculated by the integrated algorithm model based on the GEA algorithm and Kriging interpolation.The impact of each reference station to the measured station is quantified,so that a virtual reference station is constructed,which can overcome the limitation of barometric correction by a unitary reference station.In addition,the measurement error due to irregular change in atmospheric pressure will be eliminated.

Ultra-broadband and polarization-independent planar absorber based on multilayered graphene

We propose an ultra-broadband and polarization independent planar absorber comprising multilayered graphene. The bandwidth of the proposed absorber is extended by increasing the number of layers of graphene, and it is polarization independent due to its symmetrical unit structure. The full wave simulation results show that an absorber with three graphenebased layers can efficiently harvest an electromagnetic wave with random polarization from 17.9 GHz to 188.7 GHz（i.e.,covering frequency regimes from K to D bands and relative bandwidth of - 165%）. The physical absorption mechanism of ultra-broadband absorption has been elaborated upon using the destructive interference method and multiple resonances approach in a multilayered medium. The proposed absorber can be used in many applications such as medical treatment,electromagnetic compatibility, and stealth technique.

An ultra-wideband pattern reconflgurable antenna based on graphene coating

An ultra-wideband pattern reconfigurable antenna is proposed.The antenna is a dielectric coaxial hollow monopole with a cylindrical graphene-based impedance surface coating.It consists of a graphene sheet coated onto the inner surface of a cylindrical substrate and a set of independent polysilicon DC gating pads mounted on the outside of the cylindrical substrate.By changing the DC bias voltages to the different gating pads,the surface impedance of the graphene coating can be freely controlled.Due to the tunability of graphene＇s surface impedance,the radiation pattern of the proposed antenna can be reconfigured.A transmission line method is used to illustrate the physical mechanism of the proposed antenna.The results show that the proposed antenna can reconfigure its radiation pattern in the omnidirectional mode with the relative bandwidth of 58.5% and the directional mode over the entire azimuth plane with the relative bandwidth of 67%.

Low-complexity resource allocation in rate-constrained OFDMA downlink systems

A resource allocation algorithm with quality of service(QoS) guarantees in a cellular orthogonal frequency division multiple access(OFDMA) network is proposed.The algorithm is a modified water-filling algorithm.In the first phase,power and subcarriers are allocated together,and in the second phase,users' minimum data rate requ irements are met,while the remaining resources are allocated in order to maximi ze sum rate.It is a cell-level algorithm,and its main advantages are low implementation complexity and capacity of maintaining higher ratio of QoS satisf ying users' requirements.Simulation results show that this scheme outperform s other proportional resour ce allocation schemes.

NOMA-Based Collaborative Beam Hopping Frequency Allocation Mechanism for Future LEO Satellite Systems

Low Earth orbit(LEO) satellite systems provide terrestrial users with services that are not limited by geographical location. However, the conflict between existing allocation schemes and the business variability between beams is becoming increasingly prominent. Beam hopping technology allows for a more flexible and versatile approach to satellite resource allocation. This paper proposes a beam hopping pattern optimization scheme that jointly considers the interference threshold distance and beam service priority, reducing the inter-beam co-channel interference(CCI). In the cluster area, a non-orthogonal multiple access(NOMA)-based collaborative beam hopping(NCBH) scheme is proposed to minimize the cell-edge user(CEU) interference. Since there is a difference in channel gain between the CEU and cellcenter user(CCU), this scheme forms a NOMA cluster to perform power domain multiplexing and formulates a NOMA cluster pairing strategy according to the user location to reduce the CCI of the CEU. After NOMA cluster pairing, the optimal carrier frequency of the NOMA cluster is selected by a reinforcement learning algorithm. The simulation results verify the excellent performance of the proposed NCBH scheme regarding the user’s received power, transmission rate, and outage probability.

Critical safe distance design to improve driving safety based on vehicle-to-vehicle communications

A critical safe distance(CSD)model in V2V(vehicle-to-vehicle)communication systems was proposed to primarily enhance driving safety by disseminating warning notifications to vehicles when they approach calculated CSD.By elaborately analyzing the vehicular movement features especially when braking,our CSD definition was introduced and its configuration method was given through dividing radio range into different communication zones.Based on our definition,the needed message propagation delay was also derived which could be used to control the beacon frequency or duration.Next,the detailed CSD expressions were proposed in different mobility scenarios by fully considering the relative movement status between the front and rear vehicles.Numerical results show that our proposed model could provide reasonable CSD under different movement scenarios which eliminates the unnecessary reserved inter-vehicle distance and guarantee the safety at the same time.The compared time-headway model always shows a smaller CSD due to focusing on traffic efficiency whereas the traditional braking model generally outputs a larger CSD because it assumes that the following car drives with a constant speed and did not discuss the scenario when the leading car suddenly stops.Different from these two models,our proposed model could well balances the requirements between driving safety and traffic throughput efficiency by generating a CSD in between the values of the two models in most cases.

Graph Laplacian Matrix Learning from Smooth Time-Vertex Signal

In this paper,we focus on inferring graph Laplacian matrix from the spatiotemporal signal which is defined as“time-vertex signal”.To realize this,we first represent the signals on a joint graph which is the Cartesian product graph of the time-and vertex-graphs.By assuming the signals follow a Gaussian prior distribution on the joint graph,a meaningful representation that promotes the smoothness property of the joint graph signal is derived.Furthermore,by decoupling the joint graph,the graph learning framework is formulated as a joint optimization problem which includes signal denoising,timeand vertex-graphs learning together.Specifically,two algorithms are proposed to solve the optimization problem,where the discrete second-order difference operator with reversed sign(DSODO)in the time domain is used as the time-graph Laplacian operator to recover the signal and infer a vertex-graph in the first algorithm,and the time-graph,as well as the vertex-graph,is estimated by the other algorithm.Experiments on both synthetic and real-world datasets demonstrate that the proposed algorithms can effectively infer meaningful time-and vertex-graphs from noisy and incomplete data.

Hop distance fairness for wireless mesh network based on queue management

Wireless mesh network(WMN) is a new multi-hop network for broadband accessing to internet.However,there exists a server unfairness problem based on different hop distances in WMN.To solve this problem,the unfairness issue was analyzed in test-bed experiment and NS2 simulation.A dynamic queue management scheme E-QMMN was proposed,which allocates the queue buffer according to the hop distance of every flow.The experimental results show that the proposed scheme can not only increase the hop distance fairness of the legacy scheme at most 50%,but also reduce the average round trip time at least 29% in congested WMN environments.

Energy-Efficient Joint User Association and Power Allocation in Relay-Aided Massive MIMO Systems

Energy efficiency is an important metric for downlink transmission in an amplify-and-forward relay-aided massive multiple-input multiple-output system,but has not been well investigated.In this work,considering the characteristics of such a system and quality-of-service requirements of users,the energy-efficient joint user asso-ciation and power allocation problem is studied.First,the closed-form expression of system energy efficiency under the proportional fairness criterion is derived.Then,the proportionally fair utility of system energy efficiency is maximized under constraints of minimum signal-to-noise ratio requirements of users and maximum transmit powers of the base station(BS)and relay stations.As it is difficult to solve this optimization problem directly due to its mixed-integer and non-convex features,the original problem is decomposed into a user association sub-problem and a power allocation sub-problem.For the former,optimum user association is determined by solving a Lagrangian dual problem with a sub-gradient algorithm;for the latter,optimum transmit powers of the BS and each relay station are determined by using Newton’s method.Finally,a sub-optimal solution of the original problem is obtained by a low-complexity iterative algorithm.Simulation results show that the proposed joint user association and power allocation algorithm can offload the traffic of the BS effectively,keep the BS and relay stations operate at low power levels,and improve the system energy efficiency significantly,compared with user association-only schemes.

New construction of highly nonlinear resilient S-boxes via linear codes

Highly nonlinear resilient functions play a crucial role in nonlinear combiners which are usual hardware oriented stream ciphers.During the past three decades,the main idea of construction of highly nonlinear resilient functions are benefited from concatenating a large number of affine subfunctions.However,these resilient functions as core component of ciphers usually suffered from the guess and determine attack or algebraic attack since the n-variable nonlinear Boolean functions can be easily given rise to partial linear relations by fixing at most nil variables of them.How to design highly nonlinear resilient functions(S-boxes)without concatenating a large number of nil variables affine subfunctions appears to be an important task.In this article,a new construction of highly nonlinear resilient functions is proposed.These functions consist of two classes subfunctions.More specially,the first class(nonlinear part)contains both the bent functions with 2k variables and some affine subfUnctions with n/2-k variables which are attained by using[n/2-k,m,d]disjoint linear codes.The second class(linear part)includes some linear subfunctions with nil variables which are attained by using[n/2,m,d]disjoint linear codes.It is illustrated that these resilient functions have high nonlinearity and high algebraic degree.In particular,It is different from previous well-known resilient S-boxes,these new S-boxes cannot be directly decomposed into some affine subftinctions with nil variables by fixing at most nil variables.It means that the S-boxes(vectorial Boolean functions)which use these resilient functions as component functions have more favourable cryptography properties against the guess and determine attack or algebraic attacks.