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For the application problems of traditional street light system,such as inconvenient centralized control,untimely information monitoring and low efficiency of human inspection,it proposed an improved street light monitoring design scheme based on narrow band internet of things (NB-IoT) technology.The solution was based on the main control chip STM32L431 RCT6,which was connected to the management platform of Huawei,and performed the real-time monitoring of street light remotely on the program of the application (APP).The experimental results showed that the system fulfilled the real-time monitoring and intelligent control of street light.

We study the reliability of light power and intensity of current (L-I) model of Vertical Cavity Surface Emitting Laser (VCSEL). We use the methods of nonlinear least squares, polynomial fitting and numerical calculation to estimate the model of parameters. The simulation shows that the characteristics of the temperature of VCSEL is almost the same as the model under 20℃. It proves the model is reliable.

Considering carrier number and photon number of vertical cavity surface emitting laser(VCSEL) in steady state,an improved empirical formula of working current and the output light power intensity(L-I) model was proposed,which employed the alternating direction method of multipliers algorithm,to determine the empirical model parameters based on measured data.Besides,this model took into account not only the effect of laser temperature on the laser bias current,but also the coupling relationship between the internal parameters of the laser.The simulation results showed that the value of mean square error between the estimated data and measured data was reduced by about 1.61 dB,by employing the same algorithm,using the improved model parameters into empirical L-I model than L-I model parameters only considering the laser bias current affected by temperature.At the same time,the effective interval of the working current of the improved L-I curve was greater when working at a higher temperature.

In this paper,we assume that a device-to-device (D2D) bidirectional relay network is deployed in a cellular network.Each D2D two-way relay is equipped with two transmit antennas,which are respectively carried out at the same time with base station and receiver.Under the assumption that D2D two-way relay adjust power transmission amplification,we propose a power allocation scheme of the two-way relay network.The simulation results show that the scheme proposed can obtain larger two-way relay network throughput than the random power allocation and the traditional communication methods.

Because of the large scale characteristic of space information network in terms of space and time and the increasing of its complexity,existing measuring methods of information transmission capacity have been unable to measure the existing and future space information networkeffectively.In this study,we firstly established a complex model of space information network,and measured the whole space information network capacity by means of analyzing data access capability to the network and data transmission capability within the network.At last,we verified the rationality of the proposed measuring method by using STK and Matlab simulation software for collaborative simulation.

Considering the requirements of enterprise data communication system functions,this article uses WebSphere message queue (MQ) technology to ensure effective data transmission for large amount of commercial files.Taking daily sales data transmission between foreground and background as example,we design and realize the typical retail data transmission function.

In space information network,satellites are connected through inter satellite links.High-queuing-delay,which is caused by the restriction of the spatial network node and the dynamic network topology as well as the intermittent connectivity of communication link,is often observed among spatial network node.It means that network congestion and even packet loss occurs and results in low reliability of data transmission.Aiming at realizing network congestion monitoring efficiently and accurately,this paper analyses the sparsity of links in space information network,and the link state detection is modeled as a compressed sensing problem.Based on greedy algorithm,the paper obtains the link delay and the location of congestion links.Numerical results show that the algorithm can recover the link delay with high accuracy in the case of less sample data.

In this paper,an operation management system for golf tournament is designed to calculate the beginning and finishing dates of the preparation automatically.The efficiency of management work during preparatory period,such as meetings before match and task announcement,is raised by nearly 40% after using our system than using traditional management tools or other software systems.And the probability of occurrence of delay and omission of work are controlled within 5%.It is proved to be helpful for reducing management costs and improving efficiency of tournament management company.

To optimize maximizing system rate,we propose an improved resource allocation algorithm based on the constraint conditions of rate proportional fairness,and solve the optimal power by using Lagrange method.The results show that,compared to the traditional resource allocation algorithm of minimum proportional rate,our algorithm can reduce computational complexity and improves the system rate effectively.

In this paper,considering time-frequency doubly selective channel,we utilize the channel's time correlation that the channel coefficientscorresponding tothe neighboring instants have a strong correlation.And we present a linear approximation method,which effectively reduces the number of unknown parameters.Considering the sparseness of the wireless channel in the delay domain,this paper reconstructs unknown channel parameters of the proposed model based on compressed sensing (CS) theory.In the simulations,we observe the system performance of the linear approximation model and the non-linear approximation model,respectively,and present the normalized mean squared error (NMSE) curves based on the least square (LS),orthogonal matching pursuit (OMP) and sparse Bayesian learning (SBL) algorithms.Simulation results show that the linear approximation method can effectively model the time-frequency doubly-selective channels.For the proposed linear approximation model,SBL algorithm can accurately recover the channel response,and overcome the Doppler effecteffectively.

To reduce the base station load,spectrum utilization in cellular network is increased by reusing the spectrum that has been used.At the same time,the users that use same spectrum are clustered via using the fuzzy c-means (FCM) algorithm to reduce interference among device-to-device (D2D) users who use the same frequency.Resource allocation is realized by using greedy algorithm to reduce interference between D2D users and cellular users.The simulation result shows that,compared with random clustering and random resource allocation,resource allocation scheme based on the FCM algorithm and greedy algorithm can improve system capacity more effectively.

With the increase of ad-hoc network size and application range,network need to provide more and more quantity and quality of services,while the qualityrequirement of networkservices also increases.Through the combination of Zigbee network and classic AODV protocol,this paper simulates and tests the delay of routing discovery and the delay of end to end based on different transmission radius,analyses the impact of transmission range on network performance,and provides some advices for improving and optimizing ZigBee network applications,with the application of NS2 simulation platform.

In massive MIMO system,pilot contamination is considered as a challenging problem,which deteriorates channel estimation at base station (BS) and therefore reduces the total throughput.In the conventional single-length pilot schemes,such contamination is severe due to the full reuse of pilot sequences in adjacent cells.Therefore,in this paper,we propose a novel multi-length pilot scheme (MLPS) so that each user equaipment (UE) in the target cell can approach respective optimal pilot length and the total throughput can be increased.First,we illustrate the fact that the optimal pilot lengths of UEs in the same cell are distributed among several values.Then,to eliminate the interferences caused by nonorthogonality of different-length pilots and simultaneous transmission of pilots and data,a feasible pilot design criterion is presented and two time-division strategies are developed.Finally,we evaluate our schemes by extensive simulations,MLPS obtains a gain of up to 18% for uplink throughput and up to 20% for downlink throughput.

With the rapid development of retail trade,the type and complexity of data keep increasing,and single data file size has a great difference between each other.How to realize an accurate,real-time and efficient data transmission based on a fixed cost is an important problem.Regarding the problem of effective transmission for business data files,this article implements analysis and comparison on 3 existing data transmission methods,considering the requirements on aspects like function in enterprise data communication system,we get a conclusion that which method can both meet the enterprise daily business development requirement better and have good extension ability.

In this paper,we discuss the interference between channels in the adjacent small-cells in the LTE-A small-cell networks.We present a small-cell group close (SCGC:Small Cell Group Close) approach according to above discussion.System-level simulation results show that SCGC can not only reduce small-cell interference with adjacent channels,but also reduce power consumption.We can conclude that SCGC can get greater throughput.

MIMO,the core technology of next generation wireless broadband communication,is faced with the contradiction between the system gain benefit by increasing antennas and the detection error due to high channel correlation.Therefore,we propose a new Lattice-Reduction(LR)-assisted K-Best algorithm.Since the children nodes of every parent node are uncertain after LR processing,on-demand expansion scheme is adopted to expand children nodes,and the sorting algorithm based on minimum candidate heap is used to decrease the sorting complexity.Then the average time complexity is decreased from O(KNlog2(KN)) to O(Klog2K),and the spatial complexity is decreased from O(KN) to O(K).In order to solve the problem of detection error caused by no longer limited constellation map after LR processing,a boundary control scheme is put forward to improve the detection accuracy.Simulations show that with the aid of boundary control,the BER performance has obtained 3dB gain when channel correlation is high.And the proposed algorithm only lost 1dB gain compared to ML algorithm with much smaller computational complexity,the complexity is only linearly increased with the number of antennas.So this proposed efficient algorithm is suitable for large scale antenna system.

Poor TSV assignment algorithm leads to a large detour of wire-length.Some of the previous works deal with TSV assignment problem using layer-by-layer methods(LBL) only gets local optimal results.In this research work,a backward layer-by-layer reassignment(BRLBL) is developed to do further optimization.This reassignment algorithm takes global information into consideration and optimizes the outcome of layer-by-layer TSV assignment methods.Also a fast layer-by-layer reassignment(FLBL) method is proposed to shorten the runtime.Experimental results show that BRLBL achieves an average reduction over 3.7% of wire-length,while the FLBL improves the execution time of BRLBL by 10 times.

By reusing the the spectrum in cellular network that has been used to increase the spectrum utilization ,reduce the base station load,and at the same time by using the location-based D2D mode selection and resource allocation algorithm,to reduce same frequency interference between the users and reduce transmission power from users.The simulation results show that,compared with the traditional communication in cellular network and resource allocation with random model,the location-based D2D mode selection and resource allocation can improve the capacity of system,and reduce the interference between the users.

In mobile wireless sensor networks,node mobility influences the topology of the hierarchically clustered network,thus affects packet delivery ratio and energy consumption of communications in clusters.To reduce the influence of node mobility,a distributed re-clustering algorithm is proposed in this paper.In this algorithm,basing on the clustered network,nodes estimate their current locations with particle algorithm and predict the most possible locations of next time basing on the mobility model.Each boundary node of a cluster periodically estimates the need for re-clustering and re-cluster itself to the optimal cluster through communicating with the cluster headers when needed.The simulation results indicate that,with small re-clustering periods,the proposed algorithm can be effective to keep appropriate communication distance and outperforms existing schemes on packet delivery ratio and energy consumption.

This paper gives an interference coordination strategy in heterogeneous network scenarios.Firstly,establish a heterogeneous network framework,reduce intercell interference and interlayer interference,at the same time,let the network gain higher capacity and data rate,on the basis of the application of the dynamic interference coordination scheme.This paper briefly describes the working process of the interference coordination scheme,and analyzes the performance of this scheme through simulation.At last,the result confirms the promotion of system performance.

This paper studies the user energy scenarios absorption efficiency optimization in multiuser broadcast channel.This paper assumed that the user terminals using full-duplex mode that the user receive uplink energy information and transfer uplink energy at the same time.In this paper,we maximize the minimum user uplink transmit power,when we ensure that each user′s energy absorption efficiency is greater than a threshold value and satisfies the premise of the base station downlink power emission limits.Finally,the simulation results confirm the effectiveness of the proposed algorithm.

This paper proposed a power control algorithm for multi-hops device to device communication system under the single cellular networks.Different D2D links communicate by the shared band and users in one D2D links transmit message in two-hop Decode-and-forward mode.D2D users among different links which share the same band in asynchronous mode would get mutual interference.We use a proposal algorithm to approximate the optimistic solution with relaxation factor method,firstly get the closed expression of optimistic power,then we modify the transmission power to decrease the co-channel interference.At last,the simulation results verify the correctness of proposed power control algorithm and the improvement of system sum rate.

With the using of intelligent terminal,which makes the traditional heterogeneous network is hard to satisfy our customer′s demand of data rate,in the face of such requirements,small cell technology become the focus of future mobile communication.Under this scenario,however,interference seriously restricts the system capacity of ascension.In order to solve this problem,a few small cell closed strategies have been proposed,such as random close,based on the load algorithm,but these methods can not consider the system capacity.So this article is based on each small cell before and after the closing system capacity gain,effective to choose the appropriate small cell closed,to reduce the interference between them,so as to improve the system capacity of community.Finally,the simulation comparison of the base station in fully open and random close and based on the load status of system throughput,the results verify the effectiveness of the proposed scheme.

The localization algorithm of based on IMU is one of autonomous localization methods while it possesses the disadvantage of drift error and accumulated error,so this paper proposes a multi-sensors including wearable multi-IMUs and IWSN data and information fusion algorithm for indoor localization.On the one hand,almost all indoor localization algorithms based on IMU use only one IMU while this single-IMU-based algorithm can′t judge the posture of person precisely,one appropriate solution is that we can utilize multi-IMUs to cooperate in localization process,besides,we can fuse position information of multi-IMUs by fuzzy voting scheme.On the other hand,in order to overcome the disadvantage of drift error and accumulate error,combining with IWSN in indoor and fusing the position information calculated by IWSN and multi-IMUs via Kalman Filter algorithm.Experiment results show that the proposed indoor localization algorithm possesses good property in judging posture of person and decreasing drift error and accumulate error comparing with traditional IMU-based indoor localization algorithm.

This paper investigates the beamforming design based on perfect channel state information (CSI) in a multi-user downlink network.The base station (BS) is equipped with multiple antennas while each user is equipped with one antenna.The BS will communicate with users through transmit beamforming technology.This paper maximizes the sum rate of all users with the constraint of transmitting power.The object function is complex and non-convex which would bring difficulties to solve this problem.This article proposes a beamforming scheme based on zero-forcing criterion.Based on this method,the original problem will be divided into two sub-problems which can be solved respectively.The simulation results suggest that the proposed beamforming scheme achieves better performance compared with the traditional leakage based beamforming scheme.

D2D (Device-to-Device) communication is under the control of base station,allowing direct communication between the terminal reusing the cell resources.It is possible to increase the spectral efficiency of a cellular communication and to reduce the transmit power of the terminal.Due to a growing number of heterogeneous devices in the future mobile network,an efficient resource allocation scheme must maximize the throughput of the system and achieve higher spectral efficiency.This paper presents an efficient resource allocation scheme to ensure the cell user throughput premise that D2D users get maximum throughput.In addition,the proposed greedy algorithm could solve the problem of resource allocation efficiently.The simulation results show that our algorithm has a lower complexity and can improve system throughput effectively.

In order to control the level of interference among adjacent small-cells effectively,in this paper,we suppress the interference between adjacent small-cells through controlling the small-cell downlink transmission power.Meanwhile,we use a low complexity subcarrier allocation scheme,making small-cell downlink rate be improved as much as possible.In small cell downlink transmission power control,we use a generalized water-filling algorithm which gives the optimal solution of downlink transmission power.Simulation results show that subcarrier allocation scheme and power allocation algorithm can improve small-cell downlink transmission rate and control the level of interference between adjacent small-cell effectively.