分频多指标算法对多功能电力电缆巡检装置的节能优化

为提高在多功能约束条件下电缆巡检装置的节能效果,以节能发电成本、有害气体排放量为切入点,提出分频多指标算法。首先,收集多功能电力电缆巡检装置的运行数据,然后分析不同指标数据之间的相关性分析,以主成分指标为研究中点,计算节能变异程度,并与传统方法进行对比,以验证计算结果的有效性。结果表明,分频多指标算法能提高电力电缆巡检装置的节能成本,其总购电成本降至307 595.39￥·h^(-1),有害气体总排放量降至0.684 t·h^(-1),低于目前常用的传统算法,节能效果均有明显差异。由此证明,分频多指标算法能降低多功能电力电缆巡检装置运行成本、减少有害气体排放,具有一定实用价值。

基于谐振积分器的分频检测算法

实际工程应用只需要考虑对有限的几次谐波进行治理即可,考虑到谐波治理工程的要求和并联型有源电力滤波器容量的大小,对并联型有源电力滤波器的分频检测算法进行了研究。通过对谐振积分器基本原理的分析,利用谐振积分器所具有的选频特性,提出了一种基于谐振积分器的分频检测算法。该检测算法既可省去锁相环及三角函数计算,也无需进行αβ坐标系变换到dq坐标系及其反变换的计算。相关实验结果验证了基于谐振积分器的分频检测算法的有效性。

应用于GPS频率综合器的可编程分频器的设计

设计了应用于全球定位系统（GPS）1．2GHz频率综合器中的可编程分频器。该分频器可实现600-700范围的分频比，并利用改进的均匀分频算法使分频输出波形的占空比更加理想。设计采用SMIC 0．18μm CMOS工艺标准单元的半定制设计方法，按照标准数字集成电路设计流程进行设计，包括Verilog代码编写、逻辑综合、版图规划、布局布线、后端时序仿真分析等过程。该可编程分频器模块已采用SMIC 0．18μm CMOS工艺进行流片，核心芯片面积为115μm×115μm。测试结果表明，通过控制芯片预置逻辑，分频器能与控制端口相匹配，完成分频功能，实现了预期结果。

基于CPLD有理数分频器的设计方法

介绍了一种通用的可预置数的有理数分频器的设计方法。本设计利用VHDL语言实现分频算法的设计,利用键盘、液晶显示、单片机、CPLD实现硬件电路的设计,并用QuartusⅡ进行仿真。

基于FPGA的多显示模式VGA接口研究与设计

本文设计了一种基于现场可编程逻辑器件FPGA计的多显示模式VGA接口。通过设计一种全新的分频算法,使该接口能支持从VGA到SVGA多达13种显示模式,在实际利用FPGA的嵌入式系统中能替代VGA专用显示芯片,节省了计算机处理过程,加快了数据处理速度,节约了硬件成本。

数字示波表中超高速数据采集系统的设计

针对数字示波表的数据采集系统接口复杂、采集速度高、单片机难以实现等特点,介绍了一种以CPLD为核心的超高速数据采集系统设计方案。该方案采用高速A/D转换器、双片高速FIFO芯片来实现数字示波表中信号的不间断采样和存储,利用等精度测频技术自动生成FIFO的写入时钟,实现滤除冗余数据的功能。分别对A/D转换器、FIFO存储器、数据处理单元之间的逻辑接口电路以及测频原理、分频算法等进行了详细介绍。仿真结果表明,该设计完全满足数据采集系统的要求。

The Novel Spectrum Allocation Algorithm in Cognitive Radio System

In order to reduce the disturbance on an authorizing user and lower the competition between cognitive users, assure the normal communication of a cognitive radio system, reliability theory is applied to describe if a channel can be used by a cognitive user or not and the probability that the channel is continually used for a period. Three aspects including space, time domain and frequency domain are united for the research on the distribution of frequency spectrum. The simulation result shows that, in the space domain, time domain, frequency domain algorithm, the transmitted data volume and the total throughput of the system are superior to those in greedy algorithm and time domain—frequency domain algorithm, the novel algorithm is helpful to reduce the disturbance caused by a cognitive user to an authorizing user and lower the competition between cognitive users, this simulation result shows that the proposed algorithm is effective.

A Bregman adaptive sparse-spike deconvolution method in the frequency domain

To improve the anti-noise performance of the time-domain Bregman iterative algorithm,an adaptive frequency-domain Bregman sparse-spike deconvolution algorithm is proposed.By solving the Bregman algorithm in the frequency domain,the influence of Gaussian as well as outlier noise on the convergence of the algorithm is effectively avoided.In other words,the proposed algorithm avoids data noise effects by implementing the calculations in the frequency domain.Moreover,the computational efficiency is greatly improved compared with the conventional method.Generalized cross validation is introduced in the solving process to optimize the regularization parameter and thus the algorithm is equipped with strong self-adaptation.Different theoretical models are built and solved using the algorithms in both time and frequency domains.Finally,the proposed and the conventional methods are both used to process actual seismic data.The comparison of the results confirms the superiority of the proposed algorithm due to its noise resistance and self-adaptation capability.

Dispersion penalty analysis gor VSR-1 optical links

This paper presents an approach to calculate dispersion penalty for VSR-1 optical links.Based on parameters of a specific VSR-1 link,dispersion penalties are computed for various modal dispersion bandwidths respectively.The worst-case eye closure is expressed numerically by using the signal waveform at time 0,and the signal waveform is obtained in frequency domain through FFT algorithm.By this approach,the dispersion penalty is determined by the shape of transfer functions of the various components in the links.To simplify the derivation of multimode fiber link transfer function,a Gaussian form of normalized impulse response is used.This calculation approach can be used to estimate the worst-case dispersion penalty of VSR-1 links in the link budget analysis.

Dynamic Subcarrier Assignment for OFDM-PON Network Based on RSOA for ACCORDANCE

In this paper, we overview the principle of Orthogonal Frequency Division Multiplexing Passive Optical Network （OFDM-PON） systems, with a particular focus on upstream architectures capable of achieving 10Gbit/s colorless upstream transmission using Reflective Semiconductor Optical Amplifier （RSOA）. We propose an architecture of RSOA based OFDM-PON which can achieve 10Gbit/s upstream transmission over a single wavelength. A novel Dynamic Subcarrier Assignment （DSA） algorithm is also proposed to support my architecture, namely Service based Polling in Pipeline （SPP） dynamic subcarrier algorithm. A simulation was conducted to study the performance of SPP algorithm. Compared with the traditional dynamic bandwidth allocation algorithms, service based polling meets the quality of in pipeline algorithm service requirements excellently, and adapts orthogonal frequency division multiplexing passive optical network better with higher bandwidth efficiency and lower algorithm complexity.

Non-dominated sorting quantum particle swarm optimization and its application in cognitive radio spectrum allocation

In order to solve discrete multi-objective optimization problems, a non-dominated sorting quantum particle swarm optimization (NSQPSO) based on non-dominated sorting and quantum particle swarm optimization is proposed, and the performance of the NSQPSO is evaluated through five classical benchmark functions. The quantum particle swarm optimization (QPSO) applies the quantum computing theory to particle swarm optimization, and thus has the advantages of both quantum computing theory and particle swarm optimization, so it has a faster convergence rate and a more accurate convergence value. Therefore, QPSO is used as the evolutionary method of the proposed NSQPSO. Also NSQPSO is used to solve cognitive radio spectrum allocation problem. The methods to complete spectrum allocation in previous literature only consider one objective, i.e. network utilization or fairness, but the proposed NSQPSO method, can consider both network utilization and fairness simultaneously through obtaining Pareto front solutions. Cognitive radio systems can select one solution from the Pareto front solutions according to the weight of network reward and fairness. If one weight is unit and the other is zero, then it becomes single objective optimization, so the proposed NSQPSO method has a much wider application range. The experimental research results show that the NSQPS can obtain the same non-dominated solutions as exhaustive search but takes much less time in small dimensions; while in large dimensions, where the problem cannot be solved by exhaustive search, the NSQPSO can still solve the problem, which proves the effectiveness of NSQPSO.

Integrating Tabu Search in Particle Swarm Optimization for the Frequency Assignment Problem

In this paper, we address one of the issues in the frequency assignment problem for cellular mobile networks in which we intend to minimize the interference levels when assigning frequencies from a limited frequency spectrum. In order to satisfy the increasing demand in such cellular mobile networks, we use a hybrid approach consisting of a Particle Swarm Optimization(PSO) combined with a Tabu Search(TS) algorithm. This approach takes both advantages of PSO efficiency in global optimization and TS in avoiding the premature convergence that would lead PSO to stagnate in a local minimum. Moreover, we propose a new efficient, simple, and inexpensive model for storing and evaluating solution's assignment. The purpose of this model reduces the solution's storage volume as well as the computations required to evaluate thesesolutions in comparison with the classical model. Our simulation results on the most known benchmarking instances prove the effectiveness of our proposed algorithm in comparison with previous related works in terms of convergence rate, the number of iterations, the solution storage volume and the running time required to converge to the optimal solution.

Performance of a novel carrier frequency offset estimation algorithm for OFDM-based WLANs

This paper presents a novel carrier frequency offset estimation (CFO) algorithm for orthogonal frequency division multiplexing (OFDM)-based Wireless Local Area Networks (WLANs). Compared with previous approaches, this paper extends the whole frequency offset acquisition range by embedding a synthetic algorithm according to the preamble structure of WLANs symbols. The numerical results presented support the effectiveness of this algorithm by which the estimation error of the whole carrier frequency offset in the WLANs is effectively decreased.

An Advanced Spectrum Allocation Algorithm for The Across-Cell D2D Communication in LTE Network with Higher Throughput

In the hybrid LTE cellular network with D2D(Device-to-Device) communication, D2D communication technologies can improve the spectral efficiency significantly. However, the D2D users have to reutilize the spectrum which is allocated to the cellular users. Therefore, the co-channel interference will be more complicated in the case of crosscell D2D communications. In this article, a novel spectrum allocation algorithm for inter-cell D2D communication considering the traffic load is proposed. The traffic load can be balanced by the proposed algorithm. Meanwhile D2D users can multiplex the spectrum allocated to a number of cellular users with a certain percentage to meet the requirements of Qo S of D2D communications and reduce the interference to cellular users. Finally, the simulation results demonstrate that the proposed algorithm can meet the needs of D2D users, balance the traffic load and improve the overall throughput of the system.

User-Oriented Graph Based Frequency Allocation Algorithm for Densely Deployed Femtocell Network

Femtocell is a promising technology for improving indoor coverage and offloading the macrocell.Femtocells tend to be densely deployed in populated areas such as the dormitories.However,the inter-tier interference seriously exists in the co-channel Densely Deployed Femtocell Network(DDFN).Since the Femtocell Access Points(FAPs) are randomly deployed by their customers,the interference cannot be predicted in advance.Meanwhile,new characteristics such as the short radius of femtocell and the small number of users lead to the inefficiency of the traditional frequency reuse algorithms such as Fractional Frequency Reuse(FFR).Aiming for the downlink interference coordination in the DDFN,in this paper,we propose a User-oriented Graph based Frequency Allocation(UGFA)algorithm.Firstly,we construct the interference graph for users in the network.Secondly,we study the conventional graph based resources allocation algorithm.Then an improved two steps graph based frequency allocation mechanism is proposed.Simulation results show that UGFA has a high frequency reuse ratio mean while guarantees a better throughput.

Optimal joint relay selection and resource allocation with QoS constraints in multiuser OFDM-based cellular networks

This paper investigates the relay selection and resource allocation problem in multiuser orthogonal frequency division multiplexing （OFDM） based cooperative cellular networks, in which user nodes could relay information for each other using the decode-and-forward （DF） protocol to achieve spatial diversity gain. Specifically, the paper proposes an optimal joint relay selection and resource allocation （0RSRA） algorithm whose objective is to maximize system total achievable data rate with the constraints of each user＇ s individual quality of service （QoS） requirement and transmission power. Due to being a mixed binary integer programming （MBIP） problem, a novel two-level Lagrangian dual-primal decomposition and subgradient projection approach is proposed to not only select the appropriate cooperative relay nodes, but also allocate subcarries and power optimally. Simulation re- suits demonstrate that our proposed scheme can efficiently enhance overall system data rate and guarantee each user＇ s QoS requirement. Meanwhile, the fairness among users can be improved dramatically.

SPATIAL COMPATIBLE USER GROUPING ALGORITHM FOR MULTIUSER MIMO SYSTEMS

A spatial compatible user grouping algorithm is proposed to reduce CoChannel Interference (CCI) in Space Division Multiple Access (SDMA) multiuser Multiple Input Multiple Output (MIMO) systems. We evaluate the interferences among users by use of distances between row spaces spanned by users’ channel matrixes, then control frequency sharing according to the compatible user grouping algorithm. Results show that the row space distance algorithm outperforms others because it can fully utilize the information from users’ channel matrixes, especially the matrix structure information. The results also prove that the algorithm based on channel matrix structure analysis is a better candidate for spatial compatibility approximation.

A NOVEL SEMI-BLIND TIME-FREQUENCY DOMAIN TRACKING ALGORITHM SUITABLE FOR MPSK-OFDM

This paper presents a semi-blind tracking algorithm used for Multiple Phase Shift Keying based Orthogonal Frequency Division Multiplexing(MPSK-OFDM) system. By using special pream-bles to assist the decision of a feedback loop and to solve the problem of phase ambiguity,the tracking performance of the algorithm has been improved greatly. Only a few preambles are needed in the al-gorithm since the preambles are not used to estimate the frequency offset but used to provide the variation information of the phase due to the presence of frequency offset. Simulations verify that the algorithm has low SNR bound for tracking as well as high tracking accuracy and the tracking range is expanded to 30% of one subcarrier spacing.

A parallel algorithm for statistical-fairness-based spectrum allocation of cognitive radios

A parallel algorithm for statistical-fairness-based spectrum allocation of cognitive radios is proposedin this paper. The key idea of the algorithm is to pursue the maximum total spectrum utilization of thesystem by adopting a parallel technique in every spectrum allocation, and to ensure the statistical fairnessrule by deploying a particular scheme during a series of allocations. The simulation results show that theproposed algorithm not only achieves a fairer and more efficient allocation of spectrum resources, but alsohas much shorter allocation duration than the color sensitive graph coloring (CSGC) algorithm.

An Enhanced Spectrum Resource Allocation Algorithm in Hetnets

Efficient spectrum resource allocation in wireless heterogeneous networks is important for improving the system throughput and guaranteeing the user's Quality-of-Service(QoS).In this paper,we propose an enhanced algorithm for spectrum resource allocation in heterogeneous networks.First,the bandwidth of each user is determined by the user's rate demand and the channel state.Second,graph theory is enhanced and used to improve the spectrum efficiency.Third,spectrum resource is dynamically split between macrocell and femtocells with the changes of users' conditions.Our simulation results show that the proposed algorithm improves the system throughput significantly and also guarantees the fairness for the users.