目标指示雷达编配的遗传算法

根据现代防空作战中目标指示雷达编配的一般原则及最优准则,建立了编配模型,并应用遗传算法对该模型进行优化,得出最优的评估方案.示例分析计算表明,基于遗传算法的目标指示雷达的编配,能较好地解决雷达编配问题,从而有效地提高侦察预警系统的效能,保障防空作战决策的准确性和及时性.     

Routing and wavelength assignment based on genetic algorithm

In this letter, the routing and wavelength assignment problem in all optical networks is considered. We improve the Max-RWA model presented by R. M. Krishnaswamy and K. N. Sivarajan (see ibid., vol.5, p.435-7, Oct. 2001) by introducing limited-range wavelength conversions. Considering transmission performance, we propose a new optimization objective, which is to establish the maximum number of connections with the least number of wavelength converters. The modified Max-RWA problem is formulated as a integer linear programming (ILP) problem, and then solved using a genetic algorithm. The extended layered-graph approach is used to assign routes and wavelengths when necessary, thus reducing the complexity of the genetic algorithm. Numerical results obtained for NSFNET are presented     

Channel assignment in cellular radio using genetic algorithms

The channel assignment problem has become increasingly important in mobile telephone communication. Since the usable range of the frequency spectrum is limited, the optimal assignment problem of channels has become increasingly important. Recently Genetic Algorithms (GAs) have been proposed as new computational tools for solving optimization problems. GAs are more attractive than other optimization techniques, such as neural networks or simulated annealing, since GAs are generally good at finding an acceptably good global optimal solution to a problem very quickly. In this paper, a new channel assignment algorithm using GAs is proposed. The channel assignment problem is formulated as an energy minimization problem that is implemented by GAs. Appropriate GAs operators such as reproduction, crossover and mutation are developed and tested. In this algorithm, the cell frequency is not fixed before the assignment procedures as in the previously reported channel assignment algorithm using neural networks. The average generation numbers and the convergence rates of GAs are shown as a simulation result. When the number of cells in one cluster are increased, the generation numbers are increased and the convergence rates are decreased. On the other hand, with the increased minimal frequency interval, the generation numbers are decreased and the convergence rates are increased. The comparison of the various crossover and mutation techniques in a simulation shows that the combination of two points crossover and selective mutation technique provides better results. All three constraints are also considered for the channel assignments: the co-channel constraint, the adjacent channel constraint and the co-site channel constraint. The goal of this paper is the assignment of the channel frequencies which satisfied these constraints with the lower bound number of channels.     

基于量子遗传算法的航空通信频率动态分配

为了更加有效地对航空通信频率进行分配,提出了一种基于量子遗传算法的航空通信频率动态分配方法。通过对频率动态分配思路进行分析,建立了频率动态分配框架,给出了频率动态分配的具体流程。在此基础上,讨论了航空通信频率动态分配问题,定义了航空通信频率动态分配约束条件,建立了航空通信频率动态分配模型。最后,运用量子遗传算法和遗传算法对算例进行仿真对比。结果表明：量子遗传算法在种群适应度和收敛速度上具备明显的优越性,频率动态分配模型能够根据不同种群数量条件动态调整适应度,能够较好满足航空通信频率分配问题动态性、准确性、时效性等实践运用要求。     

基于改进的遗传算法无线通信网频率指配问题研究

通过对无线通信频率指配问题的分析,结合遗传算法在频率指配领域的应用,提出了一种启发式的指配方法。该方法通过改进选择方式,自适应地调整交叉、变异概率来指配信道分配。仿真分析证明,该算法科学可行,有效地避免陷入局优解,加快了种群进化速度,减少了迭代次数,较快收敛到最优解。     

Fixed channel assignment in cellular radio networks using amodified genetic algorithm

With the limited frequency spectrum and an increasing demand for cellular communication services, the problem of channel assignment becomes increasingly important. However, finding a conflict-free channel assignment with the minimum channel span is NP hard. Therefore, we formulate the problem by assuming a given channel span. Our objective is to obtain a conflict-free channel assignment among the cells, which satisfies both the electromagnetic compatibility (EMC) constraints and traffic demand requirements. We propose an approach based on a modified genetic algorithm (GA). The approach consists of a genetic-fix algorithm that generates and manipulates individuals with fixed size (i.e., in binary representation, the number of ones is fixed) and a minimum-separation encoding scheme that eliminates redundant zeros in the solution representation. Using these two strategies, the search space can be reduced substantially. Simulations on the first four benchmark problems showed that this algorithm could achieve at least 80%, if not 100%, convergence to solutions within reasonable time. In the fifth benchmark problem, our algorithm found better solutions with shorter channel span than any existing algorithms. Such significant results indicate that our approach is indeed a good method for solving the channel-assignment problem     

基于遗传算法的RLS自适应算法研究

在通信系统中采用信道均衡技术是改善信道特性行之有效的方法,但研究算法的同时,往往需要通过大量的仿真实验取平均值来选取最优的参数值,本文首先利用MATLAB仿真软件对线性调制下RLS自适应算法进行仿真分析,然后引入遗传算法的寻优特性及其优点,对RLS最佳遗忘因子λ的选取进行了寻优,得出最佳遗忘因子λ的取值,提供了参数选择的一条捷径,最后通过对比最优λ与参照λ,计算RLS算法均衡已知信号的均方误差值,证明了该方法的可行性。     

基于并行分配算法的认知无线电频谱分配算法

针对传统频谱分配方式不合理造成频谱匮乏以及CSGC算法在频谱分配上消耗时间过长影响实时通信的问题,文中提出了一种基于并行分配算法的认知无线电频谱分配算法,其通过同时给各顶点进行上色,从而节省了时间开销。实验证明,并行算法不仅具有与CSGC算法同样的高频谱利用率,且其频谱分配时间开销更低,是一种理想的认知无线电频谱分配算法。     

一种基于改进遗传算法的资源分配策略

提出一种基于改进遗传算法的整体优化的动态资源分配方案。首先根据信道分配的特点构造了基因链模型,进而建立了一种整体优化模型,该算法尽量保证最大程度的紧致分配,同时针对遗传算法爬山能力差的弱点,提出一种自适应遗传方法。分析和仿真表明,该方案与现有的FCA和DCA方案相比,有较小的呼阻率和较高的频谱利用率,不论在业务量较大还是较小都能取得较好的性能指标。     

遗传算法在目标优化分配中的应用

鉴于防空作战指挥系统目标分配问题的一般数学模型及分配原则,给出了应用遗传算法实现目标分配优化问题的具体实现描述,仿真结果表明该方法运算速度较快,结果精度较高,对地面防空火力分配决策研究具有一定的参考价值。     

Channel assignment for cellular radio using simulated annealing

The channel assignment problem, i.e. the task of assigning the channels to the radio base stations in a spectrum-efficient way, is an NP-complete optimization problem occurring during design of cellular radio systems. Previously, this problem has been solved by graph coloring algorithms. An alternative approach is presented. The problem is solved using simulated annealing, which is a general approach to combinatorial optimization. The algorithm has been successfully applied to practical radio network planning situations. One major benefit of the approach consists in the enhanced flexibility it gives to the engineer     

基于频谱对称性的GNSS频率抗干扰算法

传统的卫星导航信号频域抗干扰技术在接收信号的频域将干扰信号的谱线进行抑制从而达到抗干扰的目的,但在抑制干扰的同时抑制了部分信号,造成信号能量的损失。提出一种利用卫星导航信号频谱对称性的频域抗干扰算法,该方法利用卫星导航信号在频谱上的冗余性,在进行干扰谱线抑制的过程中利用与之对称未被干扰的谱线进行恢复,即可得到完整的信号频谱。分析北斗B3频点民码仿真数据表明：当干扰信号的频谱出现在中心频点的一侧时,该方法对干扰信号的带宽不敏感,即使干扰信号的频谱占到了信号频谱的一半,其输出信号的能量仍能保持稳定;与传统的方法相比,在进行干扰谱线抑制的过程中减小了信号能量的损失。仿真实验表明,在典型场景下,提出的方法与传统的置零法相比,载噪比提升约1 dB。     

采用几何校正优化的轮廓波水印算法

针对目前的图像水印难以同时抵抗常规攻击和几 何攻击的不足,提出一种新的轮廓波 水印算法。水印嵌入阶段,该方法将宿主图像进行离散小波变换和非下采样轮廓波变换,并 将水印嵌入到熵值最大的高频子带,解决了将水印嵌入低频无法抵抗几何攻击及高频不能 很好抵抗滤波等常规攻击的问题。在水印嵌入前对嵌入区域进行加密处理,提高算法的安全 性。水印提取阶段,利用Zernike矩对含水印图像进行几何校正再进行提取,进一步提高了 算法的抗几何攻击能力。最后利用峰值信噪比和归一化系数对算法进行评价,验证算法的不 可感知性和鲁棒性。仿真实验结果表明,算法在不同的宿主图像和水印图像上均表现良好。 该算法在具有较好不可见性的基础上,除了对常规攻击具有很好的抵抗力,对几何攻击也具 有强鲁棒性,归一化系数(normalization coefficient,NC)均达到了0.99     

基于UCB算法的信道选择方案

物联网在设备中的应用导致了更多的网络交通堵塞,本地服务器无法满足大数据传输的需要。很难做到在大数据下的中央处理模式云计算。边缘计算的出现,将数据卸载到多个边缘服务器进行处理。卸载到服务器的数据需要通过信道,以前的信道选择方法是基站的统一分配。如果终端设备可以通过自己的学习选择信道,可以提高效率、减轻基站的负担。文章对此开展分析。     

基于kumar快速算法的信道估计

信道估计是无线通信系统的一项关键技术,快速信道估计能够提高通信信号处理的实时性.文章提出了一种通过构建特殊训练序列得到Toeplitz矩阵方程,并利用kumar快速算法来求解方程从而估计出信道冲击响应的方法,仿真结果表明,可以有效地降低信道估计过程中的运算复杂度.     

基于矢量平均的信道估计算法

提出一种适用于DS-CDMA无线通信系统的低计算量而性能良好的信道估计算法。在DS-CDMA系统中，当接收信号经过解扩或多用户检测等时域预处理后，可以认为干扰大大减弱、期望信号在处理后的信号中占主要地位。这样，用预处理后信号相关阵的最大特征值对应的特征矢量可以很好地近似期望信号的信道矢量。但是，直接特征分解需要很大的计算量，特征跟踪计算量较低，但瞬态性能较差。本文提出一种基于相关矩阵列矢量平均的信道估计算法，该算法不需要特征分解或跟踪。仿真结果表明：新算法在降低计算量的情况下可以获得同直接特征分解方法几乎相同的性能。     

一种基于模因演算法的频率分配新策略

分析了模因演算法的原理以及与遗传算法之间的关系。基于遗传算法在求解频率分配 问题时的有效性,指出了使用模因演算法解决同类问题的可行性。针对一个实际的频率分配 问题提出并设计了一种新颖的基于正整数序列编码方式的模因演求解算法。实验结果表明, 新算法能够在有效时间内找到满足电磁兼容特性的频率分配方案。     

基于节点密度的混合式多信道分配算法

为了减小无线传感器网络中的同频干扰和避免网络堵塞问题,文章提出了一种基于节点密度的混合式多信道分配算法。该算法通过考虑链路干扰以及节点密度等因素,来解决局部严重同频干扰问题,实现各信道负载均衡,减少网络阻塞。仿真实验结果分析表明,该算法能有效地解决网络中同频干扰问题,较好地均衡各信道的网络负载,在数据业务较重的情况下,网络性能仍比较良好。     

Channel assignment for cellular radio using extended dynamic programming

The channel assignment is an important aspect of cellular radio networks. Because of the limitations on the frequency spectrum, the optimal or near-optimal channel assignment has become an essential part of the network operations of wireless personal communication systems. We formulate a new strategy for the channel assignment problem in agreement with the electromagnetic compatibility constraints. We introduce and formulate the extended dynamic programming (EDP), as an extension of dynamic programming for solving the channel assignment problem in a cellular system. Using EDP an algorithm is developed for fixed channel assignment problem and it is tested and compared with other existing methods by solving different problems. In agreement with electromagnetic compatibility constraints, solution strategy based on EDP algorithm finds many valid solutions with minimum possible bandwidth.     

混合智能优化频率指配算法

在模拟退火算法的基础上,引入禁忌搜索的记忆功能,提出了一种基于混合智能优化的频率指配算法,仿真分析了该混合算法各参数对算法性能的影响,并将禁忌搜索、模拟退火两种算法单独应用时的性能和该混合算法的性能进行了对比.结果表明,该混合算法收敛快,稳定性好,解的质量高,能有效改善搜索效率和精度,为解决大规模复杂网系的频率指配问题进行了有益的探索.