蜂窝移动通信系统中的一种新的优化信道分配模型

本文提出了一种新的蜂窝移动通信系统最优信道分配模型.首先根据信道分配的特点构造了一种信道分配方程模型;进而建立了信道分配最优模型,利用Pontryain最小值原理获得了模型的最优解;给出的仿真结果验证了分析结论的正确性.该模型可以用来有效地研究信道分配问题的宏观性能,并提供了一种高效、快速的算法.     

一种基于Chirp探测的短波频率分配算法

针对短波通信网频率优化分配问题,本文利用chirp探测系统提供的信道参数,建立了带有信道约束的数学模型,并研究了用遗传算法求解模型的具体方法.该遗传算法采用的编码方式是信道频点的整数序列号,个体是一组经过分配的序列号.在仿真过程中发现由算法本身带来的严重违反约束条件的问题,通过比较三种不同约束处理方法得以解决.仿真计算的结果表明,模型建立得当,算法有效解决优化分配的问题.     

一种适用于多信道联合组网的时隙分配新算法

分析了多信道联合组网时隙分配问题的特点,提出分配时隙时应该综合考虑容量需求、负载均衡和分配均匀度三方面因素,并设计了估计该三方面需求满足程度的方法。基于遗传算法,提出了适用于求解该问题的优化算法。仿真试验表明,提出的新算法能够有效求解多信道联合组网环境下的时隙分配问题。     

一个用于GPRS网络性能估计的马尔可夫模型

建立了一个二维连续时间的马尔可夫链,该模型描述了GPRS业务和语音业务在一定的动态信道分配方案下对有限信道资源的共享。采用一种近似求解方法求得该马尔可夫链的稳态解,通过数值计算可以估计出GSM/GPRS网络的一些主要性能,如:呼叫阻塞率、数据平均传输速率、信道利用率等。为了验证该模型的有效性,将数值分析的结果与仿真结果进行了比较。     

模拟退火算法的WLAN信道分配中的应用

无线局域网在大规模部署时信道分配成为一个重要问题,对此提出了以最大化最小信干比为日标的无线局域网信道分配模型,并把模拟退火算法应用到模型的求解中.仿真实验结果表明,该算法具有良好的收敛性和求解效果,能显著提高整个无线局域网覆盖区域上的信干比.     

基于混沌神经网络的移动通信信道分配方法研究

该文应用混沌神经网络求解信道分配问题,给出了信道分配的能量函数表达式和混沌神经网络模型,研究了判别混沌神经网络混沌特性的Lyapunov指数法,讨论了网络模型参数对网络混沌特性的影响,提出了基于混沌神经网络的信道分配算法.仿真结果表明,混沌神经网络具有复杂的瞬态混沌特性,它比Hopfield网络具有更强的搜索全局最优解的能力,和更快的收敛速度.     

面向H.264/SVC空域-质量域可伸缩编码的码率分配算法

 针对H.264/SVC空域-质量域可伸缩性,本文提出了一种基于模型的多层次码率优化分配算法.通过分析各编码层间的相关性,对空域和质量域视频层的码率和失真特性进行了建模.在此基础上,将H.264/SVC空域-质量域两维度码率分配问题描述为一个两阶段最优化问题进行求解.最后,代入提出的率失真模型,使用拉格朗日乘数法,求取该分配问题的最优数值解.大量实验结果可以看出新的率失真模型所提供的高效码率分配算法,大幅度提高了现有参考代码JSVM的性能.     

基于不完美CSI的低轨卫星通信系统鲁棒资源分配算法

为了解决低轨卫星通信系统因资源受限导致的能量与速率不平衡的问题,同时考虑信道不确定性对实际卫星通信系统性能衰退的影响,该文提出一种基于最大化最小能效的鲁棒资源分配算法。首先,考虑每个用户中断速率约束、功率分配系数约束和最大发射功率约束,基于高斯信道不确定性,构建了联合优化卫星波束成形向量与功率分配因子的鲁棒资源分配模型。所描述的问题是一个含参数摄动的非凸、非确定性多项式难问题,很难直接求解。为此,基于丁克尔巴赫、伯恩斯坦不等式、半正定松弛和交替优化等方法将其转化为等价的凸优化问题,并提出一种基于迭代的混合鲁棒波束成形与功率分配算法。仿真结果表明,该文算法具有较好的能效和较强的鲁棒性。     

针对业务变化的TD-SCDMA信道码分配算法探讨

在三代移动通信TD—SCDMA系统信道的分配是载波、时隙、信道码（扩频码）的分配。本文针对用户使用的业务不断变化的TD—SCDMA系统提出一种新的信道码分配算法，对算法的流程进行详细的描述，并且通过仿真证明新算法在呼叫阻塞率方面强与原有信道码分配算法，对于工程的应用有重要的价值。     

结合机会链的联合频谱分配算法

基于机会链模型和遗传算法,提出一种优化信道使用的联合分配算法。该算法利用遗传算法进行初次分配,然后构建满足链和需求链两种机会链模型,在避免弱势用户问题的同时,优化初次分配方案,增大系统总带宽,降低系统带宽需求缺口,从而提高频谱利用率。通过仿真验证了该算法的有效性。     

Optimal radio channel assignment through a new binary dynamic simulated annealing algorithm

The radio channel assignment problem (CAP) is classified as an NP-complete binary optimization problem, which creates the need for faster, yet optimal optimization algorithms to reduce the time of computation when solving such a complex problem. Simulated annealing (SA), a powerful optimal combinatorial search algorithm, was found to be very suitable for CAP. This paper extends the standard capabilities of SA and proposes a new CAP-oriented, quicker binary SA, the binary dynamic SA (BDSA) algorithm, as part of a newly proposed radio channel assignment approach. Simulation results proved that the proposed BDSA has very fast convergence as a stand-alone algorithm and even faster convergence with the newly proposed radio channel assignment approach. © 1998 John Wiley & Sons, Ltd.     

Robust vector quantization for wireless channels

This study focuses on two issues: parametric modeling of the channel and index assignment of codevectors, to design a vector quantizer that achieves high robustness against channel errors. We first formulate the design of a robust zero-redundancy vector quantizer as a combinatorial optimization problem leading to a genetic search for a minimum-distortion index assignment. The performance is further enhanced by the use of the Fritchman (1967) channel model that more closely characterizes the statistical dependencies between error sequences. This study also presents an index assignment algorithm based on the Fritchman model with parameter values estimated using a real-coded genetic algorithm. Simulation results indicate that the global explorative properties of genetic algorithms make them very effective in estimating Fritchman model parameters, and use of this model can match index assignment to expected channel conditions     

无线mesh网络中基于效用最优的联合信道分配和功率分配算法

该文针对多信道无线mesh网络,采用基于效用最优的定价机制,提出了一种功率-干扰价格模型,并基于该模型提出了一种分布式联合信道分配和功率分配算法。每个节点根据自己所消耗功率状况合理地定功率价格,并根据自己所受干扰状况合理地定干扰价格。通过功率价格和干扰价格来调节链路的信道分配和功率分配,使网络效用最大化。仿真结果表明：所提出的算法能够快速、平稳地收敛到近似最优解。同时还仿真了网络可用信道数目、节点射频数目和功率对系统性能的影响,可以为网络配置提供参考。     

DS-CDMA reverse link channel assignment based on interferencemeasurements

The authors propose a DS-CDMA reverse link channel assignment algorithm based on received interference. A new channel is assigned if the required power is less than the `current interference margin'. The proposed algorithm is adaptable to dynamically changing environments with the capability of assigning more channels than conventional channel assignment methods in nonhomogeneous traffic loads and path loss changes     

基于图论的无线传感器网络并行禁忌搜索信道分配方法

Wireless sensor networks are suffering from serious frequency interference. In this paper, we propose a channel assignment algorithm based on graph theory in wireless sensor networks. We first model the conflict infection graph for channel assignment with the goal of global optimization minimizing the total interferences in wireless sensor networks. The channel assignment problem is equivalent to the generalized graph coloring problem which is a NP complete problem. We further present a meta heuristic Wireless Sensor Network Parallel Tabu Search (WSN PTS) algorithm, which can optimize global networks with small numbers of iterations. The results from a simulation experiment reveal that the novel algorithm can effectively solve the channel assignment problem.     

Nodes organization for channel assignment with topology preservation in multi-radio wireless mesh networks

The wireless mesh network is a new emerging broadband technology providing the last-mile Internet access for mobile users by exploiting the advantage of multiple radios and multiple channels. The throughput improvement of the network relies heavily on the utilizing the orthogonal channels. However, an improper channel assignment scheme may lead to network partition or links failure. In this paper we consider the assignment strategy with topology preservation by organizing the mesh nodes with available channels, and aim at minimizing the co-channel interference in the network. The channel assignment with the topology preservation is proved to be NP-hard and to find the optimized solution in polynomial time is impossible. We have formulated a channel assignment algorithm named as DPSO-CA which is based on the discrete particle swarm optimization and can be used to find the approximate optimized solution. We have shown that our algorithm can be easily extended to the case with uneven traffic load in the network. The impact of radio utilization during the channel assignment process is discussed too. Extensive simulation results have demonstrated that our algorithm has good performance in both dense and sparse networks compared with related works.     

Power control supported dynamic channel assignment in cellular radio systems

Transmitter power control is an effective technique to reduce co-channel interference and increase system capacity for cellular radio networks. Dynamic channel assignment can also be used to improve spectrum efficiency and thus increases the system capacity. This paper investigates channel assignment algorithms which combine dynamic channel assignment with signal-to-interference ratio balanced power control and proposes a new algorithm. Simulation results show that this new scheme can greatly reduce the channel reassignment rate and still maintain satisfactory performance. It may thus be used as an effective channel assignment scheme in cellular mobile systems. © 1997 by John Wiley & Sons, Ltd.     

Graph coloring based channel assignment framework for rural wireless mesh networks

IEEE 802.11 based wireless mesh networks with directional antennas are expected to be a new promising technology and an economic approach for providing wireless broadband services in rural areas. In this paper, we discuss interference models and address how they can affect the design of channel assignment in rural mesh networks. We present a new channel assignment framework based on graph coloring for rural wireless mesh networks. The goal of the framework is to allow synchronously transmitting or receiving data from multiple neighbor links at the same time, and continuously doing full-duplex data transfer on every link, creating an efficient rural mesh network without interference. Channel assignment is shown to be NP-hard. We frame this channel allocation problem in terms of Adjacent Vertex Distinguishing Edge Coloring （AVDEC）. Detailed assignment results on grid topology are presented and discussed. Furthermore, we design an algorithm. Finally, we evaluate the perform- ance of the proposed algorithm through extensive simulations and show the algorithm is effective to the regular grid topologies, and the number of colors used by the algorithm is upper bounded by A ~ 1. Hence the algorithm guarantees that the number of channels available in standards such as IEEE 802.11a is sufficient to have a valid AVDEC for many grid topologies. We also evaluate the proposed algorithm for arbitrary graphs. The algorithm provides a lower upper bound on the minimum number of channels to the AVDEC index channel assignment problem.     

An efficient channel assignment algorithm for multicast wireless mesh networks

Multicast can enhance the performance of wireless mesh networks (WMNs) effectively, which has attracted great attentions in recent years. However, multicast communication in WMNs requires efficient channel assignment strategy to reduce the total network interference and maximize the network throughput. In this paper, the concept of local multicast is proposed to measure interference and solve hidden channel problem in multicast communication. Basing on the concept, we propose a channel assignment algorithm considering the interference of local multicast and forwarding weight of each node (LMFW). The algorithm fully considers partially overlapped channels and orthogonal channels to improve the network performance. Simulations show that the proposed algorithm can reduce interference and improve network capacity of WMNs.