改进蛙跳算法的多中继协作系统最优功率分配

协作通信与直接通信相比能够显著地提高系统性能,功率分配是协作通信中的一个关键问题。为了获得合理的协作中继通信系统功率分配方案,提出一种基于改进蛙跳算法的多中继节点功率分配方法。首先对功率分配问题进行分析,将其转换为一个非线性优化问题,然后将青蛙表示为源节点,中继节点的功率,以平均信噪比作为青蛙的食物,并通过青蛙的信息交流和协作找到最优的功率分配方案,最后采用仿真对比实验对本文算法性能进行测试。仿真结果表明,相对于其它功率分配方法,改进蛙跳算法有效地提高了系统的信道容量,降低了中断概率,以较低的复杂度提高了系统的性能。     

一种多源协作网络的分布式功率分配与中继选择算法

该文针对多源-多中继放大转发协作通信网络,以最小化系统总功率为目标,在保证系统满足一定中断概率的前提下,提出了一种分布式功率分配与中继选择算法.算法由源节点自主选择为其转发信息的中继节点,并引入定时器,通过竞争方式避免了分布式所导致的中继选择冲突.中继收到来自源节点的信号后,只需根据转发门限自主判断是否进行转发,从而完成传输.仿真结果表明该分布式算法能够有效降低传输所需要的总发射功率.并且与集中式控制所获得的最优中继选择与功率分配算法相比性能相近,但所提分布式算法显著降低了系统的控制开销.     

最佳中继协作通信系统的功率分配算法

 为提高基于最佳中继选择的协作通信系统的性能,提出了以最小化系统中断概率为目标的功率分配算法.首先建立了系统的优化模型并证明了待解的优化问题实质是凸优化问题,由此提出了最优功率分配算法并给出了算法步骤.其次,在此基础上提出了一种有效的次最优功率分配算法,该算法计算简单且仅需已知各个中继节点的平均信道状态信息,无需在传输中实时更新,因而不增加系统的额外开销.仿真结果表明,本文提出的最优算法和次最优算法所得到的功率分配方案与穷举搜索方法的结果非常接近;与等功率分配方案相比,这两种算法均能显著提高系统的中断概率性能.     

基于中断概率的协作通信中继选择与功率分配算法

研究了功率受限情况下多中继协作通信网络的中继选择和功率优化问题。在AF网络中,提出了一种低复杂度中继选择与功率分配算法,其目标是在总功率一定的条件下使系统的中断概率最小。本算法对源节点和所有潜在中继节点进行功率分配,结合当前信噪比选择最优的中继集合,通过最速下降法求出使系统中断概率最低的功率分配因子。该算法不需要知道大量瞬时信道信息、不需要系统在等功率条件下进行中继选择,只需求得中继节点排列矩阵便可根据当前信噪比自适应获得最优中继节点集合。仿真结果表明,在相同条件下,该算法明显优于不同中继节点集合下几种算法的中断性能,并且与传统的SAF及AAF算法相比,有效降低了中断概率,提升了系统性能和功率效率。     

多中继合作通信系统的功率分配研究

针对功率分配对于多中继系统的重要性,对混合转发多中继合作系统的功率分配进行了研究,提出了基于等效信噪比最大化的最优功率分配方案。仿真结果表明:合作伙伴的增加对于系统等效信噪比有积极的影响,但不是随着中继数目的增加无限地改善。在多中继混合转发合作系统中,最优的功率分配对于多中继合作系统的性能有很大的改善。     

低复杂度放大转发多中继选择及功率分配

为了解决传统多中继选择协作通信网络算法复杂度高、资源利用率低等问题,本文提出了低复杂度放大转发多中继选择及其功率分配方案.它先利用修正的选择函数选择最优中继集合,再采用改进的低复杂度功率分配方案,对选择的中继集合功率分配.所提方案考虑到等功率分配时,分配功率应随中继数不同而改变,添加修正因子以充分利用功率资源.同时,所提功率分配避免了超越方程求解,极大降低了计算复杂度.仿真表明：当中断概率为10^-4时,所提方案相对于现有预选择单中继放大转发(pre-select Single relay Amplify-and-Forward,SAF)和全中继放大转发(All relay Amplify-and-Forward,AAF)方案,所需信噪比(Signal-to-Noise Ratio,SNR)分别降低约2.5 dB和5.3 dB.其性能与穷举法相当,二者所需SNR仅相差约0.01 dB.     

双中继协作通信的功率分配改进方案

为克服信息处于深度衰落情况下单中继协作困难,减少多中继协作目的端信号处理的复杂度,给出了双中继节点参与协作通信的功率分配方案。两个中继节点分别采用放大转发(AF)、译码转发(DF)以及混合译码放大转发(HDAF)3种协作方式进行通信。在满足一定的中断概率和节点功率限制情况下,利用MATLAB软件中的Fmincon优化函数,得到了各节点的最小发射功率。数值分析表明,在相同条件下,两个中继节点采用HDAF协作方式比采用AF协作方式、DF协作方式消耗的系统总功率分别少4~9 dBm、0.5~1 dBm,最大限度地节约了系统功率的消耗。     

多天线系统中多中继传输的时间分配和功率分配优化方法

本文考虑单小区内的两个中继使用解码转发的方法为两个用户提供下行数据的场景,基站和中继配置多根天线,用户配置单天线。两中继使用相同的频率资源同时为两个用户提供服务。为减小两中继同时向两用户传输时产生的干扰,中继到用户的传输采用协作干扰避免的策略;相应的基站到中继的传输采用多用户空分复用的传输策略。本文在时间分配和功率分配两个方面对上述两跳传输过程进行了优化,提出了两跳传输最优的时间分配策略。由于功率分配最优化问题难以求解,本文提出了一种匹配链路容量的次优功率分配方法,并对其进行简化以降低复杂度。通过仿真可以看出,简化的功率分配方法与匹配链路容量的功率分配性能很接近;所提出的时间分配和功率分配方案可以获得有效的性能提升。      

多中继放大转发协作通信中的功率分配和中继位置联合优化

文章研究了多中继放大转发协作分集系统中的功率分配和中继位置联合优化问题。利用信道的统计状态信息,在总功率一定的条件下,以最大化系统的信道容量为目标,推导了多中继和选择中继两种模型下基于高信噪比近似的联合优化算法的闭式解。理论分析和仿真验证表明,提出的算法大大提高了传统的等功率分配方案下系统的性能。     

多中继AF协作系统功率分配研究

功率分配是协作通信中一个重要的研究方向,文章分析了放大转发（AF）协作方式下,基于正交信道的多协作中继系统模型,在此基础上推导了系统中断概率。并以最小化系统中断概率为目标,给出系统功率分配约束表达式,进一步分析了功率分配与中继节点位置的关系,计算求得单中继和两中继情况系统最优功率分配系数。系统仿真表明最优功率分配相对常规的等功率分配,系统性能明显提升。     

萤火虫群优化算法多阈值的脑CT图像分割

在基于多阈值的脑,CT图像分割算法中,最佳阈值选取是脑CT图像中的关键,针对传统多阈值法的阈值选择难题为了提高脑。CT图像的分割准确率,提出一种萤火虫群算法优化多阈值的脑CT图像分割方法首先建立了基于多阈值法的脑图像分割数学模型,然后通过萤火虫群算法数学模型进行求解,搜索到脑CT图像分割的最佳阈值,CT最后采用最佳阈值完成脑CT图像的分割。仿真结果表明,萤火虫群算法提高了脑CT图像的精度,获得了更加理想的脑CT图像结果。     

Joint power allocation and multi-relay selection scheme based on system outage probability

An amplify-and-forward （AF） based multi-relay network is studied. In order to minimize the system outage probability with a required transmission rate, a joint power allocation （PA） and multi-relay selection scheme is proposed under both total and individual power constraints （TIPC）. In the proposed scheme, the idea of ordering is adopted to avoid exhaustive search without losing much system performance. Besides the channel quantity, the ordering algorithm proposed in this article also takes relays＇ maximal output ability into consideration, which is usually ignored in traditional relay ordering algorithms. In addition, simple power reallocation method is provided to avoid repetitive PA operation during the process of searching all possible relay subsets. By Adopting the idea of ordering and using the proposed power reallocation method lead to remarkable decrease of the computation complexity, making the scheme easier and more feasible to implement in practical communication scenarios. Simulations show that the proposed multi-relay selection scheme provides similar performance compared to the optimal scheme with optimal PA and exhaustive search （OPAES） but with much lower complexity.     

Research on the low complexity adaptive power allocation algorithm in cooperative systems

Cooperative diversity is a new technology to improve bit error rate(BER)performance in wireless communications.A new power allocation algorithm to improve BER performance in cellular uplink has been proposed in this paper.Some existing power allocation schemes were proposed for the purpose of maximizing the channel capacity or minimizing the outage probability.Different from these schemes,the proposed algorithm aims at minimizing the BER of the systems under the constraint of total transmission power.Besides this characteristic,the proposed algorithm can realize a low complexity real-time power allocation according to the fluctuation of channels.Simulation results show that the proposed algorithm can decrease the BER performance of the systems effectively.     

QoS-guaranteed multi-relay selection and power allocation optimization in cooperative systems

This paper investigates the relay selection and power allocation problem in multi-user based cooperative networks, where intermediate relay nodes help source forward information to destination using decode-and-forward (DF) relaying protocol. Specifically, we propose a novel multi-relay nodes selection strategy taking both instantaneous channel state information (I-CSI) and residual energy into consideration, by which 'emergence' diversity gain can be achieved and the imbalance of resource utilization can be overcome. Besides, using Largangian dual-primal decomposition and subgradient projection approach, an optimal power allocation algorithm at source and cooperative relay nodes is presented with the constraints of each user's individual quality of service (QoS) requirements and system total transmit power. Theoretical analysis and simulation results demonstrate that the proposed scheme can significantly improve energy efficiency, while guaranteeing a good balance between achievable data rate and average network lifetime with relatively low implementation complexity.     

基于多维离散粒子群优化的协同 OFDMA 系统跨层资源分配

摘 要：针对多服务情况下协同OFDMA（orthogonal frequency division multiple access）系统的资源分配问题,在基站和中继单独功率约束条件下,以最大化用户的效用(utility)总和为目标,提出了一种基于多维离散粒子群（MDPSO）的渐进最优资源分配算法。该算法采用多值离散变量来编码粒子位置,并针对多维离散空间构建了新的基于概率信息的粒子速度和位置更新算法,且引入变异操作来克服粒子群算法的早熟问题。此外,还采用了迭代注水法进行最优功率分配。仿真结果表明,所提算法在总效用、吞吐量和公平性上均明显优于已有资源分配算法。     

OFDMA协同通信系统子载波和功率联合分配算法

针对OFDMA协同通信系统资源分配仅考虑平均功率下的子载波分配,中继存在未用功率情况,研究子载波分配后中继剩余功率分配问题。提出一种既满足业务QoS需求又兼顾用户间公平性的子载波和功率联合分配算法,并设计一种基于二分法的功率注水分配方案。测试表明,该算法能在满足业务QoS需求及用户公平性的同时,提升系统容量。     

Power allocation in multibeam satellites based on particle swarm optimization

In this paper, a power allocation in multibeam satellite (MBS) communication based on heuristic particle swarm optimization (PSO) is proposed. The PSO algorithm is evocated to solve the problem of power allocation in the multiple narrow spotbeams aiming to provide the minimum signal-to-noise plus interference ratio (SNIR) required by Earth station users to establish reliable communication. In the developed model it is considered the multibeam interference and the different channel conditions of each beam by rain attenuation. The numerical results have been generated taking into account different sky situations, including clear and rainy scenarios; such results have revealed the viability and accuracy of the PSO algorithm deployment in solving the power allocation problem. In addition, with the proposed scheme it is observed the decrement of transmitted power for non-rainy beams with guarantee of the minimum SNIR at the Earth receivers input, while increase the power availability to the rainy beams; as a consequence, the overall energy efficiency of the MBS system has been improved substantially. Moreover, the convergence of the proposed heuristic PSO-based algorithm is discussed while such heuristic approach comes with computational complexity reduction when compared with others efficient power allocation schemes.     

Resource allocation scheme in two-way multi-relay OFDM system

A joint optimization scheme for power allocation and subcarrier pairing under high SNR in two-way multi-relay OFDM system was proposed.Unlike those schemes in which relays use subcarriers separately,all the relays were allowed to forward signal on each subcarrier pair for providing much space diversity.With the constraint of total system power,the proposed scheme firstly allocated each relay power with Cauchy inequality with the assuming that the total relay power was fixed.Then the dichotomy was used to calculate the power allocation between the source node and the relay node by maximizing the equivalent channel gain for different subcarrier pairs.Lastly,the power of different subcarrier pairs was allocated by convex programming,and the subcarriers were paired by Hungarian algorithm to obtain the maximum system capacity.There was no optimal power allocation method with low complexity because of the complexity of the power allocation algorithm in two-way multi-relay networks.This algorithm greatly reduces the complexity of power allocation and simulation results show that the proposed scheme outperforms the relay selection scheme and the relays use subcarriers separately scheme.