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。     

携能网络中保障能效的缓存队列中继选择与能量分配方案

在无线携能（SWIPT）网络中,带有缓存队列的一对半双工SWIPT中继可以在一个时隙内完成信息同时收发,实现虚拟全双工通信。针对SWIPT虚拟全双工网络的资源分配问题,该文研究了缓存队列机制的最佳SWIPT中继选择与子载波能量分配方案。首先建立数学模型,参考注水因子辅助搜索算法,以最大化能效为目标,在满足能量、信息传输速率、最佳接收中继干扰等多个约束条件下,通过求解优化问题选择SWIPT最佳转发中继,同时得到最佳转发中继的子载波能量分配最优解。仿真结果表明,与最大化端到端可达速率为目标的联合资源分配算法相比,所提方案考虑了SWIPT网络中继间干扰。且当源端发送功率较大时,所提方案可以获得较高的能效。      

LSAPSP: Load distribution‐based slot allocation and path establishment using optimized substance particle selection in sensor networks

Sensor node energy conservation is the primary design parameters in wireless sensor networks (WSNs). Energy efficiency in sensor networks directly prolongs the network lifetime. In the process of route discovery, each node cooperates to forward the data to the base station using multi‐hop routing. But, the nodes nearer to the base station are loaded more than the other nodes that lead to network portioning, packet loss and delay as a result nodes may completely loss its energy during the routing process. To rectify these issues, path establishment considers optimized substance particle selection, load distribution, and an efficient slot allocation scheme for data transmission between the sensor nodes in this paper. The selection of forwarders and conscious multi‐hop path is selected based on the route cost value that is derived directly by taking energy, node degree and distance as crucial metrics. Load distribution based slot allocation method ensures the balance of data traffic and residual energy of the node in areal‐time environment. The proposed LSAPSP simulation results show that our algorithm not only can balance the real‐time environment load and increase the network lifetime but also meet the needs of packet loss and delay.     

Efficient flow‐control algorithm cooperating with energy allocation scheme for solar‐powered WSNs

Recently, solar energy emerged as a feasible supplement to battery power for wireless sensor networks (WSNs) which are expected to operate for long periods. Since solar energy can be harvested periodically and permanently, solar‐powered WSNs can use the energy more efficiently for various network‐wide performances than traditional battery‐based WSNs of which aim is mostly to minimize the energy consumption for extending the network lifetime. However, using solar power in WSNs requires a different energy management from battery‐based WSNs since solar power is a highly varying energy supply. Therefore, firstly we describe a time‐slot‐based energy allocation scheme to use the solar energy optimally, based on expectation model for harvested solar energy. Then, we propose a flow‐control algorithm to maximize the amount of data collected by the network, which cooperates with our energy allocation scheme. Our algorithms run on each node in a distributed manner using only local information of its neighbors, which is a suitable approach for scalable WSNs. We implement indoor and outdoor testbeds of solar‐powered WSN and demonstrate the efficiency of our approaches on them. Copyright © 2010 John Wiley & Sons, Ltd.     

非对称协作通信中的时变功率分配算法

针对反射、散射影响下的非对称无线协作通信网络,提出了一种时变功率分配(Time Variant Power Allocation, TVPA)算法。根据无线协作网络中,各节点之间信道条件实时变化且不对称的特点,在信号传输过程中对信源节点和中继节点的发送信号功率进行优化分配。借助信道编码定理,将系统错误概率最小的非凸优化问题转化为最大化系统容量的凸优化问题来解。与固定功率分配(Fixed Power Allocation, FXPA)算法和平均功率分配(Average Power Allocation, AVPA)算法相比,该算法能充分利用无线信道的时变特性,重新分配功率以降低系统错误概率。在多种网络模型中的仿真结果表明,准静态瑞利衰落信道下,相比于FXPA算法,TVPA算法可获得多达5.5dB的比特错误概率性能增益。随着网络质量的进一步改善,该性能优势也逐步增大。      

Distributed SNR-Based Power Allocation in Wireless Parallel Amplify-and-Forward Relay Transmissions Using Cournot Game

In wireless communications, power allocation plays a paramount role in sustainable network lifetime prolongation with quality-of-service and network interference reduction. This paper investigates a distributed power allocation problem in wireless parallel amplify-and-forward (AF) relay transmissions. Particularly, the objective is set to minimize the total transmit power while guaranteeing the signal-to-noise ratio (SNR) requirement at the destination node. The distributed SNR-based power allocation problem is formulated and modeled as a Cournot game. Moreover, a distributed SNR-based power allocation algorithm is proposed to solve the Cournot game. The proposed distributed SNR-based power allocation algorithm is proved to converge to a unique equilibrium. To evaluate the distributed method, a centralized optimal SNR-based power allocation algorithm is also proposed. Numerical results show that the proposed distributed SNR-based power allocation algorithm can achieve comparable performance to the centralized optimal SNR-based power allocation algorithm.     

Residual energy based multi-relay selection and power allocation scheme in two-way relay network

In this paper, we have proposed a multi-relay selection and power allocation scheme for two-way relay network which aims to maximize the sum-rate of two-way relay system. First, to prolong network lifetime, a multi-relay selection strategy is proposed in which both channel state information （CSI） and remaining energy （RE） are considered. Next, a multi-relay power allocation algorithm based on convex optimization （MRPA-CO） is presented. To reduce the computational complexity, it can be divided into two steps： terminal nodes power allocation （TNPA） and relay nodes power allocation （RNPA）. Simulation results indicate that the proposed relay selection strategy can significantly prolong network lifetime compared to other relay selection strategies which consider CSI only, and the MRPA-CO algorithm has great advantage over equal power allocation （EPA） on sum-rate in two-way relay network.     

An Efficient Cross-Layer Optimization Algorithm for Data Transmission in Wireless Sensor Networks

In this paper, we propose a cross layer congestion optimization scheme for allocating the resources of wireless sensor networks to achieve maximization of network performance. The congestion control, routing selection, link capacity allocation, and power consumption are all taken account to yield an optimal scheme based on the Lagrangian optimization. The Lagrangian multiplier is adopted to adjust power consumption, congestion rate, routing selection and link capacity allocation, so that the network performance can be satisfied between the trade-off of efficiency and fairness of resource allocation. The proposed algorithm can significantly achieve the maximization of network performance in relieving the network congestion with less power consumption. Excellent simulation results are obtained to demonstrate our innovative idea, and show the efficiency of our proposed algorithm.     

一种基于IEEE802.16无线MESH网络集中调度机制的时隙分配方法

在基于IEEE 802.16的无线Mesht网络中,时隙分配算法对网络性能有重要影响.针对现有时隙分配算法只研究上行链路且时隙分配的结果导致中继节点在转发数据时频繁在相邻时隙间进行收发切换的问题,提出了一种上下行链路通用的时隙分配方法,对于上行链路,跳数较小节点的数据优先传输,而对于下行链路,跳数较大节点的数据优先传输,在传输路径上采用逐跳传输的策略.仿真结果证明了该算法的有效性.     

Optimized in-band control channel with channel selection scheduling and network coding in distributed cognitive radio networks

This article proposes an optimized in-band control channel scheme with channel selection scheduling algorithm and network coding based transmission paradigm in the distributed cognitive radio network (...     

基于能量采集异构蜂窝网络的功率分配算法研究

针对能量采集异构蜂窝网络,由于能量到达和信道状态的随机性导致离线功率分配算法只能取得理论最优,本文提出了一种在线功率分配算法.算法在每个时隙开始时,基站控制器通过能量判别选出满足开启条件的小蜂窝基站,然后采用基于拉格朗日乘子的两层迭代算法对所选择的小蜂窝基站分配发射功率,能够实际最大化系统在每个时隙的能效.仿真表明在满足基站开启条件的情况下,所提算法可以为密集异构网络提供更高的能量效率.该算法适用于信道状态和能量状态不可预测的网络.     

Radio resource management for cellular CDMA systems supporting heterogeneous services

A novel radio resource management (RRM) scheme for the support of packet-switched transmission in cellular CDMA systems is proposed by jointly considering the physical, link, and network layer characteristics. The proposed resource management scheme is comprised of a combination of power distribution, rate allocation, service scheduling, and connection admission control. Power distribution allows individual connections to achieve their required signal-to-interference-plus-noise ratio, while rate allocation guarantees the required delay/jitter for real-time traffic and the minimum transmission rate requirement for non-real-time traffic. Efficient rate allocation is achieved by making use of the randomness and burstiness; of the packet generation process. At the link layer, a packet scheduling scheme is developed based on information derived from power distribution and rate allocation to achieve quality of service (QoS) guarantee. Packet scheduling efficiently utilizes the system resources in every time slot and improves the packet throughput for non-real-time traffic. At the network layer, a connection admission control (CAC) scheme based on the lower layer resource allocation information is proposed. The CAC scheme makes use of user mobility information to reduce handoff connection dropping probability (HCDP). Theoretical analysis of the grade of service performance, in terms of new connection blocking probability, HCDP, and resource utilization, is given. Numerical results show that the proposed RRM scheme can achieve both effective QoS guarantee and efficient resource utilization.     

基于迁移深度强化学习的低轨卫星跳波束资源分配方案

针对低轨(LEO)卫星场景下,传统资源分配方案容易造成特定小区资源分配无法满足需求的问题,该文提出一种基于迁移深度强化学习(TDRL)的低轨卫星跳波束资源分配方案。首先,该方案联合星上缓冲信息、业务到达情况和信道状态,以最小化卫星上数据包平均时延为目标,建立支持跳波束技术的低轨卫星资源分配优化模型。其次,针对低轨卫星网络的动态多变性,该文考虑动态随机变化的通信资源和通信需求,采用深度Q网络(DQN)算法利用神经网络作为非线性近似函数。进一步,为实现并加速深度强化学习(DRL)算法在其他目标任务中的收敛过程,该文引入迁移学习(TL)概念,利用源卫星学习的调度任务快速寻找目标卫星的波束调度和功率分配策略。仿真结果表明,该文所提出的算法能够优化卫星服务过程中的时隙分配,减少数据包的平均传输时延,并有效提高系统的吞吐量和资源利用效率。     

基于功率分配的无线传感器网络拥塞控制协议

由于无线传感器网络的资源受限,相比传统网络其传输过程更容易导致丢包和拥塞。为了避免和控制拥塞,本文提出了一种利用功率分配重新选择路径的拥塞控制算法,首先参考路径传输的多种QoS相关参数度量网络的路径代价和节点可用资源的信息,基于测量得到的网络拥塞水平通过传输功率递增和递减选择不同的路径控制网络拥塞。仿真结果表明所提出的协议减少了网络时延,提高了系统吞吐量和网络生命周期。      

无线多跳网络下基于过时信道状态信息的跨层资源分配

对于无线多跳网络跨层资源分配算法的研究大多是建立在假定每个节点能获得网络中其他节点的完美的信道状态信息(CSI)的基础上。但是由于信道的时变特性和CSI的反馈延时,在动态变化较快的无线网络中,节点所获得的CSI很可能是过时或者部分过时的。基于这个前提,该文首次在动态无线多跳网络跨层资源优化分配算法中考虑了CSI这种变化的影响,并提出了一种相应的分布式联合拥塞控制和功率分配算法。仿真结果证明该算法能够极大地提高网络效用和能量效用。     

放大转发中继网络中绿色的物理层安全通信技术

该文基于物理层安全理论,针对能量受限的无线中继网络提出一种绿色的保密通信方案。该方案在节点功率约束和系统最小目标保密速率要求下,通过最优功率控制实现系统的安全能效最大化,并基于分式规划、对偶分解和DC(Difference of Convex functions)规划理论提出了一种迭代的功率分配算法。通过仿真比较,能效优化可以显著提升系统的安全能效,然而相对于保密速率最大化会有一定保密速率损失,这是由于能效和保密之间存在固有的折中。但是,能效优化的保密速率仍然大于发送总功率最小化的保密速率。     

太赫兹无线局域网MAC协议优化设计

针对现有太赫兹无线网络MAC(Medium Access Control)协议中存在的无线局域网场景下原有波束赋形方案不适用、关联请求时段在新入网节点数量受限情况下时隙利用率低,以及网络流量较大时扇区号靠后的节点一直无法获得时隙导致时延陡增的情况,提出了一种适用于无线局域网的高效低时延太赫兹MAC协议(High Efficiency and Low Latency Terahertz MAC,HELL-MAC)。该协议利用中心控制节点与普通节点间的信息交互减少了不必要的波束赋形过程,采用机会性复用关联S-CAP(Sub-channel Access Period)机制提高了时隙利用率,采用公平时隙分配机制提高了时隙分配的公平性,从而减少了波束赋形时间,降低了平均端到端时延,提高了信道利用率。     

有线无线融合的卫星时间敏感网络流调度研究

随着空间通信任务日趋复杂化,尤其是对时间敏感的需求不断提升,一方面要求星内系统的高带宽、可靠性和实时性;另一方面星间无线链路也应具备低时延和高可靠性.但由于卫星内部有线链路与星间无线链路差异大,业务数据经过有线和无线链路联合传输时,容易引发节点拥塞,而无法保障时敏业务的时延有界需求.为了提升数据在空间网络传输的实时性,...     

基于双频通信的空间飞行器自组网动态时隙分配

针对分布式空间飞行器自组网使用传统时分多址(Time Division Multiple Access,TDMA)时隙分配方式时网络时延大、传输效率不高的问题,提出了一种基于双频通信的动态时分多址时隙分配(Dual Frequency Dynamic Time Division Multiple Access,DF-D...     

Energy‐Aware Hybrid Cooperative Relaying with Asymmetric Traffic

In this paper, we study an asymmetric two‐way relaying network where two source nodes intend to exchange information with the help of multiple relay nodes. A hybrid time‐division broadcast relaying scheme with joint relay selection (RS) and power allocation (PA) is proposed to realize energy‐efficient transmission. Our scheme is based on the asymmetric level of the two source nodes’ target signal‐to‐noise ratio indexes to minimize the total power consumed by the relay nodes. An optimization model with joint RS and PA is studied here to guarantee hybrid relaying transmissions. Next, with the aid of our proposed intelligent optimization algorithm, which combines a genetic algorithm and a simulated annealing algorithm, the formulated optimization model can be effectively solved. Theoretical analyses and numerical results verify that our proposed hybrid relaying scheme can substantially reduce the total power consumption of relays under a traffic asymmetric scenario; meanwhile, the proposed intelligent optimization algorithm can eventually converge to a better solution.