OFDM双向多跳网络的新型比特和功率分配算法

结合新型双向多跳网络协议和正交频分复用技术,研究旨在保证通信质量情况下的自适应比特和功率分配算法,其目的是以较小发送功率和较高频谱效率完成通信。通过凸优化理论推导出最优功率分配算法,并提出一种基于贪婪原则的自适应比特分配算法,能够以较低的复杂度在实际工程中完成部署。仿真分析表明,提出的双向多跳算法是传统多跳协议频谱效率的2倍,所需发送功率是平均资源分配算法的1/3。     

基于OFDM的协同认知网络跨层资源调度

协同通信与认知无线电是未来移动通信的重要技术。针对基于OFDM的无线协同认知网络中的资源分配问题,该文提出了一种有效的跨层资源调度方案。该调度方案在考虑对主用户所受干扰功率进行控制的前提下,以最大化认知用户超帧中总的传输速率为目标,在调度帧中对各传输帧两阶段的子载波进行最佳配对,并为配对子载波分配最优的发送功率。通过分步求解的方法,该调度方案形成的优化问题得到有效解决。仿真结果表明该资源调度方案使得认知用户传输速率有显著提升,方案的可行性与有效性得到了验证。     

全双工大规模MIMO异构网络频谱效率分析及优化

本文研究全双工大规模多输入多输出（multiple-input-multiple-output, MIMO）异构网络。推导了采用迫零（zero-forcing, ZF）预编码/检测方案的上下行渐近信干噪比（signal-to-interference-plus-noise ratio, SINR）的闭合表达式。根据理论分析,提出了基于几何规划（geometric programming, GP）的功率控制方案和基于部分用户选择（partial users selection, PUS）的跨层干扰消除方案,改善系统频谱效率。仿真结果表明,与传统方案相比本文提出的功率控制方案和跨层干扰消除方案能够显著提升异构网络的频谱效率。      

基于拥塞反馈的Semi-TCP优化方法

Semi-TCP根据无线多跳网络的特性,利用跨层设计的思想,端到端的拥塞控制调整为节点之间逐跳的拥塞控制,将传输层的拥塞控制下移到MAC层,形成递归逐跳的拥塞控制,旨在提高拥塞控制的效率和拥塞处理的即时性。现有的算法要通过增加或修改MAC控制帧的方式来实现拥塞的控制,因而需要对节点已安装的MAC层协议做适当的修改。文中提出了一种基于拥塞反馈的优化方法,不需要对传统TCP协议进行太多的修改。在EXata平台上进行了仿真,证明了该优化方法的有效性。     

联合速率控制与功率分配的多信道无线网络跨层优化

本文基于凸优化方法,以提升网络效用与降低网络总功耗为目标,针对多无线多信道(Multi-radio Multi-channel)的多跳无线网络提出了一种联合速率控制与功率分配的跨层优化模型,并利用对偶分解方法设计了优化模型对应的分布式算法,证明了该分布式算法收敛性.该算法通过改变本征权的取值能够在网络效用与网络功耗之间取得折衷,并能根据速率要求动态调整各条链路的注入速率与发射功率使得网络达到效用与功耗的联合最优.通过仿真实验验证了该分布式算法可有效的调节网络效用与总功耗之间的平衡.     

差错信道下IEEE 802.11 DCF最优帧长分析及信道自适应策略

分析了差错信道下IEEE 802.11 DCF在饱和状态下的吞吐量以及帧长度对吞吐量的影响.研究表明在一定的误码率（BER）下存在最优的帧长使得系统吞吐量最大,并且该最优值与发送节点的数目无关.在此基础上,提出了一种简单的基于BER区间划分的帧长控制的信道自适应发送策略.仿真表明,与固定帧长的发送策略相比较,使用该策略在差错信道下可以有效地提高吞吐量.     

多信道认知用户能量高效的最优功率分配

针对多信道认知用户能量效率问题,提出认知用户能量效率优化模型,进而优化传输功率和感知帧长。首先,多信道认知用户基于多带宽联合能量检测方案,在一定传输功率和干扰功率限制下,建立了以单位数据能耗为目标的最优化问题;其次,通过非线性分式规划的对偶优化将目标函数转换为内点法求解形式;然后,结合内点法和二分法给出算法流程,进而配置最优功率和感知时间。仿真结果表明,对应不同通信环境采用该优化方法都能通过配置最优功率和感知时间达到能量效率最优。     

基于跨层的加权自组网路由协议的设计及实现

以优化的链路状态路由（Optimized Link State Routing,OLSR）协议为原型,为无线移动自组织网络（Mobile Ad Hoc Networks,MANETs）设计了基于跨层的速率自适应的加权路由协议。该协议充分考察无线信道的时变性质,在路由计算过程中通过跨层信息共享节点的邻居关系及获取节点的当前发送速率,削减了协议的开销。将无线链路的速率与跳数相结合,设计了一种新的路由度量规则。仿真结果表明,提出的加权路由协议能够显著降低网络层的路由开销,提升网络吞吐量,降低端到端时延。     

面向医护监测的无线体域网MAC层协议策略研究

针对医疗护理领域的业务需求和监护设备节点存在多样性的特点,在IEEE802.15.4协议基础上,讨论一种无线体域网混合MAC层协议策略。通过使用长超帧结构消除多余信标帧结构以提高时隙的利用率;通过短中断机制发送随机数据保证了数据的实时性;在竞争访问阶段使用短中断机制,提高能量利用率,延长网络的生存时间。仿真实验结果证明,混合MAC协议提高了医护监测应用中的网络效率。     

无线多跳网络下基于干扰管理的高容量跨层优化策略

在多跳多基站无线网络环境下,设计了一种基于干扰管理的高容量跨层优化策略。算法的物理层采用串行干扰消除实现干扰管理,在上层首先通过Voronoi图实现区域划分,然后基于节点的最小跳数建立每个节点到基站的初始链路分配和多跳路由方案,之后通过多时间片分配或多跳路由的节点选取对方案进行优化,并通过迭代的方式寻找吞吐量更大的优化策略。理论分析证明了该方案具有多项式时间复杂度,仿真结果显示引入了干扰管理相关技术后,整个网络的吞吐率有2到5倍的提升。     

A medium access control scheme for TDD-CDMA cellular networks with two-hop relay architecture

In this paper, we propose a multihop medium access control (mMAC) scheme for time division duplexing-code division multiple access (TDD-CDMA) cellular networks with two-hop relay architecture to support packet data transmission. The proposed mMAC is based on joint CDMA/PRMA (packet reservation multiple access) protocol and it includes BCH code selection, power control and multihop relaying. Simulation results reveal that cellular networks with two-hop relay architecture with the proposed mMAC scheme can substantially provide a good performance as well as larger cell coverage as compared to conventional TDD-CDMA single-hop cellular networks.     

Optimization scheme with pre-processing for cooperative relay multicast networks in cellular system

For cooperative relay multicast networks, the general cross-layer optimization approaches converge to the global optimal value slowly because of the large quantity of relay terminals. However, the mobility of relay terminals requires quick converging optimization strategies to refresh the relay links frequently. Based on the capacity analysis of multiple relay channels, an improved cross-layer optimization scheme is proposed to resolve this problem, in which the bound of the relay selecting region is determined as a pre-processing. Utilizing the primal-dual algorithm, a cross-layer framework with pre-processing optimizes both the relay terminal selection and power allocation with quick convergence. The simulation results prove the effectiveness of the proposed algorithm.     

Cross-layer design scheme for multihop communications

A cross-layer design scheme for wireless communications is proposed and the performance evaluated. The scheme combines a truncated automatic repeat request (ARQ) protocol at the data link layer and multihop transmission at the physical layer. Closed-form solutions are derived for the average throughput and the average number of transmissions required to send a packet when the channel surfers from Nakagami-m fading. Finally, the improvement, when the cross-layer design is implemented is shown.     

Enhanced performance based on cross-layer design from physical to transport layers for multihop wireless networks

This paper puts forward a novel cognitive cross-layer design algorithms for multihop wireless networks optimization across physical,mediam access control(MAC),network and transport layers.As is well known,the conventional layered-protocol architecture can not provide optimal performance for wireless networks,and cross-layer design is becoming increasingly important for improving the performance of wireless networks.In this study,we formulate a specific network utility maximization(NUM)problem that we believe is appropriate for multihop wireless networks.By using the dual algorithm,the NUM problem has been optimal decomposed and solved with a novel distributed cross-layer design algorithm from physical to transport layers.Our solution enjoys the benefits of cross-layer optimization while maintaining the simplicity and modularity of the traditional layered architecture.The proposed cross-layer design can guarantee the end-to-end goals of data flows while fully utilizing network resources.Computer simulations have evaluated an enhanced performance of the proposed algorithm at both average source rate and network throughput.Meanwhile,the proposed algorithm has low implementation complexity for practical reality.     

A utility-based capacity optimization framework for achieving cooperative diversity in the hierarchical converged heterogeneous wireless networks

A hierarchical convergence mechanism for the heterogeneous wireless communication system via the heterogeneous cooperative relay node is presented in this paper, in which the techniques of cooperative communication and wireless relay are utilized to improve performances of the individual user and the overall converged networks. In order to evaluate the benefits of the proposal, a utility-based capacity optimization framework for achieving the heterogeneous cooperative diversity gain is proposed. The heterogeneous cooperative capacity, relay selection and power allocation theoretical models are derived individually. The joint optimization model for relay selection and power allocation is presented as well. Owing to the computation complexity, the sub-optimal cooperative relay selection algorithm, the sub-optimal power allocation algorithm and the sub-optimal joint algorithm are determined to approach the maximum overall networks' spectrum efficiency. These proposed algorithms are designed in conformance to guarantee the equivalent transmission rates of the different wireless access networks. The simulation results demonstrate that the utility-based capacity model is available for the heterogeneous cooperative wireless communication system, and the proposed algorithms can improve performances by achieving the cooperative gain and taking full advantage of the cross-layer design. Copyright © 2008 John Wiley & Sons, Ltd.     

Throughput maximization of ad-hoc wireless networks using adaptive cooperative diversity and truncated ARQ

We propose a cross-layer design which combines truncated ARQ at the link layer and cooperative diversity at the physical layer. In this scheme, both the source node and the relay nodes utilize an orthogonal space-time block code for packet retransmission. In contrast to previous cooperative diversity protocols, here cooperative diversity is invoked only if the destination node receives an erroneous packet from the source node. In addition, the relay nodes are not fixed and are selected according to the channel conditions using CRC. It will be shown that this combination of adaptive cooperative diversity and truncated ARQ can greatly improve the system throughput compared to the conventional truncated ARQ scheme and fixed cooperative diversity protocols. We further maximize the throughput by optimizing the packet length and modulation level and will show that substantial gains can be achieved by this joint optimization. Since both the packet length and modulation level are usually discrete in practice, a computationally efficient algorithm is further proposed to obtain the discrete optimal packet length and modulation level.     

Delay-aware cross-layer optimization method for FANET

An asynchronous distributed cross-layer optimization (ADCO) method was proposed to solve the problem of jointly considering real-time routing,rate allocation and power control in FANET (flying ad hoc network).And a delay-constrained cross-layer optimization framework was designed to formally represent proposed problem.Then Lagrangian relaxation and dual decomposition methods was used to divide joint optimization problem into several sub-problems.ADCO allowed each relay node to perform the optimization operation for different sub-problems with local information,and the relay nodes could update the dual variables based on asynchronous update mechanism.The simulation results show that the proposed algorithm can improve the network performance effectively in terms of energy efficiency,packet timeout ratio and network throughput.     

Energy-efficient performance of cooperative relay network with joint sensing-transmission time duration and power allocation

A joint optimal sensing-transmission time duration and power allocation scheme has been proposed to maximize the energy efficiency for cooperative relay network.In particular,observing that the spectrum sensing and data transmission time duration lies within a strict interval,the joint optimal solutions of our proposed scheme are achieved by sequential optimization method.Numerical evaluation results reveal that the relay-assisted transmission using our proposed scheme significantly outperforms the non-relay transmission in terms of the network energy-efficiency.     

Energy-efficient joint relay node selection and power allocation over multihop relaying cellular networks toward LTE-Advanced

Cooperative relaying is emerging as an effective technology to fulfill requirements on high data rate coverage in next-generation cellular networks,like long term evolution-advanced (LTE-Advanced).In this paper,we propose a distributed joint relay node (RN) selection and power allocation scheme over multihop relaying cellular networks toward LTE-Advanced,taking both the wireless channel state and RNs’ residual energy into consideration.We formulate the multihop relaying cellular network as a restless bandit system.The first-order finite-state Markov chain is used to characterize the time-varying channel and residual energy state transitions.With this stochastic optimization formulation,the optimal policy has indexability property that dramatically reduces the computational complexity.Simulation results demonstrate that the proposed scheme can efficiently enhance the expected system reward,compared with other existing algorithms.     

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.