全复用多小区系统下行链路用户调度与功率分配

对全复用多小区系统下行链路用户调度与功率分配问题进行了研究,提出了一种半分布式的用户调度与功率分配方案.首先,各小区根据自身所辖用户的信道与干扰信息,采用最大信干噪比准则进行用户调度,然后各基站将所调度用户的信息上报给中央资源控制器,最后中央资源控制器基于最速下降法的思想,采用贪婪功率分配(GPA)算法为各用户分配相应的发射功率.所提方案利用小区之间的相互协作有效地弱化了小区间干扰,与现有方法相比获得了更好的吞吐量性能和更高的功率效率.     

无线中继网络系统容量最大化中继选择机制

分析了基于用户频谱效率的中继选择算法的不足,基于最大流最小割定理,给出了系统容量最优化问题模型,分析了两跳中继网络接入链路和中继链路对系统容量的不同影响.基于链路权重因子,提出一种基于系统容量最大化的中继选择算法.对不同中继选择算法下的系统容量差异的理论与仿真分析结果表明,提出的系统容量最大化中继选择算法可以获得更优的系统容量性能,并对网络拓扑和节点个数具有良好的鲁棒性.     

一种功率节省的协作传感器网络伙伴选择方法

针对无线传感器网络的传统协作伙伴选择方法不允许链路复用中继,致使产生中继节点抢占的问题,建立了允许协作链路间复用中继节点的系统模型,运用拉格朗日乘子法优化中继节点上功率分配最大化协作增益,分析复用中继能获得误码率增益和功率增益的条件和功率分配,提出一种中继复用的分布式协作伙伴选择方法。理论分析和仿真结果表明,允许中继通过功率分配进行复用的新伙伴选择方案能降低无线传感器网络的系统总功耗,并使更多链路的误码率需求得到满足。     

认知OFDM系统的一种公平有效的多用户资源分配方案

在可用子载波、干扰温度、次级用户功率预算及公平性等约束条件下,提出了一种适用于认知OFDM系统的公平有效的多用户资源分配方案.该方案将子载波和功率分配分为两个相继的步骤,以降低计算复杂度.第一步引入子载波分配的比例公平原则,保证每个用户都能满足一定的通信要求;第二步采用一种改进的快速迭代注水算法,通过选择适当的调整步长...     

一种多源协作网络中轮询节点选择算法

针对放大转发(AF)的多源多中继两跳协作通信网络模型,提出了一种基于轮询分组调度算法的节点选择与用户调度策略.与之前所提出的中继选择选择算法相比,所提出的中继节点轮询分组调度算法,不需要额外的信令开销,复杂度低,并保证中继间的负载均衡.此外,为保证用户传输的公平性,提出一种结合多用户分集的轮询分组调度算法.最后在已选择的中继节点和所调度的源节点用户中引入分布式空时编码.仿真结果表明,该节点选择和用户调度算法能保证所有节点使用的公平性,并且结合分布式空时编码之后,可以提高频谱利用率,从而提高了系统性能.     

消除小区间干扰的OFDMA系统多小区上行资源分配方案

针对OFDMA系统多小区上行链路资源分配问题,提出了一种新的基于基站合作(BSC)和软频率复用(SFR)的资源分配方案。该方案通过相邻小区使用不同的子载波的软频率复用减少小区间干扰,利用基站合作对边缘用户的信号重构,使小区间干扰进一步消除,从而将多小区资源分配转化为单一小区资源分配。然后根据选择子载波避免冲突原则进行第一次子载波分配。最后根据速率要求,在不影响其他用户最低速率要求的前提下,对子载波进行二次分配。分析和仿真结果表明,该方案可以很好地解决小区边缘干扰严重的问题,降低用户的中断率,使多小区资源分配更加简单、公平、有效,尤其可保证边缘用户的服务质量,从而改善了系统的性能。     

基于公共DF中继的认知无线电中继选择和功率分配

为提高认知无线电网络中主用户和次用户的通信质量,并可简单有效地利用中继节点来控制主用户和次用户之间的相互干扰,提出了一种基于公共中继的最佳中继选择和功率分配方案.首先,在认知无线电网络中建立了基于公共DF中继的无线通信模型;然后,根据无线通信理论推导出要优化的目标函数;最后,在保证主用户中断概率低于目标值的前提下,利用凸优化理论得出了模型中的最佳中继选择和功率分配方案.仿真实验结果表明,与常见的直接传输方案和功率平均分配的中继方案相比,本文提出的中继选择和功率分配方案提高了次用户的通信距离和速率,并且降低了主用户的中断概率,为更好地解决认知无线电网络中主用户和次用户的相互干扰问题提供了新的思路.     

上行虚拟MIMO系统的双比例公平用户配对算法

在分析上行虚拟多输入多输出(V-MIMO)系统的传统正交用户配对算法的基础上,提出了一种先按比例公平准则选取第一个用户,然后基于一种改进的比例公平准则选取其配对用户的新的双比例公平(D-PF)用户配对算法,并基于不同的接收机结构分析评估了该算法的吞吐量性能以及用户之间的公平度.仿真结果表明,与传统的正交用户配对算法相比,所提D-PF算法能够取得更好的吞吐量和用户公平度性能.     

Mesh模式下基于最小干扰流量的带宽调度算法

研究了干扰链路流量大小对IEEE802．16Mesh网络传输性能的影响,提出了一种通过计算用户站（SS）和基站（BS）的通信路径干扰的总流量来寻找总干扰流量最小的路由算法,并结合路由树给出了一种冲突避免调度的方法。该算法既考虑了干扰链路的数量,又考虑了干扰链路的实际通信强度,在建立路由树的过程中能够更快地使系统达到更佳的负载均衡状态,最大强度地避免调度中可能出现的带宽冲突。由于干扰流量的影响可以得到有效的控制,系统的吞吐量可以明显提高。仿真结果验证了该算法的有效性。     

一种光传送网动态联合选路与资源分配算法

提出了一种融合IP/WDM、IP/SDH/WDM的光传送网分层网络模型,它将基于波分复用(WDM)的物理光网络划分为IP、SDH和WDM层,IP和SDH层分别产生基于IP的分组交换型业务和同步时分复用业务,WDM层以波长颗粒度为IP和SDH层提供信道.给出了这种分层网络模型中的动态联合选路与资源分配(DJRRA)算法,该算法能优化层间链路和层内逻辑链路的带宽使用.仿真结果表明,与传统的分离式逐层选路和资源分配算法相比,DJRRA能有效降低网络阻塞率,提高网络吞吐量.     

An interference and latency aware uplink scheduling mechanism in IEEE 802.16j networks

IEEE 802.16j spreads out the coverage of WiMAX networks and strengthens wireless signal transmission using relay technology. To take advantage of relaying in IEEE 802.16j networks, an efficient scheduling schedule with quality of service (QoS) provision for multiple link transmissions is necessary, especially when link interference exists. In this paper, we propose an uplink scheduling mechanism in the transparent mode of IEEE 802.16j, which enables multiple devices to transmit without interference. The maximum latency of each connection has been considered in order to optimize the violation and transmission rate. An interference detection task is first carried out, and then a resource allocation algorithm and a dynamic frame adjustment method are developed. Two simulation experiments were conducted with different interference levels. The results demonstrate that under a fixed QoS type of connection, when the total number of connections goes up to 360 and 420 and the maximum latency violation rate approaches 20%, the average uplink transmission rate of the proposed mechanism can achieve 6.67 and 7.92 Mbps, which apparently outperform regular relay scheduling schemes with rate of 4 and 3.91 Mbps, respectively.     

Cross-layer queuing analysis on multihop relaying networks with adaptive modulation and coding

Multihop relaying is one of the promising techniques in future generation wireless networks. The adaptive modulation and coding (AMC) mechanisms can be applied in order to increase the spectral efficiency of wireless multihop networks. However, most of these mechanisms concentrate on the physical layer without taking the queuing effects at the data link layer into account, whose performances are overestimated. Therefore the cross-layer analytical framework is presented in analysing the quality-of-service (QoS) performances of the decode-and-forward (DF) relaying wireless networks, where the AMC is employed at the physical layer under the conditions of unsaturated traffic and finite-length queue at the data link layer. Considering the characteristics of DF relaying protocol at the physical layer, the authors first propose modelling a two-hop DF relaying wireless channel with AMC as an equivalent Finite State Markov Chain (FSMC) in queuing analysis. Then, the performances in terms of queuing delay, packet loss rate and average throughput are derived. The numerical results show that the proposed analytical method can be efficiently applied for studying the issues including the relay deployment and the cross-layer design in the multihop relaying networks.     

Dynamic Resource Pricing and Allocation in Multilayer Satellite Network

The goal of delivering high-quality service has spurred research of 6G satellite communication networks. The limited resource-allocation problem has been addressed by next-generation satellite communication networks, especially multilayer networks with multiple low-Earth-orbit (LEO) and non-low-Earth-orbit (NLEO) satellites. In this study, the resource-allocation problem of a multilayer satellite network consisting of one NLEO and multiple LEO satellites is solved. The NLEO satellite is the authorized user of spectrum resources and the LEO satellites are unauthorized users. The resource allocation and dynamic pricing problems are combined, and a dynamic game-based resource pricing and allocation model is proposed to maximize the market advantage of LEO satellites and reduce interference between LEO and NLEO satellites. In the proposed model, the resource price is formulated as the dynamic state of the LEO satellites, using the resource allocation strategy as the control variable. Based on the proposed dynamic game model, an open-loop Nash equilibrium is analyzed, and an algorithm is proposed for the resource pricing and allocation problem. Numerical simulations validate the model and algorithm.     

Dynamic resource allocation for supporting real-time multimedia applications in IEEE 802.15.3 WPANs

The IEEE 802.15.3 medium access control (MAC) protocol is an emerging standard for high-rate wireless personal area networks (WPANs), especially for supporting high-quality real-time multimedia applications. Despite defining quality of service (QoS) signalling mechanisms for interoperability between devices, IEEE 802.15.3 does not specify resource allocation algorithms that are left to manufacturers. To guarantee the QoS of real-time variable bit rate (VBR) videos and utilise the radio resource efficiently, the authors propose a dynamic resource allocation algorithm. The proposed bandwidth allocation algorithm is based on a novel traffic predictor. Recently, the variable step-size normalised least mean square (VSSNLMS) algorithm was employed for on-line traffic prediction of VBR videos. However, the performance of the VSSNLMS algorithm significantly degrades due to the abrupt traffic variation occurring at the scene boundary. To tackle this problem, the authors design a novel traffic predictor based on a simple scene detection algorithm and the VSSNLMS algorithm. Analyses using real-life MPEG video traces indicate that the proposed traffic predictor significantly outperforms the VSSNLMS algorithm with respect to the prediction error. The performance of the proposed bandwidth allocation algorithm is also investigated by comparing several existing algorithms. Simulation results demonstrate that the proposed bandwidth allocation algorithm surpasses other mechanisms in terms of channel utilisation, buffer usage and packet loss rate.     

A tutorial survey of topics in wireless networking: Part II

This is the second part of the survey of recent and emerging topics in wireless networking. We provide an overview of the area of wireless networking as that of dealing with problems of resource allocation so that the various connections that utilise the network achieve their desired performance objectives. In Part I we provided a taxonomy of wireless networks as they have been deployed. We then provided a quick survey of the main issues in the wireless ‘physical’ layer. We then discussed some resource allocation formulations in CDMA (code division multiple access) cellular networks and OFDMA (orthogonal frequency division multiple access) networks. In this part we begin with a discussion of random access wireless networks. We first provide an overview of the evolution of random access networks from Aloha to the currently popular 802·11 (Wi-Fi) networks. We then analyse the performance of the 802· 11 random access protocol. We briefly discuss the problem of optimal association of nodes to Wi-Fi access points. Next, we consider topics in ad hoc multihop wireless networks. We first discuss topology and cross layer control. For the latter, we describe the important maximum weight link scheduling algorithm. The connectivity and capacity of randomly deployed networks are then analysed. Finally, we provide an overview of the technical issues in the emerging area of wireless sensor networks.     

Energy Efficient Resource Allocation Approach for Renewable Energy Powered Heterogeneous Cellular Networks

In this paper, maximizing energy efficiency (EE) through radio resource allocation for renewable energy powered heterogeneous cellular networks (HetNet) with energy sharing, is investigated. Our goal is to maximize the network EE, conquer the instability of renewable energy sources and guarantee the fairness of users during allocating resources. We define the objective function as a sum weighted EE of all links in the HetNet. We formulate the resource allocation problem in terms of subcarrier assignment, power allocation and energy sharing, as a mixed combinatorial and non-convex optimization problem. We propose an energy efficient resource allocation scheme, including a centralized resource allocation algorithm for iterative subcarrier allocation and power allocation in which the power allocation problem is solved by analytically solving the Karush-Kuhn-Tucker (KKT) conditions of the problem and a water-filling problem thereafter and a low-complexity distributed resource allocation algorithm based on reinforcement learning (RL). Our numerical results show that both centralized and distributed algorithms converge with a few times of iterations. The numerical results also show that our proposed centralized and distributed resource allocation algorithms outperform the existing reference algorithms in terms of the network EE.     

基于部分可观察马尔可夫决策过程的受控无线网络系统动态资源分配

研究了受控无线网络的动态资源分配。针对传统无线通信传输模型的局限性随着无线通信系统架构的发展日益凸显的问题,提出了一种引入反馈控制策略的受控无线网络模型。该模型结合部分可观察马尔可夫决策过程(POMDP),将用户接收功率与数据传输误码率作为反馈观测对象,对通信小区内基站天线开启数与用户接入数进行动态资源最优匹配。仿真结果表明,这种方法能够有效提升系统传输能效性与可靠性,降低传输误码率,改善系统资源动态匹配控制性能。     

Joint power allocation and relay positioning in multi-relay cooperative systems

The authors consider a dual-hop multi-relay cooperative relay system in this study. Both decode-and-forward (DF) and amplify-and-forward (AF) protocols are considered. Under different relay selection strategies, the authors derive closed-form outage probability expressions. With the second-order channel statistics, the authors propose to jointly optimise power allocation (PA) and relay positions in order to minimise the system outage probability. Simulation results show that the proposed adaptive allocation algorithms significantly outperform fixed allocation algorithms. With the proposed joint optimisation algorithm, AF relaying outperforms DF relaying when multiple relays are selected to help. When only the best relay is selected to help, DF relaying is shown to have better performance.     

A Robust Resource Allocation Scheme for Device-to-Device Communications Based on Q-Learning

One of the most effective technology for the 5G mobile communications is Device-to-device (D2D) communication which is also called terminal pass-through technology. It can directly communicate between devices under the control of a base station and does not require a base station to forward it. The advantages of applying D2D communication technology to cellular networks are: It can increase the communication system capacity, improve the system spectrum efficiency, increase the data transmission rate, and reduce the base station load. Aiming at the problem of co-channel interference between the D2D and cellular users, this paper proposes an efficient algorithm for resource allocation based on the idea of Q-learning, which creates multi-agent learners from multiple D2D users, and the system throughput is determined from the corresponding state-learning of the Q value list and the maximum Q action is obtained through dynamic power for control for D2D users. The mutual interference between the D2D users and base stations and exact channel state information is not required during the Q-learning process and symmetric data transmission mechanism is adopted. The proposed algorithm maximizes the system throughput by controlling the power of D2D users while guaranteeing the quality-of-service of the cellular users. Simulation results show that the proposed algorithm effectively improves system performance as compared with existing algorithms.