H-CRAN网络下联合拥塞控制和资源分配的网络切片动态资源调度策略

针对异构云无线接入网络(H-CRAN)网络下基于网络切片的在线无线资源动态优化问题,该文通过综合考虑业务接入控制、拥塞控制、资源分配和复用,建立一个以最大化网络平均和吞吐量为目标,受限于基站(BS)发射功率、系统稳定性、不同切片的服务质量(QoS)需求和资源分配等约束的随机优化模型,并进而提出了一种联合拥塞控制和资源分配的网络切片动态资源调度算法。该算法会在每个资源调度时隙内动态地为性能需求各异的网络切片中的用户分配资源。仿真结果表明,该文算法能在满足各切片用户QoS需求和维持网络稳定的基础上,提升网络整体吞吐量,并且还可通过调整控制参量的取值实现时延和吞吐量间的动态平衡。     

Utility-based resource allocation and scheduling in OFDM-based wireless broadband networks

This article discusses downlink resource allocation and scheduling for OFDM-based broadband wireless networks. We present a cross-layer resource management framework leveraged by utility optimization. It includes utility-based resource management and QoS architecture, resource allocation algorithms, rate-based and delay-based multichannel scheduling that exploits wireless channel and queue information, and theoretical exploration of the fundamental mechanisms in wireless resource management, such as capacity, fairness, and stability. We also provide a solution that can efficiently allocate resources for heterogeneous traffic with diverse QoS requirements.     

Traffic Aided Uplink Opportunistic Scheduling with QoS Support in Multiservice CDMA Networks

In this letter, we address the problem of resource allocation with efficiency and quality of service (QoS) support in uplink for a wireless CDMA network supporting real‐time (RT) and non‐realtime (NRT) communication services. For RT and NRT users, there are different QoS requirements. We introduce and describe a new scheme, namely, traffic aided uplink opportunistic scheduling (TAUOS). While guaranteeing the different QoS requirements, TAUOS exploits the channel condition to improve system throughput. In TAUOS, the cross‐layer information, file size information, is used to improve fairness for NRT users. Extensive simulation results show that our scheme can achieve high system throughput in uplink wireless CDMA systems, while guaranteeing QoS requirements.     

QoS‐aware LTE‐A downlink scheduling algorithm: A case study on edge users

4G/LTE‐A (Long‐Term Evolution—Advanced) is the state of the art wireless mobile broadband technology. It allows users to take advantage of high Internet speeds. It makes use of the OFDM technology to offer high speed and provides the system resources both in time and frequency domain. A scheduling algorithm running on the base station holds the allocation of these resources. In this paper, we investigate the performance of existing downlink scheduling algorithms in two ways. First, we look at the performance of the algorithms in terms of throughput and fairness metrics. Second, we suggest a new QoS‐aware fairness criterion, which accepts that the system is fair if it can provide the users with the network traffic speeds that they demand and evaluate the performance of the algorithms according to this metric. We also propose a new QoS‐aware downlink scheduling algorithm (QuAS) according to these two metrics, which increases the QoS‐fairness and overall throughput of the edge users without causing a significant degradation in overall system throughput when compared with other schedulers in the literature.     

双参数跨层自适应资源分配算法研究

针对多用户OFDM系统,该文提出了一种适合于混合业务的双参数跨层自适应资源分配方案,它只需调整时延补偿因子和吞吐量补偿因子两个参数,就可将现有的调度算法灵活高效地应用于系统中.仿真结果表明,该方案可以灵活地在系统功率效率和用户服务质量满意度之间取得折衷,并保证不同类型业务用户间的公平性.     

CDMA蜂窝移动通信系统中基于Eb/No的无线分组公平调度算法

在第三代移动通信的无线资源管理机制中,分组调度机制在保证预期的服务质量（QoS）和优化无线资源的利用率方面起到了至关重要的作用.至今已经有很多的调度算法被提出,用来有效地提高无线网络资源的利用率.本文提出一种基于Eb/No并且利用功率控制和管理机制的无线分组公平调度算法用来保证QoS,优化资源配置并且达到调度公平性.     

Proactive load balancing with admission control for heterogeneous overlay networks

The next generation wireless networks will be the coexistence of heterogeneous wireless technologies. Balancing the traffic load among different networks can effectively utilize the overall radio resources in the system. In this paper, we propose an efficient load balancing scheme for the heterogeneous overlay systems, which is applied in the call admission control process. If the available network(s) cannot provide enough resource for the request call without degrading the quality‐of‐service (QoS) obtained by the ongoing calls, the system will perform load balancing operations first by initiating vertical handoffs among networks in order to create more rooms for the request call. The load balancing algorithm is to minimize the variance between the network utilizations of the entire system, which can be formulated as a quadratic binary programming problem. Simulation results show that the proposed scheme can admit more calls into the system compared with the other three reference schemes and then improve the overall throughput. Meanwhile, the scheme can keep the networks working in effective states and provide a better QoS support for users. Copyright © 2011 John Wiley & Sons, Ltd.     

Design of MAC protocols with fast collision resolution for wireless local area networks

Development of efficient medium access control (MAC) protocols providing both high throughput performance for data traffic and good quality of service (QoS) support for real-time traffic is the current major focus in distributed contention-based MAC protocol research. In this paper, we propose an efficient contention resolution algorithm for wireless local area networks, namely, the fast collision resolution (FCR) algorithm. The MAC protocol with this new algorithm attempts to provide significantly higher throughput performance for data services than the IEEE 802.11 MAC algorithm and more advanced dynamic tuning backoff (DTB) algorithm. We demonstrate that this algorithm indeed resolves collisions faster and reduces the idle slots more effectively. To provide good fairness performance and to support good QoS for real-time traffic, we incorporate the self-clocked fair queueing algorithm and a priority scheme into the FCR algorithm and come up with the real-time FCR (RT-FCR) algorithm, and show that RT-FCR can simultaneously achieve high throughput and good fairness performance for nonreal-time traffic while maintaining satisfactory QoS support for real-time traffic.     

基于QoS保证的负载均衡频谱决策算法

针对不同无线网络间频谱资源利用率不均衡的问题,在IEEE 1900.4标准的框架下提出了基于服务质量(QoS)保证的负载均衡算法,使得认知终端可以通过频谱决策动态地接入不同的无线接入网频段,从而提高频谱利用效率。该算法以网络吞吐量的优化为目标,在资源约束和QoS保证的条件下,通过简化算法而减少开销。仿真结果表明,基于QoS保证的负载均衡频谱决策算法较之传统的基于信噪比(SNR)的频谱接入算法能够使网络的吞吐量得到大幅的提升。     

Cross-Layer Optimized Rate Adaptation and Scheduling for Multiple-User Wireless Video Streaming

We present a cross-layer optimized video rate adaptation and user scheduling scheme for multi-user wireless video streaming aiming for maximum quality of service (QoS) for each user,, maximum system video throughput, and QoS fairness among users. These objectives are jointly optimized using a multi-objective optimization (MOO) framework that aims to serve the user with the least remaining playback time, highest delivered video seconds per transmission slot and maximum video quality. Experiments with the IS-856 (1timesEV-DO) standard numerology and ITU pedestrian A and vehicular B environments show significant improvements over the state-of- the-art wireless schedulers in terms of user QoS, QoS fairness, and the system throughput.     

Impacts of Radio Channel Characteristics, Heterogeneous Traffic Intensity, and Near–Far Effect on Rate Adaptive Scheduling Algorithms

Applying adaptive modulation combined with scheduling in a shared data channel can substantially improve the spectral efficiency for wireless systems. This performance gain results from the multiuser diversity, which exploited independent channel variations across multiple users. In this paper, we present a cross-layer analysis to integrate physical-layer channel characteristics, media access control (MAC) layer scheduling strategies, and the network layer issue of heterogeneous traffic intensity across near–far users. Specifically, for radio channel characteristics, we take account of path loss, slowly varying log-normal shadowing and fast-varying Nakagami fading. We also evaluate the impact of selective transmit diversity on the throughput and fairness of wireless data networks. Furthermore, we consider three MAC schedulers: random scheduler, greedy scheduler (GS), and a newly proposed queue-length-based scheduler (QS). By applying the proposed cross-layer analytical framework, the following insights can be gained. First, for the three considered schedulers, channel fluctuations induced by Nakagami fading or log-normal shadowing can improve both total throughput and fairness. Second, using selective transmit diversity can improve throughput, but is unfavorable for the fairness performance. Third, the GS and the QS methods can improve throughput at the expense of unfairness to the far users. However, the throughput improvement from using the GS and the QS decreases as the traffic intensity of the far user increases. In summary, this cross-layer analysis can be used to develop new scheduling mechanisms for achieving better tradeoff between the fairness and throughput for wireless data networks.     

Multihop Cellular Networks: Potential Gains, Research Challenges, and a Resource Allocation Framework

Recently, there has been increasing interest in integrating multihop relaying functionalities into cellular wireless networks. Multihop cellular networks can potentially enhance coverage, data rates, QoS performance in terms of call blocking probability, bit error rate, as well as QoS fairness for different users. However, in-depth investigations and careful system designs are required to exploit these potential advantages. Specifically, routing and resource allocation algorithms should be designed such that the maximum performance gain can be achieved. A number of different architectures, protocols, and analytical models for MCNs have been proposed in the literature where different system aspects were investigated. This article aims to present an overview of existing work in this area, pointing out key research issues and their possible solutions. Also, we present a resource allocation framework for out-of- band relaying. The throughput enhancement due to the proposed framework is demonstrated through numerical results.     

虚拟两天线蜂窝网络中考虑中继公平性的协作博弈调度方法(英文)

In thsssse cellular network, Relay Stations (RSs) help to improve the system performance; however, little work has been done considering the fairness of RSs. In this paper, we study the cooperative game approaches for scheduling in the wireless relay networks with two-virtual-antenna array mode. After defining the metric of relay channel capacity, we form a cooperative game for scheduling and present the interpretation of three different utilization objectives physically and mathematically. Then, a Nash Bargaining Solution (NBS) is utilized for resource allocation considering the traffic load fairness for relays. After proving the existence and uniqueness of NBS in Cooperative Game (CG-NBS), we are able to resolve the resource allocation problem in the cellular relay network by the relay selection and subcarrier assignment policy and the power allocation algorithm for both RSs and UEs. Simulation results reveal that the proposed CG-NBS scheme achieves better tradeoff between relay fairness and system throughput than the conventional Maximal Rate Optimization and Maximal Minimal Fairness methods.     

Low Complexity Modified Viterbi Decoder with Convolution Codes for Power Efficient Wireless Communication

To attain high quality of service (QoS) with efficient power consumption with minimum delay through Wireless Local Area Network (WLAN) through mesh network is an important research area. But the existing real-time routing system involves multiple hops with time varying mobility channels for fastest data propagation is greatly degraded with power utilization factor through congestion traffic queue. Required allocation and resource management through desired access points plays vital roles in which multiple hops demands delay rates by interconnected data nodes. In order to achieve high throughput with minimum delay the QoS in real-time data communication have to be concentrated by using Viterbi decoder with convolution codes. By undertaking IEEE 802.11 WLAN physical layers afford multiple transmission rates by engaging various modulations and channel coding schemes, major point arises to pinpoint the desired transmission rate to enhance the performance. Because each node exhibits different dynamic characteristics based on the token rings passed from the server to the end links. In order to validate the real-time traffic with power consumption and average delay communication, an improved Viterbi decoder is designed with convolution codes to determine accurate channel estimation based on learning the utilization ration of the needed to execute the current wireless channel optimization. The proposed methodology can attain accurate channel estimation without additional implementation effort and modifications to the current 802.11 standard. And each node is capable to choose the optimized transmission rate, so that the system performance can be improved with very minimum power with high packet transmission ratio with minimum traffic rate to improve QoS. The proposed scheme also offers an appealing combination of the allocation of transmission rate and the current link condition. Based on the basic relationship between them, the proposed decoding scheme maximizes the throughput with periodic learning of channel variation and system status.

     

Optimal Routing for Wireless Mesh Networks With Dynamic Traffic Demand

Wireless mesh networks have attracted increasing attention and deployment as a high-performance and low-cost solution to last-mile broadband Internet access. Traffic routing plays a critical role in determining the performance of a wireless mesh network. To investigate the best routing solution, existing work proposes to formulate the mesh network routing problem as an optimization problem. In this problem formulation, traffic demand is usually implicitly assumed as static and known a priori. Contradictorily, recent studies of wireless network traces show that the traffic demand, even being aggregated at access points, is highly dynamic and hard to estimate. Thus, in order to apply the optimization-based routing solution into practice, one must take into account the dynamic and unpredictable nature of wireless traffic demand. This paper presents an integrated framework for wireless mesh network routing under dynamic traffic demand. This framework consists of two important components: traffic estimation and routing optimization. By studying the traces collected at wireless access points, we first present a traffic estimation method which predicts future traffic demand based on its historical data using time-series analysis. This method provides not only the mean value of the future traffic demand estimation but also its statistical distribution. We further investigate the optimal routing strategies for wireless mesh network which take these two forms of traffic demand estimations as inputs. The goal is to balance the traffic load so that minimum congestion will be incurred. This routing objective could be transformed into the throughput optimization problem where the throughput of aggregated flows is maximized subject to fairness constraints that are weighted by the traffic demands. Based on linear programming, we present two routing algorithms which consider the mean value and the statistical distribution of the predicted traffic demands, respectively. The trace-driven simulation study demonstrates that our integrated traffic estimation and routing optimization framework can effectively incorporate the traffic dynamics in mesh network routing.     

A cellular neural network and utility-based radio resource scheduler for multimedia CDMA communication systems

The paper proposes a cellular neural network and utility (CNNU)-based radio resource scheduler for multimedia CDMA communication systems supporting differentiated quality-of-service (QoS). Here, we define a relevant utility function for each connection, which is its radio resource function weighted by a QoS requirement deviation function and a fairness compensation function. We also propose cellular neural networks (CNN) to design the utility-based radio resource scheduler according to the Lyapunov method to solve the constrained optimization problem. The CNN is powerful for complicated optimization problems and has been proved that it can rapidly converge to a desired equilibrium; the utility-based scheduling algorithm can efficiently utilize the radio resource for system, keep the QoS requirements of connections guaranteed, and provide the weighted fairness for connections. Therefore, the CNNUbased scheduler, which determines a radio resource assignment vector for all connections by maximizing an overall system utility, can achieve high system throughput and keep the performance measures of all connections to meet their QoS requirements. Simulation results show that the CNNU-based scheduler attains the average system throughput greater than the EXP [9] and the HOLPRO [5] scheduling schemes by an amount of 23% and 33%, respectively, in the QoS guaranteed region.     

Resource scheduling scheme with QoS support in two-hop relay-enhanced OFDMA systems

As the system performance is obviously improved by introducing the concept of relay into the traditional orthogonal frequency division multiple access(OFDMA)systems,resource scheduling in relay-enhanced OFDMA systems is worthy of being studied carefully.To solve the optimization problem of achieving the maximum throughput while satisfying the quality of service(QoS)and guaranteeing the fairness of users,a novel resource scheduling scheme with QoS support for the downlink of two-hop relay-enhanced OFDMA systems is proposed.The proposed scheme,which is considered both in the first time sub-slot between direct link users and relay stations,and the second time sub-slot among relay link users,takes QoS support into consideration,as well as the system throughput and the fairness for users.Simulation results show that the proposed scheme has good performance in maximizing system throughput and guaranteeing the performance in the service delay and the data loss rate.     

Bandwidth utilization efficiency enhancement for OFDM‐based WSN

Normally IEEE 802.16 (WiMAX) is used for mainly downlink traffic applications. However in the upper tier of 2‐tier (WiMAX‐WiFi) wireless sensor network, the uplink bandwidth faces bottlenecks for high throughput. In this paper, a solution has been proposed for this limitation of uplink bandwidth allocation through the use of queuing theoretic performance modeling. A Markov‐modulated Poisson process traffic model has been formed for orthogonal frequency division multiple access‐based transmission along with discrete time Markov chain system model for queuing. A downlink traffic pattern has been defined for wireless sensor network nodes. Analytical methods are used to estimate the performance parameters like throughput, delay, and probability of packet drop for resource allocation. An algorithm is formulated to find out minimum resource requirement for downlink and to transfer rest of the resources to uplink bandwidth allocation, for throughput enhancement. Uplink frame utilization is determined through another discrete time Markov chain model for adaptive triggering between the proposed maximum and the normal downlink to uplink ratio operations, for efficient distribution of bandwidth resources. Algorithm and simulation results prove outstanding improvement in the uplink throughput around 50%, without degrading the downlink throughput.     

Managing Resources and Quality of Service in Heterogeneous Wireless Systems Exploiting Opportunism

We propose a novel class of opportunistic scheduling disciplines to handle mixes of real-time and best-effort traffic at a wireless access point. The objective is to support probabilistic service rate guarantees to real-time sessions while still achieving opportunistic throughput gains across users and traffic types. We are able to show a ldquotightrdquo stochastic lower bound on the service a real-time session would receive assuming that the users possibly heterogeneous capacity variations are known or estimated, and are fast fading across slots. Such bounds are critical to enabling predictable quality of service and thus the development of complementary resource management and admission control strategies. Idealized simulation results show that the scheme can achieve 80%-90% of the maximum system throughput capacity while satisfying the quality of service (QoS) requirements for real-time traffic, and that the degradation in system throughput is slow in the number of real-time users, i.e., inter- and intra-class opportunism are being properly exploited. We note however, that there is a tradeoff between strictness of QoS requirements and the overall system throughput one can achieve. Thus if QoS requirements on real-time traffic are very tight, one would need to simply give priority to real-time traffic, and in the process lose the throughput gains of opportunism.     

Distributed resource allocation with fairness for cognitive radios in wireless mobile ad hoc networks

Both spectrum sensing and power allocation have crucial effects on the performance of wireless cognitive ad hoc networks. In order to obtain the optimal available subcarrier sets and transmission powers, we propose in this paper a distributed resource allocation framework for cognitive ad hoc networks using the orthogonal frequency division multiple access (OFDMA) modulation. This framework integrates together the constraints of quality of service (QoS), maximum powers, and minimum rates. The fairness of resource allocation is guaranteed by introducing into the link capacity expression the probability that a subcarrier is occupied. An incremental subgradient approach is applied to solve the optimization problems that maximize the weighted sum capacities of all links without or with fairness constraints. Distributed subcarrier selection and power allocation algorithms are presented explicitly. Simulations confirm that the approach converges to the optimal solution faster than the ordinary subgradient method and demonstrate the effects of the key parameters on the system performance. It has been observed that the algorithms proposed in our paper outperform the existing ones in terms of the throughput and number of secondary links admitted and the fairness of resource allocation.